Dentistry, Faculty of
DSpace
UBCV
Alawaji, Yasmine
Doctor of Philosophy - PhD
University of British Columbia
The current thesis includes three projects that covered several aspects of periodontitis epidemiology. The first project focused on studying the prevalence, extent, and associations with untreated periodontitis. A purposive sample of 431 subjects never treated for periodontal conditions was clinically examined at screening dental school clinics. Background data were collected using questionnaires. The prevalence, extent, and associations with untreated periodontitis were evaluated. Our findings showed that the prevalence and extent of untreated periodontitis were high in untreated subjects. Significant exposures associated with untreated periodontitis included age ≥35 years, male sex, lower education, lower income, uncontrolled diabetes mellitus, current cigarette smoking, and lower perceived stress. The second thesis project compared the performance of partial-mouth recording protocols (PRP) with the full-mouth recording protocol (FRP) to estimate the prevalence, extent, and associations of untreated periodontitis. Three PRPs were selected: full-mouth at the mesiobuccal and distolingual sites [(FM)MB-DL], half-mouth at mesiobuccal and distolingual [(HM)MB-DL] and random-half-mouth (RHM) protocol. The accuracy of PRPs was compared with that of FRP by calculating the sensitivity, negative predictive value, and absolute bias. Our findings showed that PRPs had the highest overall accuracy in estimating the untreated periodontitis prevalence, extent, and associations were the (FM)MB-DL and RHM. The third project focused on studying the accuracy of using PRPs in estimating the prevalence, extent, severity, and associations of periodontitis for population-based studies using a systematic review and meta-analyses. A systematic literature search was conducted to retrieve the studies that examined the accuracy of PRP toward estimating the periodontitis prevalence, its extent, severity, and its associations. Data selection, extraction, synthesis, and meta-analyses were performed for 14 studies that matched the eligibility criteria. Our findings include the following: the PRPs that had the highest overall accuracy in studying the periodontitis prevalence, its extent and severity were the (FM)MB-B-DL, (FM)MB-DL, full-mouth at Mesiobuccal-Midbuccal-Distobuccal [(FM)MB-B-DB] sites, (FM)MB-DB, a total of 84 sites using random site selection method, and RHM. Based on a limited number of studies, estimating the associations with periodontitis using PRPs resulted in marginal bias.
Periodontal Disease Epidemiology: Assessment of Untreated Periodontitis and Accuracy of Partial Mouth Recording Protocols by Yasmine Alawaji Diploma in Periodontics, University of British Columbia, 2018 MSc., University of British Columbia, 2018 BDS., King Saud University, 2011 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Craniofacial Science) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) October 2022 © Yasmine Alawaji, 2022 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Periodontal Disease Epidemiology: Assessment of Untreated Periodontitis and Accuracy of Partial Mouth Recording Protocols. submitted by Yasmine Alawaji in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Craniofacial Science Examining Committee: Jolanta Aleksejuniene, Associate Professor, Department of Oral Health Sciences, Faculty of Dentistry, The University of British Columbia. Supervisor Ricardo M Carvalho, Professor, Department of Oral Biological and Medical Sciences, Faculty of Dentistry, The University of British Columbia. Supervisory Committee Member Amee Manges, Professor, Epidemiology, Biostatistics, and Public Health Practice, School of Population and Public Health, The University of British Columbia. Supervisory Committee Member Karen Bartlett, Professor, Occupational and Environmental Health Division, School of Population and Public Health, The University of British Columbia. University Examiner Edwards Putnins, Associate Professor, Department of Oral Biological and Medical Sciences, Faculty of Dentistry, The University of British Columbia. University Examiner Brenda Heaton, Associate Professor, Department of Health Policy and Health Services Research and Department of Epidemiology, School of Public Health, Boston University. External Examiner Additional Supervisory Committee Member Nesrine Mostafa, Assistant Professor, Department of Oral Health Sciences, Faculty of Dentistry, The University of British Columbia. Supervisory Committee Member iii Abstract The current thesis includes three projects that covered several aspects of periodontitis epidemiology. The first project focused on studying the prevalence, extent, and associations with untreated periodontitis. A purposive sample of 431 subjects never treated for periodontal conditions was clinically examined at screening dental school clinics. Background data were collected using questionnaires. The prevalence, extent, and associations with untreated periodontitis were evaluated. Our findings showed that the prevalence and extent of untreated periodontitis were high in untreated subjects. Significant exposures associated with untreated periodontitis included age ≥35 years, male sex, lower education, lower income, uncontrolled diabetes mellitus, current cigarette smoking, and lower perceived stress. The second thesis project compared the performance of partial-mouth recording protocols (PRP) with the full-mouth recording protocol (FRP) to estimate the prevalence, extent, and associations of untreated periodontitis. Three PRPs were selected: full-mouth at the mesiobuccal and distolingual sites [(FM)MB-DL], half-mouth at mesiobuccal and distolingual [(HM)MB-DL] and random-half-mouth (RHM) protocol. The accuracy of PRPs was compared with that of FRP by calculating the sensitivity, negative predictive value, and absolute bias. Our findings showed that PRPs had the highest overall accuracy in estimating the untreated periodontitis prevalence, extent, and associations were the (FM)MB-DL and RHM. The third project focused on studying the accuracy of using PRPs in estimating the prevalence, extent, severity, and associations of periodontitis for population-based studies using a systematic review and meta-analyses. A systematic literature search was conducted to retrieve the studies that examined the accuracy of PRP toward estimating the periodontitis prevalence, its extent, severity, and its associations. Data selection, extraction, synthesis, and meta-analyses were performed for 14 studies that matched the eligibility criteria. Our findings include the following: the PRPs that had the highest overall accuracy in studying the periodontitis prevalence, its extent and severity were the (FM)MB-B-DL, (FM)MB-DL, full-mouth at Mesiobuccal-Midbuccal-Distobuccal [(FM)MB-B-DB] sites, (FM)MB-DB, a total of 84 sites using random site selection method, and RHM. Based on a limited number of studies, estimating the associations with periodontitis using PRPs resulted in marginal bias. iv Lay Summary We studied the presence of gum disease and the factors that could impact the chance of having this disease in a group of patients never treated for this condition. We clinically examined the patients for their gum conditions and obtained their background information using questionnaires. We found a high rate of gum diseases in the untreated patients, and many factors such as the increased age, male sex, low education, low income, cigarette smoking and diabetes mellitus contributed to having the gum disease. The findings of the gum disease of the whole mouth were then compared to those of examining parts of the mouth. We also identified which part of the mouth examinations performed well compared to the full mouth. Thereafter, we searched the literature to identify the well-performed protocols based on examining part of the mouth to estimate the gum disease distribution and the associated factors for population-based studies. v Preface This thesis had three projects that have been published in peer-reviewed journals. The data for the first and second projects were collected from screening dental clinics at King Saud bin Abdul-Aziz University for Health Sciences (KSAU-HS) in Riyadh, Saudi Arabia. Ethics approvals were obtained from the International Review Board of King Abdullah International Medical Research Center (KAIMRC) in Saudi Arabia (H-01-R-005) and from the University of British Columbia; Clinical Research Ethics Board (H19-01019). All study participants signed a consent form prior to data collection. In all the three projects, Dr. Jolanta Aleksejuniene was the Principal Investigator who critically reviewed the study designs, choice of analyses, writing the thesis and manuscripts. Dr. Yasmine Alawaji, the first author in all three studies, proposed the research ideas, and substantially contributed to the research conception, study designs, application for the Ethics approvals, data collection, conducting all the data analyses, as well as writing the thesis and manuscripts. Dr. Amee Manges, a committee member, who critically reviewed and approved the thesis. Dr. Ricardo Carvalho, a committee member, critically revised the workflow throughout the stages of the projects and approved the thesis and the manuscripts. Dr. Nesrine Mostafa, also a committee member, contributed to the conception and study design, facilitating the data collection process and the approval of the thesis manuscripts. Dr. Abdulsalam Alshammari, a faculty member and the clinical administrator at the KSAU-HS in Saudi Arabia, contributed to the study design and application to the Research Ethics board at KAIMRC, facilitated the data collection process, and approved all thesis manuscripts. A version of chapter 2 has been published: Alawaji Y, Alshammari A, Mostafa N, Carvalho RM, & Aleksejuniene J. (2022). Periodontal disease prevalence, extent, and risk associations in untreated individuals. Clinical and Experimental Dental Research, 8(1), 380–394. https://doi.org/10.1002/cre2.526 A version of chapter 3 has been published: Alawaji Y, Mostafa N, Carvalho RM, Alshammari A, & Aleksejuniene J. (2022). Accuracy and precision of using partial-mouth recordings to study the prevalence, extent and risk associations of untreated periodontitis. Saudi Dental Journal, 34(2), 142–149. https://doi.org/10.1016/j.sdentj.2021.12.005 A version of chapter 4 has been published: Alawaji, Y., Alshammari, A., & Aleksejuniene, J. (2022). Accuracy of estimating periodontitis and its risk association using partial-mouth recordings for surveillance studies: A systematic review and meta-analysis. International Journal of Dentistry, 1–16. https://doi.org/10.1155/2022/7961199 vi Table of Contents Abstract ....................................................................................................................................................... iii Lay Summary ............................................................................................................................................. iv Preface .......................................................................................................................................................... v Table of Contents ....................................................................................................................................... vi List of Tables .............................................................................................................................................. ix List of Figures ............................................................................................................................................. xi List of Abbreviations ................................................................................................................................. xv Glossary ................................................................................................................................................... xviii Acknowledgements .................................................................................................................................. xxii Dedication ............................................................................................................................................... xxiv Chapter 1: Introduction ............................................................................................................................. 1 1.1 Periodontal epidemiology through the lens of natural history of disease ................................................. 1 1.1.1 Associations with untreated periodontitis ............................................................................................ 4 1.1.2 Untreated periodontitis in populations lacked access versus lacked utilization of dental care ............ 6 1.1.3 Levels of prevention along the natural course of disease ..................................................................... 7 1.2 Evolvements in measuring and summarizing periodontitis in epidemiological studies ........................... 9 1.2.1 Concurrent periodontitis case definitions in epidemiological research .............................................. 15 1.2.2 Full mouth versus partial mouth recording protocols ........................................................................ 23 1.3 Associations with periodontitis ............................................................................................................... 30 1.4 Focus of the thesis projects ..................................................................................................................... 37 Chapter 2: Periodontitis Prevalence, Extent, and its Associations in Untreated Individuals (Project I) ..................................................................................................................................................................... 38 2.1 Introduction ............................................................................................................................................. 38 2.2 Materials and methods ............................................................................................................................ 39 2.2.1 Data collection site ............................................................................................................................. 39 2.2.2 Selection of study participants ........................................................................................................... 40 2.2.3 Data collection .................................................................................................................................... 40 2.2.4 Periodontitis outcomes ....................................................................................................................... 41 2.2.5 Analytical framework ......................................................................................................................... 42 2.2.5.1 Conceptualization of lack of utilization of periodontal care ..................................................... 42 2.2.5.2 Analytical plan ........................................................................................................................... 43 2.2.6 Statistical analyses .............................................................................................................................. 44 2.3 Results ..................................................................................................................................................... 45 vii 2.4 Discussion ............................................................................................................................................... 60 2.5 Conclusions ............................................................................................................................................. 66 Chapter 3: Performance of Partial Mouth Recording Protocols in Estimating Prevalence, Extent, and Associations with Untreated Periodontitis (Project II) .......................................................................... 67 3.1 Introduction ............................................................................................................................................. 67 3.2 Materials and methods ............................................................................................................................ 69 3.2.1 Study subjects ..................................................................................................................................... 69 3.2.2 Data collection .................................................................................................................................... 69 3.2.3 Study outcomes and selection of partial-mouth-recording protocols ................................................. 70 3.2.4 Sample size calculations ..................................................................................................................... 70 3.2.5 Assessment of prevalence and extent of periodontitis ....................................................................... 70 3.2.6 Assessment of exposures’ associations with periodontitis ................................................................. 71 3.3 Results ..................................................................................................................................................... 72 3.4 Discussion ............................................................................................................................................... 81 3.5 Conclusions ............................................................................................................................................. 86 Chapter 4: Accuracy of Estimating Periodontitis and its Associations Using Partial Mouth Recording Protocols for Population-based Studies: A Systematic Review and Meta-analyses (Project III) ...... 87 4.1 Introduction ............................................................................................................................................. 87 4.2 Methods .................................................................................................................................................. 88 4.3 Results ..................................................................................................................................................... 93 4.4 Discussion ............................................................................................................................................. 113 4.4.1 Methodological considerations ......................................................................................................... 113 4.4.2 Periodontitis prevalence ................................................................................................................... 115 4.4.3 Periodontitis severity and extent ...................................................................................................... 118 4.4.4 Associations with periodontitis ........................................................................................................ 119 4.4.5 Limitations, implications, and future directions ............................................................................... 119 Chapter 5: Concluding remarks ............................................................................................................ 122 Bibliography ............................................................................................................................................ 141 Appendices ............................................................................................................................................... 169 ........................................................................................................................................................ 169 A.1 Study outcomes ................................................................................................................................ 169 A.2 Exposures ......................................................................................................................................... 170 Study Questionnaire ...................................................................................................................... 172 Perceived Stress Scale (PSS) ......................................................................................................... 176 Multidimensional Scale of Perceived Social Support (MSPSS) ................................................... 177 viii Supplementary tables for the systematic review and meta-analyses ............................................. 178 Supplementary figures for the systematic review: PRP performance in estimating periodontitis prevalence defined using the CDC/AAP case definitions ................................................................................. 183 ix List of Tables Table 1. Community Periodontal Index of Treatment Needs (CPITN) codes and it's modification, Community Periodontal Index (CPI) by the World Health Organization. ................................................................................... 13 Table 2. Distribution of subjects’ background characteristics ................................................................................. 52 Table 3. Distribution of the study subjects according to oral behaviors and oral health status ............................... 53 Table 4. Distribution of periodontitis prevalence using the case definition criteria by the AAP/EFP and the CDC/AAP ................................................................................................................................................................. 54 Table 5. Periodontitis extent stratified by age group based on clinical attachment loss and periodontal probing depth. .................................................................................................................................................................................. 55 Table 6. Unadjusted and adjusted exposure associations with total periodontitis cases using the American Academy of Periodontology and the European Federation of Periodontology (AAP/EFP) criteria ........................................ 56 Table 7. Unadjusted and adjusted exposures of stage III/IV periodontitis using the American Academy of Periodontology and the European Federation of Periodontology (AAP/EFP) criteria ............................................ 57 Table 8. Unadjusted and adjusted exposure associations with the moderate-severe periodontitis using the Centers for Disease Control and Prevention and the American Academy of Periodontology (CDC/AAP) criteria ............ 58 Table 9. Unadjusted and adjusted exposure associations with severe periodontitis using the Centers for Disease Control and Prevention and the American Academy of Periodontology (CDC/AAP) criteria ................................ 59 Table 10. Accuracy of estimating the periodontitis prevalence and extent at different disease thresholds using partial mouth recording protocols ........................................................................................................................................ 74 Table 11. Accuracy of estimating the periodontitis prevalence and extent at different disease thresholds using partial mouth recording protocols based on two age groups ............................................................................................... 75 Table 12. Distribution of the CDC/AAP moderate-severe periodontitis per exposure using the partial-mouth recording protocols versus full-mouth recording protocol ....................................................................................... 76 Table 13. Estimation of the unadjusted (crude) exposure associations with prevalence of the CDC/AAP moderate-severe periodontitis (CAL ≥4 mm at ≥2 interproximal sites or PPD ≥5 mm at ≥2 interproximal sites) (Page RC & Eke PI, 2007) ............................................................................................................................................................ 77 Table 14. Estimation of the adjusted exposure associations with prevalence of the CDC/AAP moderate-severe periodontitis (CAL ≥4 mm at ≥2 interproximal sites or PPD ≥5 mm at ≥2 interproximal sites) (Page RC & Eke PI, 2007) ......................................................................................................................................................................... 78 Table 15. Precision of estimating the unadjusted (crude) exposure associations with prevalence of the CDC/AAP severe periodontitis (CAL ≥6 mm at ≥2 interproximal sites and PPD ≥5 mm at ≥1 interproximal site) (Page RC & Eke PI, 2007) ............................................................................................................................................................ 79 Table 16. Estimation of the adjusted exposure associations with prevalence of the CDC/AAP severe periodontitis (CAL ≥6 mm at ≥2 interproximal sites and PPD ≥5 mm at ≥1 interproximal site) (Page RC & Eke PI, 2007) ..... 80 x Table 17. Quality assessment of the included studies using the second version of the Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS-2) (Whiting PF et al., 2011). ......................................................... 106 Table 18. Included studies’ characteristics and potential concerns ....................................................................... 107 Table 19. Exploratory subgroup analysis using bivariate random effect meta-regression for identifying factors associated with absolute bias in estimating moderate-severe periodontitis prevalence ......................................... 110 Table 20. Exploratory subgroup analysis using bivariate random effect meta-regression for identifying factors associated with the absolute bias in estimating severe periodontitis prevalence ................................................... 110 Table 21. Summary of diabetes mellitus, obesity, and current cigarette smoking associations with periodontitis defined using the case definitions by the Centers for Disease Control and Prevention and the American Academy of Periodontology (CDC/AAP) case definitions (Page RC & Eke PI, 2007). ....................................................... 111 Table 22. Suggested diagnostic framework for integrated use in epidemiological research and clinical practice/research. Adapted from the AAP/EFP staging by including early phases of the natural course of disease along with different levels of prevention. .............................................................................................................. 136 Table 23. Definitions of 1st and 2nd projects’ outcomes ........................................................................................ 169 Table 24. Definition of independent variables. ..................................................................................................... 170 Table 25. Customization of the QUADAS-2 tool for quality assessment of diagnostic studies ........................... 178 Table 26. List of excluded studies from the systematic review and the reasons for exclusion ............................. 179 Table 27. Periodontitis prevalence using Partial-mouth Recording Protocol (PRP) versus Full-mouth Recording Protocol (FRP) at different minimum number of sites and disease thresholds defined by Clinical Attachment Loss (CAL) and Periodontal Probing Depth (PPD). Accuracy of the periodontitis prevalence using PRP are reported including the sensitivity, specificity, Positive Predictive Value (PPV), Negative Predictive Value (NPV), and the absolute bias (AB). ................................................................................................................................................. 181 xi List of Figures Figure 1. Four levels of prevention based on stages of natural course of disease (Kisling LA & das JM, 2022; The Association of Faculties of Medicine of Canada, 2018). ........................................................................................... 8 Figure 2. Ramfjord index teeth and Community Periodontal Index of Treatment Needs (CPITN) index teeth, a) Ramfjord index teeth: maxillary right first molar, maxillary left central incisor, maxillary left first premolar, mandibular left first molar, mandibular right central incisor, and mandibular right first premolar, b) CPITN index teeth: maxillary first and second molars, maxillary right central incisor, mandibular first and second molars, and mandibular left central incisor. The six sextants that divide the teeth into 6 segments (two posterior and one anterior segment in each arch) were illustrated. CPITN: Community Periodontal Index of Treatment Needs. ................... 11 Figure 3. Illustrations of periodontal measurements, a) periodontal probing depth (PPD) is measured from the gingival margin to the depth of pocket or sulcus while clinical attachment loss (CAL) is measured from cementoenamel junction (CEJ) to the apical base of the pocket; b) six sites that are measured around each tooth as part of periodontal assessments: mesiobuccal, midbuccal, distobuccal, mesiolingual, midlingual, and distolingual. .................................................................................................................................................................................. 14 Figure 4. Some of the most prominent periodontitis case definitions and classification systems since 1977. The case definitions recommended for epidemiological research use are outlined in orange circles while the rest of the definitions were recommended as part of clinical classification systems. AAP: the American Academy of Periodontology, CDC: the Centers for Disease Control and Prevention, EFP: the European Federation of Periodontology, CAL: clinical attachment loss. ...................................................................................................... 20 Figure 5. Illustrations of some of commonly reported periodontal recording protocols. FRP: Full mouth recording protocol, (FM)MB-B-DB: full mouth at mesiobuccal-midbuccal-distobuccal sites, (FM)MB-B-DL: full mouth at mesiobuccal-midbuccal-distolingual sites, 84 RSSM: 84 sites selected using random site selection method, CPITN: Community Periodontal Index of Treatment Needs, RHM: random half mouth, (HM)MB-B: random half mouth at mesiobuccal-midbuccal, NHANES: National Health and Nutrition Examination Survey, (HM)MB-B-DB: random half mouth at mesiobuccal-midbuccal-distobuccal, (HM)MB-B-DL: random half mouth at mesiobuccal-midbuccal-distolingual, and Ramfjord teeth. ........................................................................................................... 25 Figure 6. An analytical framework adapted from (Bouchard P et al., 2017). The exposures divided into proximal, intermediate, and underlying (distal) based on their proximity to the periodontitis outcome in the causal pathway. Variables outlined in orange boxes either lacked variations or were not consistent with objective measures (oral self-care). .................................................................................................................................................................. 42 Figure 7. Flowchart for the subject recruitment and their referrals at screening dental school clinics. .................. 47 Figure 8. Extent of periodontal probing depth (PPD), recessions (REC), or clinical attachment loss (CAL) per age cohorts. ..................................................................................................................................................................... 48 xii Figure 9. Extent of periodontal probing depth (PPD), recession (REC), clinical attachment loss (CAL) per age cohorts and sex groups. ............................................................................................................................................ 49 Figure 10. Self-assessed oral hygiene compared with clinically measured full mouth plaque scores; the study participants were asked “How do you rate the cleanliness of your mouth ?” .......................................................... 50 Figure 11. Self-assessed periodontal health compared with extent of periodontal probing depth (PPD) and clinical attachment loss (CAL); the study participants were asked “how do you rate your gum health?” ........................... 51 Figure 12. Flow chart: Selection of study subjects .................................................................................................. 72 Figure 13. Conceptual framework for key inquiries and topics concerning the use of partial-mouth recording protocols (PRP) that needed to be considered to define the research question of this systematic review. 1) How old is the population of interest? 2) What was the study design? 3) How did the study measure the periodontal conditions? 4) What was the selected PRP? 5) How did they define the gold standard? 6) How did they compare the PRP to gold standard? 7) What were the study outcomes? 8) How did they define the periodontitis? ............ 91 Figure 14. Flow chart of study selection, data extraction and analysis. .................................................................. 92 Figure 15. Summary of the Absolute Bias (AB)prevalence of moderate-severe periodontitis using Partial-mouth Recording Protocols (PRP). Total PRP sites for each PRP and minimal number of sites with Clinical Attachment Loss (CAL) are listed. ABprevalence values <0.0 underestimate the prevalence while values >0.0 overestimate it. FRP: Full-mouth Recording Protocol, N: sample size, CI: Confidence Interval, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, ML: Mesio-Lingual, L: Mid-Lingual, DL: Disto-Lingual, (FM): Full-Mouth, (HM): Half-Mouth, 84 RSSM: 84 sites selected using Random-Site-Selection-Method, 42 RSSM: 42 sites selected using Random-Site-Selection-Method, 36 RSSM: 36 sites selected using Random-Site-Selection-Method, (RHM): Random-Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs, ?: not clear. ................................................. 96 Figure 16. Subgroup analysis for the Absolute Bias (AB)prevalence of moderate-severe periodontitis using Partial-mouth Recording Protocols (PRP). The subgroups were based on the type of PRP and the number of sites per PRP. FRP: Full-mouth Recording Protocol, N: sample size, CI: Confidence Interval, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, ML: Mesio-Lingual, L: Mid-Lingual, DL: Disto-Lingual, (FM): Full-Mouth, (HM): Half-Mouth, 84 RSSM: 84 sites selected using Random-Site-Selection-Method, 42 RSSM: 42 sites selected using Random-Site-Selection-Method, 36 RSSM: 36 sites selected using Random-Site-Selection-Method, (RHM): Random-Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs, ?: not clear. ................................................. 97 Figure 17. Summary of the sensitivity of moderate-severe periodontitis prevalence using Partial-mouth Recording Protocols (PRP). Specificity and positive predictive value are 100% for all PRPs. PRP sites, minimal number of sites with Clinical Attachment Loss (CAL) and Negative Predictive Value (NPV) are listed. ............................... 98 Figure 18. Summary of the Absolute Bias (AB)prevalence of severe periodontitis using Partial-mouth Recording Protocols (PRP). Total PRP sites for each PRP and minimal number of sites with Clinical Attachment Loss (CAL) are listed. ABprevalence values <0.0 underestimate the prevalence while values >0.0 overestimate it. ....................... 99 xiii Figure 19. Summary of the sensitivity of severe periodontitis prevalence using Partial-mouth Recording Protocols (PRP). Specificity and positive predictive value are 100% for all PRPs. PRP sites, minimal number of sites with Clinical Attachment Loss (CAL), and Negative Predictive Value (NPV) are listed. FRP: Full-mouth Recording Protocol, N: sample size, CI: Confidence Interval, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, ML: Mesio-Lingual, L: Mid-Lingual, DL: Disto-Lingual, (FM): Full-Mouth, (HM): Half-Mouth, 84 RSSM: 84 sites selected using Random-Site-Selection-Method, 42 RSSM: 42 sites selected using Random-Site-Selection-Method, 36 RSSM: 36 sites selected using Random-Site-Selection-Method, (RHM): Random-Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs, ?: not clear. .......................................................................... 100 Figure 20. Subgroup analysis of the Absolute Bias (AB)prevalence of severe periodontitis using Partial-mouth Recording Protocols (PRP). Subgroups were based on the PRP types. FRP: Full-mouth Recording Protocol, N: sample size, CI: Confidence Interval, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, ML: Mesio-Lingual, L: Mid-Lingual, DL: Disto-Lingual, (FM): Full-Mouth, (HM): Half-Mouth, 84 RSSM: 84 sites selected using Random-Site-Selection-Method, 42 RSSM: 42 sites selected using Random-Site-Selection-Method, 36 RSSM: 36 sites selected using Random-Site-Selection-Method, (RHM): Random-Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs, ?: not clear. .............................................................................................. 101 Figure 21. Subgroup analysis of the Absolute Bias (AB)prevalence of severe periodontitis using Partial-mouth Recording Protocols (PRP) excluding the PRP estimates by Tran et al. 2014 where one can observe the reduction of heterogeniety in subgorups compared with Figure 20. Subgroups were based on the PRP types. FRP: Full-mouth Recording Protocol, N: sample size, CI: Confidence Interval, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, ML: Mesio-Lingual, L: Mid-Lingual, DL: Disto-Lingual, (FM): Full-Mouth, (HM): Half-Mouth, 84 RSSM: 84 sites selected using Random-Site-Selection-Method, 42 RSSM: 42 sites selected using Random-Site-Selection-Method, 36 RSSM: 36 sites selected using Random-Site-Selection-Method, (RHM): Random-Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs, ?: not clear. .......................................................................... 102 Figure 22. Summary of Absolute Bias (AB)severity, background characteristics of studies, PRP sites, and severity estimates are listed. FRP: Full-mouth Recording, (SD) standard deviation, Protocol, N: sample size, CI: Confidence Interval, NHANES: National Health And Nutrition Examination Survey, ARIC: Atherosclerosis Risk In Communities, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, ML: Mesio-Lingual, L: Mid-Lingual, DL: Disto-Lingual, (FM): Full-Mouth, 84 RSSM: 84 sites selected using Random-Site-Selection-Method, 42 RSSM: 42 sites selected using Random-Site-Selection-Method, 36 RSSM: 36 sites selected using Random-Site-Selection-Method, (HM): Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs. ................................. 103 Figure 23. Summary estimates of the Absolute Bias (AB)extent of moderate-severe periodontitis. Background characteristics of studies, PRP sites, and specific thresholds of Clinical Attachment Loss (CAL) are listed. FRP: Full-mouth Recording, Protocol, N: sample size, (SD) standard deviation, CI: Confidence Interval, NHANES: National Health And Nutrition Examination Survey, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, ML: xiv Mesio-Lingual, L: Mid-Lingual, DL: Disto-Lingual, (FM): Full-Mouth, (HM): Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs. .................................................................................................................. 104 Figure 24. Summary of the Absolute Bias (AB)extent of severe periodontitis using Partial-mouth Recording Protocols (PRP). Total PRP sites for each PRP are listed. ABextent values <0.0 underestimate the extent, while values >0.0 overestimate it. FRP: Full-mouth Recording Protocol, N: sample size, SD: standard deviation, CI: Confidence Interval, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, ML: Mesio-Lingual, L: Mid-Lingual, DL: Disto-Lingual, (FM): Full-Mouth, (HM): Half-Mouth, 84 RSSM: 84 sites selected using Random-Site-Selection-Method, 42 RSSM: 42 sites selected using Random-Site-Selection-Method, 36 RSSM: 36 sites selected using Random-Site-Selection-Method, (RHM): Random-Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs. 105 Figure 25. Illustration of multi-levels that are averaged in periodontitis severity as a single summary for the whole population. No adjustment is done for clustering at tooth-level or individual-level when severity is summarized for a population. CAL: Clinical Attachment Loss, PPD: Periodontal Probing Depth. .............................................. 124 Figure 26. Illustration for how periodontitis extent is measured and subsequently summarized for a population. CAL: Clinical Attachment Loss, PPD: Periodontal Probing Depth. .................................................................... 125 Figure 27. Illustration of different number of sites or teeth with periodontitis that are diagnosed similarly based on periodontitis case definition for periodontitis prevalence: Clinical attachment loss (CAL) at specific severity threshold in ≥2 non-adjacent teeth or sites. ............................................................................................................ 128 Figure 28. Summary of the Absolute Bias (AB) prevalence of CDC/AAP moderate-severe periodontitis using Partial-mouth Recording Protocols (PRP). Total PRP sites for each PRP are listed. AB prevalence values <0.0 underestimate the prevalence while values >0.0 overestimate it. .................................................................................................. 183 Figure 29. Sensitivity of CDC/AAP moderate-severe periodontitis prevalence using Partial-mouth Recording Protocols (PRP). Specificity and positive predictive value were 100% for all PRPs. PRP sites, minimal number of sites with Clinical Attachment Loss (CAL) and Negative Predictive Value (NPV) are listed. ............................. 184 Figure 30. Absolute Bias (AB) prevalence of CDC/AAP severe periodontitis using Partial-mouth Recording Protocols (PRP). Total PRP sites for each PRP are listed. AB prevalence values <0.0 underestimate the prevalence while values >0.0 overestimate it. ............................................................................................................................................... 185 Figure 31. CDC/AAP severe periodontitis prevalence using Partial-mouth Recording Protocols (PRP). Specificity and positive predictive value are 100% for all PRPs. PRP sites, minimal number of sites with Clinical Attachment Loss (CAL) and Negative Predictive Value (NPV) are listed. ............................................................................... 186 xv List of Abbreviations AAP American Academy of Periodontology AB Absolute Bias AGE Advanced Glycation End-products ARIC Atherosclerosis Risk in Communities B Midbuccal BMI Body Mass Index BOP Bleeding On Probing CAL Clinical Attachment Loss CDC Centers for Disease Control and Prevention CEJ Cementoenamel Junction CI Confidence Interval CPI Community Periodontal Index CPITN Community Periodontal Index of Treatment Needs DB Distobuccal DL Distolingual EFP European Federation of Periodontology EU European Union FM Full-mouth (FM)MB-B Full-mouth at Mesiobuccal-Midbuccal (FM)MB-B-DB Full-mouth at Mesiobuccal-Midbuccal-Distobuccal (FM)MB-B-DL Full-mouth at Mesiobuccal-Midbuccal-Distobuccal (FM)MB-DB Full-mouth at Mesiobuccal-Distobuccal (FM)MB-DL Full-mouth at Mesiobuccal-Distolingual FRP Full-mouth Recording Protocol HbA1c Glycated Hemoglobin HM Half-mouth (HM)MB-B Half-mouth at Mesiobuccal-Midbuccal (HM)MB-B-DB Half-mouth at Mesiobuccal-Midbuccal-Distobuccal sites (HM)MB-DB Half-mouth at Mesiobuccal-Distobuccal sites (HM)MB-B-DL Half-mouth at Mesiobuccal-Midbuccal-Distolingual sites (HM)MB-DL Half-mouth at Mesiobuccal-Distolingual sites HR Hazard ratio xvi IgG Immunoglobulin G INPLASY International Platform of Registered Systematic Review and Meta-analysis Protocols IOM Institute of Medicine KAIMRC King Abdullah International Medical Research Center KSAU-HS King Saud bin Abdul-Aziz University for Health Sciences L Midlingual ln Natural logarithm MB Mesiobuccal MeSH Medical Subject Headings ML Mesiolingual MSPSS Multidimensional Scale of Perceived Social Support N Sample size n Number of studies NHANES National Health and Nutrition Examination Survey NPV Negative Predictive Value OR Odds ratio PDI Periodontal Disease Index by Ramfjord PI Periodontal Index by Russel PMN Poly-morpho-nuclear Leukocytes PPD Periodontal Probing Depth PPV Positive Predictive Value PRISMA-DTA Preferred Reporting Items for Systematic review and Meta-analysis of Diagnostic-test Accuracy Studies PRP Partial-mouth Recording Protocol PSS Perceived Stress Scale QUADAS-2 2nd version of Quality Assessment of Diagnostic Accuracy Studies R2 Explained variance RAGE Receptor for Advanced Glycation End-products RB Relative Bias REC Recession RHM Random-Half-Mouth ROB Risk of Bias RSSM Random Site Selection Method xvii RR Risk ratio SAR Saudi Riyal (currency) SD Standard Deviation UK United Kingdom U.S. United States USA United Stated of America WHO World Health Organization xviii Glossary Absolute bias A measurement of systematic error quantified as the difference between an estimated value and its reference value. Area under the receiver operating characteristic curve The larger the area under the receiver operating characteristics curve indicates higher accuracy of a diagnostic test. Bias An estimated systematic error. Body mass index An indicator of obesity that is measured as the body weight divided by the squared height. Clinical attachment loss Clinical indicator of periodontitis measured as the distance from the level of cementoenamel junction to the apical level of periodontal pocket. CPITN teeth Includes a total of 10 teeth: The maxillary first and second molars, maxillary right central incisor, mandibular first and second molars, and mandibular left central incisor. Data dredging A method in which the handling of the data can be misused in order to find statistically significant results. Data mining A method of extracting information and certain patterns from a dataset. Diagnostic test accuracy The ability to correctly identify the presence or absence of a disease. Diagnostic test accuracy indicators may include the sensitivity, specificity, and predictive values. Emtree The controlled subject headings used to index articles in the Embase database. Epidemiology The study and analyses of the disease distribution and its associated exposures. Full-mouth recording protocol A periodontal recording protocol including measurements of six sites per tooth at a maximum of 28 teeth (excluding the third molars); it is considered the gold standard periodontal recording protocol for epidemiological studies. xix Gingival recession The exposure of the root surface due to the apical migration of soft tissues, measured as the distance between the cementoenamel junction and the gingival margin. Grey literature Information sources that are not published in the traditional scientific databases or commercial distribution channels. Examples of Grey literature are government reports, dissertations, and conference abstracts. Inflation factor An inverse function of sensitivity. Internal consistency A degree of correlation among different items of the same construct or dimension. MeSH terms Controlled medical subject headings used to index the articles in Medline database. Natural history of disease The natural course of a disease in the lack of treatment. Negative predictive value An indicator of diagnostic accuracy measured as the probability of not having a disease in subjects who test negative. Negative predictive value = true negatives(true negatives + false negatives) Odds ratio A quantification of an association between a certain exposure and an outcome; measured as a probability that an event will occur in presence of a certain exposure divided by the probability that an event will occur in the absence of certain exposure. Partial mouth recording protocol A periodontal recording protocol in which the measurements include a subset of teeth or sites per teeth only to represent the condition of the whole mouth. Periodontal indices Estimation of periodontitis using specific scoring systems based on periodontal parameters such as periodontal probing depth and bleeding on probing. Periodontal probing depth A clinical periodontal parameter measured as the distance from the gingival margin to the base of the pocket or sulcus. xx Periodontitis extent An indicator of number/proportion of sites/teeth with periodontitis; it is estimated in population-based studies as a mean proportion of sites with periodontitis at a certain disease threshold. Periodontitis prevalence A population-based estimate calculated as proportion of subjects with periodontitis divided by the total number of subjects. Periodontitis severity An indicator of the depth of the clinical attachment loss, recessions, or periodontal probing depth. In population-based studies, it is estimated as mean clinical attachment loss or periodontal probing depth for the whole population. Positive predictive value An indicator of a diagnostic accuracy measured as the probability of having a disease in subjects who test positive. Positive predictive value = true positives(true positives + false positives) Precision An indicator of how close the results from two or more measurements are. Ramfjord index teeth A set of preselected teeth includes the maxillary right first molar, maxillary left central incisor, maxillary left first premolar, mandibular left first molar, mandibular right central incisor, and mandibular right first premolar. Random Site Selection Method (RSSM) A method of random selection of the reduced number of sites to represent the whole mouth recordings. The selected number of sites can be 36, 48, etc. Receiver operating characteristic curve A curve that shows the trade-offs between the (1-specificity) and sensitivity for a diagnostic test at different thresholds. The diagnostic test that can be used is either a continuous or an ordinal variable with ≥5 categories. Relative bias An indicator of systematic error calculated as the difference between an estimated value and the reference value divided by the reference value. Reliability An overall consistency of repeated measurements if the conditions of what is tested remain stable. xxi Sensitivity An indicator of diagnostic accuracy measured as the probability of identifying individuals who truly have a disease in a population. Sensitivity = true positives(true positives + false negatives) Specificity An indicator of diagnostic accuracy measured as the probability of identifying subjects who truly do not have a disease in a population. Specificity = true negatives(true negatives + false positives) Sufficient cause A set of exposures that can be sufficient to cause a disease while a single exposure out of this set of exposures cannot be sufficient to cause a disease. Validity The extent to which a test or a scale measure what it is intended to be measured. xxii Acknowledgements I would like to express my deepest gratitude to my supervisor, Dr. Jolanta Aleksejuniene. You provided me with a safe place to think, learn, and progress independently, yet I always had your kind support and generous guidance whenever needed. You made me rethink and challenge everything I thought I knew because you had your innovative prospects; I learned that there is always a better way of getting things done regardless of how frequently or traditionally they have been done by others. Your help to conduct my Ph.D. degree work was only a fraction of what you helped me prepare for my future professional career. I cannot thank you enough for your kindness and for the exceptional experience I gained throughout the program. I extend my thanks to my committee members, Dr. Rick Carvalho, Dr. Amee Manges, and Dr. Nesrine Mostafa, who always treated me with respect and having confidence in my abilities. I appreciate your kindness, guidance, and support throughout the program. I also take this opportunity to express gratitude to all study participants who are important contributors to this thesis and will not forget how you warmly welcomed and appreciated the conduct of my research and tried to contribute in every possible way. I cannot thank you enough for your kind help, respect, and support. I would like to thank all the employees, faculty members and staff at KSAU-HS and KAIMRC. Thank you for allowing me to collect data at the screening dental school clinic and providing all support I needed. I am also grateful to Dr. Abdulsalam Alshammari for making the conduct of this research possible across the seas. You helped me through communication and frame my research to be suitable way for the data collection site. I appreciate how you kept checking the research flow and ensured that it moved smoothly. Thank you for your respect, kindness, and support. Dental students and dental assistants at KSAU-HS, I appreciate your help in communicating with patients, obtaining consent forms, helping illiterate patients in filling the questionnaires, and assisting me in documenting the periodontal charting. Special thanks to the fourth-year students Nouf, Zahraa, and Dalal, for helping me the most during my data collection. I would also like to extend special thanks to the dental assistants Amal, Hanan, and Ghozayel for making my data collection process a much more pleasant experience because of your help and support. I express my gratitude for all the help and assistance provided by the front desk staff at KSAU-HS Abdulmajeed, Bassam, Sultan, Haifaa, Afnan, and Zahraa. I cannot thank you enough for all the help with xxiii patient communication, organizing the patient flow, helping the patients to obtain the consent forms, and filling the questionnaires. I acknowledge the responsiveness, help, and financial support for my research I received from the Saudi Arabian Cultural Bureau in Ottawa, Canada. It would not be possible to accomplish all what I did without your kind support. You supported me through all the difficult times I experienced in my Ph.D., especially throughout the unascertained times during the pandemic. I would like to express my sincere thanks to my amazing and supportive family who helped me throughout the process, especially during the stressful period of the pandemic. Special thanks to my mom, who encouraged me to seeking high education degrees and supported me throughout the process by every possible means. I would also like to especially thank my beautiful little niece Nour. I kept her nice drawings in my office to help cheer me up during the write-up of this Ph.D. thesis. xxiv Dedication “Experience all things with the enthusiasm of a child, as if you were seeing it for the first time. This is the Zen mind, always new, always aware, always that of a beginner”. — A quote from Daniel Levin that was posted on the first lecture’s slides by Professor Susan Cox at School of Population and Public Health, University of British Columbia; a professor among those who inspired me the most throughout this journey and possibly beyond it. 1 Chapter 1: Introduction 1.1 Periodontal epidemiology through the lens of natural history of disease Evolvements in understanding natural history of periodontal disease, that is, natural course of disease under a lack of treatment, have had fundamental impacts on clinical practice of periodontology, guiding direction of research, and planning preventive programs. Throughout the first half of 20th century, the “focal infection theory” was a prominent notion that dominated the clinical practice in developed countries where periodontitis was treated through “therapeutic edentulism” (Burt BA, 1991, 1993). Mass dental extractions were performed for periodontally involved teeth in order to prevent several systemic diseases. Such approach gradually faded in the second half of the 20th century after adopting scientific methods in periodontal research; it was discovered that focal infection theory that motivated the extractions of periodontally involved teeth to prevent systematic diseases was mainly based on personal opinions rather than compelling evidence (Baelum V & Lopez R, 2013). Among several notions that dominated the second half of 20th century: “all gingivitis progresses to periodontitis with consequent bone loss and tooth loss” and “virtually everyone is susceptible to periodontitis that becomes serious enough to threaten the dentition” (Burt BA, 1993). These beliefs were mainly aided by erroneous interpretations of national data from developed countries including the United States and New Zealand where an increase in tooth loss with aging was interpreted as an inevitable consequence of periodontitis; ignoring the fact that the edentulism occurred due to the mass extractions which was motivated earlier by focal infection theory (Burt BA, 1991, 1993). A paradigm shift in understanding of periodontal disease occurred after observing the natural history of disease in rural areas where oral self-care and access to dental care were nearly absent; it was found that despite having a uniformly high levels of plaque, only small proportion of populations developed severe periodontitis threatening the dentition (Baelum V, Wen-Min L, et al., 1988; Loe H, Anerud A, et al., 1978; Manji F et al., 1988). Thus, observations from untreated populations led to fundamental changes in understanding the natural course of periodontal disease. This highlights an essential point to consider when studying the natural history of disease in the lack of treatment rather than simply studying the disease progression while disregarding the possible impacts of treatment. In the second half of the 20th century, among a few epidemiological studies available in that era, a study has published findings that supports the notion: gingivitis invariably leads to periodontitis and consequently results in tooth loss (Marshall-Day CD et al., 1955). Accordingly, many periodontal indices were proposed to diagnose periodontal disease based an assumption that gingivitis inevitably leads to periodontitis including Russell’s periodontal index and Ramfjord’s periodontal disease index; the distribution of periodontal diseases was reported as population’s mean index score (Ramfjord SP, 1959; Russell AL, 1956). During the periodontal indices’ era, it was generally accepted that gingivitis progresses to periodontitis following a linear model of disease progression manifested as a universally slow and continuous process (Ramfjord SP, 1959; Russell AL, 1956). Based on data from two population-based studies, it has been concluded that plaque and age alone are responsible for 90.3% of 2 variations in periodontal disease in any population (Russell A, 1963). This study that highlighted the role of dental plaque in initiation of periodontal disease was followed by a study on experimental gingivitis which has been used to support the claim: plaque is the cause of periodontal disease (Löe H et al., 1965). Though, observed variations in individuals’ responses in the experimental gingivitis study were disregarded (Baelum V & Lopez R, 2013). Consequently, clinical practice and preventive programs during that era had almost solely focused on plaque control (Hirschfeld L & Wasserman B, 1978; Lindhe J & Nyman S, 1975; Rosling B et al., 1976). It was believed that unless plaque is controlled, gingivitis will inevitably develop and subsequently lead to periodontitis. However, such notion had been proved later to be invalid since both periodontal indices and plaque index were calculated as population-based mean index scores that were derived from averaged individual scores; therefore, inherent variations at the population level (Baelum V & Lopez R, 2013; Burt B, 1991). Due to the use of periodontal indices during that era, research on variations in host responses and exposures that could explain potential variations were hampered (Baelum V & Lopez R, 2013). In later years, a transition was made from using periodontal indices to using site-specific measurements of periodontal disease. Studies focusing on untreated populations in rural areas, using site-specific measurements, revealed variations in host responses despite uniformly high levels of plaque and calculus (Baelum V et al., 1996; Cutress TW et al., 1982; Löe H et al., 1978, 1986; Timmerman MF et al., 2000). Consequently, it was no longer accepted plaque being the only cause of periodontal disease and periodontal indices era that were based on reporting mean index scores was abandoned (Baelum V & Lopez R, 2013; Beltran-Aguilar ED et al., 2012; Burt BA, 1991; Papapanou P & Lindhe J, 2015). Findings from studies on untreated populations having uniformly high levels of plaque revealed several limitations of the monocausal linear model of periodontal disease progression (Baelum V & Lopez R, 2013; Burt BA, 1993). A longitudinal study in Sri Lankan tea workers identified three patterns of periodontitis progression: rapid progression in 8.0% of individuals with an annual mean clinical attachment loss (CAL) of 0.1 to 1.0 mm; moderate progression in 81.0% of individuals with an annual mean CAL of 0.05 to 0.5 mm; no (or minimal) progression in 11.0% of individuals with an annual mean CAL of 0.05 to 0.09 mm (Löe H et al., 1978, 1986). By the age of 45 years, mean CAL of 13.0 mm was observed in the rapid progression group and mean CAL of 7 mm in the moderate progression group; in the no progression group, ≤1 mm CAL occurred at 35 years (Löe H et al., 1986). In a study on Indonesian tea workers, periodontitis progression rate within the first 7 years of observation was similar to the moderate progression group of the Sri Lankan study (Löe H et al., 1986), where the mean annual CAL was 0.05 mm (Timmerman MF et al., 2000). However, in the following 8 years, the progression rate increased with a mean annual progression rate of 0.15 mm (van der Velden U et al., 2006). In addition to the observed variations in the Sri Lankan and Indonesian tea workers (Löe H et al., 1986; van der Velden U et al., 2006), other studies also found variations in periodontitis occurrence patterns among different populations including rural Kenyans, rural Chinese population, and South Pacific Islanders (Baelum V et al., 1996; Cutress TW et al., 1982). Variations based on the tooth type were also observed with molars and incisors having a more severe CAL than the rest of the dentition 3 (Cutress TW et al., 1982; Haffajee A et al., 1982; Löe H et al., 1978, 1986). When variations were analyzed at the site level (Goodson JM et al., 1982; Haffajee A et al., 1982), it was observed that sites with periodontitis undergo cycles of exacerbations followed by spontaneous remissions (Goodson JM et al., 1982; Haffajee A et al., 1982). Over a year of observation, 82.8% of sites had no progression, 5.7% of had increased CAL, and 11.5% of sites had decreased CAL (Goodson JM et al., 1982). Furthermore, interproximal sites had higher CAL than facial or lingual sites (Becker W et al., 1979; Haffajee A et al., 1982; Löe H et al., 1978). Early in 1980s, alternative periodontal disease progression models based on “burst theory” were proposed to replace the linear model (Socransky S et al., 1984). This theory was mainly based on site-specific observations of periodontitis progression in untreated individuals (Goodson JM et al., 1982; Haffajee A et al., 1982). The theory assumes that disease activity occurs at certain time periods followed by longer periods of remission (Socransky S et al., 1984). Two models have been proposed by the theory: random burst and asynchronous random burst. The random burst model assumes that periodontitis activity occurs randomly at any site and variations occurs among different sites; some sites may not have any disease activity whereas other sites have one or several bursts of activity. The occurrence of multiple bursts “at random” refers to possibility of disease occurrence in previously diseased or non-diseased sites and at random periods of time. While the asynchronous multiple burst model had the same underlying assumptions as the random burst model, an additional assumption of this model was that most of disease activity on multiple sites occurred in certain periods of life followed by longer periods of remission. The importance of the burst models is acknowledgement of variation in periodontal disease activity which motivated the exploration of local factors/exposures and highlighted the site-specific variations in host susceptibility (Baelum V & Lopez R, 2013). Perhaps one of the main drawbacks of the burst models is their focus on variations at the site-level while disregarding the cluster effects of these sites at an individual-level. Such approach has been criticized since teeth sites cannot be considered independent from an individual (Imrey PB, 1986). Therefore, the use of site-specific analyses did not allow the proper exploration of exposures at an individual level. After development of advanced statistical analyses, it has been suggested that multilevel modeling could potentially revitalize this line of research (Baelum V & Lopez R, 2013). However, another limitation of the burst models was the inadequate consideration of measurement errors (Imrey PB, 1986). Therefore, variations in attachment loss or gain in burst models were attributed to measurement errors and analytical errors rather than actual variations. After abandoning the indices era, a gradual distinction was made between the terms: periodontal disease and periodontitis. Periodontal diseases represent a broad entity of diseases and include two main categories of heterogenous diseases: gingivitis and periodontitis. Since 1999, “gingival diseases” were introduced as a distinct category in the classification system of periodontal diseases by the American Academy of Periodontology (AAP) (Armitage GC, 1999), which continues to be the case in the current classification (Caton JG et al., 2018). In simple terms, gingivitis can be defined as an inflammation of gingival tissues that does not involve the supporting structures 4 of the periodontium (cementum, periodontal ligament, alveolar bone), whereas the periodontitis is an inflammation that results in a damage to the supporting structures of periodontium (Torabi S & Soni A, 2022). In contrast to the understanding of periodontal diseases during the indices era, gingivitis can be either reversible or self-limited, that is, it does not always lead to periodontitis (Trombelli L et al., 2015). However, periodontitis is almost always preceded by gingivitis. A similar line of distinction has been made, by the end of indices era, regarding the role of plaque in initiation of periodontal diseases. Although presence of plaque almost always precedes the development of periodontal disease, plaque alone does not inevitably lead to periodontal disease (Bouchard P et al., 2017). 1.1.1 Associations with untreated periodontitis Since 1980, understanding the variations in host susceptibility to periodontitis have directed the research to identify “high-risk individuals” and “high-risk groups” (Beck, 1994; Borrell LN & Papapanou PN, 2005; Johnson NW et al., 1988; van Dyke TE & Sheilesh D, 2005). In untreated populations, some efforts were done to identify the exposures associated with periodontitis (Baelum V et al., 1997; Neely AL et al., 2001; van der Velden U et al., 2006). The underlying assumption that needs to be emphasized here is that studying associations with untreated periodontitis can be particularly important to rule out the impact of periodontal treatments on such associations. Studying the associations with untreated periodontitis is directly relevant to understanding the natural course of disease. However, the periodontitis associations in populations with unknown treatment status can be impacted by periodontal treatment without proper considerations for such treatment effects. In previous studies on untreated populations, the longitudinal follow-up allowed estimation of associations with the periodontitis onset and its progression. In untreated Sri Lankan tea workers, progression of CAL was associated with several exposures including increased age, “gingival index”, “calculus index”, and longer follow-up time (Neely AL et al., 2001). In untreated Indonesian tea workers, exposures associated with the periodontitis progression included male sex, higher number of sites with periodontal probing depth (PPD) ≥5 mm, and the total number of sites with recessions, whereas exposures associated with periodontitis onset included increased age, presence of subgingival calculus, and Aggregatibacter actinomycetemcomitans (van der Velden U et al., 2006). In rural Chinese population with minimal access to dental care, exposures of disease onset and progression included male sex, lower number of present sites, and higher proportion of sites with CAL ≥4 mm (Baelum V et al., 1997). An additional exposure for disease progression was the increased age. Studying periodontitis and its exposures in untreated populations residing in rural areas may limited the number of exposures that were amenable to be studied. Published periodontal literature from rural populations often reported a lack (or minimal) access to dental care and exposure to preventive programs, consequently, high levels of plaque and calculus were universal findings (Baelum V et al., 1996, 1997; Baelum V, Fejerskov O, et al., 1988; Baelum V, Wen-Min L, et al., 1993; Cutress TW et al., 1982; Dowsett SA, Eckert GJ, et al., 2002a; Dowsett SA et al., 2001; Loe H, Anerud A, et al., 1978; Loe H, Boysen H, et al., 1978; Löe H et al., 1978, 1986; Timmerman MF et al., 5 1998, 2000; van der Velden U et al., 2006). The lack of access to dental care and having universally high plaque scores created ideal conditions to study the natural course of periodontal disease. However, those studies mainly limited their investigation to age, sex, and local factors rather than investigating the medical and non-medical underlying exposures for their potential associations with periodontitis. These untreated populations were generally reported to have low socioeconomic status including uniform occupations such as being tea workers or farmers (Baelum V, Fejerskov O, et al., 1988; Loe H, Boysen H, et al., 1978; Timmerman MF et al., 1998); lacked access to medical care (Loe H, Boysen H, et al., 1978); thus, medical conditions might have been undiagnosed. It may be assumed then that these uniform underlying exposures in untreated rural populations hampered the studying of wider range of exposures associations with periodontitis. Though, these background characteristics of rural populations were mostly reported as generic statements rather than reporting quantitative descriptions as evidence of lacking variations in underlying exposures. In Sri Lankan tea workers, exposures that were examined beyond demographic characteristics and local factors in rural populations included smoking and chewing of betel nuts in addition to generic descriptions of nutrition and fluoride content in the water (Loe H, Boysen H, et al., 1978). In Indonesian tea workers, medical conditions, use of medications, smoking status, and oral self-care were assessed; smoking was restricted to males, oral self-care included a self-report of daily tooth brushing, and no information was reported regarding the health status or if subjects had used medications (van der Velden U et al., 2006). The level of education in this study was generally low. However, variation in education levels was observed at a smaller scale since it ranged from less than elementary school to senior high school degree. Furthermore, the authors suggested that higher progression rate among Indonesian tea workers in the latest observation period as compared with initial period might be attributed to an economic recession; it was thought that such economic recession might have resulted in diet changes and increased psychological stress. However, psychosocial and economical exposures were not evaluated in this study. In rural Kenya’s Machakos district, the rural population had minimal access to dental care and oral self-care was limited to brushing with finger and charcoal or using a wooden chewing stick (Baelum V, Fejerskov O, et al., 1988). In this report, the authors cited a reference that described the socioeconomic status in more details; it appears that dental examinations were conducted as part of multidisciplinary team that established a surveillance system called “Machakos project” (van Ginneken JK & Muller AS, 1984). This multidisciplinary team examined population’s demographics, education, occupations, income, social factors, behaviors, medical conditions, agriculture, and nutrition; such exposures were analyzed for their association with several medical conditions (Mosley WH et al., 1986; van Ginneken JK & Muller AS, 1984). However, these exposures were not described or analyzed for their potential associations in the periodontal literature. Based on overall findings, there are reasons to believe that these untreated populations had variations in their medical as well as non-medical underlying exposures which were either not assessed, unreported, or not considered in the analyses for their possible associations with untreated 6 periodontitis. Therefore, despite the variations in susceptibility to periodontitis observed among the untreated populations, the current literature is deficient about the associations that could explain these variations. 1.1.2 Untreated periodontitis in populations lacked access versus lacked utilization of dental care In contrast to studies focused on natural history of periodontitis in untreated rural populations, other studies that improved our understanding of the untreated periodontitis recruited individuals who presented themselves in dental offices yet, refused periodontal care (Becker W et al., 1979; Fowler C et al., 1982; Haffajee A et al., 1982; Harris RJ, 2003; Lindhe J et al., 1983; Silva-Boghossian CM et al., 2008; Socransky S et al., 1984; Watts T, 1987). Among the contributions of studies on untreated individuals in dental offices is the proposal of burst theory which motivated the research on variations in susceptibility to periodontitis (Goodson JM et al., 1982; Haffajee A et al., 1982; Lindhe J et al., 1983; Socransky S et al., 1984). The reality is some individuals may refuse periodontal treatments despite their ability to access dental facilities. Perhaps what can be learned from studies recruiting population from dental offices who lack the utilization of dental care is that findings from these investigations could still serve the purpose of studying the untreated periodontitis. However, a distinction between untreated rural residents versus those who present themselves in dental offices is potential systematic differences in their underlying exposures of periodontitis. A differentiation was made in the literature between the terms “potential access” and “utilization” of health care; utilization of health care “realized access” is the actual use of health services, while potential access depends upon enabling resources (Aday LA & Andersen RM, 1981). Thus, lack of potential access means a definitive lack of access. Importantly, potential access to health care is only one of several attributes that could explain the utilization of health care (Institute of Medicine (US) Committee on Monitoring); thus, having a potential access to health care does not necessarily always equate the utilization of health care service. An adapted model that conceptualizes the access to dental care was suggested (McKernan S et al., 2020); where the original model was proposed by the Institute of Medicine (IOM) which was further modified by adding awareness as another dimension (Institute of Medicine (US) Committee on Monitoring Access to Personal Health Care Services, 1993; Saurman E, 2016). The access to dental care model assumes that the need for dental care often dictates the motivation of utilizing it if potential access is equitable (McKernan S et al., 2020). However, several barriers can impede the utilization of the dental care. When an individual has a need for care but cannot access it, this could lead to inequity, in turn to disparities in health outcomes. An elaboration on the need for care was suggested where “perceived need” related to individual judgments, while “evaluated needs” judgements made by health care professionals (Andersen RM, 1995). Three main sources of interrelated barriers to access health care are financial (affordability), structural (accessibility, availability of resources, and accommodation), and personal/cultural (acceptability and awareness) (Institute of Medicine (US) Committee on Monitoring Access to Personal Health Care Services, 1993; McKernan S et al., 2020; Saurman E, 2016). It can be inferred that lack of perceived need for dental care, despite the actual need for care, could act as an additional barrier. These several 7 attributes that may explain the lack of utilization of dental care may highlight some of the complexity when conceptualizing the lack of access to dental care. Access to health care was broadly defined by the IOM as “the timely use of personal health services to achieve the best possible health outcomes” (Institute of Medicine (US) Committee on Monitoring Access to Personal Health Care Services, 1993). It can be inferred from such definition that receiving emergency dental care towards reducing acute symptoms or having extractions does not mean that individuals had proper access to dental care. Some of studies focused on untreated rural residents whose dental history was limited to emergency treatments but without receiving any kind of periodontal treatment (Dowsett SA, Eckert GJ, et al., 2002a; Dowsett SA et al., 2001; Timmerman MF et al., 2000). Thus, studying such populations might still be relevant given their dental history was limited to non-periodontal treatments. However, the interpretation of tooth loss can be possibly misleading since the natural course was interrupted by the emergency treatments including having dental extractions (Dowsett SA, Eckert GJ, et al., 2002b, 2002a; Timmerman MF et al., 1998, 2000). In contrast, recruitment of untreated population groups who had an absolute lack of access to dental care such as Sri Lankan tea workers provided an ideal sample for studying the etiology of tooth loss; tooth loss only occurred by having teeth falling out or being removed by individuals themselves rather than being extracted by dental professionals (Loe H, Boysen H, et al., 1978). Therefore, the selection of the study sample for studying the natural history of a specific disease in the lack of its treatment may depend upon the study context and its objectives. 1.1.3 Levels of prevention along the natural course of disease Understanding the natural course of disease forms the basis for its prevention. Four levels of prevention, based on the natural course of disease were described: primordial, primary, secondary, and tertiary prevention (Kisling LA & das JM, 2022; The Association of Faculties of Medicine of Canada, 2018). Primordial prevention targets the earliest point along the natural course of disease where it aims to prevent the underlying exposures such as social, economic, and behavioral exposures. Primordial prevention targets the population or society rather than individuals, mostly through policy makers, by implementing health promotion, population-based interventions, and social programs. Examples of primordial prevention may include promoting healthy behaviors during childhood, fluoridation of drinking water, sin tax on tobacco products, or enforcing food companies to produce food labels outlining the nutritional values and amount of calories. Primary prevention targets the exposures at an individual- or population-level after the exposures have been identified. Primary prevention aims to prevent the disease development and it is mainly applied by public health practitioners. Exposures that are targeted by primary prevention are often disease specific. Examples of primary prevention may include smoking cessation programs and oral health promotion campaigns that target specific population groups. Secondary prevention targets individuals by clinicians at asymptomatic stage of the disease; it aims to intervene when therapy can be more effective to prevent disease progression. An example of secondary prevention may include frequent dental check- 8 ups to detect and monitor oral diseases at an early stage of their development. Tertiary prevention targets the individuals at clinically symptomatic stage and clinicians aim to prevent further progression of the disease, its complications, or relapses. An example of tertiary prevention can be periodontal treatment to prevent tooth loss or loss of masticatory function. All levels of prevention target the modifiable exposures and aim to prevent the disease incidence or its further progression (Figure 1). Figure 1. Four levels of prevention based on stages of natural course of disease (Kisling LA & das JM, 2022; The Association of Faculties of Medicine of Canada, 2018). When the four-levels prevention are translated to the context of periodontitis, both secondary and tertiary levels of prevention may overlap since periodontitis is rarely associated with symptoms until its advanced stages, that is, when individuals experience excessive teeth mobility or loss of masticatory function. Although surgical periodontal treatment followed by maintenance can be considered a tertiary prevention, a systematic review that evaluated effectiveness of professional mechanical debridement in patients who had surgical treatment phase named it “secondary prevention” (Trombelli L et al., 2015). Nevertheless, the systematic review found a mean CAL of <1.0 mm occurred at up to 12 years of follow-up; indicating a successful long-term treatment outcome. In contrast to secondary and tertiary prevention, both primordial and primary preventions are generally the least targeted prevention levels in the context of periodontitis. Implementing primordial and primary level of prevention for periodontitis means that preventive programs need to target the population at an early time point prior to the development of the disease, perhaps during adolescence. However, this might be difficult to support with evidence 9 since the vast majority of periodontal literature focused on studying the periodontitis and its exposures in adults or elderly (Billings M et al., 2018; Eke PI et al., 2015, 2016; Lorenzo SM et al., 2015; Susin C et al., 2004). The is issue of deficient evidence for younger population groups is especially true in regard to primordial prevention since the underlying exposures, including social determinants of health, have not been a focus of periodontal research (Bouchard P et al., 2017). A recent review focused on public health efforts to prevent periodontitis concluded that up to date, efforts to prevent periodontitis were mainly individual-level approaches whereas population-based strategies are scarce (Janakiram C & Dye BA, 2020). Perhaps one way to advance our knowledge for planning population-based strategies is to better understand the underlying exposures including the social determinants of health (Borrell L et al., 2002; Borrell L & Crawford N, 2012; Bouchard P et al., 2017). In summary, understanding the natural history of disease forms the basis that could possibly shape its prevention, clinical practice, and the direction of future research. Studies on untreated subjects improved our understanding of periodontitis being a multifactorial, heterogenous, and complex disease. In spite of the variations in susceptibility to periodontitis that were observed among the untreated populations, the overall literature is deficient on potential exposures that may further explain these variations. The concurrent research mostly considered studying associations with periodontitis without properly accounting for the impact of periodontal treatment on such associations. The literature also mostly focused on periodontitis terminal stages including tooth loss in older populations rather than its earlier stages. Based on the scope of the natural course of disease, knowledge gaps yet to be addressed, include understanding the underlying exposures of periodontitis. Building on a better understanding of the underlying exposures, a primordial prevention of periodontitis can therefore be planned and implemented. Accordingly, there is possible need to shift the focus in studying periodontitis in its earlier stages and in younger populations where prevention can be more effective. 1.2 Evolvements in measuring and summarizing periodontitis in epidemiological studies The approach of defining periodontitis has evolved over time, where early studies used mean scores of indices (Ramfjord SP, 1959; Russell AL, 1956), and a majority of the later studies employed their own definitions (Manau C et al., 2008; Preshaw PM, 2009). Up until early 1980s, the linear model of disease progression was the dominant paradigm that reflected the historical understanding of periodontal disease where gingivitis and periodontitis were diagnosed as a continuum (Baelum V & Lopez R, 2013). Periodontal indices that were proposed for assessment of periodontal disease in epidemiological studies used mean index scores to report a summary for a given population (Beltran-Aguilar ED et al., 2012). The most prominent periodontal indices were the periodontal index (Russell AL, 1956) and periodontal disease index (Ramfjord SP, 1959). Russell’s Periodontal Index was one of the most widely used indices in epidemiological studies (Beltran-Aguilar ED et al., 2012; Papapanou P & Lindhe J, 2015). The periodontal index measures periodontal disease using a plain periodontal probe (without markings) and evaluates the whole mouth using the following incrementally increasing severity scores (Russell AL, 1956): 10 0. Absence of inflammation and loss of function due to destruction of periodontium. 1. Inflammation of free gingival margins but not circumferentially around the tooth. 2. Gingivitis around the tooth without attachment loss. 6. Gingivitis with pocket formation, no loss of masticatory function, no mobility or drifting. (Periodontal pocket formation was recorded as present or absent without precise measurement). 8. Advanced destruction of attachment with loss of masticatory function, excessive mobility, or drifting. The individual teeth scores are averaged based on the number of teeth present; scores from 0 to 0.2 indicate having normal periodontium; ranges from 0.3 to 0.9 indicate the presence of gingivitis; ranges from 1.0 to 1.9 indicate a beginning of destructive periodontal disease; ranges from 2.0 to 4.9 indicate the presence of established destructive periodontal disease; and 5 to 8.0 indicate having a terminal disease (Russell AL, 1956). Russell’s index was a composite index (measured gingivitis and periodontitis as a continuum) and it was also a reversible index due to relying on measurements of gingival inflammation and pocket formation; however, these criteria tend to fluctuate or can be reversed with treatment (Beltran-Aguilar ED et al., 2012; Papapanou P & Lindhe J, 2015). Unlike Russell’s reversible index, the periodontal disease index (Ramfjord SP, 1959) by Ramfjord relied on the measurement of CAL that was more stable since it measured using a fixed reference point: the cementoenamel junction (CEJ). Thus, the periodontal disease index is considered an irreversible index. The Ramfjord’s index is both a tooth- and site-specific index. This index uses a periodontal probe with markings at 3, 6, and 8 mm. The index score ranges from 0 to 6 and it is scored as following: 0. An absence of inflammation. 1. Mild to moderate gingival inflammation that does not extend around the tooth. 2. Mild to moderately severe gingivitis that extends around the tooth. 3. Severe gingivitis with pronounced redness, bleeding, and ulceration. 4. CAL ≤3 mm. 5. CAL of 3-6 mm. 6. CAL >6 mm. Scores 0-3 indicate the presence of gingivitis, whereas scores 4-6 indicate the presence of periodontitis. The Ramfjord’s index was flexible since it can be used as the whole mouth measurement or a measurement of six index teeth only. The index teeth were called ‘Ramfjord teeth’ and included: maxillary right first molar, maxillary left central incisor, maxillary left first premolar, mandibular left first molar, mandibular right central incisor, and mandibular right first premolar (Figure 2,a). The index was initially developed to measure mesial, midbuccal, and distal sites around teeth. However, it was later modified to measure only the mesial and midbuccal sites. 11 Both Russel and Ramfjord realized the importance of examiner training and their calibration before conducing the periodontal examinations (Ramfjord SP, 1959; Russell AL, 1956). This was especially required for the Ramfjord’s index since CAL measurements tend to more challenging to record. Ramfjord’s index, in contrast to the widely used Russell’s index, were seldom used in epidemiological research (Beltran-Aguilar ED et al., 2012). Figure 2. Ramfjord index teeth and Community Periodontal Index of Treatment Needs (CPITN) index teeth, a) Ramfjord index teeth: maxillary right first molar, maxillary left central incisor, maxillary left first premolar, mandibular left first molar, mandibular right central incisor, and mandibular right first premolar, b) CPITN index teeth: maxillary first and second molars, maxillary right central incisor, mandibular first and second molars, and mandibular left central incisor. The six sextants that divide the teeth into 6 segments (two posterior and one anterior segment in each arch) were illustrated. CPITN: Community Periodontal Index of Treatment Needs. *Figure of Human dental arches–upper and lower: © Kaligula, retrieved from Wikimedia.org and was used under the Creative Commons Attribution-Share Alike 3.0 Unported license. Periodontal indices have been criticized due to several limitations (Baelum V & Lopez R, 2013; Beltran-Aguilar ED et al., 2012; Burt BA, 1991; Papapanou P & Lindhe J, 2015). Periodontal indices lack precision since periodontal clinical parameters were recorded as either present or absent (e.g., Russell’s periodontal index) or employed categorical measurements (in 3 mm increments) rather than using more precise measurements (e.g., Ramfjord’s periodontal disease index) (Ramfjord SP, 1959; Russell AL, 1956). The notion of gingivitis invariably leading to 12 periodontitis in a linear pattern was criticized for being a “built-in” assumption in periodontal indices since the assigned scores diagnose gingivitis and periodontitis as a continuum then they are summarized into population mean scores, this resulted in loss of variations (Baelum V & Lopez R, 2013; Burt BA, 1991). Other criticisms of periodontal indices include the complexity of some indices that required extra training and calibration of examiners; underestimation of periodontal disease prevalence; indices that relied on recording the gingival bleeding and pocket formation were considered reversible indices since these clinical parameters tend to fluctuate or change with treatment (Beltran-Aguilar ED et al., 2012; Papapanou P & Lindhe J, 2015). Despite the criticisms and right before the indices era was abandoned, the World Health Organization adopted the Community Periodontal Index of Treatment Needs (CPITN) (Ainamo J et al., 1982). The CPITN along with its further modifications had been the most widely used index globally until nowadays. Of importance, that the CPITN index was mainly designed for assessing the periodontal treatment needs in populations rather than for describing the periodontal disease in populations (Papapanou P & Lindhe J, 2015). The CPITN clinical measurements were used a World Health Organization periodontal probe that has a 0.5 mm ball tip, with a black band covering 3.5-5.5 mm, and two rings placed at 8.5 and 11.5 mm (Ainamo J et al., 1982). In addition, these measurements are performed at the index teeth to represent sextants (Figure 2, b). The sextant could be examined if two or more teeth are present in it and these teeth are not indicated for extraction. If only one tooth is present, it could be included in the adjacent sextant, and the most severe score represents the sextant. No replacement is done if any of the index teeth are missing, and the measurements are performed only at the mesiobuccal and midbuccal sites. The CPITN index teeth are the maxillary first and second molars, maxillary right central incisor, mandibular first and second molars, and mandibular left central incisor. The CPITN codes are presented in Table 1, where the individual treatment needs score is assigned based on the most severe condition code of the whole mouth. The treatment needs scores range from 0 to 4; score 0 means no treatment need; score 1 indicates need to improve oral self-care; scores 2 and 3 mean there is a need for periodontal debridement and improvement in oral self-care; and the score 4 that there is need for advanced periodontal treatment. Although the CPITN was not advocated for studying the periodontal disease distribution, it has been widely used for reporting the periodontal conditions in populations particularly in developing countries (Beltran-Aguilar ED et “At the verge of the exhaustion of the era of periodontal indices, an unfortunate digression was made when the World Health Organization in 1982 endorsed the Community Periodontal Index of Treatment Needs (Ainamo J et al., 1982) as an extension of the Periodontal Treatment Need System (Johansen JR et al., 1973) of 1973. This development sparked the use of the Community Periodontal Index of Treatment Needs for countless assessments of periodontal disease treatment needs in populations and population groups, to little avail.” (Baelum V & Lopez R, 2013). 13 al., 2012; Papapanou P & Lindhe J, 2015). The limitations of the CPITN for epidemiological use include the hierarchal scoring based on the inherent assumption that when a pocket is present (scores of 3 or 4), calculus and bleeding are also present; the index measures PPD rather than CAL which means that the index scores can fluctuate or change after treatment. Thus, the CPITN index can estimate the periodontitis prevalence in populations with possible information bias because it relies on a potentially reversible PPD scores in addition to the use of partial mouth recording protocol (PRP). The index also uses incremental measurements of PPD rather than precise measurements. Thus, CPITN did not seem to offer an advantage over the inherent limitations of the previous periodontal indices (Baelum V & Lopez R, 2013; Baelum V & Papapanou PN, 1996; Beltran-Aguilar ED et al., 2012). Moreover, the use of the CPITN for assessing the treatment needs and treatment planning in populations is also questionable. Table 1. Community Periodontal Index of Treatment Needs (CPITN) codes and it's modification, Community Periodontal Index (CPI) by the World Health Organization. Periodontal Index Periodontal parameter Codes Criteria Community Periodontal Index for Treatment Need (CPITN) (Ainamo J et al., 1982) Gingival bleeding, calculus, and Periodontal Probing Depth (PPD) 0 Healthy periodontium. 1 Bleeding observed after probing. 2 Calculus detected during probing, but the black band on the WHO probe is visible. 3 PPD 4-5 mm (the gingival margin is within the black band of the probe). 4 PPD ≥6 mm (black band on the probe is not visible). X Excluded sextant (<2 teeth present). 9 Not recorded. Modifications for the Community Periodontal Index (CPI) (World Health Organization, 1997) Clinical Attachment Loss (CAL) Codes Criteria 0 CAL 0-3 mm 1 CAL 4-5 mm (CEJ within the black band of the probe). 2 CAL 6-8 mm (CEJ between the black band and the 8.5 mm ring). 3 CAL 9-11 mm (CEJ between the 8.5 mm and 11.5 mm rings). 4 CAL ≥12 mm or more (CEJ beyond the 11.5 mm ring). X Excluded sextant (<2 teeth present). 9 Not recorded (CEJ neither visible nor detectable). CEJ: Cementoenamel junction. PPD: Periodontal Probing Depth, CAL: Clinical Attachment Loss. 14 A modification to the CPITN was described in the fourth edition of the World Health Organization manual for oral health survey basic methods, following which it was referred to as the Community Periodontal Index (CPI) (World Health Organization, 1997). The use of index for evaluating the treatment needs was abandoned, and measurement of CAL was included. The CPI scoring is presented in Table 1. A further modification to the CPI was published in the 5th edition of the World Health Organization manual for oral health survey basic methods to measure gingival bleeding and PPD considering the whole mouth examination (World Health Organization, 2013). The calculus measurements were removed. Also, the gingival bleeding, PPD and CAL are reported separately. Nevertheless, most of the limitations of the original CPITN still apply to its updated versions. Figure 3. Illustrations of periodontal measurements, a) periodontal probing depth (PPD) is measured from the gingival margin to the depth of pocket or sulcus while clinical attachment loss (CAL) is measured from cementoenamel junction (CEJ) to the apical base of the pocket; b) six sites that are measured around each tooth as part of periodontal assessments: mesiobuccal, midbuccal, distobuccal, mesiolingual, midlingual, and distolingual. The indices era where mean index scores were reported was abandoned after improving measurement approaches; by replacing indices by site-specific measurements (Baelum V & Lopez R, 2013; Papapanou P & Lindhe J, 2015). This transition to site specific measurements resulted in several implications since it allowed the identification of the variations in periodontitis prevalence, its severity, extent, patterns, and rates of progression as stated in section 1.1. Site specific measurements for periodontitis require the assessment of periodontal clinical parameters including the CAL, PPD and recessions. Both CAL and PPD are among the main clinical parameters that reflect the damage to periodontal tissues (Figure 3). CAL mainly reflects the accumulative disease experience while the PPD better reflects the current disease status (Leroy R et al., 2010). PPD is measured from the gingival margin to the apical base of a pocket or sulcus (Armitage GC, 2004). While the PPD measurements are conducted circumferentially 15 around the tooth, the deepest measurements are recorded around 6 sites per tooth: mesiobuccal (MB), midbuccal (B), distobuccal (DB), mesiolingual (ML), midlingual (L), and distolingual (DL). Recording the PPD is important since periodontal pockets are considered as a habitat for biofilm. The reduction of PPD measurements is one of the main goals of the periodontal therapy; thus, the reduction in PPD is considered as an indicator of periodontal treatment effectiveness. The disadvantages of using PPD include the lack of precision in estimating the damage to the periodontal tissues since the level of gingival margin tends to fluctuate either by treatment or by degree of swelling. As an example, having a bulbous gingival margin due to swelling may increase the PPD measurement by 2 mm without reflecting the actual tissue damage (Armitage GC, 2004). In addition, PPD may result in poor reliability of measurements compared with CAL (Dye BA et al., 2014). Due to the abovementioned limitations, PPD is considered a less desirable indicator to be used in epidemiological studies compared with CAL (Beltran-Aguilar ED et al., 2012). Similar to the PPD, both CAL and recessions are ideally measured circumferentially around the tooth while recorded at the deepest site that is closer to these 6 sites per tooth: MB, B, DB, ML, L, and DL. Recessions, defined as the exposure of root surface, are measured from the CEJ to the margin of the gingiva (Armitage GC, 2004). CAL can be either measured using direct method form the cementoenamel junction (CEJ) to the base of the pocket (Corraini P et al., 2013), or indirectly by adding the recession to the PPD measurements (Ramfjord SP, 1959). CAL is considered as the most valid clinical indicator that reflects the past disease damage since it is measured using a fixed reference point (the CEJ) (Armitage GC, 2004). It is also the most reliable indicator of disease stability versus progression when measured over time (Dye BA et al., 2014; Goodson J, 1986). These advantages make CAL a suitable indicator for epidemiological studies (Beltran-Aguilar ED et al., 2012). However, the CAL measurement is more challenging to perform clinically since it requires locating the CEJ (Armitage GC, 2004). Unless there is recession where the CEJ is clearly visible, locating the CEJ using the tactile method makes the measurement more difficult in some cases. 1.2.1 Concurrent periodontitis case definitions in epidemiological research Since the transition from indices era, the population-based outcome measures for periodontitis are prevalence, extent, and severity (Holtfreter B et al., 2015). Prevalence can be defined as the proportion of individuals with periodontitis in a given population. Extent can be defined as the mean proportion of sites with periodontitis. Both periodontitis prevalence and extent require case definitions at specific disease thresholds, whereas periodontitis severity is presented as an averaged CAL or PPD. The challenges often encountered with periodontitis case definitions is that they continuously evolve or defined differently among studies. Consequently, making it difficult to compare findings among studies, to assess distribution over different geographical areas, or time trends of periodontitis distribution even within a specific population (Baelum V & Lopez R, 2013; Beltran-Aguilar ED et al., 2012; Papapanou P & Lindhe J, 2015). Since the identification of exposures associated with periodontitis tend to 16 be sensitive to the thresholds used in definitions, this has further complicated the issues resulting from the lack of universal definitions (Manau C et al., 2008; Preshaw PM, 2009; Tonetti MS et al., 2005). While clinical definitions and classifications for periodontitis continue to evolve based on updates in evidence, case definitions recommended for epidemiological research need to be empirical, simplified, and more stable to allow comparisons across studies (Baelum V & Lopez R, 2013; Manau C et al., 2008; Preshaw PM, 2009). Some of the most prominent classifications and definitions since 1977 are depicted in Figure 4. Clinical classifications and definitions may not be suitable for epidemiological studies since they typically have too many disease categories, more complex, and require a more comprehensive patient examination to arrive at specific clinical diagnosis (American Academy of Periodontology, 2015; Caton J, 1989; Caton JG et al., 2018; Lindhe J et al., 1999). To date, there is no universally acceptable definition for periodontitis to be used in epidemiological studies (Holtfreter B et al., 2015). For periodontitis extent, the joint EU/USA epidemiology group in 2015 (Holtfreter B et al., 2015) suggested using the following thresholds to allow for universal comparisons as standards for reporting: two thresholds for CAL (CAL ≥3 mm and CAL ≥5 mm) and two thresholds for PPD (PPD ≥4 mm and PPD ≥6 mm). In addition, this group suggested reporting the extent at several CAL and PPD thresholds for different age cohorts to enable age-related comparisons among studies. Two of the most important empirical definitions for periodontitis prevalence in epidemiological studies are the case definitions suggested by the European Federation of Periodontology (EFP) (M. Tonetti & Claffy, 2005) and case definitions recommended by the U.S. Centers for Disease Control and Prevention (CDC) and the AAP (Eke PI et al., 2012; Page RC & Eke PI, 2007). The EFP recognized the need for standardization of case definitions mainly to identify the associations between risk factors and periodontitis (Tonetti MS et al., 2005). This was an important initiative since the identification of exposures associated with periodontitis tends to be dependent upon both the extent and severity thresholds in case definitions (Manau C et al., 2008). The two defined categories were (Tonetti MS et al., 2005): 1. CAL ≥3 mm at ≥2 non-adjacent interproximal sites of teeth. 2. CAL ≥5 mm at ≥30% of the interproximal sites of all teeth. The justification of the first definition is that it is more sensitive in identifying subjects with periodontitis including “incipient” periodontitis; sensitive case definition means being inclusive of periodontitis cases by using a lower disease threshold. The second threshold is more specific as it attempts to identify generalized and severe cases; meaning being exclusive to those with high disease thresholds. The selection of interproximal sites at two non-adjacent teeth is to minimize the chance of including CAL due to other etiologies such as midbuccal or midlingual recessions that may result from traumatic tooth brushing, endodontic involvement of a single isolated site, or dental caries. 17 Another important initiative in the proposed definitions by the EFP is that they defined the minimum thresholds to indicate the periodontitis progression in longitudinal studies as follows: 1. CAL ≥3mm at ≥2 interproximal sites of teeth. 2. Radiographic evidence of ≥2 mm at ≥2 teeth (as a substitute for the first criteria for CAL). Despite that the EFP definitions were proposed for identification of exposures associated with periodontitis, the definitions were not recommended to be used for defining the prevalence of periodontitis (Tonetti MS et al., 2005); no justification for such recommendation had been provided. Additionally, unlike the CDC/AAP definitions, the EFP definitions were not commonly used in epidemiological studies. On the other hand, the CDC/AAP definitions, were widely used globally and were recommended for standard reporting in epidemiological studies for the time being (Holtfreter B et al., 2015). In 2007, the CDC/AAP suggested two definitions: severe and moderate periodontitis (Page RC & Eke PI, 2007). In 2012, an update was done to include “mild periodontitis” (Eke PI et al., 2012). The three current case definitions are as follows: 1. Severe periodontitis, defined as CAL ≥6 mm at ≥2 interproximal sites (not in the same tooth) and PPD ≥5 mm at ≥1 interproximal site (can be at one of the two teeth with CAL). 2. Moderate periodontitis defined as CAL ≥4 mm at ≥2 interproximal sites (not in the same tooth), or PPD ≥5 mm at ≥2 interproximal sites (not in the same tooth). 3. Mild periodontitis defined as CAL ≥3 mm at ≥2 interproximal sites and PPD ≥4 mm at ≥2 interproximal sites or PPD ≥5 mm at ≥1 interproximal site. The CDC/AAP definitions of the periodontitis can generally be considered more conservative than the EFP definitions because they use higher disease thresholds; thus, possibly increasing the specificity of detecting disease. In addition, the CDC/AAP includes two periodontal parameters, the CAL and PPD, rather than solely relying on CAL. Importantly, the original publications of the definitions by the CDC/AAP did not explicitly mention that these categories are mutually exclusive (independent). However, a recent review revealed that periodontitis cases should be diagnosed at severe thresholds; those cases that do not fit in the severe should be included in the moderate category; and those that do not fit in moderate category should be considered as either mild or non-cases (Eke PI et al., 2020). Despite being advocated for standards of reporting for the time being, the CDC/AAP definitions have potentially resulted in some ambiguity and have been applied differently across studies (Akinkugbe AA et al., 2015; Beltran-Aguilar ED et al., 2012; Eke PI et al., 2018, 2020; Romano F et al., 2019; Tran DT et al., 2014). This ambiguity can be in part related to methods of handling cases in gray zones. A hypothetical example to demonstrate this issue can 18 be a case that has CAL ≥10 mm in ≥2 interproximal sites but no PPD ≥5 mm at an interproximal site would fall in a gray zone; such case could be classified as moderate despite of the severe CAL. Another issue with the criteria is moderate category being highly heterogenous since the cases can be diagnosed either using the CAL thresholds at two sites or PPD thresholds at two sites. For example, a PPD threshold of ≥5 mm in the absence of recession, could potentially correspond with a CAL ≥3 mm; thus, overlapping with a mild category. Furthermore, moderate category could potentially have cases with lower disease thresholds than mild category if PPD ≥5 mm had a corresponding CAL ≥2 mm. This means that an individual, as stated in a previous example, with (CAL ≥10 mm in ≥2 interproximal sites but no PPD ≥5 mm) and those with (PPD ≥5 mm that corresponds to CAL ≥3 mm or CAL ≥2 mm at ≥2 interproximal sites) are both classified under moderate category. Consequently, moderate category is a potentially heterogeneous category that could include more severe cases than severe category and milder cases than mild category. Of importance, the authors who reported the CDC/AAP definitions have seldomly applied the criteria as proposed; their publications classify cases as severe, non-severe (combined mild and moderate), total cases, and non-cases (Eke PI et al., 2015, 2016, 2018, 2020). Such classification: severe, total cases, and non-cases can be more reasonable since it simplifies the definitions and potentially minimizes the issues with cases falling in gray zones, however this has not been proposed as an update or recommended for universal use. Nevertheless, some studies reported their findings by grouping some categories (Akinkugbe AA et al., 2015; Romano F et al., 2019). The issues presented in the CDC/AAP definitions can more broadly highlight the fact that proportion of cases in the gray zone and potential overlaps need to be considered when evaluating the validity of case definitions and classification systems. In epidemiological terms, the gray zone cases can be an indication of having a misclassification bias, that is, “the erroneous classification of an individual, a value, or an attribute into a category other than that to which it should be assigned” (Porta MS, 2014). When misclassification occurs similarly in all study groups, it is called a non-differential misclassification; the bias can be only towards the null. In contrast, probability of misclassification that varies among study groups results in a non-differential misclassification; this type of bias can be either towards or away from the null. As exemplified in the above-mentioned examples, using the CDC/AAP moderate category could potentially result in a differential misclassification bias. A hypothetical example can demonstrate how this phenomenon of misclassification occurs; periodontitis can be naturally measured as a continuous variable range from 0 CAL to the loss of the entire attachment. For this continuous variable to diagnose a disease, there is always a trade-off between sensitivity and specificity across different disease thresholds. When dichotomization of the continuous variable is introduced based on a certain disease threshold, it classifies individuals as cases or non-cases. Due to the trade-offs between sensitivity and specificity, any selected threshold for dichotomization could result in either a compromised sensitivity or specificity (or both). The selection of higher disease threshold produces more specific definition at the expense of having lower sensitivity, and vice versa. These compromised results arising from dichotomization can be defined as 19 misclassification bias. When more disease categories are introduced, more sensitivity/specificity cut-offs are introduced and could amplify the compromised sensitivities or specificities at multicategories; consequently, could increase the misclassification bias (more cases in gray zones). Such issues have not been considered when classifying periodontitis into too many categories and subcategories without providing compelling justifications (Armitage GC, 1999; Caton J, 1989; Caton JG et al., 2018; Eke PI et al., 2012; Page RC & Eke PI, 2007). Since the EFP definitions are seldomly used and studies are applying the CDC/AAP differently, then the need for universal definition continues to be an outstanding issue. As stated earlier, lack of universal standard definitions means that outcomes cannot be compared among different studies, trends of disease distribution are difficult to trace due to the continuous change and updates of definitions, and more importantly, this could result in spurious reporting of associations with periodontitis. In a study that could not demonstrate a significant association between periodontitis and adverse birth outcomes using a pre-specified periodontitis definition, the authors retrieved different definitions suggested for periodontitis in the literature to examine how they may lead to different interpretations of their study findings (Manau C et al., 2008). A literature search retrieved 14 definitions for periodontitis as a dichotomous variable and 50 periodontitis definitions as continuous variables. This study found statistically significant associations in 6 out of 14 dichotomous outcomes and in 17 out of 50 continuous outcomes. The authors have concluded that “the results of this secondary analysis support the hypothesis that the significance of the association between periodontal disease and pregnancy outcomes may be determined by the periodontal disease definition or measurement used”. However, this issue generally applies to any associations between an exposure and an outcome. Unless universal standards for reporting of case definitions is enforced in publications, there is a potential room for acquiring statistically significant results by just altering the thresholds of case definitions; (Borrell LN & Papapanou PN, 2005; Manau C et al., 2008; Preshaw PM, 2009). 20 Figure 4. Some of the most prominent periodontitis case definitions and classification systems since 1977. The case definitions recommended for epidemiological research use are outlined in orange circles while the rest of the definitions were recommended as part of clinical classification systems. AAP: the American Academy of Periodontology, CDC: the Centers for Disease Control and Prevention, EFP: the European Federation of Periodontology, CAL: clinical attachment loss. Despite the frequent evolvements of case definitions and classifications of periodontal disease, the rationale behind the defined disease thresholds continues to be ambiguous or inadequately justified. Perhaps one way to achieve universally accepted definitions is to provide explicit statements regarding the underlying rationale by supporting it with compelling evidence; this could in part resolve some debates around the case definitions. Among a few publications that provided justifications for their definitions were both the EFP and CDC/AAP which were briefly discussed (Eke PI et al., 2012; Page RC & Eke PI, 2007; Tonetti MS et al., 2005). In the EFP definitions, the minimum threshold was justified as being a balance between selection of sensitive and inclusive thresholds while exceeding a margin of error in incremental measurements that is equivalent to “2.5 mm” (Tonetti MS et al., 2005). However, an error of incremental measurements equivalent to 2.5 mm have been part of the past since current periodontal probe has up to 1 mm precision and margin of error. 21 An alternative explanation that could possibly justify the selection of CAL ≥3 mm as a minimum threshold in epidemiological research is that several factors could add up to lower the overall measurement precision such as having limited tools, equipment, number of personnel/examiners outweighing the number of individuals to be examined, limited time, and the need for multiple examiners (often non-specialists) to conduct the assessments (Beltran-Aguilar ED et al., 2012). In addition, having a CAL ≥1 mm tends also to be a universal finding even in young individuals (Baelum V & Lopez R, 2013) as indicated by findings from several studies (Albandar JM, 2002; Baelum V, Fejerskov O, et al., 1988; Brown LJ et al., 1996; Lopez R et al., 2001). Therefore, a selection of a minimum threshold of CAL ≥3 mm to define periodontitis cases in epidemiological research could have been justified in order to exceed the margin of measurement error of 1mm and avoid a selection of a low threshold that will universally classify individuals as having periodontitis. In contrast to the lower periodontitis thresholds in case definitions that are justified by being inclusive, higher disease thresholds are justified by being specific based on less plausible rationales. The EFP justified the selection of the higher disease threshold by “to identify only cases with substantial extent and severity” (Tonetti MS et al., 2005), without further explanation. For the CDC/AAP definitions, it was suggested that severe periodontitis needs a minimum threshold that exceeds a CAL ≥5.5 mm which was calculated based on a measurement error of 1.07 mm and a histological distance from bone crest to the CEJ that can be up to a 3.36 mm (Page RC & Eke PI, 2007). Thus, the threshold was selected to exceed a minimum CAL ≥5.5 mm to exclude potentially normal sites (without disease). It was not clear, however, why the distance from CEJ to bone crest was selected as a reference to differentiate sites with periodontitis from normal sites. Clinical measurements of PPD ideally stop at junctional epithelium by avoiding excessive probing force or may accidently penetrate the most coronal portion of connective tissue in inflamed tissues, however, it does not penetrate to bony crest during periodontal assessment (Fowler C et al., 1982; Garnick JJ & Silverstein L, 2000; Robinson PJ & Vitek RM, 1979). Another source of ambiguity in proposed periodontitis case definitions is the lack of clear practical implications to support specific disease thresholds. Due to the lack of clear distinction between what defines health and disease, a review suggested that such distinction can be made based on “benefits from therapy”; following the approach used in diagnosing diabetes or hypertension; as such approach could be adjusted based on the presence of risk factors (Baelum V & Lopez R, 2013). It has not been made clear, however, what could possibly define “benefits from therapy”. In clinical periodontology, periodontal treatment is mainly based on a “critical probing depth” (Lindhe J et al., 1982), which can be defined as the balance between risk and benefit from periodontal therapy in terms of loss versus gain in attachment. For the non-surgical treatment, the critical probing depth was estimated to be a 2.9 mm whereas for surgical treatment a 4.2 mm was suggested. The critical probing depth for surgical treatment was revised later to suggest a threshold of 5.3 mm (Heitz-Mayfield L & Lang N, 2013). However, the use of critical probing 22 depth can be challenged by the inherent limitations of using PPD since it tends to be less reliable indicator of periodontitis in epidemiological studies (Beltran-Aguilar ED et al., 2012; Papapanou P & Lindhe J, 2015). In the latest update of periodontitis classification by the AAP/EFP, practical implications for patient management are used to diagnose periodontitis, though, in a much more complex approach (Caton JG et al., 2018; Tonetti MS et al., 2018). The current periodontitis diagnosis has adopted the cancer staging and grading framework (Tonetti MS et al., 2018). Staging is assigned to the individual mainly based on CAL severity where stage I (mild) has CAL range 1-2 mm; stage II (moderate) with CAL range 3-4 mm; stage III (severe) with CAL ≥5 mm; stage IV (very severe) with CAL ≥5 mm. Alternatively, staging can be based on proportion of bone loss on radiographs, though, such approach is less desirable as it tends to be less sensitive to detect early stages as indicated by the authors. The staging is further modified based on several treatment complexity factors such as: PPD, tooth loss, furcation involvements, residual ridge defects, and total numbers of remaining teeth. Furthermore, periodontitis extent (localized versus generalized based on 30.0% cut off) and pattern (molar-incisor) are added to the diagnosis as descriptors. Stage I represent the borderline between gingivitis and periodontitis which requires professional mechanical debridement and enforcement of oral hygiene to prevent the disease progression. Although stage II represents a further progression of attachment loss, the management is essentially the same as in stage I which is limited to non-surgical treatment. Stage III represents the borderline between stable function of the supportive periodontal structures and the unstable function as present in stage IV. Surgical periodontal treatment is required for stages III and IV with an additional need for functional rehabilitation in stage IV. After staging is determined, grading is assigned based on the rate of progression or case phenotype (Tonetti MS et al., 2018). Risk factors such as glycemic control of diabetes mellitus and smoking status are considered grade modifiers. Further elaborations of how to arrive at a diagnosis and addressing cases in “gray zones” along with several supplementary charts and simplified algorithms were published, which may reflect the level of complexity of such diagnostic criteria (Kornman KS & Papapanou PN, 2020; Tonetti MS & Sanz M, 2019). Beside incorporating the practical implications in the current diagnostic criteria of periodontitis by the AAP/EFP (Tonetti MS et al., 2018), several longstanding issues have been addressed. Diagnosing periodontitis under one main category has partly resolved the ambiguity in differentiation between categories that were directly or indirectly based on age since the 1977 (Highfield, 2009). This can be an important step since diagnosing periodontitis based on age categories can be in part responsible for separating findings between the young and older individuals in the literature. The uniqueness of current diagnostic criteria of periodontitis is that it seems to incorporate the natural course of periodontitis. Though, the diagnosis of periodontitis has mainly focused on the latest stages of the natural history of disease (asymptomatic, symptomatic, and terminal stages) since the management of these stages mainly aims to reduces the patient specific risk factors and prevent further progression by clinicians. Therefore, the 23 diagnostic criteria can mainly help the clinicians to address the patient needs but it was not made clear how these criteria can be incorporated into research. 1.2.2 Full mouth versus partial mouth recording protocols During the indices era (1950s to 1980), some indices were suggested where assessments were done at some preselected teeth using PRPs (Ainamo J et al., 1982; Ramfjord SP, 1959). PRP at Ramfjord’s index teeth was considered as an alternative to full mouth recording protocol (FRP) in the Ramfjord’s periodontal disease index which can be potentially due to difficulty of CAL measurements (Ramfjord SP, 1959). Such approach of recording CAL using PRP was also recommended in the modified CPI, whereas it was recommended to record PPD and bleeding on probing using FRP (World Health Organization, 2013). Thus, it can be inferred that the goal of recording CAL at PRP (in specific) is to minimize the inherent challenges in clinical examinations. The gold standard method of periodontal recordings in epidemiological studies is to use FRP which is measured at six sites per tooth for a total of 28 teeth (excluding third molars) (Holtfreter B et al., 2015). However, periodontal examination time can be extensive; measurement of PPD and CAL alone using the FRP may take approximately 40 minutes per individual (Preisser JS et al., 2018). Therefore, PRP can be an alternative for FRP when considering the time, cost, and number of personnel required for conducting population-based studies. PRP might be also a desirable alternative from the research participants’ perspective due to decreased chair time and potential discomfort compared to FRP; these advantages can be especially important to consider when studying elderly population (Siukosaari P et al., 2012). The downside of using PRPs as compared to FRP, however, is the potential bias. Several PRPs were suggested in the literature mainly by measuring fixed number of sites or teeth in a study population (Hunt RJ & Fann SJ, 1991; Kingman A et al., 2008; Mills WH et al., 1975; Relvas M et al., 2014; Silness J & Roynstrand T, 1988; Susin C et al., 2005), or by using random site selection method (RSSM) which requires selection of sites per individual by simple random sample of certain number of sites (for example can be 36 or 42 sites) (Akinkugbe AA et al., 2015; Beck JD et al., 2006; Preisser JS et al., 2017). Based on a systematic review (Tran DT et al., 2013), a literature search retrieved approximately 32 PRPs. Two protocols based on random-half-mouth (RHM) examination at partial sites were used in two of the U.S. national surveys: National Health and Nutrition Examination Survey (NHANES) III examined the MB-B sites at half mouth (HM) and the NHANES IV examined the (HM)MB-B-DB (Dye BA & Thornton-Evans G, 2007; Eke PI et al., 2010). Several other PRPs measured the full-mouth (FM) at partial sites were also suggested such as (FM)MB-B-DB and (FM)MB-B-DL. According to the systematic review, the most frequently used PRPs included the Ramfjord index teeth, (HM)MB-B-DB, (HM)MB-B, RHM at 6 sites, (FM)MB-B-DB, CPITN index teeth, (FM)MB-B, (HM)MB-B-DL, and (FM)MB-B-DL (Tran DT et al., 2013). Some of the commonly used protocols were depicted in Figure 5. 24 When PRPs are compared with FRP for estimating periodontitis prevalence using indicators of diagnostic accuracy, the specificity and positive predictive values are always 100.0% since PRP can only identify cases with periodontitis that were already identified using a FRP (Kingman A et al., 2008; Preisser JS et al., 2018). Therefore, the sensitivity was recommended for evaluating the accuracy (Kingman A et al., 2008). Another method recommended for comparisons was by quantifying the bias, defined as the difference between the estimated and true values (Kingman A et al., 2008). Bias is often estimated as an absolute bias or relative bias. Absolute bias can be calculated as (PRP estimated value - FRP true value) (Kingman A et al., 2008). Relative bias can be calculated as [(PRP estimated value - FRP true value)/FRP true value] (Beck JD et al., 2006). A bias value that has a negative sign indicates an underestimation of the FRP value, while a positive sign indicates an overestimation of the FRP value. The relative bias was defined differently by Kingman et al. where relative bias = (PRP estimated value/FRP true value); without subtracting the FRP value from PRP value at the numerator (Kingman A et al., 2008). The relative bias is also sometimes reported as percentage when multiplied by 100.0%. However, the absolute bias tends to be reported similarly across different studies. Other methods of comparison of PRP with FRP performance include the use of intraclass correlation coefficient (Chu Y & Ouyang X, 2015; Dowsett SA, Eckert GJ, et al., 2002b; Kingman A et al., 2008), presenting the difference as underestimation or overestimation in proportion to the true values (Beck JD et al., 2006; Chu Y & Ouyang X, 2015), using receiver operating characteristics curve and area under the curve (Botelho J et al., 2020; Nomura et al., 2020), inflation factors (Susin C et al., 2005), or concordance and discordance measures (Heaton, Garcia, et al., 2018; Relvas et al., 2014). 25 Figure 5. Illustrations of some of commonly reported periodontal recording protocols. FRP: Full mouth recording protocol, (FM)MB-B-DB: full mouth at mesiobuccal-midbuccal-distobuccal sites, (FM)MB-B-DL: full mouth at mesiobuccal-midbuccal-distolingual sites, 84 RSSM: 84 sites selected using random site selection method, CPITN: Community Periodontal Index of Treatment Needs, RHM: random half mouth, (HM)MB-B: random half mouth at mesiobuccal-midbuccal, NHANES: National Health and Nutrition Examination Survey, (HM)MB-B-DB: random half mouth at mesiobuccal-midbuccal-distobuccal, (HM)MB-B-DL: random half mouth at mesiobuccal-midbuccal-distolingual, and Ramfjord teeth. *Figure of Human dental arches–upper and lower: © Kaligula, retrieved from Wikimedia.org and was used under the Creative Commons Attribution-Share Alike 3.0 Unported license. 26 Studies that evaluated the impact of PRP for estimating periodontitis prevalence found that the degree of underestimation differed based on the type of PRPs; where absolute bias ranged from |2.1|% to |26.1|% (Beck JD et al., 2006; Dowsett SA, Eckert GJ, et al., 2002b; Kingman A et al., 2008; Tran DT et al., 2014). Among the factors that impacted the estimation of periodontitis prevalence, PRPs that included a higher number of sites per tooth had a smaller absolute bias in estimating prevalence; for example, (FM)MB-B-DB or (FM)MB-B-DL had an absolute bias ranging from |3.8|% to |13.8|% compared with PRP with a fewer number of sites such as (HM)MB-B-DB or (HM)MB-B-DL where absolute bias ranged from |9.0|% to |20.8|% (Beck JD et al., 2006; Susin C et al., 2005; Teixeira F et al., 2020). Moreover, the PRP type had an impact on estimating prevalence even when the same number of sites was used; for example, the absolute bias for (FM)MB-B-DB was |13.8|% while for RHM it was |5.9|% despite having the same total number of 84 sites (Susin C et al., 2005). A higher severity of CAL in periodontitis case definition had a lower sensitivity; as an example, RHM had a sensitivity of 91.5% at CAL ≥4 mm compared with a sensitivity of 82.8% at CAL ≥6 mm threshold (Susin C et al., 2005). In 24-year young adults where a prevalence of PPD ≥4 mm was 3.3%, the sensitivity of different PRPs was 29.2% for Ramfjord index teeth; 66.7% for CPITN index teeth; ranged from 58.3% to 70.8% for RHM at two opposing diagonal quadrants (Peres MA et al., 2012). In a study on untreated Guatemalan population, the correlations between PRP and FRP in estimating prevalence at CAL ≥6 mm was lower in individuals <35 years (correlations ranged from 0.74 to 0.79) compared to older individuals who were ≥35 years (correlations ranged from 0.92 to 0.97) (Dowsett SA, Eckert GJ, et al., 2002b). Ramfjord index teeth protocol had consistently lower performance in estimating prevalence across all age cohorts compared with RHM. This study on untreated Guatemalan population, is one of rare studies that reported direct age-based comparisons across a wide age range (18 to 78 years). Other studies precluded direct comparisons as these reported their findings in younger individuals (Eaton KA et al., 2001; Peres MA et al., 2012; Thomson WM & Williams SM, 2002) or older individuals (Beck JD et al., 2006; Tran DT et al., 2014). Although some studies considered recruiting wide age range (14 to 103 years), no age-based comparisons were conducted across different age cohorts (Romano F et al., 2019; Susin C et al., 2005). When periodontitis severity was estimated using PRPs, overall findings suggest that it could be either underestimated or overestimated compared to that of FRP; the overall absolute bias ranged from 0.00 to |0.43| (Beck JD et al., 2006; Chu Y & Ouyang X, 2015; Kingman A et al., 2008; Relvas M et al., 2014; Teixeira F et al., 2020; Vettore MV et al., 2007). Periodontitis severity estimated using PRP can result in different magnitude of bias based on the selected site types, number of sites, number of quadrants, or when using PPD versus CAL. Amongst 20 PRPs evaluated by Kingman et al., absolute bias of mean PPD was ≥|0.40| while absolute bias of mean CAL was ≥|0.17|; indicating that mean PPD resulted in a larger magnitude of bias compared to mean CAL (Kingman A et al., 2008). PRPs that had the smallest magnitude of bias and closest estimations to that of FRP included RHM, Ramfjord index teeth, and (FM)MB-B-DL where the absolute bias was <|0.04| (Kingman A et al., 2008). When RSSM protocols were compared to protocols with fixed selected sites of protocols with similar total number of sites, RSSM had no 27 bias in estimation while fixed selected sites either underestimated or overestimated both the mean PPD (absolute bias was ≤|0.23|) and mean CAL (absolute bias was ≤|0.05|) (Beck JD et al., 2006). The CPITN index teeth protocol when compared with 14 other PRPs resulted in the highest overestimation of periodontitis severity (absolute bias of mean CAL was |0.27|, and absolute bias of mean PPD was |0.4|) (Chu Y & Ouyang X, 2015). In contrast, RHM protocol had the best estimation of periodontitis severity among 19 different PRPs, and it had no bias in estimation of mean CAL or mean PPD (Chu Y & Ouyang X, 2015; Kingman A et al., 2008). Based on overall findings from several studies, the protocols based on RSSM and RHM seem to have the most superior performance and almost no bias for estimating periodontitis severity. Similar to periodontitis severity, PRPs either underestimated or overestimated periodontitis extent where the absolute bias ranged from to 0.0% to |4.4|% (Chu Y & Ouyang X, 2015; Relvas M et al., 2014; Teixeira F et al., 2020; Tran DT et al., 2016). The CPITN index teeth protocol overestimated the periodontitis extent; where the absolute bias was |4.4|% for mean % of CAL ≥4 mm (Chu Y & Ouyang X, 2015). RHM had the best performance in estimating periodontitis extent compared to 14 other PRPs where the absolute bias was ≤|1.99|% when estimating PPD or CAL extent (Chu Y & Ouyang X, 2015; Relvas M et al., 2014). In younger individuals, the periodontitis extent was found to be overestimated and the overall absolute bias was ≤0.4% for index teeth protocols (Eaton KA et al., 2001). Among the three main summaries of periodontitis in population-based studies, the two continuous outcomes (periodontitis severity and extent) had small bias magnitude when using PRPs. However, periodontitis prevalence (dichotomous outcome) had a major impact in its estimation when using PRPs. If only PRPs can be applied, Kingman et al. suggested the use of severity as a summary for periodontitis in a population (Kingman A et al., 2008). Furthermore, Kingman et al. suggested to evaluate the PRPs performance in a subset of population (about 5.0% to 10.0%) before it is used for the rest of study population. It was argued, however, that testing PRP in a 10.0% of the sample may not adequately represent population subgroups (Holtfreter B et al., 2015). Correction for the underestimated prevalence to represent the whole study population was suggested using a correcting factor based on the findings from the subset of the population (Dye BA, 2012; Susin C et al., 2005). Inflation factor which is an inverse function of sensitivity was suggested to correct for underestimated prevalence (Susin C et al., 2005). Another reported method for correcting the bias was the following formula: FRPprevalence = [ PRPprevalence / (1 - percent relative bias)] (Dye BA, 2012); such approach was employed for correcting the estimates of prevalence in two of the U.S. national surveys that used PRPs: NHANES III and IV (Eke PI et al., 2010). While majority of studies evaluated the impact of PRP performance for estimating the periodontitis prevalence, extent, and its severity, only a few considered examining the impact of PRP on estimating associations between the exposures and periodontitis. Kingman et al. stated that exposures’ distribution could be impacted by the 28 misclassification of periodontitis cases and findings would be attenuated towards the null (Kingman A et al., 2008). Similarly, Eke et al. assumed that since periodontitis is underestimated when using PRPs, then exposures associated with periodontitis would also be biased towards the null value, that is, leading to a non-differential misclassification bias (Eke PI et al., 2010). When impact of using PRPs on periodontitis sociodemographic and behavioral associations were evaluated in 24 years old individuals, RHM protocol resulted in the closest estimates to that of FRP when compared with Ramfjord and CPITN index teeth protocols. However, the exposures’ odds ratio (OR) were either underestimated or overestimated (Peres MA et al., 2012). Another study in 25-26 years old adults compared the impact of using different combinations of RHM on estimations of exposures (sex, smoking, and dental visit patterns) found that OR were either underestimated or overestimated (Thomson WM & Williams SM, 2002). Akinkugbe et al. adapted the calculation of absolute bias at the natural logarithm scale of OR and confirmed previous findings that PRPs could either underestimate or overestimate the OR of exposures including smoking, diabetes mellitus, alcohol consumption, and Body Mass Index (BMI) (Akinkugbe AA et al., 2015). The magnitude and direction of the bias were attributed to the PRP type and severity thresholds in periodontitis case definitions. A simulation study by Preisser et al., evaluated the impact of periodontitis misclassification on its associations due to using PRP, found that PRP mainly results in a differential misclassification bias, that is, the exposures can be either underestimated or overestimated (Preisser JS et al., 2018). This was attributed to a probability of periodontitis prevalence that is different between individuals who are exposed or unexposed, consequently leading to either underestimation or overestimation of ORs in PRP as compared to FRPs. Preisser et al. attributed the differential impact of periodontitis prevalence on distribution of exposures to the PRP type (specific site type and number of sites), periodontitis case definitions, and the periodontitis distribution in terms of extent and pattern in the mouth. In another simulation study by Heaton et al., the estimation of exposures using the CDC/AAP moderate periodontitis threshold resulted in a differential misclassification (underestimation or overestimation of OR), whereas employing the CDC/AAP severe periodontitis threshold resulted in a non-differential misclassification (consistently underestimated ORs) (Heaton B, Garcia RI, et al., 2018). In a study that evaluated the impact of using PRPs on two exposures (diabetes and cardiovascular disease), using NHANES 2009 to 2014 data, found that PRPs mainly underestimated the OR except when using CPITN index teeth protocol for the CDC/AAP severe periodontitis threshold (Alshihayb TS et al., 2020). However, the overall absolute bias ranged from |0.07| to |0.09|. The impact of PRP on estimation of exposures OR were attributed to the severity threshold of the periodontitis outcome and the exposures. The importance of identifying whether the misclassification of exposures is differential or non-differential can be possibly explained by attempts to predict the impact of PRPs on exposures OR based on its impact on prevalence; having a differential misclassification can possibly result in a less predictable misclassification compared with non-differential bias. Perhaps a more important consideration is how much does the PRP impact the interpretation of 29 periodontitis associations? if the PRP only results in a small bias magnitude, then the direction of the bias might be less of an issue. In the simulation study by Heaton et al., the magnitude of the bias was found to be dependent on the severity of periodontitis case definition, distribution of CAL and PPD when using the CDC/AAP definitions, and the size of associations (Heaton B, Garcia RI, et al., 2018). The relative bias of severe periodontitis ranged from |21.76|% to |30.38|% whereas using the moderate periodontitis thresholds resulted in a higher relative bias ranging from |8.59|% to |177.17|%. The simulation study, however, only evaluated the use of the RHM protocol. Other limitations and possible knowledge gaps related to estimation of periodontitis associations using PRPs may include that most studies evaluated the performance of PRP on exposures’ OR had narrow age group (24 years or 25-26 years) (Peres MA et al., 2012; Thomson WM & Williams SM, 2002), limited to older age group where age ranged from 52-74 years (Akinkugbe AA et al., 2015), or relatively small magnitude of associations (OR ranged from 1.04 to 1.26) (Alshihayb TS et al., 2020). Thus, evaluation of the impact of using PRP on associations by considering real individuals’ data (rather than simulation studies), wide age range, different magnitude of associations, and different PRPs are possibly still deficient. Earlier studies at a time of transitioning from using periodontal indices to site specific measurements almost solely relied on using PRPs to evaluate untreated periodontitis (Baelum V et al., 1996; Baelum V, Fejerskov O, et al., 1988; Cutress TW et al., 1982; Loe H, Boysen H, et al., 1978; Löe H et al., 1978, 1986; Timmerman MF et al., 1998, 2000; van der Velden U et al., 2006). It can be hypothetically assumed that performance of PRPs when studying untreated populations can result in a relatively small bias since those populations had an overall high prevalence, extent, and severity of periodontitis as compared to general populations. However, none of these earlier studies evaluated the potential bias of using such approach by comparing PRP performance with that of FRP. A relatively recent study, on untreated Guatemalan population, evaluated the impact of using two PRPs: RHM and Ramfjord index teeth to study periodontitis prevalence, severity, and extent (Dowsett SA, Eckert GJ, et al., 2002b). Using the two PRPs (RHM and Ramfjord), prevalence defined as PPD thresholds of ≥4 mm to ≥6 mm had an absolute bias ≤|21.0|%. When periodontitis prevalence was defined using CAL ≥3 mm to ≥7 mm, the resulted absolute bias was ≤|24.0|%. For periodontitis extent with CAL thresholds ranged from ≥3 mm to ≥7 mm, the absolute bias was ≤|0.9|%. For periodontitis extent with PPD thresholds PPD ≥4 mm to ≥6 mm, the absolute bias was ≤|1.4|%. For periodontitis severity, both mean PPD and mean CAL were ≤|0.04|. The overall performance of RHM protocol was superior to that of Ramfjord teeth protocol when estimating all three periodontitis outcomes. Thus, despite that the untreated Guatemalan population had an overall high periodontitis prevalence and extent which can hypothetically result in small bias in estimation of periodontitis outcomes, the use of Ramfjord teeth resulted in a drastic underestimation of periodontitis prevalence (up to 24.0% absolute bias). Such findings may potentially impact the interpretations of findings from other untreated populations that mostly relied on using PRPs when studying periodontitis. Thus, there is possibly a need for further investigation of the impact of using PRPs on estimation of periodontitis outcomes in untreated populations. In addition, the impact of using PRPs on estimating 30 exposures associations with periodontitis prevalence was not evaluated in that study on untreated population (Dowsett SA, Eckert GJ, et al., 2002b). When different PRPs were compared in a systematic review, PRPs that had best performance in estimating the prevalence and severity of periodontitis were the RHM, (FM)MB-B-DB), (FM)MB-B-DL, and (HM)MB-B-DL. For estimating the periodontitis extent, the best PRPs were RHM and (FM)MB-B-DB (Tran DT et al., 2013). While the systematic review focused on the validity of different PRPs on estimating periodontitis prevalence, extent, and severity, the impact of using PRPs on periodontitis exposures was not evaluated possibly due to deficiency of such studies at the time of conducting the review. In addition, factors that could impact the performance of PRPs for estimating periodontitis prevalence, extent, severity, and their associations with different exposures have not been evaluated. The systematic review also suggested for future studies to evaluate the impact of using PRPs when using universally recommended definitions such as the CDC/AAP. Thus, there is possibly a need for an updated systematic review. In summary, periodontitis prevalence can be underestimated when using PRPs whereas periodontitis extent, severity, and exposures OR can be either underestimated or overestimated. Continuous outcomes: extent and severity had an overall lower bias when using PRPs compared with dichotomous outcome: prevalence. In general, estimating periodontitis prevalence using PRPs seems to differentially impact the estimation of exposures (underestimation or overestimation of ORs). Factors that could impact the performance of PRPs could vary per periodontitis outcome. Knowledge gaps in the literature regarding the performance of PRPs in studying periodontitis may include deficient evaluation of PRPs in young age groups for periodontitis outcomes, direct comparisons across different age cohorts were rarely reported, performance of PRP in untreated individuals had been rarely studied, limited number of studies assessed the performance of PRPs for estimating periodontitis exposures using real patient data, previous systematic review did not evaluate the impact of using PRPs on estimating exposures or the factors that could impact the performance of PRPs for different periodontitis outcomes. 1.3 Associations with periodontitis In spite that variations in susceptibility to periodontitis had been observed among populations with no (or minimal) access to dental care (Baelum V et al., 1996; Cutress TW et al., 1982; Dowsett SA, Eckert GJ, et al., 2002a; Löe H et al., 1986; Timmerman MF et al., 2000), these populations had an overall high periodontitis prevalence, extent, severity, and rate of progression when compared with general populations (Billings M et al., 2018; Eke PI et al., 2018). These findings may highlight the role of plaque in addition to the importance of other host related exposures. Plaque alone does not inevitably lead to periodontitis. However, periodontitis is always preceded by having dental plaque. Thus, the etiology of periodontitis can be attributed to “sufficient cause” which is a set of components (exposures) where plaque is a necessary component (agent) (Bouchard P et al., 2017; Heaton B & Dietrich T, 2012; 31 Hujoel P & Kotsakis G, 2019). Sufficient cause of a disease is a term originally proposed by Kenneth J. Rothman as a practical method of conceptualizing the etiology of multifactorial diseases (Rothman KJ, 1976). In some diseases, such as periodontitis, several sets of sufficient causes can be responsible for causing the disease. Several theories evolved trying to explain the role of dental plaque in causing periodontitis including specific and non-specific plaque theories (Bartold PM & van Dyke TE, 2019). Earlier epidemiological studies attempted to isolate specific microbial species to study their role in periodontitis etiology such as Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, and Fusobacterium nucleatum (Dowsett SA, Kowolik MJ, et al., 2002; Timmerman MF et al., 1998, 2000). Recently, there was an agreement that the dysbiosis of oral biofilm, rather than having certain types of microorganisms, could provoke an inflammatory response in a susceptible host to cause periodontitis (Kumar, 2021). Dysbiosis can be defined as a shift in the species within the oral microbiome that results in loss of homeostasis that may impact the human health. The dysbiosis can result due to any of the following: an expansion of pathogenic microorganisms, reduction of beneficial microorganisms, altered metabolic capacity, or decreased diversity of the species. Exposures in epidemiology are “potential causal characteristics” (Rothman KJ et al., 2021). Exposures associated with chronic diseases such as periodontitis can possibly be divided into proximal, intermediate, and distal exposures based on their proximity in a causal pathway of periodontitis (Bouchard P et al., 2017). Proximal exposures include the risk factors based on well-established evidence such as plaque, uncontrolled diabetes mellitus, and smoking. Proximal exposures are also called: risk factors or established risk factors. Proximal exposures have the most direct role in initiation of a disease. Intermediate exposures can be the “causes of causes” of periodontitis and are sometimes called risk indicators, or putative risk factors. Intermediate exposures are associated with periodontitis in a less direct manner compared with proximal exposures and their role is mainly supported by evidence from cross-sectional studies. Distal exposures can be the “causes of causes of causes” of periodontitis and can be called upstream exposures, underlying exposures, predisposing exposures, non-medical exposures, or risk determinants. Distal exposures can include social determinants of health and their importance possibly relies on linking individual-level exposures to society-level exposures (Bouchard P et al., 2017; Braveman P & Gottler L, 2014; Ratcliff KS, 2017). Distal exposures are mainly associated with periodontitis by impacting oral health behaviors. As an example, dental plaque considered as a proximal exposure of periodontitis could be caused by lack of utilization of dental care (intermediate exposure) that could be caused by having a low socioeconomic status (distal or underlying exposure) (Bouchard P et al., 2017). Compared to non-smokers, smokers may have increased progression of periodontitis manifested as PPD, CAL and bone loss (Leite FR et al., 2018). Cigarette smoking reduces the gingival crevicular fluid and gingival bleeding, thus, possibly masking the signs of inflammation (Dietrich T et al., 2004; Mirbod SM et al., 2001; Morozumi T et 32 al., 2004). Cigarette smoking also impairs the function of polymorphonuclear leukocytes (PMNs) and suppresses T-cell, B-cell, and immunoglobulin functions, especially IgG2 (Johannsen et al., 2014; Zee KY, 2009). Functions of gingival fibroblast including proliferation, attachment, collagen production, and fibronectin syntheses can be impaired in smokers. The association between cigarette smoking and periodontitis was evaluated in the NHANES III study and found to be a dose-dependent (Tomar SL & Asma S, 2000). After adjustment for demographic and socioeconomic determinants, the probability of periodontitis in current smokers who smoked ≥31 cigarettes daily was substantially higher (adjusted OR = 6.0, 95% confidence interval [CI]: 3.2, 4.9) than in subjects who smoked <10 cigarettes per day (adjusted OR=2.8, 95% CI: 1.9, 4.1); former smokers who quit smoking within the past two years had an adjusted OR of 3.2 (95% CI: 2.2, 4.8), while those who quit smoking ≥11 years ago had an adjusted OR of 1.2 (95% CI: 0.8, 1.6). In 2004, the Surgeon General’s report that examined the overall evidence of periodontitis association with smoking has concluded that “The evidence is sufficient to infer a causal relationship between smoking and periodontitis” (Office of the Surgeon General (US); Office on Smoking and Health (US), 2004). Based on a recent systematic review, smoking cessation appears to be effective in reducing the risk of periodontitis (Ramseier CA et al., 2020). Chronic hyperglycemia may result in increased non-enzymatic oxidation of proteins and lipids, which leads to the accumulation of irreversible advanced glycation products (AGE) (Lalla E et al., 1998). The interaction between AGE and receptors of immunoglobulin superfamily of cell surface molecules (RAGE) enhances cellular oxidative stress, which activates pro-inflammatory pathways that lead to an increased tissue breakdown and decreased healing. The accumulation of AGE on vessel walls leads to microvascular and macrovascular complications, which are often associated with uncontrolled diabetes (Lind M et al., 2008). Chemotaxis, adherence, and phagocytosis of PMNs are altered in diabetic patients (Taylor JJ et al., 2013). The T-lymphocyte and monocyte functions are upregulated (Lalla E et al., 1998; Taylor JJ et al., 2013). Fibroblasts produce less collagen while the secretion of matrix metalloproteinase is enhanced. Osteoblast proliferation and collagen production are also decreased in diabetic patients. Unsurprisingly, poorly controlled diabetic individuals could have more gingival inflammation, deeper PPD, extensive CAL, bone loss, and higher progression of periodontitis compared to non-diabetic subjects (Haas AN et al., 2014; Stöhr J et al., 2021; Taylor JJ et al., 2013; Tervonen T & Oliver RC, 1993; Tsai C et al., 2002). In contrast to poorly controlled diabetes, subjects with pre-diabetes or controlled diabetes mellitus may not have increased susceptibility for periodontitis compared with non-diabetic subjects (Kowall B et al., 2015; Tsai C et al., 2002). In more general terms, both macrovascular and microvascular diabetic complications can be better predicted by the poor glycemic control over long term rather than having a diagnosis of diabetes mellitus alone (Lind M et al., 2008). In addition, the level of the glycemic control level in diabetes mellitus cases seems to have a dose-dependent association with periodontitis (Tervonen T & Oliver RC, 1993). 33 Obesity is a chronic metabolic disorder that can be associated with altered lipid metabolism, increased insulin resistance, increased inflammation, and oxidative stress (Papapanou P & Lindhe J, 2015). Among different methods of diagnosing obesity, a practical method is based on a BMI ≥30 kg/m2 (Purnell J, 2018). Such approach can be limited in body builders where increased weight is due to lean muscular weight rather than accumulation of fat. More direct diagnostic approaches, though less practical, for assessing obesity can be done using imaging modalities such as computed tomography or magnetic resonance imaging. Another approach for assessing obesity is by evaluating fat distribution or central obesity as indicated by an increased waist circumference or waist to hip ratio. Central obesity can be associated with higher risk for hypertension (metabolic syndrome), type II diabetes mellitus, and cardiovascular diseases (Balkau B et al., 2007; Janssen I et al., 2004). Cross-sectional studies found positive associations between periodontitis and obesity (Al-Zahrani MS et al., 2003; Genco RJ et al., 2005; Wood N et al., 2003). In a longitudinal study with up to five years of follow-up in Japan, incidence of periodontitis was evaluated after adjusting for age, diabetes mellitus, and smoking (Morita I et al., 2011). Adjusted hazard ratio (HR) of periodontitis incidence was 1.30 and 1.44 in men with BMI 25-30 kg/m2 and ≥30 kg/m2 respectively compared with BMI <22 kg/m2. The adjusted HR of periodontitis incidence was 1.7 and 3.24 in women with BMI 25-30 kg/m2 and ≥30 kg/m2 respectively compared with BMI <22. The study findings suggest a possible dose response relationship between increased BMI and periodontitis. In another longitudinal study in the U.S. veterans, adjusted hazard ratio for periodontitis incidence in individuals with BMI ≥30 kg/m2 was 1.52 (95% CI: 1.05-2.21) compared with the ones with BMI <25 kg/m2; adjusted HR for periodontitis incidence in individuals with waist to height ratio ≥50.0% was 1.41 (95% CI: 1.01, 1.97) compared with the ones with <50.0%; adjustment was done for age, smoking, education, number of decayed or filled teeth, and having periodontal treatment in previous year (Gorman A et al., 2012). Age was associated with periodontitis in several cross-sectional surveys (Eke PI et al., 2016; Susin C et al., 2004). Studies that analyzed the association of age with different periodontitis indicators found that increased age was associated with higher prevalence, severity, and extent of recessions and CAL (Billings M et al., 2018; Dowsett SA, Eckert GJ, et al., 2002a; Papapanou P & Lindhe J, 2015). The PPD severity and extent showed a less clear pattern related to age (Billings M et al., 2018; Dowsett SA, Eckert GJ, et al., 2002a). Studies that analyzed the association between age and periodontitis progression found only a small effect (Haas AN et al., 2014; Needleman I et al., 2018; Neely AL et al., 2001). These age-related findings suggest that age association with periodontitis might be attributed to an accumulative effect of a disease experience over time rather than having an increased susceptibility to periodontitis at an older age (Papapanou P & Lindhe J, 2015). Studies reported that males compared with females had a higher periodontitis prevalence, extent, and severity (Eke PI et al., 2016; Shiau HJ & Reynolds MA, 2010; Susin C et al., 2004). This sex related difference was robust despite adjusting for behavioral factors such as smoking and oral self-care (Shiau HJ & Reynolds MA, 2010). In contrast 34 to some suggestions that sex related differences can be attributed to having better oral self-care and increased utilization of dental care, studies on populations with uniformly high levels of plaque and minimal access to dental care also found a higher periodontitis progression in males than in females (Baelum V et al., 1997; van der Velden U et al., 2006). However, a recent systematic review found almost no sex-related differences in terms of periodontitis progression rates (Needleman I et al., 2018), but this finding was based on meta-analysis of only two studies. As a general rule, subgroup meta-analysis can be conducted when there are at least 10 available studies (Deeks JJ et al., 2021). Different psychological exposures were found to be associated with periodontitis (Genco RJ et al., 1999; Merchant AT et al., 2003; Tanveer SA et al., 2021). Genco et al. study found that among different daily strains, only financial strain associated with higher CAL and increased bone loss after adjustment for age, sex, and smoking (Genco RJ et al., 1999). Additionally, inadequate coping resulted in higher CAL and bone loss regardless of the level of financial strain. In another study, higher perceived stress measured using perceived stress scale was associated with periodontal disease (measured using CPI) in socially deprived women living in shelter homes; adjusted OR was 2.43 (95% CI: 1.50, 3.94) after adjustment for age and education (Tanveer SA et al., 2021). In a prospective study where periodontitis was self-reported by health care providers, the adjusted risk ratio (RR) for periodontitis was 1.72 (95% CI: 1.39, 2.12) in those who had highest “anger scores” after adjusting for age, marital status, smoking, BMI, alcohol consumption, and diabetes (Merchant AT et al., 2003). The study also reported a dose dependent increase in adjusted RR of developing periodontitis with increased anger score. Although it was implied that social support may countereffect stress, this study did not attempt to evaluate a link between social and psychological factors. Additionally, stress can be indirectly associated with periodontitis by decreasing the oral self-care or increasing smoking (da Silva AM et al., 1995; Deinzer R et al., 2001; Genco RJ et al., 1998). However, some studies that evaluated the role of psychological factors considered their effect adjusting for smoking but not for oral self-care in their multivariate models (Genco RJ et al., 1999; Merchant AT et al., 2003). It has been suggested that nearly 10.0% to 20.0% of “modifiable health outcomes” can be attributed to clinical care while 80.0% to 90.0% of these outcomes can be attributed to modifiable social determinants of health including socioeconomic and environmental determinants (Adler KG, 2018; Magnan S, 2017). Social determinants of health are the underlying or non-medical exposures that may impact health; comprised of conditions in which individuals live, grow, age, work, learn, and worship within the surrounding environment or system (Braveman P & Gottler L, 2014; Ratcliff KS, 2017; World Health Organization, 2022). Social determinants of health may include education, income, employment, housing, residential neighborhoods, environmental safety, early childhood development, equity, discrimination, racism, and social support network (Adler KG, 2018; Braveman P et al., 2011; Braveman P & Gottler L, 2014; Dahlan R et al., 2019; Magnan S, 2017; Ratcliff KS, 2017; World Health Organization, 2022). 35 When ethnicity was studied in the NHNANES (2009-2012), both the Hispanics and non-Hispanic blacks had higher susceptibility to periodontitis than Caucasians (Eke PI et al., 2016). However, in the Brazilian population, the associations between ethnicity and periodontitis prevalence and its progression rate have not been confirmed (Haas AN et al., 2014; Susin C et al., 2004). In a study that compared the periodontitis prevalence in NHANES I and III based on ethnicity, an increased prevalence was found in African Americans compared with Caucasians; African Americans had an adjusted OR of 1.31 (95% CI: 0.78, 2.19) in NHANES I which increased to an adjusted OR of 2.09 (95% CI: 1.68, 2.60) in NHANES III; the adjustments were done for age, socioeconomic indicators, smoking, diabetes, and time elapsed since last dental visits (Borrell L et al., 2002). It was suggested that such disparity in periodontitis prevalence between African Americans and Caucasians in the U.S. can be attributed to racism, discrimination, and residential segregation. A conceptual explanation of how residential segregation may impact health outcomes is by potentially impacting quality of education, employment opportunities, level of exposures to environmental hazards, and influencing certain behaviors such as increased tobacco consumption is some neighbourhoods. However, these attributes that may explain such disparities were only suggested and not directly supported by an empirical data. The authors recommended investigating social and behavioral exposures that may explain the disparities in periodontal health outcomes in future studies. In the Brazilian population, both medium and low socioeconomic status were associated with higher rates of severe periodontitis with or without adjustment for demographic, medical, and behavioral factors (Susin C et al., 2004). However, a small magnitude of association was found between the periodontitis progression and low socioeconomic status in Brazilian population (Haas AN et al., 2014). In the NHANES (2009-2012), both lower than high school and high school education when compared with more than high school education were associated with higher periodontitis prevalence despite the adjustment for demographic, behavioral, and medical exposures (Eke PI et al., 2016). In a systematic review, low education level had a pooled OR of 1.86 for having periodontitis (95% CI: 1.66, 2.10) compared with higher education levels (Boillot A et al., 2011). Although education and income have been almost consistently associated with periodontitis in different studies, it has been suggested that such approach of studying socioeconomic exposures might be limited without further investigations of health disparities based on socioeconomic indicators and explaining how these indicators can contribute to higher rates of periodontitis (Baelum V & Lopez R, 2004; Borrell L et al., 2002; Borrell L & Crawford N, 2012). Evidence suggests that social factors including education, employment, income, and their consequent stressful conditions can potentially shape the overall health-related behaviors (Braveman P et al., 2011; Stringhini S et al., 2010). In untreated Indonesian population, despite the uniformly high levels of plaque, periodontitis progression rate has increased in the last 8 years of follow-up compared with the initial observation period (van der Velden U et al., 2006). The authors suggested that such increase in progression might be attributed to the economic recession that happened over the observation period and may consequently had some psychological impact on the study population. Similarly, studies that found difference in periodontitis susceptibility based on socioeconomic disparities suggested that psychological 36 factors might contribute to explaining their associations with periodontitis (Borrell L et al., 2002; Borrell L & Crawford N, 2012). These studies assumed that impact of lower income on periodontitis can be attributed to increased stress without supporting such assumptions by empirical data. However, a study that found association between periodontitis and financial strain may indirectly support such assumption (Genco RJ et al., 1999). Although social exposures can be an important link between individual-level and society-level exposures, the periodontal literature lacks studies focused on associations between such exposures and periodontitis (Bouchard P et al., 2017). The impact of social network was studied where marital status had no significant association with either periodontitis prevalence or its progression (Eke PI et al., 2016; Haas AN et al., 2014; Merchant AT et al., 2003; Sabbah W et al., 2011). However, based on the NHANES 2001-2004 data, having fewer friends, and being widowed, were associated with the higher extent of periodontitis (Sabbah W et al., 2011). In a prospective study, health care professional men who had at least one friend had a lower risk of developing periodontitis (self-reported); adjusted RR was 0.70 (95% CI: 0.51, 0.96) after adjustments for age, marital status, smoking, BMI, alcohol consumption, and diabetes mellitus (Merchant AT et al., 2003). Furthermore, those health care professionals who participated in religious meetings had lower risk for periodontitis; adjusted RR was 0.73 (95% CI: 0.64, 0.83). Despite that periodontal literature have deficient studies focused on social exposures, a recent systematic review found a positive association between social support and different dental related outcomes including oral health related quality of life, oral health literacy, oral health behaviors, and utilization of dental care among immigrants and ethnic minorities (Dahlan R et al., 2019). Thus, it can be inferred that association between the social support and periodontitis can be conceptually complex. Similar to the concerns raised in regard to lack of universal case definitions for periodontitis, mentioned earlier in section 1.2.1, operational definitions of exposures considerably varied among different studies, though, this did not seem to be perceived as problematic. Changes in the operational definitions of exposures may have the same potential for data dredging that could occur with changes in periodontitis case definitions. There is possibly a need for guidelines and standardization for operational definitions of exposures such as diabetes mellitus and smoking. In addition, there is a need for reporting both adjusted and unadjusted estimates of associations to enhance the comparability among different studies. Underlying exposures that were reported in periodontal literature were mostly limited to age, sex, race, education, and income (Borrell L et al., 2002; Eke PI et al., 2016; Haas AN et al., 2014; Susin C et al., 2004). However, potential exposures that could explain why people having low income, low education, or disparities based on ethnicity/race and how these exposures can impact periodontal outcomes have not been sufficiently explored (Borrell L et al., 2002; Borrell L & Crawford N, 2012). While several reports highlighted the need to direct the periodontal research towards the upstream (underlying) exposures including social exposures (Baelum V & Lopez R, 2004; Borrell L et al., 2002; Lopez R & Baelum V, 2012), it can be concluded that only little has been done thus far. 37 1.4 Focus of the thesis projects Project I: Periodontitis prevalence, extent, and its associations in untreated individuals. The aim of the study was to describe and analyze several exposures for their potential associations with untreated periodontitis, including underlying exposures, in a wide age range sample. The study hypothesis was: Untreated periodontitis is associated with increased age, male sex, low education, low income, low perceived social support, high perceived stress, cigarette smoking, lack of glycemic control, and other chronic medical conditions. Secondary study objectives were to 1) compare the prevalence and extent of untreated periodontitis between younger and older age groups, and 2) describe potential barriers for lack of utilization of dental care. Project II: Performance of PRPs in estimating untreated periodontitis prevalence, its extent, and associations. The project aimed to assess the performance of PRPs in estimating prevalence, extent, and associations with untreated periodontitis using three PRPs: RHM, (FM)MB-DL and (HM)MB-DL and to compare the performance of the PRPs to estimate the periodontitis prevalence and its extent between the younger and older individuals. Project III: Accuracy of estimating periodontitis and its associations with exposures using PRPs for population-based studies: A systematic review and meta-analyses. The project aimed to answer the research question: should we rely on the PRPs to study the periodontitis and its associations in population-based studies? Specific objectives were: 1) to conduct an up-to-date systematic review and meta-analysis to assess the accuracy of PRPs to estimate the prevalence, extent, severity of periodontitis and its associations, and 2) to identify the factors that may impact the performance of PRPs. 38 Chapter 2: Periodontitis Prevalence, Extent, and its Associations in Untreated Individuals (Project I) A version of this chapter has been published (Alawaji Y, Alshammari A, et al., 2022). 2.1 Introduction Studies on untreated populations unveiled variations in susceptibility to periodontitis despite accumulations of uniformly high levels of plaque and calculus (Baelum V et al., 1996; Cutress TW et al., 1982; Goodson J, 1986; Haffajee A et al., 1982; Loe H, Anerud A, et al., 1978; Löe H et al., 1986; Timmerman MF et al., 2000). Variations in susceptibility to periodontitis were observed among different individuals, different population groups, and at different teeth sites within an individual. Thus, it was no longer accepted that plaque is the only cause of periodontal disease. Accordingly, periodontal research interests were redirected to explore exposures that may explain these variations in susceptibility (Beck, 1994; Grossi SG et al., 1994; Johnson NW et al., 1988). Despite that main contribution of studies on untreated populations was by revealing the variations in susceptibility to periodontitis, the studied exposures that could explain such variations were mainly limited to demographic characteristics and local factors (Baelum V et al., 1997; Neely AL et al., 2001; van der Velden U et al., 2006). The importance of studying the association with untreated periodontitis can be explained by the need for identifying the role of exposures while ruling out the impact of plaque and periodontal treatment; such approach can be more relevant to the natural course of disease that needs to be studied in individuals who lack treatment. In contrast, concurrent studies frequently report the associations with periodontitis without adjusting for plaque scores or treatment status. Considering that both plaque levels and periodontal treatment are exposures that have a non-negligible impact on the periodontal status, studying periodontitis associations while disregarding impact of these exposures may not be appropriate. Over the last few decades, studies in periodontal literature tend to separate their findings between older and younger individuals (Albandar JM et al., 1997, 1999; Baelum V et al., 2003; Eke PI et al., 2016, 2018; Susin C et al., 2004, 2011), with a higher focus being given to older age groups. This age-based disconnection might be in part motivated by historical distinction of recommended periodontitis diagnoses based on age since 1977 (American Academy of Periodontology, 2015; Califano JV & American Academy of Periodontology, 2003; Caton J, 1989; Highfield, 2009; Lindhe J et al., 1999). In the most recent update of periodontitis classification, however, all individuals with periodontitis are diagnosed under one entity (Caton JG et al., 2018; Tonetti MS et al., 2018). Age was limited to assigning grading based on individual’s risk profile (Tonetti MS et al., 2018). Studying periodontitis under one category with wide age range can be potentially important to allow direct age-based comparisons for several reasons: identifying age ranges where periodontitis occurs, steeply increases, or peaks. In addition, the use of wide age range can help in identifying some exposures that can be masked in samples where periodontitis prevalence 39 lack variation in older age groups. Based on recent systematic reviews, periodontitis appears to occur early during adolescence and steeply increases in severity and extent during third and fourth decades until it reaches its peak around 38 years (Frencken JE et al., 2017; Kassebaum NJ et al., 2014). However, the concurrent literature is focused on studying periodontitis in older age groups (30 years or above) where the prevalence nearly reached its peak. Since periodontitis preventive efforts that are based on upstream (underlying) exposures are more important to younger age groups (Kisling LA & das JM, 2022; The Association of Faculties of Medicine of Canada, 2018), there is possibly a need to switch the focus on studying periodontitis exposures in a wider age range while focusing on younger age groups. Therefore, the aim of this study was to describe and analyze several exposures for their potential associations with untreated periodontitis, including underlying exposures, in a wide age range group. The study hypothesis was: Untreated periodontitis is associated with increased age, male sex, low education, low income, low perceived social support, high perceived stress, cigarette smoking, lack of glycemic control, and having other chronic medical diseases. Secondary objectives were to 1) compare the untreated periodontitis prevalence and its extent between younger and older age groups and 2) describe potential barriers for lack of utilization of dental care. 2.2 Materials and methods The ethics approvals were obtained from the KAIMRC (H-01-R-005) and from the University of British Columbia; Clinical Research Ethics Board (H19-01019). Data were collected from early September to end of December 2019. Participants who agreed to participate signed an informed consent form prior to data collection. 2.2.1 Data collection site Study subjects were recruited from screening dental clinics at KSAU-HS. This dental school is located at the eastern boundary of Riyadh city in Saudi Arabia, and it was established in 2013. The clinics’ capacity to accept new patients has gradually increased over the past few years. The dental school mainly offers two lines of treatment: a limited symptomatic treatment by general dentists or comprehensive dental treatment mainly provided by dental students. All dental treatments are provided at no cost. The dental school’s policy mandates all new patients who arrive at the school to be screened before they can be assigned either to limited symptomatic treatments or comprehensive dental care. Referrals of all new patients are done based on the following considerations: 1) patient treatment needs evaluated by dentists during screening, 2) having stable medical conditions that can be safely treated in dental school clinics, and 3) patients’ perceived needs for treatment and willingness to attend regular appointments. Patients who had unstable medical conditions and/or physical or mental disabilities were referred to affiliated hospital dental clinics for medically complex patients. 40 2.2.2 Selection of study participants A purposive sample was used to collect data at the dental school which is conveniently located in close proximity to residences of some descendants of nomadic tribes. The nomadic tribes are generally known to have low socioeconomic status, limited access to dental care, and their residential places range from living in housings to living as nomads (continually travelling) and living in tents. Although the nomadic tribes represent most of the patients seen at the dental school clinics, a selection bias of sampling study participants is acknowledged, therefore, representativeness of this study’s population is limited; consequently, the statistical inference of this study findings is limited to those new patients who were recruited during the study period (September to December 2019). Patients who visit the dental school clinics are mostly known to have some or all of the following features: low socioeconomic status; high levels of illiteracy; limited past dental care; high levels of plaque and calculus. The patients also commonly report that they seek regular medical care from a primary care center that is located close to their underserved residential areas. The new patients who arrived at dental school during the study period either sought limited symptomatic treatments or requested regular dental care. Recruitment of the study subjects was carried consecutively where every new patient was invited to participate. Those who refused to participate in the study or did not meet the study’s inclusion criteria were also examined as part of mandatory screening (without using their data for research). All patients were referred for treatment following the screening based on the above-mentioned criteria (refer to subsection 2.3.1). Inclusion criteria: Dentate or partially dentate individuals who have never been treated periodontally in their lifetime (either surgically or non-surgically), that is, their dental history has been limited to symptomatic treatments such as extractions, pulpal extirpations, or a few restorations. Exclusion criteria: Patients who received any type of periodontal treatment (non-surgical or surgical) in the past, had mental illness/conditions that prevented them from participating, had unstable medical conditions, needed prophylactic antibiotics or other medications prior to clinical examinations; fully edentulous subjects; and individuals with acute dental conditions that required urgent care such as an acute abscess, cellulitis, or diseases impacting the jawbones including cysts and neoplasms. 2.2.3 Data collection A certified periodontist conducted all clinical assessments, which consisted of a full-mouth periodontal examination of 28 teeth, excluding the third molars. Manual probing was performed at six sites per tooth, and all measurements were rounded to the nearest millimeter. The periodontal examination included the following: full-mouth plaque scores based on the presence of plaque at the site level, PPD, recession (REC), CAL, and bleeding on probing (BOP). 41 The background characteristics of study subjects were digitally collected using questionnaires. The questionnaires inquired about age, sex, ethnicity, formal education level, monthly household income measured in the local currency (Saudi Riyal), medical conditions, use of medications, daily toothbrushing habits, use of interdental cleaning aids, smoking status, perceived stress using the 10-item perceived stress scale (Cohen S & Williamson G, 1988) in Appendix C and perceived social support using the 12-item multidimensional scale of perceived social support (Zimet GD et al., 1988) in Appendix D. All medical conditions were self-reported, and subjects identified as diabetics were asked about their glycemic control and self-reported most recent glycated hemoglobin (HbA1c) level. Perceived stress and perceived social support measures used a visual analog scale ranging from 0% to 100%. The study questionnaires were translated into Arabic using the forward-backward method (Appendix B). Illiterate subjects were assisted in completing the questionnaires. 2.2.4 Periodontitis outcomes The periodontitis extent was defined as the mean proportion of sites with CAL or PPD at several disease thresholds (Holtfreter B et al., 2015). Periodontitis cases (for disease prevalence) were defined in this study using two main approaches recommended in the current literature 1) the AAP/EFP staging/grading diagnostic criteria suggested in the most recent classification system of periodontitis (Caton JG et al., 2018; Tonetti MS et al., 2018), and 2) case definitions suggested by the CDC/AAP (Eke PI et al., 2012; Page RC & Eke PI, 2007) and recommended by standards for reporting in epidemiological studies (Holtfreter B et al., 2015). The AAP/EFP diagnostic criteria were used (Caton JG et al., 2018) in which periodontitis was defined based staging and grading criteria. Staging was used to define periodontitis cases (used as dependent variables in regression analyses to study associations). Staging was mainly assigned based on the most severe CAL at ³2 interproximal sites or midbuccal sites with a CAL ³3 mm and PPD ³3 mm at ³2 teeth (Tonetti MS et al., 2018). Stage I was based on CAL of 1–2 mm; stage II had a CAL range of 3–4 mm; stage III/IV had a CAL of ³5 mm. The complexity factors were considered as stage modifiers including the PPD, tooth loss, or presence of <20 remaining teeth. Grading was used in this study to present the distribution of study subjects based on smoking and diabetes which are the two risk factors used in grading framework based on the AAP/EFP criteria (Tonetti MS et al., 2018). However, due to the incorporation of these risk factors in the grading, periodontitis gradings were not used as dependent variables to analyze the associations with periodontitis. Grade A included those who were diagnosed with periodontitis based on staging, never smoked, and had no diabetes mellitus. Grade B included subjects with periodontitis, smoked less than 10 cigarettes daily, and/or self-reported diabetes mellitus with a HbA1c <7.0%. Grade C included subjects with periodontitis, smoked ³10 cigarettes daily, and/or had self-reported uncontrolled diabetes mellitus based on HbA1c ³7.0%. The grading criteria based on radiographic examinations were not used since no radiographs were collected as part of examinations in this study. 42 Additionally, periodontitis case definitions for epidemiological studies recommended by the CDC/AAP were used (Eke PI et al., 2012; Page RC & Eke PI, 2007). The CDC/AAP severe periodontitis was defined as CAL ³6 mm at ³2 interproximal sites (not at the same tooth) and PPD ³5 mm at ³1 interproximal site (can be at one of the two teeth with CAL). The CDC/AAP moderate periodontitis was defined as CAL ³4 mm at ³2 interproximal sites (not at the same tooth) or PPD ³5 mm at ³2 interproximal sites (not at the same tooth). In order to study the exposures associated with periodontitis in multivariate regression models, we selected four dependent variables: 1) the AAP/EFP total periodontitis (stages I/II/III/IV); 2) the AAP/EFP severe periodontitis (stages III/IV); 3) the CDC/AAP moderate-severe periodontitis; and 4) the CDC/AAP severe periodontitis. 2.2.5 Analytical framework Figure 6. An analytical framework adapted from (Bouchard P et al., 2017). The exposures divided into proximal, intermediate, and underlying (distal) based on their proximity to the periodontitis outcome in the causal pathway. Variables outlined in orange boxes either lacked variations or were not consistent with objective measures (oral self-care). 2.2.5.1 Conceptualization of lack of utilization of periodontal care The “need factors” as defined by Andersen were “perceived need” as indicated by the reason behind the participant’s visits to dental school clinics were compared with the “evaluated need” based on the assessments of periodontal 43 conditions (Andersen RM, 1995). Perceived barriers of “lack of access to health care model” (Institute of Medicine (US) Committee on Monitoring Access to Personal Health Care Services, 1993) were used to describe the reasons for lack of utilization of dental care (McKernan S et al., 2020) including three main categories: personal (acceptability), financial (affordability), and structural (accessibility, and accommodation). Under personal category, we inquired about the lack of trust in dentists and dental anxiety. Under financial category, we inquired about the lack of affordability of dental treatment. Under structural category, we inquired about the lack of accommodation (dental appointments in public dental centers), lack of time, and lack of transportation. The level of awareness regarding the self-assessed oral hygiene was compared with objectively measured full mouth plaque scores. Similarly, self-assessed periodontal health was compared with objectively measured periodontal extent based on the following thresholds: CAL ≥4 mm and PPD ≥3 mm. Since the study’s population were restricted to those who had limited utilization of dental care, the attributes of lack of access to health care model were only described rather than being used in the regression analyses. 2.2.5.2 Analytical plan The analytical framework was adapted from (Bouchard P et al., 2017) (Figure 6). The exposures were divided into proximal, intermediate, and underlying (distal) based on their proximity to the periodontitis outcome in the causal pathway. Proximal exposures are the established risk factors for periodontitis including uncontrolled diabetes mellitus (Chavarry NG et al., 2009; Emrich LJ et al., 1991; Stöhr J et al., 2021; Taylor GW et al., 1998; Taylor JJ et al., 2013; Tervonen T & Oliver RC, 1993; Winning L et al., 2017). Using the suggested AAP/EFP criteria in grading (Tonetti MS et al., 2018), uncontrolled diabetes is based on HbA1c ³7.0%. Smoking is another established risk factor (Johannsen et al., 2014; Leite FR et al., 2018; Office of the Surgeon General (US); Office on Smoking and Health (US), 2004; Zee KY, 2009). Both former smokers and current smokers were found to have associations with periodontitis in these previous reports. The operational definition for current cigarette smoking was based on the AAP/EFP grading (Tonetti MS et al., 2018); smokers were categorized into smokers of <10 cigarettes daily and ³10 cigarettes daily. Intermediate exposures include exposures with a less direct associations with periodontitis (causes of causes of periodontitis) and the evidence that supports their associations with periodontitis is mainly based on cross-sectional studies such as chronic medical conditions including obesity (Al-Zahrani MS et al., 2003; Genco RJ et al., 2005; Gorman A et al., 2012; Morita I et al., 2011; Wood N et al., 2003) and higher stress (Deinzer R et al., 2001; Genco RJ et al., 1998, 1999; Tanveer SA et al., 2021). Subjects were asked if they stop brushing or increase smoking in stressful days based on reports suggested that a link between periodontitis and stress could be partly explained by these behaviors (da Silva AM et al., 1995; Genco RJ et al., 1998). 44 Underlying exposures (non-medical predisposing causes) are distal exposures that mostly have indirect associations with periodontitis including increased age (Billings M et al., 2018; Eke PI et al., 2016; Susin C et al., 2005), ethnicity (Borrell L et al., 2002; Eke PI et al., 2016), male sex (Eke PI et al., 2016; Shiau HJ & Reynolds MA, 2010), lower income (Haas AN et al., 2014; Susin C et al., 2004), lower education (Boillot A et al., 2011; Eke PI et al., 2016; Haas AN et al., 2014), and lower perceived social support (Dahlan R et al., 2019; Sabbah W et al., 2011). Most of the intermediate and underlying exposures were defined differently in each study. For both scales: Perceived stress and perceived social support, the authors recommended comparing the study participants amongst each other rather than suggesting specific thresholds (Cohen S, 2014; Cohen S & Williamson G, 1988; Zimet GD et al., 1988). A general approach used for analyzing the overall intermediate and underlying exposures was based on the study sample’s distribution. Variables such as perceived need, perceived barriers, lack of utilization of periodontal care, and plaque scores were only measured and described without using them in regression analyses due to the expected lack of variations based on the eligibility criteria of selecting study subjects. 2.2.6 Statistical analyses Sample size estimation: The minimum sample size was calculated based on the primary data of the first 100 subjects using the G*power program version 3.1.9.2 (Faul F et al., 2009). To calculate the minimum sample size for multivariate logistic models, we selected a power of 0.8 and an alpha level of 0.05. For the CDC/AAP moderate-severe periodontitis, the estimated minimum sample size was 350 based on the current smoking odds ratio (OR=2.9), current smoking frequency of 22.0%, and explained variance (R2) =0.450. The estimated minimum sample size for studying the CDC/AAP severe periodontitis was 330 based on the following measures: current smoking (OR=2.6), frequency of 22.0%, and R2 =0.263. To compensate for the possibility of missing data and ensure an adequate number/proportion of cases per exposure, we recruited an additional 81 subjects. All statistical analyses were performed at the individual level using SPSS version 27.0 software (IBM, Chicago, IL, USA). The proportion of listwise missing data was 1.4%. The reliability of the subjects’ responses was tested using Cohen’s kappa test by comparing repeated responses to an education-related question placed in two different places within the same questionnaire; reliability was equal to 0.99. The internal consistency of the subjects’ responses was tested using Cronbach’s alpha for the 10-item perceived stress scale (Cohen S & Williamson G, 1988) and the 12-item perceived social support scale (Zimet GD et al., 1988); the values for internal consistency were 0.77 and 0.92, respectively. To assess intra-examiner reliability, duplicate clinical measurements were performed in 10 randomly selected subjects. Intra-examiner agreement was calculated using the intraclass correlation coefficient which compared duplicate recordings of the total number of sites at the CAL thresholds of ³3 mm and CAL ³5 mm. The intra-examiner reliability as indicated by intraclass correlation coefficient was 0.99 for the total number of sites 45 with CAL ³3 mm (95% CI, 0.94–0.99) and the intraclass correlation coefficient for the total number of sites with a CAL ³5 mm was 0.97 (95% CI, 0.89–0.99). The distribution of the sample background characteristics including the perceived barriers to dental care access was described using univariate statistics. Age in years was originally measured as a continuous variable then subsequently divided into younger and older groups based on the sample’s mean age of 35 years. The distribution of periodontitis prevalence and extent were stratified by age into two groups to compare the periodontal findings between younger and older individuals. For the exposure associations with periodontitis, we used the four abovementioned periodontitis outcomes as dependent variables: 1) The AAP/EFP total periodontitis (stages I/II/III/IV); 2) The AAP/EFP severe periodontitis (stages III/IV); 3) The CDC/AAP moderate-severe periodontitis; and 4) The CDC/AAP severe periodontitis. Bivariate logistic regression was used to calculate the unadjusted exposure associations, while multivariate logistic regression analyses were used to estimate the adjusted exposure associations of periodontitis. The following independent variables were included in the logistic models: 1) age: <35 years versus ≥35 years. The age was dichotomized around the sample’s mean age of 35 years and the periodontitis prevalence also peaks around this age group in our sample; 2) sex: Males versus females; 3) level of formal education: Less than high school compared with high school or more; 4) household monthly income: Lower income (<5,000 Saudi Riyals) compared with higher income (≥5,000 Saudi Riyals); and 5) subjects with self-reported diabetes mellitus and high glycemic levels (HbA1c ≥7.0%) were compared with the rest of the sample including two subjects who reported controlled glycemic levels (n=2); 6) self-reported obesity versus non-obesity; 7) cigarette smoking: Dummy variables were created and current or former smokers were compared with never-smokers. The two current smoking categories were combined due to having low proportion of smokers of <10 cigarettes daily; 8) perceived stress; and 9) perceived social support were initially measured as continuous variables, then divided into lower or higher categories based on the sample’s mean scores. Ethnicity had no variations in our study population and excluded from regression analyses. The self-reported oral self-care was not used in the analyses because it was not consistent with clinically measured full mouth plaque scores. In addition, we excluded from logistic regression analyses variables that had an insufficient number of subjects, that is, less than 10 subjects in any of the variable’s category including few medical conditions. Multicollinearity diagnostics was assessed to ensure that the findings were valid. 2.3 Results Among 515 new patients approached screening dental clinics as depicted in Figure 7, a total of 67 individuals did not meet the inclusion criteria and 17 refused to participate (response rate: 97%). Only 63.0% of the subjects visited 46 the dental school clinics requested to be referred to get regular dental care (comprehensive care including restorative, periodontal, and/or prosthodontic treatment); the rest of the subjects either requested emergency treatment for pain only (20.2%), or extractions only (16.2%). The tentative treatment needs were explained to the subjects after the screening was completed. The referrals were done based on the patients’ requests. Of the 431 recruited subjects, 185 (42.5%) were males and 246 (57.5%) were females. The sample age range was 13–80 years, with a mean (SD) age of 35.4 (13.3) years. The distribution of subjects’ background data, oral health status, and oral behaviors is depicted in Table 2 and Table 3. The following determinants lacked variation: ethnicity, where Arabs represented 90% of the sample; overall high dental plaque levels (full mouth plaque scores ³25% was 96.3%). The distribution of periodontitis prevalence stratified by age is shown in Table 4. The prevalence of the AAP/EFP total periodontitis and stage III/IV periodontitis was 85.4% and 48.5%, respectively. The prevalence of the CDC/AAP moderate-severe and severe periodontitis was 78.4% and 31.1%, respectively. The extent of periodontitis as indicated by CAL and PPD stratified by age is shown in Table 5. The mean (SD)% of sites with a CAL ³3 mm was 34.9 (33.6) %, while the mean (SD)% of sites with a PPD ³4 mm was 16.6 (22.0)%. The extent of periodontitis for different periodontal parameters, namely PPD, REC, and CAL, was compared among different age cohorts in Figure 8; the REC and CAL increased with age, while the PPD did not have a clear age-related pattern. The sample distribution regarding the extent of PPD, REC, and CAL for different age cohorts are depicted by patient sex in Figure 9; males had a higher extent of PPD, REC, and CAL than females in most of the age cohorts. Self-assessed oral hygiene by study subjects was compared with the clinically examined full mouth plaque scores in Figure 10 which shows that most subjects who rated their oral hygiene as good to excellent had a high full mouth plaque score. The self-assessed periodontal health was compared with the extent of patients with a CAL ³3 mm and PPD ³4 mm in Figure 11. some of the subjects who rated their periodontal health as good to excellent had high proportions of periodontitis. For the AAP/EFP total periodontitis cases (Table 6), the unadjusted associated exposures were: age ³35 years (OR=10.5), male sex (OR=2.2), lower income (OR=1.8), and current cigarette smoking (OR=3.7), while the adjusted associations included age ³35 years (OR=11.5) and lower income (OR=2.5). 47 Figure 7. Flowchart for the subject recruitment and their referrals at screening dental school clinics. For the AAP/EFP stage III/IV periodontitis (Table 7), the unadjusted associated exposures were: ³35 years of age (OR=9.7), male sex (OR=2.7), lower education (OR=2.2), lower income (OR=1.7), uncontrolled diabetes mellitus (OR=5.0), former smoking (OR=3.3), current smoking (OR=2.3), and lower perceived stress (OR=1.6). The adjusted associated exposures of stage III/IV periodontitis were age ³35 years (OR=8.2), male sex (OR=2.5), lower income (OR=2.3), and lower perceived stress (OR=2.0). For the CDC/AAP moderate-severe periodontitis (Table 8), the unadjusted associated exposures were: age ³35 years (OR=13.0), male sex (OR=2.0), lower education (OR=1.7), uncontrolled diabetes mellitus (OR=3.7), obesity (OR=2.5), and current cigarette smoking (OR=4.0); the adjusted exposures included age ³35 years (OR=12.0), lower income (OR=2.1), and current cigarette smoking (OR=4.2). For the CDC/AAP severe periodontitis (Table 9), the unadjusted associated exposures included age ³35 years (OR=6.5), male sex (OR=2.5), lower education (OR=2.5), lower income (OR=1.6), uncontrolled diabetes mellitus (OR=4.6), former smoking (OR=2.7), and current smoking (OR=2.5); the adjusted exposures were age ³35 years (OR=4.5), male sex (OR=1.9), lower education (OR=2.0), lower income (OR=1.7), uncontrolled diabetes mellitus (OR=2.0), and current smoking (OR=2.3). 48 Figure 8. Extent of periodontal probing depth (PPD), recessions (REC), or clinical attachment loss (CAL) per age cohorts.Age in yearsExtent of PPD, REC or CALPPD 4 mm+REC 1 mm+CAL 3 mm+ 49 Figure 9. Extent of periodontal probing depth (PPD), recession (REC), clinical attachment loss (CAL) per age cohorts and sex groups.Age in yearsExtent of PPD, REC or CALPPD 4 mm+REC 1 mm+CAL 3 mm+ 50 Figure 10. Self-assessed oral hygiene compared with clinically measured full mouth plaque scores; the study participants were asked “How do you rate the cleanliness of your mouth ?”% 51 Figure 11. Self-assessed periodontal health compared with extent of periodontal probing depth (PPD) and clinical attachment loss (CAL); the study participants were asked “how do you rate your gum health?”Extent of PPD and CAL% 52 Table 2. Distribution of subjects’ background characteristics Exposures N (%) Exposures N (%) Age <35 years 215 (49.9) Sex Males 183 (42.5) 35+ years 216 (50.1) Females 246 (57.1) Ethnicity Arabic 388 (90.0) Smoking Never smoked 309 (71.7) Other 41 (10.0) Former smoker 42 (9.7) Education > High school 162 (37.6) <10 cigarettes daily 30 (7.0) ≤ High school 266 (61.7) ≥10 cigarettes daily 48 (11.1) Household monthly income Lower <5,000 Saudi Riyals 239 (55.5) Household members 1-6 200 (46.3) Higher ³5,000 Saudi Riyals 189 (43.9) > 6 228 (52.9) Self-reported medical conditions Uncontrolled diabetes mellitus 63 (14.5) Perceived Stress Lower (≤42 score) 212 (49.2) Hypothyroidism 26 (6.0) Higher (>42 score) 213 (49.4) Obesity 80 (18.6) Perceived Social Support Lower (<69.5 score) 213 (49.4) Osteoporosis 27 (6.3) Higher (≥69.5 score) 212 (49.2) 53 Daily brushing, N (%) 272 (63.1) Daily use of interdental aids, N (%) 137 (31.8) Stop brushing in stressful days, N (%) 236 (54.8) Smoking more in stressful days (among smokers), N (%) 48 (11.1) Total number of remaining teeth, mean (SD) 23.8 (5.2) Full mouth plaque scores ³25%, N (%) 415 (96.3) Perceived barriers to access regular dental care, N (%) Structural Accessibility: lack of transportation 140 (32.5) Accommodation: unavailable appointments at the public dental centers 191 (44.3) Lack of time 233 (54.1) Financial Affordability of treatment 183 (42.5) Personal Dental anxiety: fear from dental treatments 144 (33.4) Lack of trust in dentists 73 (16.9) Other reasons 57 (13.2) Table 3. Distribution of the study subjects according to oral behaviors and oral health status 54 Table 4. Distribution of periodontitis prevalence using the case definition criteria by the AAP/EFP and the CDC/AAP AAP/EFP periodontitis prevalence, N (%) Grade A Grade B Grade C Total Stage I (mild) 34 (7.9) 3 (0.7) 3 (0.7) 40 (9.3) Stage II (moderate) 89 (20.7) 7 (1.6) 23 (5.3) 119 (27.6) Stage III (severe) 81 (18.8) 36 (8.4) 42 (9.8) 159 (36.9) Stage IV (very severe) 24 (5.6) 9 (2.1) 17 (3.9) 50 (11.6) <35 years (N:215) ≥35 years (N:216) Total (N:431) Total periodontitis cases 159 (74.0) 209 (96.8) 368 (85.4) Total severe (stage III/IV) cases 49 (22.8) 160 (74.1) 209 (48.5) CDC/AAP periodontitis prevalence, N (%) <35 years (N:215) ≥35 years (N:216) Total (N:431) Moderate-severe periodontitis 132 (39.1) 206 (95.4) 338 (78.4) Severe periodontitis 28 (13.0) 107 (49.5) 135 (31.1) AAP: the American Academy of Periodontology, EFP: the European Federation of Periodontology, CDC: the Centers for Disease Control and Prevention. • Staging was mainly categorized based on the severity of CAL, where Stage I: CAL range 1-2mm, Stage II: CAL range 3-4 mm, Stage III/IV: CAL ≥5 mm. The staging was then modified by the complexity factors such as periodontal probing depth and tooth loss. • Grading was applied in this study based on the glycemic control of subjects with diabetes mellitus and/or by smoking status. Grade A: non-smokers, non-diabetic subjects, Grade B: smokers of <10 cigarettes daily and/or diabetic with glycemic control (HBA1c <7%), Grade C: smokers of ³10 cigarettes daily and/or diabetic subjects without glycemic control (HbA1c ³7%). 55 Table 5. Periodontitis extent stratified by age group based on clinical attachment loss and periodontal probing depth. Periodontitis Extent <35 years (N= 215) ³35 years (N=216) All subjects (N=431) Clinical Attachment Loss (CAL) Mean (SD)% of CAL ³3 mm 12.9 (19.1) 56.9 (30.4) 34.9 (33.6) Mean (SD)% of CAL ³4 mm 8.0 (15.8) 42.0 (32.7) 25.0 (30.8) Mean (SD)% of CAL ³5 mm 3.4 (11.3) 25.3 (30.9) 14.4 (25.7) Mean (SD)% of CAL ³6 mm 1.6 (7.8) 16.5 (26.2) 9.1 (20.7) Periodontal Probing Depth (PPD) Mean (SD)% of PPD ³4 mm 12.0 (17.2) 21.1 (25.2) 16.6 (22.0) Mean (SD)% of PPD ³5 mm 2.2 (5.3) 9.4 (17.3) 5.8 (13.2) Mean (SD)% of PPD ³6 mm 0.6 (2.4) 5.2 (12.3) 2.9 (9.2) Mean (SD)% of PPD ³7 mm 0.3 (1.4) 2.9 (8.1) 1.6 (6.0) 56 Table 6. Unadjusted and adjusted exposure associations with total periodontitis cases using the American Academy of Periodontology and the European Federation of Periodontology (AAP/EFP) criteria Exposures AAP/EFP total periodontitis cases Adjusted Model summary: Nagelkerke R2=0.252; (p<.001) Unadjusted OR Adjusted OR OR (95% CI) p-value OR (95% CI) p-value Age (years) <35* years 1.0 1.0 35+ years 10.5 (4.7, 23.7) <.001 11.5 (4.5, 29.0) <.001 Sex Females* 1.0 1.0 Males 2.2 (1.2, 4.0) .010 1.6 (0.7, 2.4) .256 Education > High school* 1.0 1.0 ≤ High school 1.0 (0.6, 1.8) .880 0.6 (0.3, 1.2) .126 Household monthly income Higher (≥5,000 Saudi Riyals)* 1.0 1.0 Lower (<5,000 Saudi Riyals) 1.8 (1.0, 3.2) .043 2.5 (1.3, 4.9) .007 Diabetes mellitus Other* 1.0 1.0 Uncontrolled 2.8 (0.9, 7.9) .058 0.8 (0.2, 2.7) .710 Obesity Non-obese* 1.0 1.0 Obese 1.6 (0.8, 3.6) .213 1.0 (0.4, 2.6) .949 Cigarette smoking Never-smokers* 1.0 1.0 Former smokers 1.3 (0.5, 3.4) .622 0.7 (0.2, 0.2.1) .470 Current smokers 3.7 (1.3, 10.4) .015 2.5 (0.8, 8.6) .134 Perceived stress Higher (≥42.1) * 1.0 1.0 Lower (≤42) 1.4 (0.8, 2.4) .222 1.2 (0.6, 2.3) .565 Perceived social support Higher (≥69.5) * 1.0 1.0 Lower (<69.5) 0.8 (0.5, 1.4) .502 0.8 (0.4, 1.4) .365 *Reference category, OR: Odds Ratio, CI: confidence interval. Unadjusted OR (bivariate logistic regression), adjusted ORs (multivariate logistic regression) 57 Table 7. Unadjusted and adjusted exposures of stage III/IV periodontitis using the American Academy of Periodontology and the European Federation of Periodontology (AAP/EFP) criteria Exposures AAP/EFP severe periodontitis (stage III/IV) Adjusted Model summary: Nagelkerke R2=0.459; (p<.001) Unadjusted OR Adjusted OR OR (95% CI) p-value OR (95% CI) p-value Age (years) <35* years 1.0 1.0 35+ years 9.7 (6.2, 15.0) <.001 8.2 (5.0, 13.6) <.001 Sex Females* 1.0 1.0 Males 2.7 (1.8, 4.1) <.001 2.5 (1.4, 4.6) .003 Education > High school* 1.0 1.0 ≤ High school 2.2 (1.5, 3.3) <.001 1.6 (0.9, 2.8) .063 Household monthly income Higher (≥5,000 Saudi Riyals)* 1.0 1.0 Lower (<5,000 Saudi Riyals) 1.7 (1.2, 2.5) .006 2.3 (1.3, 3.9) .002 Diabetes mellitus Other* 1.0 1.0 Uncontrolled 5.0 (2.6, 9.6) <.001 1.8 (0.8. 3.8) .154 Obesity Non-obese* 1.0 1.0 Obese 1.8 (1.1, 2.9) .023 1.3 (0.7, 2.5) .357 Cigarette smoking Never smoked* 1.0 1.0 Former smokers 3.3 (1.6, 6.8) <.001 2.1 (0.8, 5.2) .133 Current smokers 2.3 (1.4, 3.9) .001 2.0 (0.9. 4.1) .073 Perceived stress Higher (≥42.1)* 1.0 1.0 Lower (≤42) 1.6 (1.1, 2.3) .018 2.0 (1.2, 3.4) .008 Perceived social support Higher (≥69.5) * 1.0 1.0 Lower (<69.5) 1.3 (0.9, 2.0) .132 1.7 (0.9, 2.7) .051 *Reference category, OR: odds ratio, CI: Confidence Interval. Unadjusted OR (bivariate logistic regression), adjusted ORs (multivariate logistic regression). 58 Table 8. Unadjusted and adjusted exposure associations with the moderate-severe periodontitis using the Centers for Disease Control and Prevention and the American Academy of Periodontology (CDC/AAP) criteria Exposures CDC/AAP moderate-severe Periodontitis Adjusted Model summary: Nagelkerke R2=0.327; (p<.001) Unadjusted OR Adjusted OR OR (95% CI) p-values OR (95% CI) p-values Age <35* years 1.0 1.0 35+ years 13.0 (6.5, 25.9) <.001 12.0 (5.6, 25.8) <.001 Sex Females* 1.0 1.0 Males 2.0 (1.2, 3.3) .006 1.1 (0.6, 2.1) .822 Education > High school* 1.0 1.0 ≤ High school 1.7 (1.0, 2.7) .003 0.9 (0.5, 1.6) .786 Household monthly income Higher (≥5,000 Saudi Riyals)* 1.0 1.0 Lower (<5,000 Saudi Riyals) 1.5 (0.9, 2.4) .101 2.1 (1.2, 3.7) .014 Diabetes mellitus Other* 1.0 1.0 Uncontrolled 3.7 (1.4, 9.4) .007 0.9 (0.3, 2.7) .839 Obesity Non-obese* 1.0 1.0 Obese 2.5 (1.2, 5.2) .015 1.6 (0.7, 3.7) .300 Cigarette smoking Never smoked* 1.0 1.0 Former smokers 2.2 (0.8, 5.7) .113 1.5 (0.7, 3.7) .466 Current smokers 4.0 (1.7, 9.4) .002 4.2 (1.5, 11.7) .006 Perceived stress Higher (≥42.1)* 1.0 1.0 Lower (≤42) 1.4 (0.9, 2.2) .166 1.3 (0.8, 2.3) .343 Perceived social support Higher (≥69.5)* 1.0 1.0 Lower (<69.5) 1.0 (0.6, 1.5) .834 0.9 (0.5, 1.5) .636 *Reference category, OR: odds ratio, CI: Confidence Interval. Unadjusted OR (bivariate logistic regression), adjusted ORs (multivariate logistic regression). 59 Table 9. Unadjusted and adjusted exposure associations with severe periodontitis using the Centers for Disease Control and Prevention and the American Academy of Periodontology (CDC/AAP) criteria Exposures CDC/AAP severe periodontitis Adjusted Model summary: Nagelkerke R2=0.325; (p<.001) Unadjusted OR Adjusted OR OR (95% CI) p-value OR (95% CI) p-value Age <35* years 1.0 1.0 35+ years 6.5 (4.1, 10.6) <.001 4.5 (2.9, 8.3) <.001 Sex Females* 1.0 1.0 Males 2.5 (1.6, 3.7) <.001 1.9 (1.0, 3.6) .037 Education > High school* 1.0 1.0 ≤ High school 2.5 (1.6, 4.0) <.001 2.0 (1.2, 3.5) .012 Household monthly income Higher (≥5,000 Saudi Riyals)* 1.0 1.0 Lower (<5,000 Saudi Riyals) 1.6 (1.1, 2.4) .024 1.7 (1.0, 3.0) .039 Diabetes mellitus Other* 1.0 1.0 Uncontrolled 4.6 (2.6, 8.0) <.001 2.0 (1.0, 3.8) .039 Obesity Non-obese* 1.0 1.0 Obese 1.6 (0.9, 2.7) .062 1.3 (0.7, 2.4) .437 Cigarette smoking Never smoked* 1.0 1.0 Former smokers 2.7 (1.1, 4.1) .018 1.4 (0.6, 3.2) .439 Current smokers 2.5 (1.5, 4.2) <.001 2.3 (1.2, 4.6) .018 Perceived stress Higher (≥42.1) * 1.0 1.0 Lower (≤42) 1.5 (0.9, 2.3) .056 1.6 (0.9, 2.7) .057 Perceived social support Higher (≥69.5) * 1.0 1.0 Lower (<69.5) 1.1 (0.7, 1.6) .701 1.1 (0.7, 1.9) .612 *Reference category, OR: Odds Ratio, CI: Confidence Interval. Unadjusted OR (bivariate logistic regression), adjusted ORs (multivariate logistic regression). 60 2.4 Discussion Under uniformly high levels of plaque, exposures associated with untreated periodontitis included age ≥35 years, male sex, lower education, lower income, uncontrolled diabetes mellitus, obesity, lower perceived stress, and current cigarette smoking. The study participants were selected from a dental school that is close to scattered residential areas of some descendants of nomadic tribes who are known to have limited access to dental care and generally low socioeconomic status. The fact that the dental school is relatively new and have been increasing the capacity of accepting new patients may offered an opportunity for those who wished to be treated but were unable in the past. A selection bias, however, has been introduced by recruiting the individuals from dental school using purposive (non-probability) sampling, consequently, the study had low statistical generalizability. The representativeness of study findings can be limited to the examined study group during the data collection period and may not represent the source population. Obtaining a random sample to study a minority group can be difficult to achieve as previously acknowledged in the literature (Kalsbeek WD, 2003). This can be especially true when the minority population of interest is mainly made of nomads who may present several difficulties to recruit them in research such as national registry may or may not have enough records regarding nomads, having unstable lifestyle and lack of fixed residential places, moving too quickly, scattered distribution across the country, and mostly concentrated in difficult to reach areas such as desserts or mountains. In addition to the fact that most of what is known and documented about nomads is based on anecdotal evidence and only little is known about them thus far. On the other hand, the sampling approach in this study has been conducted consecutively and the response rate was high (97.0%); thus, the study potentially avoided volunteer bias and non-response bias. Factors that may have increased the internal validity in our study include high measurement reliability for subjects’ responses, high intra-examiner measurements agreement, clinical measurements (performed by certified periodontist), and minimum proportion of listwise missingness. In contrast, factors that may have decreased the internal validity include lack of objective measurements to validate the self-reported medical conditions by assessment of HbA1c and BMI (or waist to height ratio). The self-reported oral self-care did not align well with having a uniformly high levels of plaque scores. Thus, such measure could be biased by social desirability, that is, subjects may report practicing daily oral self-care because they know it is a socially desirable behavior rather reporting the actual behavior. Internal validity can be further limited by the inherent limitations of cross-sectional study design including lack of ascertainment of temporal sequence and direction of associations with exposures. Possible sources of confounding could exist and may be inadequately controlled. Furthermore, the natural course of disease can only be inferred based on the wide spectrum of disease stages rather than being directly evaluated using longitudinal study design. 61 In contrast to our study design, cross-sectional studies that use random samples have better design compared to our study in terms of representativeness; external validity of periodontitis prevalence that can be generalized to the whole underlying population (Lash TL & Rothman KJ, 2021b). In addition, general population-based studies may have higher variations in the distribution of exposures compared to our targeted untreated group. However, the representativeness of random sampling of large-scale population-based studies can often be undermined by different sources of bias including non-response bias where those who participate can be systematically different than those who refuse to participate (Bose J, 2002; Shi L, 2007); difficulty of applying stringent protocol in large scale studies can increase the missingness of data; information bias that may result from measurement errors due to the need for multiple examiners that reduces the internal validity and consequently reduces the external validity as well (Hefti AF & Preshaw PM, 2012; Lash TL & Rothman KJ, 2021b). Compared to our study, previous studies on untreated populations had superior study designs in terms of: obtaining random samples of individuals with uniformly high levels of plaque which could increase representativeness of their sampled groups (Baelum V, Fejerskov O, et al., 1988; Baelum V, Wen-Min L, et al., 1988; Cutress TW et al., 1982; Manji F et al., 1988); populations residing in rural areas with uniform lack of access to dental and medical care have created ideal samples for studying the natural history of disease with an absolute lack of treatment (Loe H, Boysen H, et al., 1978; Löe H et al., 1986); longitudinal study designs allowed a direct inference when studying natural history of periodontitis (Baelum V et al., 1997; Loe H, Anerud A, et al., 1978; Löe H et al., 1986; Timmerman MF et al., 2000); longitudinal designs also allowed studying the risks of periodontitis onset and progression (Baelum V et al., 1997; Neely AL et al., 2001; van der Velden U et al., 2006). In our study, however, we could not follow up the subjects over time without providing them treatments in the current era due to ethical concerns (Bhopal RS, 2016; Jewell NP, 2016). Periodontitis prevalence and/or extent in our study were generally comparable to those of untreated Guatemalan, Sri Lankan, Kenyan, Indonesian, and Chinese rural populations (Baelum V et al., 1996; Dowsett SA, Eckert GJ, et al., 2002a; Dowsett SA et al., 2001; Loe H, Boysen H, et al., 1978; Timmerman MF et al., 1998). However, head-to-head comparisons of periodontitis distributions was challenged by differences in reporting and methodological heterogeneity among these studies including approaches of clinical assessments (Using PRP versus FRP), periodontitis case definitions, and presentations of within group comparisons. Despite having an overall low socioeconomic status in our study, some variations were observed and allowed us to study several exposures, including the underlying exposures of periodontitis. Our study design could be superior to previous studies on untreated populations in terms of measuring several exposures which allowed us to differentiate between exposures that had uniform distribution among study subjects versus those exposures that were amenable to be used in statistical analyses. In contrast, previous studies on untreated populations mostly provided generic descriptions of the populations or considered limited number of exposures without investigating, quantifying, 62 reporting, or analyzing the distribution of wider spectrum of exposures that could be associated with periodontitis. Exposures that were previously studied for their potential associations with periodontitis were generally limited to age, sex, smoking, and local factors (Baelum V et al., 1997; Baelum V, Fejerskov O, et al., 1988; Cutress TW et al., 1982; Neely AL et al., 2001; van der Velden U et al., 2006). In one previous study, the level of education and medical conditions were investigated; the medical conditions were not reported (not clear if medical conditions existed); Level of education was excluded from the analyses due to having a p-value ³0.1 in stepwise linear regression (van der Velden U et al., 2006). Exclusion of independent variables from regression models due to having undesirable p-value is commonly employed even in concurrent literature which can be inappropriate for several reasons (Smith G, 2018). Exclusion of such variables means the study did not consider adjustment of the outcome variable based on these independent variables. Having undesirable p-value does not indicate lack of clinically meaningful effect but could possibly indicate the “uncertainty” of such effect (Leek J et al., 2017). Another aspect criticized for methods employed in stepwise regression analyses was the possible “data mining” based on statistical significance rather than conceptual or scientific basis which can lead to spurious interpretations of study findings (Altman N & Krzywinski M, 2017; Smith G, 2018). The periodontitis prevalence was stratified based on age in our study. In adolescents and young adults (13 to 34 years), the prevalence of the CDC/AAP moderate-severe periodontitis and severe periodontitis was 39.1% and 13.0%, respectively which is considered substantially high compared to a prevalence of similar age groups; a prevalence of moderate periodontitis was 1.1% in young Saudi females (14 to 27 years) (AlQahtani NA et al., 2017); a prevalence of moderate periodontitis was 21.7% in general Saudi subjects examined at dental school clinics (25 to 34 years) (Hossain et al., 2018); and a prevalence of moderate-severe and severe periodontitis were 16.0% and 1.6% respectively reported in New Zealand young adults (25-26 years) (Thomson WM & Williams SM, 2002). In contrast, the prevalence of moderate-severe and severe periodontitis in our young subjects was similar to the corresponding prevalence of periodontitis in Southern Brazilian youth (14 to 29 years) which were 33.9% and 8.4%, respectively (Susin C et al., 2011) and lower than that of Guatemalan youth (18 to 34 years) where the prevalence was 93.0% and 32.0%, respectively (Dowsett SA et al., 2001). In young individuals, the periodontitis extent at thresholds of CAL ≥3 mm and CAL ≥5 mm was 12.9% and 3.4%, respectively, which were fairly comparable with the periodontitis extent of 9.7% and 1.1% in Southern Brazilian populations (Susin C et al., 2011). In contrast, a much lower extent of 0.9% (CAL ≥3 mm threshold) was reported in young military recruits from the UK (Eaton KA et al., 2001). Our findings indicate that our young group had a substantially higher susceptibility to periodontitis as compared to most of the local or global reported estimates (AlQahtani NA et al., 2017; Eaton KA et al., 2001; Hossain et al., 2018; Thomson WM & Williams SM, 2002). Due to our eligibility criteria, we were only able to use the access to health care model to describe some potential attributes for lack of utilization of dental care. Despite that the dental school was conveniently located closer to the 63 participants’ residential areas and offered comprehensive treatment at no cost, nearly half of the sample visited the dental school sought symptomatic treatment only despite having high proportions of plaque scores and periodontitis prevalence. Thus, along with the different barriers for utilization dental care, the lack of perceived need for dental care can be an additional barrier. This can be a particularly an issue with periodontitis since it is mostly a silent disease and there is a low chance that patients would visit the emergency clinic to seek periodontal care. In general, unless patients with periodontitis are bothered by excessive tooth mobility, bleeding, halitosis, or exposed roots, they may not seek dental care for periodontitis. A possibly related concept to the lack of perceived need for treatment is the lack of awareness (Saurman E, 2016). In our study, we compared the self-assessed oral hygiene and periodontal health to objective measurement of full mouth plaque score and periodontitis extent respectively; some of the subjects who rated their conditions to have good to excellent had high plaque scores and periodontitis extent; these findings may imply the lack of awareness regarding the oral self-care and periodontal health. The study confirmed associations of known modifiable exposures that may increase the probability of having periodontitis such as low socioeconomic status, current smoking, lack of glycemic control, and obesity (Eke PI et al., 2016; Susin C et al., 2004). The two unmodifiable exposures: increased age and male sex also had increased probability of having periodontitis. When periodontitis extent was plotted based on age cohorts and sex, males had higher periodontitis extent across most of age cohorts compared to females. In the youngest group (£20 years), however, males and females had similar periodontitis extent. This may indicate that both males and females have similar probability of developing periodontitis at younger age, then some exposures modify the susceptibility to periodontitis for males compared with females prior to 20 years. These findings of increased prevalence and extent of periodontitis in males confirm previous findings from rural populations with uniformly high levels of plaque and minimal access to dental care (Baelum V et al., 1997; van der Velden U et al., 2006). Thus, these findings contradict some suggestions that increased susceptibility to periodontitis in males compared with females can be attributed to poor oral self-care and lower access to dental care. An unexpected finding in our study was the significant association between a lower level of perceived stress and stage III/IV periodontitis. This finding can be hypothetically attributed to having a higher perceived stress within beneficial limits or because perceived stress effect could be countered by the effect of perceived social support. It has been suggested before that social support could act as a moderator that buffers the effect of stress (Merchant AT et al., 2003; Zimet GD et al., 1988). Such hypothesis was not evaluated in this study and will be tested in future. On the other hand, the perceived stress finding could be spurious due to the use of cross-sectional design and inability to preclude possible interactions with unmeasured stress-related exposures, such as having specific daily strains or inadequate coping (Genco RJ et al., 1999). Another suggestion in the literature related to periodontitis association with stress is that it could be attributed to increase in smoking or decrease in oral self-care (da Silva AM et al., 1995; Genco RJ et al., 1998). In our study, despite that half of the subjects reported stop brushing in stressful 64 days, this finding might be misleading since our study population had uniformly high levels of plaque. Furthermore, in some of those who answered that they did not stop brushing in stressful days, they explained it by stating that they do not brush their teeth at all. In addition, only small proportion of smokers reported to increase smoking in stressful days. Underlying exposures such as perceived social support, socioeconomic, as well as the perceived barriers to access dental care are important to consider since they potentially link the individual-level exposures and the community- or population-level exposures (Bouchard P et al., 2017; Braveman P & Gottler L, 2014). Despite that the overall perceived social support was high in our study, it did not seem to help in having a lower periodontitis prevalence. Perhaps a missing concept that was needed but unmeasured in our study is the “subjective norms” which can be defined as the subjective social pressure to perform or avoid a certain behavior (Ajzen, 1991). We can assume that having high social support may not help in improving the health outcomes if neglecting health and not seeking health care is perceived as “normal” by the individual as well as their own social network. These different links between the individual and the society in the predisposing exposures highlight the fact that using the contemporary approaches of periodontitis prevention and management at the individual level may not adequate and there is a need to involve other stakeholders such as decision makers to undertake community-level interventions. When the CDC/AAP case definitions (Eke PI et al., 2012; Page RC & Eke PI, 2007) were compared with the AAP/EFP staging criteria (Tonetti MS et al., 2018), the CDC/AAP had more specific and conservative thresholds, though, both definitions had classified nearly 100.0% of older subjects ≥35 years as periodontitis cases. Thus, considering studying a wide age range may have allowed us to explore the associations with exposures that could have been masked if we restricted our sample to older age group. Different case definitions and disease thresholds had different significant associations with periodontitis; confirming the need for standardized case definitions when studying periodontitis related associations (Manau C et al., 2008; Preshaw PM, 2009). Although the CDC/AAP is the most widely used case definitions in epidemiological studies, the practical implications of the different severity thresholds may not be clear. On the contrary, the AAP/EFP staging criteria have a more practical implications for clinicians, but it’s use in epidemiological studies is less clear. When the practical implications of staging were justified at the time of proposing the framework, both stage I and II had the same management, yet classified separately. The use of grading may not work for epidemiological studies, since it relies on using radiographs which are not routinely collected as part of screening. Assigning the grading are meant to change over time and fluctuate which does not work for epidemiological studies use. Furthermore, grading is modified by using risk factors such as smoking and diabetes in assigning a diagnosis. Consequently, diagnosing periodontitis based on grading cannot be used as dependent variable for predicting the exposures that can be associated with periodontitis. Studies that used the AAP/EFP criteria for defining periodontitis for their populations either used the staging only (Botelho J et 65 al., 2020) or acknowledged the difficulty of applying such exhaustive criteria for population groups (Germen M et al., 2021; Ndjidda Bakari W et al., 2021). While the AAP/EFP classification of periodontitis offered an advantage by assigning classifications based on natural course of disease, the use of cancer staging/grading framework may have unnecessarily complicated the classification by adding too many categories (Tonetti MS et al., 2018). Also, limiting the exposures that can be considered to smoking and diabetes may have limited the clinicians from considering other possible exposures that could impact the treatment outcomes and the compliance of patients with treatment. For example, a patient who have dental anxiety, lack of awareness, or low perceived need for therapy may be less likely to comply with the treatment or maintenance. Thus, considering a wider prospective of exposures, including some underlying exposures, could impact the patient management regardless of the periodontitis stage. Also, the patient could have exposures that may increase the probability of developing periodontitis prior to the development of periodontitis clinically but are not considered in the staging. Based on the stages of natural course of disease, efforts to prevent the periodontitis at primary or primordial levels need to focus on exposures prior to the development of the disease. Thus, an alternative framework that could have simplified the classification is the one used in diagnosing the Medication Related Osteonecrosis of the Jaw (MRONJ) (Ruggiero SL et al., 2014). The MRONJ staging diagnoses the patient based on being at risk of developing the disease then stages ranging from 0 to 3 are based on some signs and symptoms specific to MRONJ. The management of patients begins early at (risk) stage and more extensive management is recommended based on the progress of disease. Therefore, MRONJ framework offered the advantages of considering the patient management at early stages. Also, different exposures are considered along the line rather than overwhelmingly diagnosing patients on different grades based on some exposures and rate of progression. Study’s implications for policy makers: Among the different efforts that can be applied by policy makers are providing public documentations that could facilitate the research on a population subgroup such as nomadic tribes. Some suggestions for strategies that could potentially improve the dental health outcomes is enforcement of education for all population including the minorities, facilitating dental insurance for individuals with low socioeconomic status and low-profile jobs, and increasing number of dental clinics at underserved areas. Implications for public health professionals: Public health professionals can help in advocating for an overall healthy lifestyle and promoting health behaviors such as regular visits to medical and dental care, smoking cessations, and healthy diet. Implications for clinical practice: a number of exposures need to be investigated and managed rather than focusing on two exposures (diabetes and smoking) which are listed as part of periodontitis grading framework. Examples of modifiable underlying exposures need to be considered can include barriers of utilization of dental care such as lack of awareness, dental anxiety which may improve the patient’s management and increase the motivation for attending regular dental visits and maintenance. There is also a potential need for 66 integrated dental and medical care in order to improve the patient management since most study individuals had more frequent visits to medical care but did not seek dental care. It is possible that the participants perceive the medical care to have higher priority than dental care. Medical professional could help in advising patients to seek regular dental care especially for patients diagnosed with chronic medical conditions including diabetes mellitus. Future research directions: the fact that we have limited current knowledge about the possible links between underlying exposures and health behaviors my necessitates conducting qualitative research to allow in depth investigation of possible links; this can be especially relevant to the nomadic tribes since little is known about them. The interaction between psychosocial exposures and buffering hypothesis of perceived social support on perceived stress will be tested in future using a full structural equation model. A suggestion for future studies that attempt to evaluate the role of social support is to evaluate subjective norms as a construct since high social support alone may not be enough to explain the health outcomes or health related behaviors. It is also important to consider in future studies that social network can have impact on behaviors in either positive or negative ways. 2.5 Conclusions Despite the uniformly high levels of plaque, exposures associated with untreated periodontitis included age ≥35 years, male sex, lower education, lower income, uncontrolled diabetes mellitus, obesity, lower perceived stress, and current cigarette smoking. The use of the AAP/EFP staging can be applied to estimate periodontitis prevalence in population-based studies. However, diagnoses based on grading can be inappropriate due to the tendency to fluctuate and the need for radiographic assessment. Furthermore, the use of smoking and diabetes as inherent part of grading further limit its use for studying periodontitis exposures. 67 Chapter 3: Performance of Partial Mouth Recording Protocols in Estimating Prevalence, Extent, and Associations with Untreated Periodontitis (Project II) A version of this chapter has been published (Alawaji Y, Mostafa N, et al., 2022). 3.1 Introduction Among the main goals of epidemiological studies are to estimate the population-based disease distribution and its exposures (Lilienfeld DE, 1978). In periodontitis examinations, the FRP including 28 teeth, with six sites per tooth, is considered the gold standard approach (Holtfreter B et al., 2015). In comparison, the PRPs can be more convenient and cost-effective approach for population-based studies. Though, bias is often introduced when using PRPs. More than 32 PRPs have been proposed in the literature and tested for their accuracy in estimating the prevalence, extent, and severity of periodontitis (Tran DT et al., 2013). The most frequently used PRPs included the Ramfjord teeth (Ramfjord SP, 1959), a protocol used in the NHANES III: (HM)MB-B, the NHANES IV protocol: (HM)MB-B-DB, and RHM at six sites per tooth. A majority of the studies in which the accuracy of PRPs was compared to FRPs mainly focused on studying the prevalence, extent, and severity of periodontitis (Eaton KA et al., 2001; Hunt RJ, 1987; Hunt RJ & Fann SJ, 1991; Kingman A et al., 1988, 2008; Susin C et al., 2005; Tran DT et al., 2014, 2016). In recent years, the precision of PRPs in estimating the exposures associations of periodontitis was also assessed (Akinkugbe AA et al., 2015; Alshihayb TS et al., 2020; Peres MA et al., 2012; Thomson WM & Williams SM, 2002). Impact of PRPs on estimating associations with periodontitis mainly resulted in a differential misclassification bias since the probability of periodontitis misclassification can be different among periodontitis cases with or without exposures (Preisser JS et al., 2018). Consequently, periodontitis OR can be either underestimated or overestimated when using PRPs. Among the suggested factors that may impact the performance of PRPs in estimating the exposures include the selection of PRP type and number of sites (Preisser JS et al., 2018); severity thresholds of case definitions (Alshihayb TS et al., 2020; Heaton B, Garcia RI, et al., 2018); extent and pattern of disease (Preisser JS et al., 2018); underlying distribution of periodontitis clinical parameters: CAL or PPD (Heaton B, Garcia RI, et al., 2018); and magnitude of specific associations (Heaton B, Garcia RI, et al., 2018). A few studies attempted to evaluate the impact of using PRPs in studying periodontitis associations and some of their possible limitations include using narrow age groups: limited to 24-26 years young adults (Peres MA et al., 2012; Thomson WM & Williams SM, 2002) or older groups: 52-74 years (Akinkugbe AA et al., 2015), having small magnitude of associations that ranged from 1.04 to 1.26 (Alshihayb TS et al., 2020), being simulation studies (Alshihayb TS & Heaton B, 2022; Heaton B, Garcia RI, et al., 2018), or used hypothetical data (Preisser JS et al., 2018). 68 It has been reported in the literature that the use of PRPs in older individuals could have better performance in estimation of periodontitis based on an assumption that adults may have higher periodontitis prevalence, extent and symmetrical distribution compared with young individuals (Papapanou P & Lindhe J, 2015). However, such assumption can be difficult to support with evidence based on the current literature. Studies either focused on young individuals with narrow age groups (24-26 years) only (Peres MA et al., 2012; Thomson WM & Williams SM, 2002), focused on adults and elderly only (Akinkugbe AA et al., 2015; Alshihayb TS et al., 2020; Beck JD et al., 2006; Tran DT et al., 2014, 2016), or considered recruitment of wide age range (14 to 103 years) without reporting any age-based comparisons (Kingman A et al., 2008; Romano F et al., 2019; Susin C et al., 2005). The study on Guatemalan population is a rare study that evaluated PRP performance considering direct age-based comparisons upon wide age range group (18 to 78 years) (Dowsett SA, Eckert GJ, et al., 2002b). For periodontitis prevalence, younger individuals (<35 years) had a sensitivity of ≥50.0% using RHM whereas older individuals (≥35 years) had sensitivity of ≥71.0%. For periodontitis extent, younger age group had correlations ≥0.74 using RHM compared with FRP while the correlations were ≥0.0 using Ramfjord index teeth compared with FRP. In older age group, correlations were ≥0.81 using RHM compared with FRP, and correlations were ≥0.63 using Ramfjord index teeth compared with FRP. Despite that reporting correlations can give some insights regarding the PRP performance, it was not clear if periodontitis extent was underestimated or overestimated using PRPs since the study only reported the correlations or sensitivities for age related comparisons without reporting the actual summaries of periodontitis prevalence and extent among different age groups. Nevertheless, findings from this study supports the claim that PRP performance can be different in young individuals compared with older individuals which may need to be further tested. Considering the assumption that the use of PRPs could have better performance in adult population due to higher periodontitis prevalence, more generalized distribution, and higher degree of symmetry (Papapanou P & Lindhe J, 2015), similar argument can be possibly made assuming that using PRPs in untreated populations would result in a superior performance. Studies on untreated rural populations almost solely relied on using PRPs in conducting their periodontal evaluations. Study on Sri Lankan tea workers measured the mesial and buccal sites of the whole mouth; the protocol was modified in later reports to limit the measurements to mesial surfaces only (Loe H, Boysen H, et al., 1978; Löe H et al., 1978, 1986). The Java project on untreated Indonesian tea workers employed measurements of all interproximal surfaces of Ramfjord index teeth (MB-DB-ML-DL) in addition to ML-DL of all teeth except molars (Timmerman MF et al., 1998). Studies on rural Chinese and Kenyan populations measured the MB-B-DB-L of all teeth (Baelum V, Fejerskov O, et al., 1988; Baelum V, Wen-Min L, et al., 1993). However, none of these studies reported attempts to verify the performance of PRPs in those untreated populations. To the best of our knowledge, only one study attempted to evaluate the performance of PRPs in untreated population (Dowsett SA, Eckert GJ, et al., 2002b). Estimation of periodontitis severity using PRP had no bias in untreated 69 population, however, estimation of prevalence, and extent varied based on the PRP type: RHM versus Ramfjord index teeth protocols. For periodontitis extent, the absolute bias was generally small (≤|1.04|% for Ramfjord teeth) and (≤|0.5|% for RHM) at different CAL thresholds (≥3mm to ≥7 mm). For periodontitis prevalence, the absolute bias ranged from 0.0% to |13.0|% at different CAL thresholds (≥3mm to ≥7 mm) for RHM. For estimation of prevalence using Ramfjord index teeth, the absolute bias ranged from |1.0|% to |24.0|% at different CAL thresholds (≥3mm to ≥7 mm). It can be inferred based on such findings that there is a possibility of having large magnitude of bias in estimation of periodontitis prevalence when using PRPs in previous studies on untreated populations. Therefore, further testing of the impact of using PRPs in untreated populations is possibly needed. This study aims were to 1) determine the performance of PRPs in estimating the prevalence, extent, and associations of untreated periodontitis, and 2) compare the PRPs performance for periodontitis findings between younger and older individuals. 3.2 Materials and methods 3.2.1 Study subjects The current study recruited a purposive sample of subjects who had never been treated for periodontal conditions from the screening dental clinics at the College of Dentistry at KSAU-HS in Saudi Arabia. Most of recruited individuals were descendants of nomadic tribes who reside in scattered underserved areas eastern to Riyadh city. Thus, these patients had limited access to dental care. A selection bias is expected due to the recruitment of study population from screening dental clinics at the dental school and statistical inference of study findings can be limited to the recruited study population. The recruitment period ranged from early September 2019 to the end of December 2019. The Ethics approval was obtained from the KAIMRC (H-01-R-005) and from the University of British Columbia; Clinical Research Ethics Board (H19-01019). Consent forms were signed by all participants before data collection. Inclusion criteria: Dentate or partially dentate subjects who had never been treated for periodontal conditions (dental history was limited to symptomatic dental treatments), were able to communicate in Arabic or English, did not need premedication or prophylactic antibiotics, and did not have cellulitis, acute dental abscesses, cysts, or tumors. 3.2.2 Data collection Clinical examinations were performed by a certified periodontist using a FRP examining 28 teeth, with six sites per tooth. The intra-examiner agreement was tested by employing duplicate measurements of 10 subjects using Cohen’s kappa at two disease thresholds: CAL ≥3 mm at ≥2 interproximal sites and CAL ≥5 mm at ≥2 interproximal sites. 70 Questionnaires collected sociodemographic data, and information about participant medical conditions, their use of medications, oral health-related behaviors, perceived stress (Appendix C) (Cohen S & Williamson G, 1988) and perceived social support (Appendix D) (Zimet GD et al., 1988) Cohen’s kappa test determined the reliability of the subjects’ repeated responses to a repeated question about education levels. The internal consistency of a 10-item perceived stress scale and a 12-item perceived social support were tested using Cronbach’s alpha. 3.2.3 Study outcomes and selection of partial-mouth-recording protocols The following PRPs were tested: 1) RHM at two diagonal quadrants; 2) (FM)MB-DL, and 3) (HM)MB-DL. Periodontitis prevalence was based on the recommended case definitions for epidemiological studies developed by the CDC/AAP (Page RC & Eke PI, 2007), and were defined as follows: a. Severe periodontitis: CAL ≥6 mm at ≥2 interproximal sites (not at the same tooth) and PPD ≥5 mm at ≥1 interproximal site (can be at one of the sites with CAL). b. Moderate periodontitis: CAL ≥4 mm at ≥2 interproximal sites (not at the same tooth) or PPD ≥5 mm at ≥2 interproximal sites (not at the same tooth). The periodontitis extent was defined as the mean percentage of interproximal sites with CAL ≥3 mm or CAL ≥5 mm (Holtfreter B et al., 2015) 3.2.4 Sample size calculations The calculation of the minimum sample size for multivariate logistic regression was based on the primary data collected from the first 100 subjects using the G*Power program, version 3.1.9.2 (Faul F et al., 2009). The sample size required for the CDC/AAP moderate-severe periodontitis was 350 subjects based on the status of current smoking, the proportion of current smokers was in the primary data was 22.0%, OR=2.9, a=0.05, Power=0.80, and the squared variance of other variables: R2=0.450, whereas the minimal sample size required for studying the CDC/AAP severe periodontitis was 330 subjects, where OR=2.6, a=0.05, Power=0.80, and R2 for other variables=0.263. An additional 81 subjects were recruited to account for anticipated missing data and to ensure a sufficient number and proportion of cases per explanatory predictor variables to be included into the multivariate regression models. 3.2.5 Assessment of prevalence and extent of periodontitis The statistical analyses were performed at the subject level using SPSS, version 27.0 software (IBM, Chicago, IL, USA). The accuracy for assessing the prevalence of periodontitis using three PRPs was compared to that for the FRP. PRPs result in a 100.0% specificity and positive predictive values since PRPs can only identify cases with 71 periodontitis that are already identified using FRP (Preisser JS et al., 2018). However, the sensitivity and negative predictive value were calculated in this study as following: Sensitivity = true positives(true positives + false negatives) Negative predictive value = true negatives(true negatives + false negatives) The absolute bias estimation for periodontitis prevalence and extent (Kingman A et al., 2008): Absolute biasprevalence = Prevalence "#" − Prevalence $#" Absolute biasextent= Extent "#" − Extent $#" The accuracy of using PRPs for estimating the prevalence and extent of periodontitis were also compared between the younger (13-34 years) and older age groups (35-80 years). 3.2.6 Assessment of exposures’ associations with periodontitis Multivariate logistic regression models evaluated the size of unadjusted and adjusted associations with periodontitis. The exposures considered in the multivariate model included age, perceived stress, and perceived social support, originally measured as continuous variables, subsequently for analyses divided into two categories based on their respective mean scores. Medical conditions were self-reported, and only two subjects with diabetes mellitus reported having glycemic control. Thus, subjects with uncontrolled diabetes were compared to subjects without diabetes mellitus and subjects with controlled diabetes mellitus. Variables that lacked variation (only a few cases in some categories) were excluded from the statistical analyses. The excluded variables were ethnicity, other medical conditions, and plaque scores (uniformly high levels of plaque were observed, that is, ³25% of subjects’ dentitions were covered with a plaque in >96.3% of the sample). The regression analyses were performed introducing dummy variables for variables with ³3 categories. The absolute bias was calculated at the natural logarithmic (ln) scale of OR as follows (Akinkugbe AA et al., 2015): Absolute biasOR= ln(OR"#") − ln(OR$#"). 72 3.3 Results A total of 431 subjects with a mean age (SD) of 35.4 (13.3) years were recruited. Among these subjects, 42.5% were males and 57.5% were females. The selection process for the study subjects based on their eligibility criteria is presented in Figure 12. In the study sample, the individual numbers of present teeth ranged from 3 to 28 teeth, with a sample mean (SD) of 23.8 (5.2) teeth. The intra-examiner agreement using Cohen’s kappa was 0.99 for the two CAL thresholds. The reliability of the repeated question item based on Cohen’s kappa was 0.99. The internal consistency of participant responses indicated by Cronbach’s alpha was 0.77 for the perceived stress scale and 0.92 for the perceived social support scale. Listwise missingness of data was 1.4%. The prevalence and extent of periodontitis using three PRPs were compared to those determined using the FRP, findings are presented in Table 10. The prevalence of moderate-severe periodontitis using the RHM was 68.4%, the (FM)MB-DL was 68.7%, (HM)MB-DL was 58.7%, and 78.4% using the FRP reference standard. Estimating the prevalence using the (FM)MB-DL protocol resulted in the highest overall accuracy. The accuracy of estimating prevalence using (FM)MB-DL with the severe periodontitis threshold was compared to that using the moderate-severe periodontitis threshold: the sensitivity increased from 87.6% to 88.2%, the negative predictive value increased from 68.9% to 94.9% and the absolute biasprevalence decreased from -9.7% to -3.5%. A similar pattern was seen with the use of RHM; however, there was a decrease in the sensitivity when measuring severe periodontitis compared to measuring moderate-severe periodontitis. The lowest sensitivity, negative predictive value and the Figure 12. Flow chart: Selection of study subjects 73 highest absolute biasprevalence were observed using (HM)MB-DL. The extent of periodontitis had a low absolute biasextent that ranged from -0.6 to -2.3 for the three PRPs and two disease thresholds. The accuracy of prevalence and extent of periodontitis compared between the two age groups: 13-34 years and 35-80 years are presented in Table 11. In the younger age group (13-34 years) the sensitivity of diagnosing the moderate-severe periodontitis using either RHM or (FM)MB-DL was 75.0%. However, the sensitivity of diagnosing severe periodontitis in the younger age group using RHM and (FM)MB-DL were 53.6% and 82.1% respectively. The sensitivity of (HM)MB-DL was <60.0% for both disease thresholds. In the older age group (35-80 years), the sensitivity was >80.0% for moderate-severe and severe periodontitis with the use of either RHM or (FM)MB-DL. The absolute bias of PRPs for measuring the periodontitis extent in the younger age group ranged from -0.8 to 0.1 while in the older age group the absolute bias ranged from -3.9 to -1.0. The distribution of moderate-severe periodontitis prevalence for different exposures is presented in Table 12. For moderate-severe periodontitis among the tested PRPs, the (HM)MB-DL resulted in the highest level of bias for all exposures as indicated by decreased ORs as compared to those while applying FRP. The unadjusted (crude) exposure associations for the moderate-severe periodontitis are presented in Table 13, and the effect sizes of the adjusted exposure associations in Table 14. For the severe periodontitis, the unadjusted exposure associations are presented in Table 15, and the adjusted in Table 16. The overall absolute bias for unadjusted ORs ranged from -0.6 to 0.5 and for the adjusted ORs from -0.8 to 0.8. The overall magnitude of absolute bias was the largest when (HM)MB-DL protocol was used. 74 Table 10. Accuracy of estimating the periodontitis prevalence and extent at different disease thresholds using partial mouth recording protocols Full mouth (reference) Total sites: 112 RHM Total sites: 56 (FM)MB-DL Total sites: 56 (HM)MB-DL Total sites: 28 Moderate-severe periodontitis prevalence* (CAL ≥4 mm at ≥2 interproximal sites or PPD ≥5 mm at ≥2 interproximal sites) Prevalence (%) 78.4 68.4 68.7 58.7 Sensitivity (%) 87.3 87.6 74.9 Negative predictive value (%) 68.4 68.9 52.2 Absolute biasprevalence (%) -10.0 -9.7 -19.7 Severe periodontitis prevalence* (CAL ≥6 mm at ≥2 interproximal sites and PPD ≥5 mm at ≥1 interproximal site) Prevalence (%) 31.3 23.4 27.8 18.4 Sensitivity (%) 74.3 88.2 58.8 Negative predictive value (%) 89.4 94.9 84.0 Absolute biasprevalence (%) -7.9 -3.5 -12.7 Periodontitis extent† at CAL ≥3 mm Mean% (SD) 34.9 (33.6) 33.9 (32.8) 32.6 (31.6) 33.1 (32.4) Absolute biasextent -1.0 -2.3 -1.8 Periodontitis extent† at CAL ≥5 mm Mean% (SD) 14.4 (25.6) 13.8 (25.1) 13.0 (23.9) 12.9 (24.2) Absolute biasextent -0.6 -1.4 -1.5 CAL: Clinical Attachment Loss, PPD: Periodontal Probing Depth, FRP: Full-mouth Recording Protocol, RHM: Random-Half-Mouth, MB: Mesiobuccal, DB: Distobuccal, ML: Mesiolingual, DL: Distolingual, (FM): Full-Mouth, (HM) Half-Mouth. * Periodontitis prevalence is defined as proportion of subjects with periodontitis using case definitions by the Centers for Disease Control and Prevention and the American Academy of Periodontology (CDC/AAP) 2007, 2012. † Periodontitis extent is defined as the mean (SD) percentage of sites with interproximal CAL ≥3 mm or CAL ≥5 mm. 75 Table 11. Accuracy of estimating the periodontitis prevalence and extent at different disease thresholds using partial mouth recording protocols based on two age groups Periodontal disease threshold Age group Accuracy and precision FRP (reference) Total sites: 112 RHM Total sites: 56 (FM)MB-DL Total sites: 56 (HM)MB-DL Total sites: 28 Moderate-severe periodontitis prevalence* (CAL ≥4 mm at ≥2 interproximal sites or PPD ≥5 mm at ≥2 interproximal sites) 13-34 years Prevalence (%) 61.4 46.0 46.0 34.0 Sensitivity (%) 75.0 75.0 55.3 Negative predictive value (%) 71.6 71.6 58.5 Absolute biasprevalence (%) -15.4 -15.4 -27.4 35-80 years Prevalence (%) 95.4 90.7 91.2 83.3 Sensitivity (%) 95.1 95.6 87.4 Negative predictive value (%) 50.0 52.6 27.8 Absolute biasprevalence (%) -4.7 -4.2 -12.1 Severe periodontitis prevalence* (CAL ≥6 mm at ≥2 interproximal sites and PPD ≥5 mm at ≥1 interproximal site) 13-34 years Prevalence (%) 13.0 7.0 10.7 6.5 Sensitivity (%) 53.6 82.1 50.0 Negative predictive value (%) 93.5 97.4 93.0 Absolute biasprevalence (%) -6.0 -2.3 -6.5 35-80 years Prevalence (%) 49.5 39.8 44.9 30.6 Sensitivity (%) 80.4 90.7 61.7 Negative predictive value (%) 83.8 91.6 72.7 Absolute biasprevalence (%) -9.7 -4.6 -18.9 Periodontitis extent† at CAL ≥3 mm 13-34 years Mean% (SD) 12.9 (19.1) 12.4 (18.8) 12.1 (18.2) 12.4 (18.7) Absolute biasextent -0.5 -0.8 -0.5 35-80 years Mean% (SD) 56.9 (30.4) 55.2 (29.6) 53.0 (28.8) 53.5 (29.7) Absolute biasextent -1.7 -3.9 -3.4 Periodontitis extent† at CAL ≥5 mm 13-34 years Mean% (SD) 3.0 (10.8) 3.1 (10.8) 3.0 (10.8) 3.1 (11.3) Absolute biasextent 0.1 0.0 0.1 35-80 years Mean% (SD) 25.3 (30.9) 24.3 (30.2) 22.9 (29.2) 22.6 (29.2) Absolute biasextent -1.0 -2.4 -2.7 CAL: Clinical Attachment Loss, PPD: Periodontal Probing Depth, FRP: Full-mouth Recording Protocol, RHM: Random-Half-Mouth, MB: Mesiobuccal, DB: Distobuccal, ML: Mesiolingual, DL: Distolingual, (FM): Full-Mouth, (HM) Half-Mouth. * Periodontitis prevalence is defined as proportion of subjects with periodontitis using case definitions by the Centers for Disease Control and Prevention and the American Academy of Periodontology (CDC/AAP) 2007, 2012 (Eke PI et al., 2012; Page RC & Eke PI, 2007). † Periodontitis extent is defined as the mean (SD) percentage of sites with interproximal CAL ≥3 mm or CAL ≥5 mm (Holtfreter B et al., 2015). 76 Table 12. Distribution of the CDC/AAP moderate-severe periodontitis per exposure using the partial-mouth recording protocols versus full-mouth recording protocol Exposures Moderate-severe periodontitis. N (%) Full mouth RHM (FM)MB-DL (HM)MB-DL Age (years) <35 132 (61.4) 99 (46.0) 99 (46.0) 73 (34.0) 35+ 206 (95.4) 196 (90.7) 197 (91.2) 180 (83.3) Sex Females 181 (73.6) 147 (59.8) 150 (61.0) 124 (50.4) Males 155 (84.7) 147 (80.3) 146 (79.8) 129 (70.5) Level of education ≤High school 120 (74.1) 98 (60.5) 98 (60.5) 79 (48.8) >High school 215 (80.8) 195 (73.3) 197 (74.1) 173 (65.0) Household monthly income Low (<5,000 Saudi Riyals) 178 (74.5) 151 (63.2) 153 (64.0) 130 (54.4) High (>5,000 Saudi Riyals) 157 (83.1) 142 (75.1) 142 (75.1) 122 (64.6) Diabetes mellitus Other 279 (76.0) 237 (64.6) 239 (65.1) 199 (54.2) No glycemic control 58 (92.1) 57 (90.5) 57 (90.5) 54 (85.7) Obesity No 265 (75.9) 228 (65.3) 230 (65.9) 197 (56.4) Yes 71 (88.8) 65 (81.3) 65 (81.3) 55 (68.8) Cigarette smoking Never smoked 227 (73.5) 190 (61.5) 192 (62.1) 158 (51.1) Former smokers 37 (88.1) 34 (81.0) 35 (83.3) 31 (73.8) Current smokers 72 (92.3) 69 (88.5) 68 (87.2) 63 (80.8) Perceived stress Lower (≤42) 52 (24.4) 163 (76.9) 160 (75.5) 141 (66.5) Higher (≥42.1) 161 (75.6) 128 (60.1) 133 (62.4) 109 (51.2) Perceived social support Lower (<69.5) 166 (77.9) 145 (68.1) 151 (70.9) 123 (57.7) Higher (≥69.5) 167 (78.8) 146 (68.9) 142 (67.0) 127 (59.9) FRP: Full-mouth Recording Protocol, RHM: Random-Half-Mouth, (HM): Half-Mouth, (FM): Full-Mouth, MB-DL: Mesiobuccal-Distolingual. The CDC/AAP moderate-severe periodontitis is defined as CAL ≥4 mm at ≥2 interproximal sites or PPD ≥5 mm at ≥2 interproximal sites (Page RC & Eke PI, 2007). 77 Table 13. Estimation of the unadjusted (crude) exposure associations with prevalence of the CDC/AAP moderate-severe periodontitis (CAL ≥4 mm at ≥2 interproximal sites or PPD ≥5 mm at ≥2 interproximal sites) (Page RC & Eke PI, 2007) Exposures Full mouth (Reference) RHM (FM)MB-DL (HM)MB-DL OR (95% CI) OR (95% CI) AB OR (95% CI) AB OR (95% CI) AB Age (years) <35* 1.0 1.0 1.0 1.0 35+ 13.0 (6.5-25.9) 11.5 (6.7-19.6) -0.1 12.2 (7.7-20-9) -0.1 9.7 (6.2-15.3) -0.3 Sex Females* 1.0 1.0 1.0 1.0 Males 2.0 (1.2-3.3) 2.8 (1.8-4.3) 0.3 2.5 (1.6-3.9) 0.2 2.4 (1.6-3.5) 0.2 Level of education >High school* 1.0 1.0 1.0 1.0 ≤High school 1.5 (0.9-2.4) 1.8 (1.2-2.7) 0.2 1.9 (1.2-2.8) 0.2 2.0 (1.3-2.9) 0.3 Household monthly income Higher (≥5,000 Saudi Riyals)* 1.0 1.0 1.0 1.0 Lower (<5,000 Saudi Riyals) 1.7 (1.0-2.7) 1.8 (1.2-2.7) 0.1 1.7 (1.1-2.6) 0.0 1.5 (1.0-2.3) -0.1 Diabetes mellitus Other 1.0 1.0 1.0 1.0 No glycemic control 3.7 (1.4-9.4) 5.2 (2.2-12.4) 0.3 5.1 (2.1-12.1) 0.3 5.1 (2.4-10.6) 0.3 Obesity Non-obese 1.0 1.0 1.0 1.0 Obese 2.5 (1.2-5.2) 2.3 (1.3-4.2) -0.1 2.2 (1.2-5.0) -0.1 1.7 (1.0-2.9) -0.4 Cigarette smoking Never smoked* 1.0 1.0 1.0 1.0 Former smokers 2.2 (0.8-5.7) 2.1 (0.9-4.7) -0.1 2.4 (1.1-5.7) 0.1 2.1 (1.0-4.3) -0.5 Current smokers 4.0 (1.7-9.4) 4.4 (2.1-9.0) 0.1 3,7 (1.9-7.5) -0.1 3.6 (2.0-6.6) -0.1 Perceived stress Lower (≤42)* 1.0 1.0 1.0 1.0 Higher (≥42.1) 0.7 (0.5-1.2) 0.5 (0.3-0.7) -0.3 0.5 (0.4-0.8) -0.3 0.5 (0.4-0.8) -0.3 Perceived social support Higher (≥69.5)* 1.0 1.0 1.0 1.0 Lower (<69.5) 0.9 (0.6-1.5) 0.9 (0.6-1.5) 0.0 1.2 (0.8-1.8) 0.3 0.9 (0.6-1.4) 0.0 * Reference category, CAL: Clinical Attachment Loss, PPD: Periodontal Probing Depth, CDC: the Centers for Disease Control and Prevention, AAP: American Academy of Periodontology, OR: Odds Ratio, R2: Explained variance, CI: Confidence Interval, AB: Absolute Bias, FRP: Full-mouth Recording Protocol, RHM: Random-Half-Mouth, MB: Mesiobuccal, DL: Distolingual, (FM): Full-Mouth, (HM): Half-Mouth. 78 Table 14. Estimation of the adjusted exposure associations with prevalence of the CDC/AAP moderate-severe periodontitis (CAL ≥4 mm at ≥2 interproximal sites or PPD ≥5 mm at ≥2 interproximal sites) (Page RC & Eke PI, 2007) Exposures Full mouth (Reference) RHM (FM)MB-DL (HM)MB-DL Nagelkerke R2=0.327 Nagelkerke R2=0.435 Nagelkerke R2=0.413 Nagelkerke R2=0.413 OR (95% CI) OR (95% CI) AB OR (95% CI) AB OR (95% CI) AB Age (years) <35* 1.0 1.0 1.0 1.0 35+ 12.0 (5.6-25.8) 10.2 (5.5-18.6) -0.2 10.3 (5.6-18.8) -0.2 8.5 (5.0-14.3) -0.4 Sex Females* 1.0 1.0 1.0 1.0 Males 1.1 (0.6-2.1) 1.7 (0.9-3.2) 0.5 1.5 (0.8-2.9) 0.4 1.3 (0.7-2.4) 0.2 Level of education >High school* 1.0 1.0 1.0 1.0 ≤High school 0.9 (0.5-1.6) 1.2 (0.7-2.0) 0.2 1.3 (0.8-2.9) 0.3 1.4 (0.9-2.4) 0.4 Household monthly income Higher (≥5,000 Saudi Riyals)* 1.0 1.0 1.0 1.0 Lower (<5,000 Saudi Riyals) 2.1 (1.2-3.7) 2.8 (1.6-4.9) 0.3 2.3 (1.3-3.9) 0.1 2.0 (1.2-3.4) -0.1 Diabetes mellitus Other 1.0 1.0 1.0 1.0 No glycemic control 0.9 (0.3-2.7) 1.6 (0.6-4.5) 0.6 1.5 (0.5-4.0) 0.5 1.9 (0.8-4.5) 0.8 Obesity Other 1.0 1.0 1.0 1.0 Obese 1.6 (0.7-3.7) 1.6 (0.8-3.3) 0.0 1.4 (0.7-2.9) -0.1 1.1 (0.6-2.0) -0.4 Cigarette smoking Never smoked* 1.0 1.0 1.0 1.0 Former smokers 1.5 (0.5-4.7) 1.2 (0.4-3.4) -0.2 1.5 (0.6-4.3) 0.0 1.5 (0.6-3.8) 0.0 Current smokers 4.2 (1.5-11.7) 4.0 (1.6-10.0) -0.1 3.5 (1.5-8.5) -0.2 4.1 (1.9-9.1) -0.1 Perceived stress Lower (≤42)* 1.0 1.0 1.0 1.0 Higher (≥42.1) 0.8 (0.4-1.3) 0.4 (0.2-0.6) -0.8 0.4 (0.3-0.8) -0.6 0.5 (0.3-0.8) -0.5 Perceived social support Higher (≥69.5)* 1.0 1.0 1.0 1.0 Lower (<69.5) 0.9 (0.5-1.5) 1.0 (0.6-1.8) 0.2 1.4 (0.8-2.4) 0.5 0.9 (0.6-1.5) 0.0 * Reference category, CAL: Clinical Attachment Loss, PPD: Periodontal Probing Depth, CDC: the Centers for Disease Control and Prevention, AAP: the American Academy of Periodontology, OR: Odds Ratio, R2: explained variance, CI: Confidence Interval, AB: Absolute Bias, FRP: Full-mouth Recording Protocol, RHM: Random-Half-Mouth, MB: Mesiobuccal, DL: Distolingual, (FM): Full-Mouth, (HM): Half-Mouth. 79 Table 15. Precision of estimating the unadjusted (crude) exposure associations with prevalence of the CDC/AAP severe periodontitis (CAL ≥6 mm at ≥2 interproximal sites and PPD ≥5 mm at ≥1 interproximal site) (Page RC & Eke PI, 2007) Exposures Full mouth (Reference) RHM (FM)MB-DL (HM)MB-DL OR (95% CI) OR (95% CI) AB OR (95% CI) AB OR (95% CI) AB Age (years) <35* 1.0 1.0 1.0 1.0 35+ 6.6 (4.1-10.6) 8.8 (4.9-15.9) 0.3 6.8 (4.1-11.3) 0.0 6.3 (3.4-11.7) -0.1 Sex Females* 1.0 1.0 1.0 1.0 Males 2.5 (1.6-3.8) 2.6 (1.6-4.1) -0.1 2.4 (1.6-3.7) -0.1 2.7 (1.6-4.5) 0.1 Level of Education >High school* 1.0 1.0 1.0 1.0 ≤High school 2.5 (1.6-4.0) 2.6 (1.6-4.5) 0.1 1.5 (1.5-4.0) -0.5 1.8 (1.1-2.9) -0.3 Household monthly income Higher (≥5,000) Saudi Riyals* 1.0 1.0 1.0 1.0 Lower (<5,000) Saudi Riyals 1.6 (1.1-2.4) 1.4 (0.9-2.1) -0.1 1.6 (1.0-2.4) 0.0 2.6 (1.5-4.6) 0.5 Diabetes Mellitus Other 1.0 1.0 1.0 1.0 No glycemic control 4.6 (2.6-8.0) 4.5 (2.6-7.8) 0.0 3.8 (2.2-6.7) -0.2 4.9 (2.7-8.6) 0.1 Obesity Other 1.0 1.0 1.0 1.0 Obese 1.6 (0.9-2.7) 1.4 (0.8-2.5) -0.1 1.6 (0.9-2.7) 0.0 1.1 (0.6-1.9) -0.4 Cigarettes Smoking Never-smokers* 1.0 1.0 1.0 1.0 Former smokers 2.2 (1.1-4.1) 2.0 (1.0-3.9) -0.1 2.1 (1.1-4.1) -0.1 1.2 (0.6-2.7) -0.6 Current smokers 2.5 (1.5-4.2) 2.7 (1.6-4.6) -0.1 2.4 (1.5-4.0) -0.1 2.8 (1.6-4.9) 0.1 Perceived Stress Lower (≤42) * 1.0 1.0 1.0 1.0 Higher (≥42.1) 0.7 (0.4-1.0) 0.7 (0.4-1.1) 0.0 0.6 (0.4-1.0) -0.2 0.7 (0.6-1.5) 0.0 Perceived Social Support Higher (≥69.5) * 1.0 1.0 1.0 1.0 Lower (<69.5) 1.1 (0.7-1.6) 0.9 (0.5-1.3) -0.2 1.2 (0.8-1.8) 0.1 1.1 (0.7-1.8) 0.0 * Reference category, CAL: Clinical Attachment Loss, PPD: Periodontal Probing Depth, CDC: the Centers for Disease Control and Prevention, AAP: the American Academy of Periodontology, OR: Odds Ratio, R2: Explained variance, CI: Confidence Interval, AB: Absolute Bias, FRP: Full-mouth Recording Protocol, RHM: Random-Half-Mouth, MB: Mesiobuccal, DL: Distolingual, (FM): Full Mouth, (HM): Half Mouth. 80 Table 16. Estimation of the adjusted exposure associations with prevalence of the CDC/AAP severe periodontitis (CAL ≥6 mm at ≥2 interproximal sites and PPD ≥5 mm at ≥1 interproximal site) (Page RC & Eke PI, 2007) Exposures Full mouth (Reference) RHM (FM)MB-DL (HM)MB-DL Nagelkerke R2=0.325 Nagelkerke R2=0.326 Nagelkerke R2=0.309 Nagelkerke R2=0.280 OR (95% CI) OR (95% CI) AB OR (95% CI) AB OR (95% CI) AB Age (years) <35* 1.0 1.0 1.0 1.0 35+ 4.9 (2.9-8.3) 6.7 (3.5-12.7) 0.3 5.2 (3.0-9.0) 0.1 4.8 (2.5-9.4) 0.0 Sex Females* 1.0 1.0 1.0 1.0 Males 1.9 (1.1-3.6) 1.8 (0.9-3.6) -0.1 1.9 (1.1-3.7) 0.0 2.4 (1.2-5.0) 0.2 Level of education >High school* 1.0 1.0 1.0 1.0 ≤High school 2.0 (1.2-3.5) 2.2 (0.9-4.2) 0.1 2.0 (1.1-3.6) 0.0 1.8 (0.9-3.6) -0.1 Household monthly income Higher (≥5,000 Saudi Riyals)* 1.0 1.0 1.0 1.0 Lower (<5,000 Saudi Riyals) 1.7 (1.0-3.0) 1.4 (0.8-2.4) -0.2 1.7 (0.9-2.9) 0.0 1.9 (1.0-3.5) 0.1 Diabetes mellitus Other 1.0 1.0 1.0 1.0 No glycemic control 2.0 (1.1-3.8) 1.9 (0.9-3.7) -0.1 1.6 (0.8-3.0) -0.2 2.6 (1.3-5.1) 0.3 Obesity Non-obese 1.0 1.0 1.0 1.0 Obese 1.3 (0.7-2.4) 1.1 (0.5-2.0) -0.2 1.4 (0.7-2.6) 0.1 0.8 (0.4-1.7) -0.5 Cigarette smoking Never-smokers* 1.0 1.0 1.0 1.0 Former smokers 1.4 (0.6-3.2) 1.3 (0.5-3.1) -0.1 1.3 (0.6-3.1) -0.1 0.6 (0.2-1.6) -0.8 Current smokers 2.3 (1.2-4.7) 2.5 (1.2-5.2) 0.1 2.2 (1.1-4.4) -0.1 1.9 (0.9-4.1) -0.2 Perceived stress Lower (≤42) * 1.0 1.0 1.0 1.0 Higher (≥42.1) 0.6 (0.4-1.0) 0.7 (0.4-1.3) 0.2 0.6 (0.3-0.9) 0.0 0.9 (0.5-1.6) 0.4 Perceived social support Higher (≥69.5) * 1.0 1.0 1.0 1.0 Lower (<69.5) 1.1 (0.7-1.9) 0.8 (0.5-1.4) -0.3 1.3 (0.8-2.1) 0.1 1.1 (0.6-1.9) 0.0 * Reference category, CAL: Clinical Attachment Loss, PPD: Periodontal Probing Depth, CDC: the Centers for Disease Control and Prevention, AAP: the American Academy of Periodontology, OR: Odds Ratio, R2: Explained variance, CI: Confidence Interval, AB: Absolute Bias, FRP: Full-mouth Recording Protocol, RHM: Random-Half-Mouth, MB: Mesiobuccal, DL: Distolingual, (FM): Full Mouth, (HM): Half Mouth. 81 3.4 Discussion The use of PRPs had the largest impact on estimating periodontitis prevalence, whereas the impact on estimating periodontitis extent and its associations was marginal. In younger age group, the impact of using PRPs was more pronounced in underestimating the prevalence, while periodontitis extent was less impacted by using PRPs in younger group compared with older group. The (FM)MB-DL was the only protocol that performed well in younger age group. The use of purposive (non-probability) sample and the consequent selection bias in our study may limited the external validity of our findings. The statistical generalizability of our study findings might be limited to the studied group. The use of purposive sample, however, matches the study aim to obtain a group who lack periodontal treatments that otherwise cannot be randomly selected from the underlying general population or from the scattered underserved areas. The use of targeted sampling approach and the recruitment from health care centers were suggested in the literature when studying minority group who may present several difficulties that preclude the use of probability sampling (Kalsbeek WD, 2003). These difficulties in sampling minority groups can include having unknown total number, unknown population elements, groups that move from a place to another too quickly, dispersed geographically, difficult to reach, or if minority group has heterogenous characteristics. Providing the features of our study group who are mostly comprised of descendants of nomadic tribes, almost all the described difficulties in obtaining a probability sampling apply, thus, may preclude the possibility of using probability sampling. In contrast to the limited statistical generalizability of our study, having an overall high internal validity can possibly make the study findings scientifically generalizable for populations with similar characteristics (Elwood JM, 2013; Lash TL & Rothman KJ, 2021b; Nohr E & Olsen J, 2013; Rothman KJ et al., 2013). Some aspects that may have increased the study’s internal validity include the high reliability of subjects’ responses to questionnaire and an acceptable to excellent internal consistency of perceived stress and perceived social support scales. High intra-examiner agreement in clinical measurements conducted by a single examiner who is certified periodontist. The listwise missingness of data was minimum and the non-response rate was also negligible. Recruitment of study subjects was conducted consecutively where every new patient was considered; thus, may avoided a volunteer bias. The consecutive recruitment of study subjects was considered as an appropriate alternative approach if probability sampling was not used based on standards for reporting in diagnostic accuracy studies (Bossuyt PM et al., 2003). In contrast, some of the limitations of internal validity in our study include the self-report of medical conditions without validation using objective measurements of HbA1c or BMI (or waist to height ratio). Other limitations of the study are inherent to using cross-sectional study design including possible lack of control over confounding; lack of ascertainment of temporal sequence; possible limited inference regarding the direction of associations. 82 The use of two thresholds for periodontitis diagnosis in our sample of untreated subjects resulted in prevalence ranging from 31.3% to 78.4%, and an extent of periodontitis ranging from 14.4% to 34.9%. Both the prevalence and extent of periodontitis in our study subjects were higher compared with other general adult population (Chu Y & Ouyang X, 2015; Relvas M et al., 2014; Teixeira F et al., 2020; Tran DT et al., 2014, 2016) but generally comparable with the prevalence and/or extent of periodontitis in untreated populations (Baelum V et al., 1996; Dowsett SA, Eckert GJ, et al., 2002b, 2002a; Dowsett SA et al., 2001; Loe H, Boysen H, et al., 1978; Timmerman MF et al., 1998). The generalizability of our findings to previous studies on untreated populations can be limited due to several methodological differences. However, previous studies on untreated populations generally used PRPs that are measured at partial sites for the whole mouth and recruited wide age range including young age groups (Baelum V et al., 1996; Loe H, Boysen H, et al., 1978; Timmerman MF et al., 1998). We may, therefore, infer that these studies had relatively small bias when estimating different periodontitis outcomes based on the performance of (FM)MB-DL protocol in our study. Among the reported studies on untreated individuals in periodontal literature, the study on Guatemalan untreated population is possibly the only one that compared performance of PRP to that of FRP (Dowsett SA, Eckert GJ, et al., 2002b). When we compare the performance of PRP in estimating periodontitis prevalence using the RHM protocol, our study resulted in a larger bias magnitude at moderate-severe threshold compared with Guatemalan study. However, the bias was smaller in our study at severe periodontitis threshold for the RHM protocol. A common finding between our study and Guatemalan study is that PRPs with smaller number of sites resulted in poor performance in estimating prevalence; (HM)MB-DL in our study and Ramfjord’s index teeth in Guatemalan study. Although the Guatemalan study concluded that it supports the use of RHM, the performance of such protocol was lower than (FM)MB-DL protocol in our study. This difference in performance between the two PRPs [RHM and (FM)MB-DL] was more drastic in younger age group. Despite that younger age group had around 50.0% sensitivity using RHM protocol in Guatemalan study, which is in agreement with our study findings, such finding was possibly overlooked and has not been discussed as a limitation of using RHM in young population. Furthermore, the poor performance of RHM in younger age groups based on our study and Guatemalan study may indirectly confirm the previously stated assumption that younger age groups have non-symmetrical distribution of periodontitis (Papapanou P & Lindhe J, 2015). In our study, periodontitis prevalence was impacted the most by using PRPs and the impact of underestimation of prevalence was generally more pronounced in younger age group. Based on the proposed standards of reporting in population-based studies, the three study periodontitis outcomes are prevalence, extent, and severity (Holtfreter B et al., 2015). Periodontitis prevalence, compared to extent and severity summaries, is possibly the most important population-based summary since it may have several practical implications at the population level. Periodontitis prevalence is the main outcome that estimates the disease burden in a population, consequently, can be used to plan 83 population-based strategies to prevent (manage) periodontitis. Prevalence is also possibly the most suitable periodontitis to evaluate the associations of exposures with periodontitis in cross-sectional surveys. However, when we consider possible impacts of using PRP on periodontitis prevalence, estimation of periodontitis burden and the consequent planning of strategies can be possibly impacted. Though, this may depend on the selection of the PRP and the magnitude of bias. In our study, (FM)MB-DL had the best performance in all study groups, and it was the only PRP that had acceptable results in estimating prevalence in younger group. The impact of using PRP on estimating exposures associations with periodontitis prevalence was only marginal regardless of the PRP type. Thus, the overall interpretation of the associations did not seem to be impacted by using PRPs despite the impact on the prevalence. On the other hand, among the limitations of estimating periodontitis prevalence is that representativeness is often bounded by place and time (Lash TL & Rothman KJ, 2021b; Rothman KJ et al., 2013; Shi L, 2007). A prevalence that is representative of a population, depending on the disease stability, may not be representative of that population over a period of time. A prevalence that is representative of specific geographical place may not be representative of another place unless the underlying populations share some common characteristics. Providing this limitation, however, a more powerful use of prevalence is the evaluation of time trend using a series of cross-sectional studies. Such approach can be also helpful in estimating the efficiency of some population-based strategies. Though, the use of PRPs for estimating the prevalence may potentially impact periodontitis trend interpretations over periods of time. It has been suggested in the literature that interpretation of periodontitis time trends can be generally challenging due to several methodological concerns (Baelum V & Lopez R, 2021; Hugoson A & Norderyd, 2008). The use of PRPs in assessment of periodontitis may potentially add up to the existing methodological challenges of evaluating time trend. It needs to be acknowledged, however, that our study is limited and possible impact on interpretations of time trends cannot be estimated. When the PRP performance was compared with FRP, we selected two main approaches for comparisons: absolute bias and diagnostic accuracy indicators (sensitivity and negative predictive value). The absolute bias was selected instead of relative bias because the method of its calculations is consistent in the literature, whereas relative bias was calculated differently in some studies (Beck JD et al., 2006; Kingman A et al., 2008). The estimations of bias alone for comparisons of PRP performance in estimating periodontitis prevalence can be possibly limited and other indicators for comparisons such as sensitivity and negative predictive value were also used. To demonstrate how the use of absolute bias alone can be limited in a hypothetical example, let us assume that periodontitis prevalence in two populations were 30.0% and 70.0% and the absolute bias for both equals 20.0%; a 20.0% absolute bias when periodontitis prevalence is 30.0% is drastically different compared with a 20.0% absolute bias when periodontitis prevalence is 70.0%. If we calculate the relative bias for the two hypothetical populations using the method suggested by James Beck (Beck JD et al., 2006), the relative bias for the first population would be 67.0% and for 84 the second population would be 29.0%. Thus, the relative bias can consider the estimation of bias in proportion to the periodontitis prevalence while the absolute bias does not. However, the common issue between absolute bias and relative bias can be the lack of clear cut-off for judging the bias magnitude and its impact on the interpretation; they mostly rely on subjective judgements. Therefore, the calculation of bias may help in estimation of the direction and magnitude of bias but does not clearly help in judging the validity of the estimated prevalence. On the other hand, the use of negative predictive value considers the prevalence of periodontitis when estimating the PRP performance (Tenny S & Hoffman M R, 2021). When the prevalence of disease is decreased, such as prevalence of severe periodontitis compared with moderate-severe periodontitis in our study, the negative predictive value generally increases. Similarly, the sensitivity, although does not depend directly on the prevalence, it can be impacted by the overall distribution of the disease in the underlying population. Specificity and positive predictive values, as previously stated, are always 100.0% since PRPs can only identify periodontitis cases if they were already identified using FRP and were not reported in this study (Preisser JS et al., 2018). In our study, the sensitivity and negative predictive value ranged from 27.8% to 97.4%. Having sensitivity or negative predictive value of ≥80.0% may indicates high accuracy level, while a value of ≥60.0% may indicates moderate accuracy (Nelson DE et al., 2001). However, a possible limitation of using accuracy indicators alone (sensitivity and negative predictive values) is that they can be specific to a certain population which may limit the comparability among studies. Thus, the use of accuracy indicators and calculation of bias may help in judging the impact of using PRPs on estimating the prevalence and enhance the comparability among different studies. Compared with periodontitis prevalence, periodontitis extent (a continuous outcome) is mostly estimated in the literature using absolute bias or relative bias. None of the studies used sensitivity or specificity to evaluate the performance of PRPs in estimating continuous outcomes, though, such estimations are theoretically feasible by using area under receiver operating characteristics curve. Providing that the impact of using PRPs on continuous outcomes (including periodontitis extent) generally result in a small information loss, the use of absolute bias (or relative bias) can be then considered adequate for comparisons with FRP. Factors that impacted the performance of PRP in estimating prevalence based on our findings included the age where older group had higher accuracy and lower bias compared with younger age group; distribution of the disease (higher prevalence resulted in higher accuracy); PRP type since (FM)MB-DL had the best overall performance; PRP total sites since both (FM)MB-DL and RHM measured at 56 sites had better performance than (HM)MB-DL which is measured at 28 sites; severity threshold of case definitions since severe periodontitis had lower accuracy compared with moderate-severe periodontitis. These factors that could impact the PRP performance in estimating periodontitis prevalence are mostly confirmation to what was previously reported in the literature (Eaton KA et al., 2001; Susin C et al., 2005; Thomson WM & Williams SM, 2002). In contrast to previous findings (Chu Y & Ouyang 85 X, 2015; Dowsett SA, Eckert GJ, et al., 2002b; Peres MA et al., 2012), however, RHM did not have the best performance compared with (FM)MB-DL protocol especially in younger group where it poorly estimated the severe periodontitis prevalence. Furthermore, (HM)MB-DL protocol was reported to perform well in estimating periodontitis prevalence based on a previous systematic review (Tran DT et al., 2013). In our study, however, (HM)MB-DL had a poor performance in estimating periodontitis prevalence in all study subgroups. For periodontitis extent, the overall bias was ≤|3.9| and this can be considered trivial. When PRP types were compared for their estimation of periodontitis extent, (FM)MB-DL had the highest bias but still considered generally small magnitude of bias. The larger the periodontitis extent, the larger the bias. Older individuals consistently had underestimation of periodontitis while younger individuals either had underestimation or overestimation of extent. The possibility of overestimation of periodontitis extent when using PRPs had been previously reported in younger individuals (Eaton KA et al., 2001) or when using index teeth protocols (Chu Y & Ouyang X, 2015). In our study, the associations were generally either underestimated or overestimated. The unadjusted associations resulted in slightly reduced absolute bias compared with the adjusted associations which is similar to previous findings (Akinkugbe AA et al., 2015). Among the three examined PRPs, the (HM)MB-DL resulted in the highest absolute bias when estimating the associations. The absolute bias was smaller for the severe periodontitis compared to moderate-severe periodontitis threshold. Higher degrees of bias resulted when the magnitude of association was smaller and non-statistically significant. Our findings were consistent with those reported by Heaton et al. in a simulation study in which the direction and magnitude of bias were associated with the severity of the case definitions and the magnitude of the associations (Heaton B, Garcia RI, et al., 2018). The overall bias in our study was ≥|0.8| which can be considered trivial. Furthermore, overall differences in estimating the OR seem to be confined within the 95.0% Confidence interval of the FRP OR. Therefore, the overall bias resulted from using PRPs did not seem to alter the interpretations of the periodontitis associations. Practical implications of our study findings might be more relevant for epidemiological studies since we do not recommend the use of PRPs for individual patient examinations in regular dental settings. The use of FRP is the gold standard protocol and generally preferable for conducting population-based examinations. However, when time and resources are limited, PRPs can be an alternative. Factors that impact the performance of using PRPs need to be considered before selection of PRPs. (FM)MB-DL protocol was the only one that performed well in estimating prevalence in young individuals. However, our finding needs further evaluations since our findings’ generalizability could be limited. Also, PRPs performance can be generally different from a population to another. The use of wide age range to conduct direct comparisons is recommended for future studies since such comparisons are overly restricted based on the current literature. Since the evaluations of periodontitis trend over time can be important and 86 could potentially be impacted by using PRPs, it is recommended for future studies to evaluate the impact on such time trend interpretations. 3.5 Conclusions The highest magnitude of bias resulted when periodontitis prevalence was estimated using PRPs, whereas the impact on estimating periodontitis extent and associations with exposures was trivial. The (FM)MB-DL had the highest overall performance and was the only PRP that performed well in estimating periodontitis prevalence in young age group. The (HM)MB-DL poorly performed in estimating the periodontitis prevalence at both younger and older age groups; also resulted in the highest bias in estimating periodontitis associations. Overall factors that impacted the performance of PRP in estimating associations with periodontitis include PRP type, periodontitis severity threshold in case definitions, magnitude of associations, and the adjustments for covariates. The use of FRP is still recommended to be used in population-based studies. However, when time and resources are limited, (FM)MB-DL demonstrated the best performance and can be used especially if the study involves young age groups. However, our findings need to be confirmed in future studies. 87 Chapter 4: Accuracy of Estimating Periodontitis and its Associations Using Partial Mouth Recording Protocols for Population-based Studies: A Systematic Review and Meta-analyses (Project III) A version of this chapter has been published (Alawaji et al., 2022). 4.1 Introduction Epidemiological studies mainly focus on the assessment of certain disease distributions in specific populations and their exposures (Lilienfeld DE, 1978). A FRP examines six sites per tooth in all teeth except for the third molars and is considered the gold standard for periodontal examinations (Eke PI et al., 2015; Holtfreter B et al., 2015). However, due to the extensive time, cost, and number of examiners needed to conduct population-based studies, the use of a PRP can be an alternative to FRP (Holtfreter B et al., 2015). Several PRPs have been suggested to be used for estimating periodontitis in population-based studies and can be mainly based on using random or fixed number of teeth or sites (Akinkugbe AA et al., 2015; Beck JD et al., 2006; Chu Y & Ouyang X, 2015; Kingman A et al., 2008; Susin C et al., 2005; Tran DT et al., 2013). Studies mainly evaluated the performance of PRPs compared to that of FRP in estimating periodontitis prevalence, extent, and severity. Impact of using PRPs on continuous outcomes such as periodontitis extent and severity was generally smaller than the impact on binary outcome: periodontitis prevalence. Using PRPs, the periodontitis extent and severity can either be underestimated or overestimated depending on the protocol type and age of population (Chu Y & Ouyang X, 2015; Dowsett SA, Eckert GJ, et al., 2002b; Eaton KA et al., 2001), whereas periodontitis prevalence can only be underestimated when using PRPs. Eke et al. suggested that the underestimation of periodontitis prevalence may result in underestimation of exposures associated with periodontitis (Eke PI et al., 2010). However, a study that used hypothetical data demonstrated that the impact of using PRPs differentially impact the estimation of periodontitis exposures since the underestimation of periodontitis is different in exposed and unexposed individuals (Preisser JS et al., 2018). The differential misclassification assumption of using PRP on periodontitis exposures is mainly inherent to the estimation method of these exposures using OR. Consequent to this differential misclassification of exposures, the OR can be either underestimated or overestimated. Findings from studies that used clinical data generally confirm the fact that exposures association with periodontitis prevalence can be differentially misclassified (Akinkugbe AA et al., 2015; Alshihayb TS et al., 2020; Peres MA et al., 2012; Thomson WM & Williams SM, 2002). Preisser et al., suggested that the misclassification of exposures under PRP can depends on selection of PRP type and number of sites; extent and pattern of periodontitis distribution; criteria of defining periodontitis prevalence (Preisser JS et al., 2018). Factors that were suggested to impact the PRP 88 performance, based on another simulation study, include the severity threshold of case definition, underlying distribution of clinical parameters: CAL or PPD, and magnitude of associations (Heaton B, Garcia RI, et al., 2018). In a 2013 systematic review (Tran DT et al., 2013), various PRPs were tested for their validity and the review concluded that the highest accuracy when examining the prevalence, severity and extent of periodontitis resulted from using the RHM protocol at six sites per tooth and a (FM)MB-B-DB. Conducting (HM)MB-B-DL or (FM)MB-B-DL sites were also effective in assessing the prevalence and severity of periodontitis. The (HM)MB-B-DL or (FM)MB-B-DL protocols were not evaluated for their performance to assess the periodontitis extent. The systemic review mainly focused on evaluating the performance of PRPs in estimating periodontitis prevalence, extent, and severity without evaluating the factors that may impact the estimation of each of these outcomes. Additionally, the impact of using PRPs on periodontitis associations and the factors that can impact it were not evaluated in the systematic review. The systematic review also suggested that the impact of using PRPs on universally used definitions such as the CDC/AAP needs to be evaluated. Therefore, an updated systematic review is possibly needed. Our main research question for this systematic review and meta-analyses was: Should we rely on PRP for assessment of periodontitis and its associations in population-based surveys? The study had two specific objectives: 1) to conduct an up-to-date systematic review and meta-analyses regarding the performance of using PRPs to estimate periodontitis prevalence, extent, severity, and its associations with exposures, 2) to identify the factors that may impact the performance of using PRPs. A secondary objective was to evaluate the PRP performance in estimating periodontitis prevalence using the CDC/AAP case definitions. 4.2 Methods This review was prepared using the Preferred Reporting Items for Systematic Review and Meta-analysis of Diagnostic Test Accuracy studies (PRISMA-DTA) (Salameh J et al., 2020). The study’s protocol was registered in the International Platform of Registered Systematic Review and Meta-analysis Protocols (Registration number: INPLASY202160032) (Alawaji et al., 2021). The analytical (conceptual) framework for key questions and topics that needed to be considered prior to defining the research question for the current systematic review and meta-analyses were outlined in Figure 13. Eligibility criteria: The following inclusion criteria were used: full-text papers in English of studies that employed a cross-sectional study design or analyzed the baseline data of longitudinal studies, included subjects of any age with permanent dentitions, studies where the PRP findings were verified with the FRP. The FRP data assessed 6 sites or 4 interproximal sites per tooth in all teeth, except third molars based on the current definition for gold standard measurement protocol (Holtfreter B et al., 2015). The studies reported the following outcomes: 89 periodontitis prevalence, its associations, and mean (SD) for estimates of periodontitis severity or extent. Studies used CAL were included, since CAL is an irreversible and a reliable indicator of periodontitis in epidemiological studies (Beltran-Aguilar ED et al., 2012; Dye BA et al., 2014). The exclusion criteria were the studies that included any of the following: simulation data, hypothetical data, studies focused on subjects with primary dentition, studies using other periodontal parameters such as the PPD or bleeding upon probing without assessment of CAL. Search strategy: The search was conducted up until May 26, 2021, using keywords and MeSH or Emtree terms based on a several field searches including titles, abstracts, author keywords, etc. The following search concepts were considered: periodontitis, prevalence, extent, severity, and partial mouth recording. Limits or filters were not used when conducting the search to increase the search sensitivity. Medline and Embase were mainly searched via Ovid, and grey literature was searched at different sources such as Dissertation and Theses Global, OpenGrey, Grey Matter, Grey literature at the Networked Digital Library, Google, and Google scholar. Related citations of retrieved articles and articles’ reference lists were also searched. Study outcomes: Accuracy of each of the following: 1) periodontitis prevalence as indicated by sensitivity, specificity, positive predictive value, negative predictive value, and absolute bias; 2) periodontitis-related associations indicated by the systematic error (absolute bias and/or relative bias); 3) extent of periodontitis indicated by absolute bias; and 4) severity of periodontitis indicated by absolute bias. Prevalence of periodontitis was defined using the two most commonly used thresholds in the previous studies: 1) moderate-severe periodontitis (≥1 site with CAL ≥4 mm) and 2) severe periodontitis (≥1 site with CAL ≥ 6 mm). Sub-outcomes for periodontitis prevalence were defined using the case definitions by the CDC/AAP (Eke PI et al., 2012; Page RC & Eke PI, 2007). The CDC/AAP severe periodontitis was defined as CAL ≥6 mm at ≥2 interproximal sites (not on the same tooth) and PPD ≥5 mm at ≥1 interproximal site (can be one of the two sites with CAL). The CDC/AAP moderate periodontitis was defined as CAL ≥4 mm at ≥2 interproximal sites (not on the same tooth) or PPD ≥5 mm at ≥2 interproximal sites (not on the same tooth). The moderate periodontitis category of the CDC/AAP definition was not considered separately but was added to severe periodontitis and the total cases were used. Periodontitis extent was defined as the mean percentage of sites with CAL ≥3 mm or ≥5 mm (Holtfreter B et al., 2015). Periodontitis severity was defined as the population’s mean of CAL. Absolute bias was calculated for each of the periodontal outcomes as follows: Absolute biasprevalence = prevalence PRP - prevalence FRP Absolute biasextent= (extent PRP) – (extent FRP) 90 Absolute biasseverity= (severity PRP) – (severity FRP) In order to estimate the potential systematic error concerning the exposures associations with periodontitis when comparing PRPs to FRPs, the absolute bias and relative bias were calculated at the natural logarithm (ln) scale of OR as follows: Absolute bias of OR= ln (ORPRP) – ln (ORFRP) (Akinkugbe AA et al., 2015). Relative bias of OR= [ln (ORPRP) – ln (ORFRP)]/ln (ORFRP) (Alshihayb TS et al., 2020). Study selection and data extraction: The preliminary study selection was done by screening the titles and abstracts, and the final selection was based on the eligibility criteria after retrieval of the full texts. A single data selection and extraction were completed then verified by another reviewer. Any disagreements in the study selection or data extraction were resolved by discussion until a consensus was reached. A data extraction form was customized using Microsoft Excel software, version 16.0 (Microsoft Corporation, 2018). Pilot forms were used initially for five studies and modifications were made to the extraction forms. The following information about each extracted study was collected: author names, publication date, study title, sample size, study design, study settings/country, participants’ age range, study’s eligibility criteria, examiner training/calibration, intra-examiner/inter-examiner reliability, management of missingness, the minimum number of included sites/teeth, type of PRP, definition of FRP, periodontitis thresholds, mean (SD) of periodontitis extent and severity for the PRP and FRP. Total subjects with or without periodontitis in the PRP and FRP was used to construct a 2x2 table to calculate the periodontitis prevalence along with the following diagnostic accuracy indicators: sensitivity, specificity, and predictive values. Both unadjusted and adjusted OR for each periodontitis associated exposures such as diabetes mellitus, obesity, and cigarette smoking. 91 Figure 13. Conceptual framework for key inquiries and topics concerning the use of partial-mouth recording protocols (PRP) that needed to be considered to define the research question of this systematic review. 1) How old is the population of interest? 2) What was the study design? 3) How did the study measure the periodontal conditions? 4) What was the selected PRP? 5) How did they define the gold standard? 6) How did they compare the PRP to gold standard? 7) What were the study outcomes? 8) How did they define the periodontitis? PPD: Periodontal Probing Depth, CAL: Clinical Attachment Loss, REC: Recession, BOP: Bleeding on Probing, FRP: Full-mouth Recording Protocol, EFP: European Federation of Periodontology, CDC/AAP: the Centers for Disease Control and Prevention and the American Academy of periodontology. 92 Figure 14. Flow chart of study selection, data extraction and analysis. n: total number of studies, FRP: Full-mouth Recording Protocol, PRP: Partial-mouth Recording Protocol, CAL: Clinical Attachment Loss, CPITN: Community Periodontal Index of Treatment Needs. 93 Risk of bias and applicability of individual studies: The second version of Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool (Whiting PF et al., 2011) was used for assessment of risk of bias (4 domains) and the applicability concerns (3 domains). Based on the suggestions by authors of QUADAS-2, the signaling questions for each domain were customized for the current review and their revised versions are presented in the Appendix E (Table 25). For the overall judgment, a high risk of bias or high applicability concerns were determined if the study was rated as such in at least one of the domains. The customization of the tool and the risk of bias assessment were done by two reviewers and any disagreement was resolved by discussion until a consensus was reached. Data synthesis: We used OpenMeta-Analyst software (Wallace BC et al., 2012) to analyze data extracted from eligible studies to summarize and compare different accuracy indicators for the prevalence, extent, and severity of periodontitis using different PRPs. Meta-analyses using a random effect model (DerSimonian and Laird inverse variance) were conducted to compare the performance of different PRPs, to examine their inherent methodological aspects, and to identify the factors that impact their performance. We do not consider the pooled estimates of the meta-analyses valid because we do not assume that the performance of different PRPs can be estimated by a single summary. Sub-analyses were done for estimating the prevalence of sensitivity and absolute bias of studies which used case definitions provided by the CDC/AAP. A bivariate random effect meta-regression was used to explore the factors that may impact the performance of PRPs. The statistical heterogeneity was examined as outlined in the Cochrane handbook (Deeks JJ et al., 2021) using the following assesments:1) visual examination of the forest plots, where minimal or no overlap of studies’ 95% confidence intervals, and/or the variation of estimate direction (positive or negative) indicates heterogeneity; 2) a Chi-square test where α=0.10 indicates a statistical significance; and 3) I2 used to quantify the heterogeneity, where I2 range from 0.0% to 40.0% indicates negligible heterogeneity, I2 ³75% indicates a considerable heterogeneity, and I2 values range between 40.0% and 75.0% indicate moderate to substantial heterogeneity. 4.3 Results Study selection: A total of 614 papers were retrieved for preliminary screening of titles and abstracts. Total numbers of included and excluded studies are presented in Figure 14. A detailed explanation of the reasons for exclusion were presented in the Appendix E (Table 26). The main PRP types of the included studies were the full mouth at partial sites, RHM, random half mouth at partial sites, and index teeth. The risk of bias and applicability assessment of 14 selected studies were presented in Table 17. A summary of study characteristics and potential concerns were outlined in Table 18. Most of the studies did not describe how the sample size was calculated or how they handled the data missingness. A majority of studies limited the inclusion of 94 subjects if they had ³6 remaining teeth. A few studies had strict eligibility criteria such as subjects being required to have ³16-24 teeth present (Chu Y & Ouyang X, 2015; Relvas M et al., 2014; Vettore MV et al., 2007), limited to subjects with periodontitis (Chu Y & Ouyang X, 2015), or untreated individuals (Alawaji Y, Mostafa N, et al., 2022; Dowsett SA, Eckert GJ, et al., 2002b), which can limit their applicability. Periodontitis prevalence: For moderate-severe periodontitis, the prevalence ranged from 22.0% to 96.9%, the absolute biasprevalence was -12.3% (95% CI: -14.8%, -9.7%, I2=96.3%, p<0.001) in Figure 15, and the sensitivity was 81.0% (95% CI:76.9%, 84.6%, I2=99.1%, p<0.001) in Figure 17. Subgroup analysis was done where PRPs were grouped considering their types and the total number of sites per PRP in Figure 16; the statistical heterogeneity ranged from negligible to moderate for estimating the prevalence using full mouth at partial sites measured at 56 sites, RHM at 84 sites or 56 sites, half mouth at partial sites measured at 28 sites. For severe periodontitis, the prevalence ranged from 11.8% to 55.1%, the absolute biasprevalence was -8.9% (95% CI: -10.9%, -7.0%, I2=95.6%, p<0.001) in Figure 18, and the sensitivity was 70.1% (95% CI: 64.6%, 75.1%, I2=98.6%, p<0.001) in Figure 19. Subgroup analysis was done based on the PRP types in Figure 20; the full mouth at partial sites had a negligible heterogeneity and RHM had a substantial heterogeneity. A sensitivity analysis performed by excluding the estimates by Tran et al.(Tran DT et al., 2014), which had the lowest prevalence of severe periodontitis, and the heterogeneity decreased in all subgroups (Figure 21). Moderate-severe periodontitis had larger absolute biasprevalence (-12.3% versus -8.9%), higher sensitivity (81.0% versus 70.1%) and lower negative predictive value compared with severe periodontitis (Figures 15, 16, 17, 18, and 19). In a sub-analysis of studies which used the CDC/AAP definitions for periodontitis, a similar pattern was seen when absolute bias, sensitivity, and negative predictive value measures were compared between moderate-severe and severe periodontitis thresholds (Supplementary Figures in Appendix F). However, the overall absolute bias was larger, and the sensitivity was lower when using the CDC/AAP case definitions compared with other studies. Factors that were significantly associated with the absolute bias for the moderate-severe periodontitis prevalence using bivariate random effect meta-regression (Table 19) included the PRP types, where the half mouth at partial sites and index teeth protocols had approximately a twofold increase in absolute bias compared with the reference category (full mouth at partial sites), and the PRP with fewer total sites (24 to 42 sites) had at least a twofold increase in absolute bias compared with the reference category (84 sites). Studies that were judged to have potential or high risk of bias had lower absolute bias. Factors that were significantly associated with the absolute bias for severe periodontitis prevalence (Table 20) include minimum number of sites with CAL used define periodontitis (≥1 or ≥2 sites), PRP types, total PRP sites, and periodontitis prevalence. Studies that compared the impact of using different minimum number of sites with CAL and or PPD on the accuracy of PRPs were summarized in Table 27. 95 Periodontitis severity: The absolute biasseverity was -0.01 (95% CI: -0.03, 0.01) which is considered small and the majority of PRPs had their 95% CI including the null value. The use of index teeth: Ramfjord teeth and CPITN protocols mainly overestimated the severity; the largest absolute biasseverity was 0.4. The heterogeneity for absolute biasseverity, as indicated by I2=6.25 and a Chi square test p=0.367 (Figure 22), can be considered negligible. Periodontitis extent: The absolute biasextent was -0.6 (95% CI: -1.1, 0.0, I2=0.0%, p=0.554) for moderate-severe periodontitis (Figure 23) and -0.1 (95% CI: -0.4, 0.1, I2=0.0%, p=0.881) for severe periodontitis (Figure 24). The extent of periodontitis was mainly underestimated when using PRPs, however, the use of index teeth: Ramfjord teeth, and CPITN protocols overestimated the periodontitis extent. The overall heterogeneity for moderate-severe and severe periodontitis was negligible as indicated by the I2=0.0 and the non-significant Chi square findings for the moderate-severe and severe periodontitis. Periodontitis associations with exposures: A few studies assessed the accuracy of the associations of periodontitis using PRPs compared with FRP, which precluded us from conducting a meta-analysis. We chose to summarize the exposures that were reported in two or more studies including diabetes mellitus, obesity, and current cigarette smoking status which are presented in Table 21. All three studies that evaluated the periodontitis exposures has defined periodontitis prevalence using the CDC/AAP case definitions. The operational definitions of these exposures, however, varied considerably among included studies. 96 Figure 15. Summary of the Absolute Bias (AB)prevalence of moderate-severe periodontitis using Partial-mouth Recording Protocols (PRP). Total PRP sites for each PRP and minimal number of sites with Clinical Attachment Loss (CAL) are listed. ABprevalence values <0.0 underestimate the prevalence while values >0.0 overestimate it. FRP: Full-mouth Recording Protocol, N: sample size, CI: Confidence Interval, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, ML: Mesio-Lingual, L: Mid-Lingual, DL: Disto-Lingual, (FM): Full-Mouth, (HM): Half-Mouth, 84 RSSM: 84 sites selected using Random-Site-Selection-Method, 42 RSSM: 42 sites selected using Random-Site-Selection-Method, 36 RSSM: 36 sites selected using Random-Site-Selection-Method, (RHM): Random-Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs, ?: not clear.Absolute bias-25.0% -20.0% -15.0% -10.0% -5.0% 0.0% 5.0%PRPSites PRP Studies NCALsitesPrevalencePRP (%)PrevalenceFRP (%) AB% (95% CI)84 (FM)MB-B-DB Susin 2005 1460 ≥1 55.5 69.3 -13.8 (-17.3, -10.4)84 (FM)MB-B-DL Susin 2005 1460 ≥1 57.4 69.3 -11.9 (-15.4, -8.4)84 (FM)MB-B-DL Teixeira 2020 350 ≥1 17.7 22.0 -4.3 (-10.4, 1.6)56 (FM)MB-DB Tran 2014 3667 ≥2 36.9 46.1 -9.2 (-11.5, -7.0)56 (FM)MB-DL Tran 2014 3667 ≥2 39.1 46.1 -7.0 (-9.3, -4.8)56 (FM)MB-DL Romano 2019 721 ≥2 71.0 77.9 -6.9 (-11.4, -2.4)56 (FM)MB-DL Alawaji 2022 431 ≥2 68.7 78.4 -9.7 (-15.6, -3.9)84 84 RSSM Beck 2006 6793 ≥1 72.4 77.2 -4.8 (-6.3, -3.3)84 RHM Dowsett 2002 292 (?) 94.9 96.9 -2.1 (-5.3, 1.2)84 RHM Susin 2005 1460 ≥1 63.4 69.3 -5.9 (-9.3, -2.5)84 RHM Teixeira 2020 350 ≥1 14.3 22.0 -7.7 (-13.4, -2.0)56 RHM Tran 2014 3667 ≥2 35.8 46.1 -10.3 (-12.5, -8.1)56 RHM Romano 2019 721 ≥2 65.9 77.9 -12.1 (-16.7, -7.5)56 RHM Alawaji 2022 431 ≥2 68.4 78.4 -10.0 (-15.8, -4.1)42 (HM)MB-B-DB Susin 2005 1460 ≥1 55.5 69.3 -10.0 (-13.0, -7.0)42 (HM)MB-B-DL Susin 2005 1460 ≥1 57.4 69.3 -9.0 (-12.0, -6.0)42 (HM)MB-B-DB Beck 2006 6793 ≥1 56.4 77.2 -20.8 (-22.3, -19.3)42 (HM)MB-B-DL Teixeira 2020 350 ≥1 10.9 22.0 -13.0 (-19.0, -9.0)28 (HM)MB-DB Tran 2014 3667 ≥2 26.3 46.1 -19.8 (-22.0, -17.6)28 (HM)MB-DL Tran 2014 3667 ≥2 29.2 46.1 -16.9 (-19.1, -14.7)28 (HM)MB-DL Alawaji 2022 431 ≥2 58.7 78.4 -19.7 (-25.8, -13.7)42 42 RSSM Beck 2006 6793 ≥1 63.7 77.2 -13.5 (-15.0, -12.0)40 CPITN Tran 2014 3667 ≥2 29.2 46.1 -12.9 (-15.1, -10.7)36 36 RSSM Beck 2006 6793 ≥1 62.5 77.2 -14.7 (-16.2, -13.2)36 Ramfjord Beck 2006 6793 ≥1 54.2 77.2 -23.0 (-24.5, -21.4)36 Ramfjord Dowsett 2002 292 (?) 89.0 96.9 -7.9 (-12.0, -3.8)24 Ramfjord Tran 2014 3667 ≥2 19.9 46.1 -26.1 (-28.1, -2.4)Heterogeneity (I2=96.3%, P<0.001) 51.4 60.1 -12.3 (-14.8, -9.7) 97 Figure 16. Subgroup analysis for the Absolute Bias (AB)prevalence of moderate-severe periodontitis using Partial-mouth Recording Protocols (PRP). The subgroups were based on the type of PRP and the number of sites per PRP. FRP: Full-mouth Recording Protocol, N: sample size, CI: Confidence Interval, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, ML: Mesio-Lingual, L: Mid-Lingual, DL: Disto-Lingual, (FM): Full-Mouth, (HM): Half-Mouth, 84 RSSM: 84 sites selected using Random-Site-Selection-Method, 42 RSSM: 42 sites selected using Random-Site-Selection-Method, 36 RSSM: 36 sites selected using Random-Site-Selection-Method, (RHM): Random-Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs, ?: not clear.Absolute bias-25.0% -20.0% -15.0% -10.0% -5.0% 0.0% 5.0%PRPSites PRP Studies NCALsitesPrevalencePRP (%)PrevalenceFRP (%) AB% (95% CI)84 (FM)MB-B-DB Susin 2005 1460 ≥1 55.5 69.3 -13.8 (-17.3, -10.4)84 (FM)MB-B-DL Susin 2005 1460 ≥1 57.4 69.3 -11.9 (-15.4, -8.4)84 (FM)MB-B-DL Teixeira 2020 350 ≥1 17.7 22.0 -4.3 (-10.4, 1.6)84 84 RSSM Beck 2006 6793 ≥1 72.4 77.2 -4.8 (-6.3, -3.3)Subgroup (I2=90.4, P=0.000) 50.7 59.5 -8.8 (-14.0, -3.7)56 (FM)MB-DB Tran 2014 3667 ≥2 36.9 46.1 -9.2 (-11.5, -7.0)56 (FM)MB-DL Tran 2014 3667 ≥2 39.1 46.1 -7.0 (-9.3, -4.8)56 (FM)MB-DL Romano 2019 721 ≥2 71.0 77.9 -6.9 (-11.4, -2.4)56 (FM)MB-DL Alawaji 2022 431 ≥2 68.7 78.4 -9.7 (-15.6, -3.9)Subgroup (I2=0.0, P=0.500) 53.9 62.1 -8.1 (-9..6, -6.7)84 RHM Dowsett 2002 292 (?) 94.9 96.9 -2.1 (-5.3, 1.2)84 RHM Susin 2005 1460 ≥1 63.4 69.3 -5.9 (-9.3, -2.5)84 RHM Teixeira 2020 350 ≥1 14.3 22.0 -7.7 (-13.4, -2.0)Subgroup (I2=51.0, P=0.130) 57.5 62.7 -4.8 (-8.0, -1.5)56 RHM Tran 2014 3667 ≥2 35.8 46.1 -10.3 (-12.5, -8.1)56 RHM Romano 2019 721 ≥2 65.9 77.9 -12.1 (-16.7, -7.5)56 RHM Alawaji 2022 431 ≥2 68.4 78.4 -10.0 (-15.8, -4.1)Subgroup (I2=0.0, P=0.779) 56.7 67.5 -10.6 (-12.5, -8.7)42 (HM)MB-B-DB Susin 2005 1460 ≥1 55.5 69.3 -10.0 (-13.0, -7.0)42 (HM)MB-B-DL Susin 2005 1460 ≥1 57.4 69.3 -9.0 (-12.0, -6.0)42 (HM)MB-B-DB Beck 2006 6793 ≥1 56.4 77.2 -20.8 (-22.3, -19.3)42 (HM)MB-B-DL Teixeira 2020 350 ≥1 10.9 22.0 -13.0 (-19.0, -9.0)42 42 RSSM Beck 2006 6793 ≥1 63.7 77.2 -13.5 (-15.0, -12.0)Subgroup (I2=93.0, P=0.000) 48.8 63.0 -14.5 (-18.7, -10.3)28 (HM)MB-DB Tran 2014 3667 ≥2 26.3 46.1 -19.8 (-22.0, -17.6)28 (HM)MB-DL Tran 2014 3667 ≥2 29.2 46.1 -16.9 (-19.1, -14.7)28 (HM)MB-DL Alawaji 2022 431 ≥2 58.7 78.4 -19.7 (-25.8, -13.7)Subgroup (I2=44.3, P=0.166) 38.1 56.9 -18.5 (-20.7, -16.3)40 CPITN Tran 2014 3667 ≥2 29.2 46.1 -12.9 (-15.1, -10.7)36 36 RSSM Beck 2006 6793 ≥1 62.5 77.2 -14.7 (-16.2, -13.2)36 Ramfjord Beck 2006 6793 ≥1 54.2 77.2 -23.0 (-24.5, -21.4)36 Ramfjord Dowsett 2002 292 (?) 89.0 96.9 -7.9 (-12.0, -3.8)24 Ramfjord Tran 2014 3667 ≥2 19.9 46.1 -26.1 (-28.1, -2.4)Subgroup (I2=97.5, P=0.000) 51.8 68.7 -17.1 (-22.7, -11.4)Heterogeneity (I2=96.3%, P<0.001) 51.4 60.1 -12.3 (-14.8, -9.7) 98 Figure 17. Summary of the sensitivity of moderate-severe periodontitis prevalence using Partial-mouth Recording Protocols (PRP). Specificity and positive predictive value are 100% for all PRPs. PRP sites, minimal number of sites with Clinical Attachment Loss (CAL) and Negative Predictive Value (NPV) are listed. FRP: Full-mouth Recording Protocol, N: sample size, CI: Confidence Interval, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, ML: Mesio-Lingual, L: Mid-Lingual, DL: Disto-Lingual, (FM): Full-Mouth, (HM): Half-Mouth, 84 RSSM: 84 sites selected using Random-Site-Selection-Method, 42 RSSM: 42 sites selected using Random-Site-Selection-Method, 36 RSSM: 36 sites selected using Random-Site-Selection-Method, (RHM): Random-Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs, ?: not clear. 38.0% 54.0% 69.0% 84.0% 99.0%SensitivityPRPSites PRP Studies NCALsitesPrevalencePRP (%)PrevalenceFRP (%)NPV(%)Sensitivity%(95% CI)84 (FM)MB-B-DB Susin 2005 1460 ≥1 55.5 69.3 92.9 80.0 (77.4, 82.4)84 (FM)MB-B-DL Susin 2005 1460 ≥1 57.4 69.3 72.0 82.8 (80.3, 85.0)84 (FM)MB-B-DL Teixeira 2020 350 ≥1 17.7 22.0 94.8 80.1 (69.8, 87.5)56 (FM)MB-DB Tran 2014 3667 ≥2 36.9 46.1 85.4 80.0 (78.0, 81.8)56 (FM)MB-DL Tran 2014 3667 ≥2 39.1 46.1 88.5 84.7 (82.9, 86.4)56 (FM)MB-DL Romano 2019 721 ≥2 71.0 77.9 76.1 91.0 (88.4, 93.1)56 (FM)MB-DL Alawaji 2022 431 ≥2 68.7 78.4 68.9 87.5 (83.5, 90.6)84 84 RSSM Beck 2006 6793 ≥1 72.4 77.2 82.3 93.6 (92.9, 94.3)84 RHM Dowsett 2002 292 (?) 94.9 96.9 0.6 97.7 (95.1, 98.9)84 RHM Susin 2005 1460 ≥1 63.4 69.3 83.9 91.5 (89.6, 93.0)84 RHM Teixeira 2020 350 ≥1 14.3 22.0 91.0 64.7 (53.6, 74.5)56 RHM Romano 2019 721 ≥2 65.9 77.9 64.6 84.5 (81.2, 87.2)56 RHM Tran 2014 3667 ≥2 35.8 46.1 93.9 77.6 (75.6, 79.6)56 RHM Alawaji 2022 431 ≥2 68.4 78.4 68.4 95.8 (93.0, 97.5)42 (HM)MB-B-DB Susin 2005 1460 ≥1 55.5 69.3 68.9 80.0 (77.4, 74.2)42 (HM)MB-B-DL Susin 2005 1460 ≥1 57.4 69.3 72.0 82.8 (80.3, 85.0)42 (HM)MB-B-DB Beck 2006 6793 ≥1 56.4 77.2 52.3 73.1 (71.8, 74.2)42 (HM)MB-B-DL Teixeira 2020 350 ≥1 10.9 22.0 87.5 49.4 (38.5, 60.3)28 (HM)MB-DB Tran 2014 3667 ≥2 26.3 46.1 73.1 57.1 (54.7, 59.4)28 (HM)MB-DL Tran 2014 3667 ≥2 29.2 46.1 76.1 63.3 (61.0, 65.6)28 (HM)MB-DL Alawaji 2022 431 ≥2 58.7 78.4 58.7 74.8 (69.9, 79.1)42 42 RSSM Beck 2006 6793 ≥1 63.7 77.2 62.8 82.5 (81.4, 83.5)40 CPITN Tran 2014 3667 ≥2 33.2 46.1 80.7 72.0 (69.8, 74.0)36 36 RSSM Beck 2006 6793 ≥1 62.5 77.2 60.8 81.0 (79.9, 82.0)36 Ramfjord Beck 2006 6793 ≥1 54.2 77.2 49.8 70.2 (69.0, 71.4)36 Ramfjord Dowsett 2002 292 (?) 89.0 96.9 28.1 91.7 (87.9, 94.4)24 Ramfjord Tran 2014 3667 ≥2 19.9 46.1 67.4 43.5 (41.1, 45.8)Heterogeneity (I2=99.1%, P<0.001) 50.0 62.5 81.0 (76.9, 84.6) 99 Figure 18. Summary of the Absolute Bias (AB)prevalence of severe periodontitis using Partial-mouth Recording Protocols (PRP). Total PRP sites for each PRP and minimal number of sites with Clinical Attachment Loss (CAL) are listed. ABprevalence values <0.0 underestimate the prevalence while values >0.0 overestimate it. FRP: Full-mouth Recording Protocol, N: sample size, CI: Confidence Interval, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, ML: Mesio-Lingual, L: Mid-Lingual, DL: Disto-Lingual, (FM): Full-Mouth, (HM): Half-Mouth, 84 RSSM: 84 sites selected using Random-Site-Selection-Method, 42 RSSM: 42 sites selected using Random-Site-Selection-Method, 36 RSSM: 36 sites selected using Random-Site-Selection-Method, (RHM): Random-Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs, ?: not clear.-30.0% 25.0% -20.0% 15.0% -10.0% 5.0% 0.0% 5.0%Absolute biasPRPsites PRP Studies NCALsitesPrevalencePRP (%)PrevalenceFRP (%) AB% (95% CI)84 (FM) MB-B-DB Susin 2005 1460 ≥1 36.6 43.6 -7.1 (-10.6, -3.5)84 (FM) MB-B-DL Susin 2005 1460 ≥1 38.9 43.6 -4.7 (-8.3, -1.2)56 (FM) MB-DB Tran 2014 3667 ≥2 7.6 11.8 -4.2 (-5.6, -2.8)56 (FM) MB-DL Tran 2014 3667 ≥2 8.6 11.8 -3.2 (-4.6, -1.8)56 (FM) MB-DL Romano 2019 721 ≥2 32.6 38.1 -5.5 (-10.5, -0.6)56 (FM) MB-DL Alawaji 2022 431 ≥2 27.8 31.3 -3.5 (-9.6, -2.6)84 84 RSSM Beck 2006 6793 ≥1 31.8 35.8 -4.0 (-5.6, -2.4)84 RHM Dowsett 2002 292 (?) 42.1 55.1 -13.0 (-21.1, -5.0)84 RHM Susin 2005 1460 ≥1 36.2 43.6 -7.5 (-11.0, -3.9)56 RHM Tran 2014 3667 ≥2 7.7 11.8 -4.1 (-5.4, -2.7)56 RHM Romano 2019 721 ≥2 27.7 38.1 -10.4 (-15.2, -5.6)56 RHM Alawaji 2022 431 ≥2 23.4 31.3 -7.9 (-13.3, -2.0)42 (HM) MB-B-DB Susin 2005 1460 ≥1 28.3 43.6 -15.3 (-18.8, -11.9)42 (HM) MB-B-DL Susin 2005 1460 ≥1 31.4 43.6 -12.3 (-15.7, -8.8)42 (HM) MB-B-DB Beck 2006 6793 ≥1 20.4 35.8 -15.4 (-16.9, -13.9)28 (HM) MB-DB Tran 2014 3667 ≥2 4.6 11.8 -7.2 (-8.4, -6.0)28 (HM) MB-DL Tran 2014 3667 ≥2 5.2 11.8 -6.6 (-7.9, -5.3)28 (HM) MB-DL Alawaji 2022 431 ≥2 18.3 31.3 -13.0 (-18.7, -7.3)42 42 RSSM Beck 2006 6793 ≥1 25.7 35.8 -10.1 (-11.6, -8.6)40 CPITN Tran 2014 3667 ≥2 7.4 11.8 -4.4 (-5.8, -3.1)36 36 RSSM Beck 2006 6793 ≥1 24.0 35.8 -11.8 (-13.3, -10.3)36 Ramfjord Beck 2006 6793 ≥1 18.0 35.8 -17.8 (-19.3, -16.4)36 Ramfjord Dowsett 2002 292 (?) 31.2 55.1 -24.0 (-31.8, -16.2)24 Ramfjord Tran 2014 3667 ≥2 2.9 11.8 -8.9 (-10.1, -7.7)Heterogeneity (I2=95.6%, P<0.001) 19.8 27.9 -8.9 (-10.9, -7.0) 100 Figure 19. Summary of the sensitivity of severe periodontitis prevalence using Partial-mouth Recording Protocols (PRP). Specificity and positive predictive value are 100% for all PRPs. PRP sites, minimal number of sites with Clinical Attachment Loss (CAL), and Negative Predictive Value (NPV) are listed. FRP: Full-mouth Recording Protocol, N: sample size, CI: Confidence Interval, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, ML: Mesio-Lingual, L: Mid-Lingual, DL: Disto-Lingual, (FM): Full-Mouth, (HM): Half-Mouth, 84 RSSM: 84 sites selected using Random-Site-Selection-Method, 42 RSSM: 42 sites selected using Random-Site-Selection-Method, 36 RSSM: 36 sites selected using Random-Site-Selection-Method, (RHM): Random-Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs, ?: not clear.24.0% 41.0% 58.0% 76.0% 93.0%SensitivityPRPsites PRP Studies NCALsitesPrevalencePRP (%)PrevalenceFRP (%)NPV(%)Sensitivity%(95% CI)84 (FM)MB-B-DB Susin 2005 1460 ≥1 36.6 43.6 88.9 83.8 (80.7, 86.4)84 (FM)MB-B-DL Susin 2005 1460 ≥1 38.9 43.6 92.3 89.1 (86.4, 91.3)56 (FM)MB-DB Tran 2014 3667 ≥2 7.6 11.8 95.5 64.4 (59.8, 68.8)56 (FM)MB-DL Tran 2014 3667 ≥2 8.6 11.8 96.5 72.7 (68.3, 76.7)56 (FM)MB-DL Romano 2019 721 ≥2 32.6 38.1 91.8 85.3 (80.6, 89.0)56 (FM)MB-DL Alawaji 2022 431 ≥2 27.8 31.3 94.9 88.6 (82.1, 93.0)84 84 RSSM Beck 2006 6793 ≥1 31.8 35.8 93.5 87.6 (86.3, 88.9)84 RHM Dowsett 2002 292 (?) 42.1 55.1 77.5 76.2 (69.1, 82.2)84 RHM Susin 2005 1460 ≥1 36.2 43.6 88.3 82.8 (79.7, 85.6)56 RHM Tran 2014 3667 ≥2 7.7 11.8 95.6 65.3 (60.7, 69.7)56 RHM Romano 2019 721 ≥2 27.7 38.1 85.6 72.6 (67.1, 77.6)56 RHM Alawaji 2022 431 ≥2 23.4 31.3 89.4 74.6 (66.7, 81.2)42 (HM)MB-B-DB Susin 2005 1460 ≥1 28.3 43.6 78.6 64.8 (61.0, 68.4)42 (HM)MB-B-DL Susin 2005 1460 ≥1 31.4 43.6 82.1 71.9 (68.2, 75.2)42 (HM)MB-B-DB Beck 2006 6793 ≥1 20.4 35.8 80.7 73.1 (71.8, 74.2)28 (HM)MB-DB Tran 2014 3667 ≥2 4.6 11.8 92.5 39.1 (34.6, 43.7)28 (HM)MB-DL Tran 2014 3667 ≥2 5.2 11.8 93.0 57.0 (55.0, 58.9)28 (HM)MB-DL Alawaji 2022 431 ≥2 18.3 31.3 84.0 58.5 (50.0, 66.4)42 42 RSSM Beck 2006 6793 ≥1 25.7 35.8 86.4 71.8 (70.0, 73.5)40 CPITN Tran 2014 3667 ≥2 7.4 11.8 95.2 62.6 (57.9, 67.0)36 36 RSSM Beck 2006 6793 ≥1 24.0 35.8 84.5 67.0 (65.1, 68.8)36 Ramfjord Beck 2006 6793 ≥1 18.0 35.8 78.3 50.2 (48.2, 52.2)36 Ramfjord Dowsett 2002 292 (?) 31.2 55.1 56.5 56.5 (48.8, 63.9)24 Ramfjord Tran 2014 3667 ≥2 2.9 11.8 90.8 27.9 (23.9, 32.2)Heterogeneity (I2=98.6%, P<0.001) 19.8 27.9 70.1 (64.6, 75.1) 101 Figure 20. Subgroup analysis of the Absolute Bias (AB)prevalence of severe periodontitis using Partial-mouth Recording Protocols (PRP). Subgroups were based on the PRP types. FRP: Full-mouth Recording Protocol, N: sample size, CI: Confidence Interval, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, ML: Mesio-Lingual, L: Mid-Lingual, DL: Disto-Lingual, (FM): Full-Mouth, (HM): Half-Mouth, 84 RSSM: 84 sites selected using Random-Site-Selection-Method, 42 RSSM: 42 sites selected using Random-Site-Selection-Method, 36 RSSM: 36 sites selected using Random-Site-Selection-Method, (RHM): Random-Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs, ?: not clear.-30.0% 25.0% -20.0% 15.0% -10.0% 5.0% 0.0% 5.0%Absolute biasPRP Studies PrevalencePRP (%)PrevalenceFRP (%) AB% (95% CI)(FM) MB-B-DB Susin 2005 36.6 43.6 -7.1 (-10.6, -3.5)(FM) MB-B-DL Susin 2005 38.9 43.6 -4.7 (-8.3, -1.2)(FM) MB-DB Tran 2014 7.6 11.8 -4.2 (-5.6, -2.8)(FM) MB-DL Tran 2014 8.6 11.8 -3.2 (-4.6, -1.8)(FM) MB-DL Romano 2019 32.6 38.1 -5.5 (-10.5, -0.6)(FM) MB-DL Alawaji 2022 27.8 31.3 -3.5 (-9.6, -2.6)84 RSSM Beck 2006 31.8 35.8 -4.0 (-5.6, -2.4)Subgroup (I2=0.0%, P=0.580) 26.3 30.9 -4.0 (-4.8, -3.3)RHM Dowsett 2002 42.1 55.1 -13.0 (-21.1, -5.0)RHM Susin 2005 36.2 43.6 -7.5 (-11.0, -3.9)RHM Tran 2014 7.7 11.8 -4.1 (-5.4, -2.7)RHM Romano 2019 27.7 38.1 -10.4 (-15.2, -5.6)RHM Alawaji 2022 23.4 31.3 -7.9 (-13.3, -2.0)Subgroup (I2=69.3%, P=0.011) 27.4 36.0 -7.6 (-10.9, -4.4)(HM) MB-B-DB Susin 2005 28.3 43.6 -15.3 (-18.8, -11.9)(HM) MB-B-DL Susin 2005 31.4 43.6 -12.3 (-15.7, -8.8)(HM) MB-B-DB Beck 2006 20.4 35.8 -15.4 (-16.9, -13.9)(HM) MB-DB Tran 2014 4.6 11.8 -7.2 (-8.4, -6.0)(HM) MB-DL Tran 2014 5.2 11.8 -6.6 (-7.9, -5.3)(HM) MB-DL Alawaji 2022 18.3 31.3 -13.0 (-18.7, -7.3)42 RSSM Beck 2006 25.7 35.8 -10.1 (-11.6, -8.6)Subgroup (I2=94.5%, P=0.000) 19.1 30.5 -11.2 (-14.2, -8.2)CPITN Tran 2014 7.4 11.8 -4.4 (-5.8, -3.1)36 RSSM Beck 2006 24.0 35.8 -11.8 (-13.3, -10.3)Ramfjord Beck 2006 18.0 35.8 -17.8 (-19.3, -16.4)Ramfjord Dowsett 2002 31.2 55.1 -24.0 (-31.8, -16.2)Ramfjord Tran 2014 2.9 11.8 -8.9 (-10.1, -7.7)Subgroup (I2=98.0%, P=0.000) 16.7 30.1 -12.6 (-17.7, -7.6)Heterogeneity: I2=95.6%, P<0.001 19.8 27.9 -8.9 (-10.9, -7.0) 102 Figure 21. Subgroup analysis of the Absolute Bias (AB)prevalence of severe periodontitis using Partial-mouth Recording Protocols (PRP) excluding the PRP estimates by Tran et al. 2014 where one can observe the reduction of heterogeniety in subgorups compared with Figure 20. Subgroups were based on the PRP types. FRP: Full-mouth Recording Protocol, N: sample size, CI: Confidence Interval, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, ML: Mesio-Lingual, L: Mid-Lingual, DL: Disto-Lingual, (FM): Full-Mouth, (HM): Half-Mouth, 84 RSSM: 84 sites selected using Random-Site-Selection-Method, 42 RSSM: 42 sites selected using Random-Site-Selection-Method, 36 RSSM: 36 sites selected using Random-Site-Selection-Method, (RHM): Random-Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs, ?: not clear. -30.0% 25.0% -20.0% 15.0% -10.0% 5.0% 0.0% 5.0%Absolute biasPRP Studies PrevalencePRP (%)PrevalenceFRP (%) AB% (95% CI)(FM) MB-B-DB Susin 2005 36.6 43.6 -7.1 (-10.6, -3.5)(FM) MB-B-DL Susin 2005 38.9 43.6 -4.7 (-8.3, -1.2)(FM) MB-DL Romano 2019 32.6 38.1 -5.5 (-10.5, -0.6)(FM) MB-DL Alawaji 2022 27.8 31.3 -3.5 (-9.6, -2.6)84 RSSM Beck 2006 31.8 35.8 -4.0 (-5.6, -2.4)Subgroup (I2=0.0%, P=0.615) 33.5 38.5 -4.6 (-5.8, -3.3)RHM Dowsett 2002 42.1 55.1 -13.0 (-21.1, -5.0)RHM Susin 2005 36.2 43.6 -7.5 (-11.0, -3.9)RHM Romano 2019 27.7 38.1 -10.4 (-15.2, -5.6)RHM Alawaji 2022 23.4 31.3 -7.9 (-13.3, -2.0)Subgroup (I2=0.0%, P=0.549) 32.4 42.1 -8.8 (-11.3, -6.4)(HM) MB-B-DB Susin 2005 28.3 43.6 -15.3 (-18.8, -11.9)(HM) MB-B-DL Susin 2005 31.4 43.6 -12.3 (-15.7, -8.8)(HM) MB-B-DB Beck 2006 20.4 35.8 -15.4 (-16.9, -13.9)(HM) MB-DL Alawaji 2022 18.3 31.3 -13.0 (-18.7, -7.3)42 RSSM Beck 2006 25.7 35.8 -10.1 (-11.6, -8.6)Subgroup (I2=84.3%, P=0.000) 24.8 38.0 -13.2 (-16.0, -10.3)36 RSSM Beck 2006 24.0 35.8 -11.8 (-13.3, -10.3)Ramfjord Beck 2006 18.0 35.8 -17.8 (-19.3, -16.4)Ramfjord Dowsett 2002 31.2 55.1 -24.0 (-31.8, -16.2)Subgroup (I2=94.5%, P=0.000) 24.4 42.3 -16.8 (-22.2, -11.4)Heterogeneity (I2=93.4%, P<0.001) 27.4 37.4 -10.6 (-13.2, -8.1) 103 Figure 22. Summary of Absolute Bias (AB)severity, background characteristics of studies, PRP sites, and severity estimates are listed. FRP: Full-mouth Recording, (SD) standard deviation, Protocol, N: sample size, CI: Confidence Interval, NHANES: National Health And Nutrition Examination Survey, ARIC: Atherosclerosis Risk In Communities, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, ML: Mesio-Lingual, L: Mid-Lingual, DL: Disto-Lingual, (FM): Full-Mouth, 84 RSSM: 84 sites selected using Random-Site-Selection-Method, 42 RSSM: 42 sites selected using Random-Site-Selection-Method, 36 RSSM: 36 sites selected using Random-Site-Selection-Method, (HM): Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs.Sample, Country PRP sitesPRP Studies N PRPMean CAL (SD)FRPMean CAL (SD)AB (95% CI)Convenience, China 84 (FM)MB-B-DB Chu 2014 200 1.77 (0.89) 1.92 (0.93) -0.15 (-0.33, 0.03)Random, Brazil 84 (FM)MB-B-DB Kingman 2008 1437 1.49 (1.64) 1.56 (1.71) -0.07 (-0.19, 0.05)Convenience, Brazil 84 (FM)MB-B-DL Teixeira 2020 350 1.37 (0.48) 1.38 (0.49) -0.01 (-0.08, 0.06)Convenience, China 84 (FM)MB-B-DL Chu 2014 200 1.81 (0.91) 1.92 (0.93) -0.11 (-0.29, 0.07)Random, Brazil 84 (FM)MB-B-DL Kingman 2008 1437 1.56 (1.77) 1.55 (1.71) 0.01 (-0.12, 0.14)Convenience, China 56 (FM)MB-DB Chu 2014 200 1.83 (0.89) 1.92 (0.93) -0.09 (-0.27, 0.09)Convenience, China 56 (FM)MB-DL Chu 2014 200 1.89 (0.94) 1.92 (0.93) -0.03 (-0.21, 0.15)Random, ARIC, USA 84 84 RSSM Beck 2006 6793 1.77 (1.04) 1.77 (1.04) 0.00 (0.04, 0.04)Random, ARIC, USA 42 42 RSSM Beck 2006 6973 1.77 (1.05) 1.77 (1.04) 0.00 (-0.04, 0.04)Random, ARIC, USA 36 36 RSSM Beck 2006 6973 1.77 (1.05) 1.77 (1.04) 0.00 (-0.04, 0.04)Convenience, Brazil 84 RHM Teixeira 2020 350 1.38 (0.49) 1.38 (0.49) 0.00 (-0.07, 0.07)Random, NHANES, USA 65 RHM Tran 2016 3734 1.68 (1.22) 1.73 (1.22) -0.05 (-0.11, 0.01)Convenience, China 56 RHM Chu 2014 200 1.91 (0.95) 1.92 (0.93) -0.01 (-0.19, 0.17)Convenience, Portugal 84 RHM Relvas 2013 108 0.97 (1.87) 0.97 (1.56) 0.00 (-0.46, 0.46)Random, Brazil 84 RHM Kingman 2008 1437 1.57 (1.79) 1.56 (1.71) 0.01 (-0.12, 0.14)Convenience, Brazil 84 RHM Vettore 2007 156 2.90 (1.38) 2.90 (1.40) 0.00 (-0.31, 0.31)Convenience, China 42 (HM)MB-B-DB Chu 2014 200 1.79 (0.90) 1.92 (0.93) -0.13 (-0.3, 0.05)Random, Brazil 42 (HM)MB-B-DB Kingman 2008 1437 1.51 (1.71) 1.56 (1.71) -0.05 (-0.18, 0.08)Random, ARIC, USA 42 (HM)MB-B-DB Beck 2006 6793 1.73 (1.02) 1.77 (1.04) -0.04 (-0.08, -0.05)Convenience, Brazil 42 (HM)MB-B-DL Teixeira 2020 350 1.37 (0.47) 1.38 (0.49) -0.01 (-0.08, 0.06)Convenience, China 42 (HM)MB-B-DL Chu 2014 200 1.83 (0.94) 1.92 (0.93) -0.09 (-0.27, 0.09)Random, Brazil 42 (HM)MB-B-DL Kingman 2008 1437 1.56 (1.71) 1.56 (1.71) 0.00 (-0.12, 0.12)Convenience, China 28 (HM)MB-DB Chu 2014 200 1.82 (0.89) 1.92 (0.92) -0.10 (-0.28, 0.08)Convenience, China 28 (HM)MB-DL Chu 2014 200 1.89 (0.94) 1.92 (0.93) -0.03 (-0.21, 0.15)Convenience, China 60 CPITN Chu 2014 200 2.14 (1.04) 1.92 (0.93) 0.22 (0.03, 0.41)Convenience, Portugal 60 CPITN Relvas 2014 108 1.38 (3.36) 0.97 (1.56) 0.41 (-0.29, 1.11)Convenience, Brazil 60 CPITN Vettore 2007 156 3.33 (1.66) 2.90 (1.40) 0.43 (0.09, 0.77)Convenience, China 36 Ramfjord Chu 2014 200 2.01 (0.97) 1.92 (0.93) 0.09 (-0.10, 0.28)Convenience, Portugal 36 Ramfjord Relvas 2013 108 1.15 (2.16) 0.97 (1.56) 0.18 (-0.32, 0.68)Random, Brazil 36 Ramfjord Kingman 2008 1437 1.60 (1.81) 1.56 (1.71) 0.04 (-0.09, 0.17)Random, ARIC, USA 36 Ramfjord Beck 2006 6793 1.78 (1.05) 1.77 (1.04) 0.01 (0.03, 0.05)Overall (I2= 6.3%, P=0.367) -0.01 (-0.03, 0.01)Absolute bias-0.5 0.0 0.5 1.0 104 Figure 23. Summary estimates of the Absolute Bias (AB)extent of moderate-severe periodontitis. Background characteristics of studies, PRP sites, and specific thresholds of Clinical Attachment Loss (CAL) are listed. FRP: Full-mouth Recording, Protocol, N: sample size, (SD) standard deviation, CI: Confidence Interval, NHANES: National Health And Nutrition Examination Survey, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, ML: Mesio-Lingual, L: Mid-Lingual, DL: Disto-Lingual, (FM): Full-Mouth, (HM): Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs.Sample, Country PRP sitesPRP Studies N CAL in mmPRP ExtentMean% (SD)FRP Extent, Mean% (SD)AB (95% CI)Convenience, China 84 (FM)MB-B-DB Chu 2014 200 ≥4 12.6 (16.2) 13.6 (17.7) -1.0 (-2.3, 2.3)Convenience, Brazil 84 (FM)MB-B-DL Teixeira 2020 350 ≥4 2.8 (8.5) 4.1 (8.8) -0.3 (-1.6, 1.0)Convenience, China 84 (FM)MB-B-DL Chu 2014 200 ≥4 13.2 (17.2) 13.6 (17.7) -0.4 (-3.8, 3.0)Convenience, China 56 (FM)MB-DB Chu 2014 200 ≥4 12.5 (16.3) 13.6 (17.7) -1.1 (-4.4, 2.2)Untreated, Saudi Arabia 56 (FM)MB-DL Alawaji 2022 431 ≥3 32.6 (33.6) 34.9 (33.6) -2.3 (-6.7, 2.1)Convenience, China 56 (FM)MB-DL Chu 2014 200 ≥4 13.4 (18) 13.6 (17.7) -0.2 (-3.7, 3.3)Untreated, Saudi Arabia 56 RHM Alawaji 2022 431 ≥3 33.9 (33.6) 34.9 (33.6) -1.0 (-5.5, 3.5)Convenience, Brazil 84 RHM Teixeira 2020 350 ≥4 3.6 (9.4) 4.1 (8.8) 0.5 (-1.9, 0.9)Random, NHANES, USA 56 RHM Tran 2016 3734 ≥3 20 (24.4) 21.2 (24.4) -1.2 (-2.3, -0.1)Convenience, China 56 RHM Chu 2014 200 ≥4 13.6 (18) 13.6 (17.7) 0.0 (-3.5, 3.5)Convenience, Portugal 84 RHM Relvas 2013 108 ≥4 10.8 (16.8) 11.13 (16.1) -0.4 (-4.7, 4.0)Convenience, China 42 (HM)MB-B-DB Chu 2014 200 ≥4 12.8 (16.9) 13.6 (17.7) -0.8 (-4.2, 2.6)Convenience, Brazil 42 (HM)MB-B-DL Teixeira 2020 350 ≥4 2.9 (9.1) 4.1 (8.8) -1.2 (-2.5, 0.1)Convenience, China 42 (HM)MB-B-DL Chu 2014 200 ≥4 13.5 (17.8) 13.6 (17.7) -0.1 (-3.6, 3.4)Convenience, China 28 (HM)MB-DB Chu 2014 200 ≥4 12.2 (16.4) 13.6 (17.7) -1.4 (-4.7, 1.9)Untreated, Saudi Arabia 28 (HM)MB-DL Alawaji 2022 431 ≥3 33.1 (32.4) 34.9 (33.6) -1.8 (-6.2, 2.6)Convenience, China 28 (HM)MB-DL Chu 2014 200 ≥4 13.3 (18.2) 13.6 (17.7) -0.3 (-3.8, 3.2)Convenience, China 60 CPITN Chu 2014 200 ≥4 18 (20.6) 13.6 (17.7) 4.4 (0.6, 8.2)Convenience, Portugal 60 CPITN Relvas 2014 108 ≥4 15.2 (20.7) 11.13 (16.1) 4.1 (-0.9, 9.0)Convenience, China 36 Ramfjord Chu 2014 200 ≥4 16.6 (19.5) 13.6 (17.7) 3.0 (-0.7, 6.7)Convenience, Portugal 36 Ramfjord Relvas 2013 108 ≥4 12.7 (17.6) 11.13 (16.1) 1.6 (-2.9, 6.0)Overall (I2= 0.0%, P= 0.554) -0.6 (-1.1, 0.0)Underestimation Overestimation Absolute bias 105 Figure 24. Summary of the Absolute Bias (AB)extent of severe periodontitis using Partial-mouth Recording Protocols (PRP). Total PRP sites for each PRP are listed. ABextent values <0.0 underestimate the extent, while values >0.0 overestimate it. FRP: Full-mouth Recording Protocol, N: sample size, SD: standard deviation, CI: Confidence Interval, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, ML: Mesio-Lingual, L: Mid-Lingual, DL: Disto-Lingual, (FM): Full-Mouth, (HM): Half-Mouth, 84 RSSM: 84 sites selected using Random-Site-Selection-Method, 42 RSSM: 42 sites selected using Random-Site-Selection-Method, 36 RSSM: 36 sites selected using Random-Site-Selection-Method, (RHM): Random-Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs.Sample, Country PRPsitesPRP Studies N CAL in mmPRP Extent,Mean% (SD)FRP Extent, Mean% (SD)AB (95% CI)Convenience, China 84 (FM)MB-B-DB Chu 2014 200 ≥6 2.2 (5.0) 2.7 (5.6) -0.5 (-1.5, 0.5)Convenience, Brazil 84 (FM)MB-B-DL Teixeira 2020 350 ≥6 0.8 (3.3) 0.9 (3.8) -0.1 (-0.6, 0.4)Convenience, China 84 (FM)MB-B-DL Chu 2014 200 ≥6 2.6 (5.7) 2.7 (5.6) -0.1 (-1.2, 1.0)Convenience, China 56 (FM)MB-DB Chu 2014 200 ≥6 2.3 (5.0) 2.7 (5.6) -0.4 (-1.4, 0.6)Untreated, Saudi Arabia 56 (FM)MB-DL Alawaji 2022 431 ≥5 13 (23.9) 14.4 (25.6) -1.4 (-4.7, 1.9)Convenience, China 56 (FM)MB-DL Chu 2014 200 ≥6 2.5 (5.5) 2.7 (5.6) -0.2 (-1.3, 0.9)Untreated, Saudi Arabia 56 RHM Alawaji 2022 431 ≥5 13.8 (25.1) 14.4 (25.6) -0.6 (-4.0, 2.8)Convenience, Brazil 84 RHM Teixeira 2020 350 ≥6 0.7 (3.9) 0.9 (3.8) -0.2 (-0.8, 0.4)Random, NHANES, USA 56 RHM Tran 2016 3734 ≥5 6.9 (18.3) 6.6 (18.3) 0.3 (-0.5, 1.1)Convenience, China 84 RHM Chu 2014 200 ≥6 2.7 (5.5) 2.7 (5.6) 0.0 (-1.1, 1.1)Convenience, China 42 (HM)MB-B-DB Chu 2014 200 ≥6 2.4 (5.6) 2.7 (5.6) -0.3 (-1.4, 0.8)Convenience, Brazil 42 (HM)MB-B-DL Teixeira 2020 350 ≥6 0.6 (3.7) 0.9 (3.8) -0.3 (-0.9, 0.3)Convenience, China 42 (HM)MB-B-DL Chu 2014 200 ≥6 2.6 (5.7) 2.7 (5.6) -0.1 (-1.2, 1.0)Convenience, China 28 (HM)MB-DB Chu 2014 200 ≥6 2.5 (5.7) 2.7 (5.6) -0.2 (-1.3, 0.9)Untreated, Saudi Arabia 28 (HM)MB-DL Alawaji 2022 431 ≥5 12.9 (24.2) 14.4 (25.6) -1.5 (-4.8, 1.8)Convenience, China 28 (HM)MB-DL Chu 2014 200 ≥6 2.3 (4.5) 2.7 (5.6) -0.4 (-1.4, 0.6)Convenience, China 60 CPITN Chu 2014 200 ≥6 4.2 (7.8) 2.7 (5.6) 1.5 (0.2, 2.8)Convenience, China 36 Ramfjord Chu 2014 200 ≥6 3.1 (6.4) 2.7 (5.6) 0.4 (-0.8, 1.6)Overall (I2= 0.0%, P= 0.881) -0.1 (-0.4, 0.1)Underestimation OverestimationAbsolute bias 106 Table 17. Quality assessment of the included studies using the second version of the Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS-2) (Whiting PF et al., 2011). Authors, date Patient selection PRP FRP Flow Overall ROB Overall applicability concerns ROB Applicability concerns ROB Applicability concerns ROB Applicability concerns ROB Alawaji et al., 2022 Low Unclear Low Low Low Low Low Low risk Potential concerns Teixeira et al., 2020 Unclear Unclear Low Low Low Low Low Potential risk Potential concerns Alshihayb et al., 2020 Low Low Low Low Low Low Low Low risk Low concerns Romano et al., 2019 Low Low Low Low Low Low Low Low risk Low concerns Tran et al., 2016 Low Low Low Low Low Low Low Low risk Low concerns Akinkugbe et al., 2015 Unclear Unclear Low Low Low Low Low Potential risk Potential concerns Tran et al., 2014 Low Low Low Low Low Low Low Low risk Low concerns Chu and Ouyang, 2014 High High Low Low Low Low Low High risk High concerns Relvas et al., 2013 Low High Low Low Low Low Low Low risk High concerns Kingman et al., 2008 Low Low Low Low Low Low Low Low risk Low concerns Vettore et al., 2007 Low High Low Low Low Low Low Low risk High concerns Beck et al., 2006 Low Unclear Low Low Low Low Low Low risk Potential concerns Susin et al., 2005 Low Unclear Unclear Low Low Low Low Potential risk Potential concerns Dowsett et al., 2002 Unclear Unclear Unclear Low Low Low Unclear Potential risk Potential concerns ROB: Risk of Bias, PRP: Partial-mouth Recording Protocol, FRP: Full-mouth Recording Protocol. 107 Table 18. Included studies’ characteristics and potential concerns Reference Settings, country Sample size, age Outcomes Partial Recording Protocol Minimum number of teeth/sites Potential concerns Alawaji et al., 2022 (Alawaji Y, Mostafa N, et al., 2022) Purposive sample of untreated individuals at university setting, Saudi Arabia 431 subjects, 13-80 years Prevalence of CDC/AAP moderate-severe and severe periodontitis, mean (SD) of periodontitis extent, exposure associations including self-reported diabetes mellitus, obesity, and current cigarette smoking. (FM)MB-DL, RHM, and (HM)MB-DL. 3 teeth. Targeted untreated subjects recruited at university settings which may limit the external validity. The medical conditions were self-reported by the subjects without adding objective measurement for glycemic control, obesity was self-reported as present/absent, no minimum number of cigarette smoking were included into the current smokers group. Teixeira et al., 2020 (Teixeira F et al., 2020) Convenience sample, Brazil 350 subjects, 35-74 years Prevalence of moderate-severe periodontitis, mean (SD) of periodontitis severity, and extent. (FM)MB-B-DL, RHM, and (HM)MB-B-DL. 4 teeth. Did not describe the background characteristics of the study subjects. It was not clear where the clinical examinations were conducted. Alshihayb et al., 2020 (Alshihayb TS et al., 2020) General population (NHANES 2009-2014), USA 9575 subjects, 30-79 years Exposure associations with periodontitis prevalence including self-reported Diabetes mellitus. RHM, CPITN teeth, and Ramfjord teeth. 2 teeth for each used PRP. Did not define the eligibility criteria for included subjects from the NHANES data, excluded all subjects with missing data without stating the proportion of missingness, did not report the values for the dependent variables used in the multivariate models. Defined diabetes mellitus status as present or absent without considering glycemic control. Romano et al., 2019 (Romano F et al., 2019) General population, Italy 721 subjects, 20-75 years Prevalence of moderate-severe and severe periodontitis. (FM)MB-B-DL and RHM. 6 teeth Excluded subjects with less than 6 remaining teeth. Tran et al., 2016 (Tran DT et al., 2016) NHANES 2009-2010, USA 3734 subjects, 30-80 years Mean (SD) of periodontitis extent and severity. RHM. 1 tooth per selected quadrant Excluded subjects who had no teeth in the selected quadrants for the RHM. Akinkugbe et al., 2015 (Akinkugbe General population based (ARIC study), USA 6259 subjects, 52 to 74 years Exposure associations were listed including current smoking (total of ≥100 cigarettes in 42 RSSM, (HM)MB-B-DL, and Ramfjord teeth. 2 eligible sites. Eligibility criteria were not described, excluded subjects who had 1 site with CAL rather than considering them in the no periodontitis category. Defined 108 Reference Settings, country Sample size, age Outcomes Partial Recording Protocol Minimum number of teeth/sites Potential concerns AA et al., 2015) lifetime) and Diabetes Mellitus. diabetes mellitus status as present or absent without considering glycemic control. Tran et al., 2014 (Tran DT et al., 2014) General population (NHANES data 2009-2010), USA 3667 subjects, 30-80 years Prevalence of CDC/AAP moderate-severe and severe periodontitis. (FM)MB-DB, (FM)MB-DL, RHM, (HM)MB-DL, (HM)MB-DL, CPITN teeth, and Ramfjord teeth. 6 teeth Excluded all subjects with missing data and those who had less than 6 remaining teeth. Chu and Ouyang, 2014 (Chu Y & Ouyang X, 2015) Convenience sample, China 200 subjects, 22-64 years Mean (SD) of periodontitis severity and extent. (FM)MB-B-DB, (FM)MB-B-DL, (FM)MB-DB, (FM)MB-DL, RHM, (HM)MB-B-DB, (HM)MB-B-DL, (HM)MB-DB, (HM)MB-DL, Ramfjord teeth, and CPITN teeth. ³16 remaining teeth, ³4 of them are molars, having ³1 site with ³5 mm PPD and CAL ³2 mm in ³2 sites in different quadrants. Convenience sample, selected subjects with ³16 remaining teeth with periodontitis which limit the external validity. Relvas et al., 2013 (Relvas M et al., 2014) Convenience sample, Portugal 108 subjects, 25-65 years Mean (SD) of periodontitis severity and extent. RHM, Ramfjord teeth, and CPITN teeth. ³24 teeth, ³5 teeth per quadrant, ³8 teeth in CPITN, ³4 teeth in Ramfjord Convenience sample and strict eligibility criteria that limits the external validity of the study. Kingman et al., 2008 (Kingman A et al., 2008) Population based, Brazil 1437 subjects, 14-103 years Mean (SD) of periodontitis severity. (FM)MB-B-DB, (FM)MB-B-DL, RHM, (HM)MB-B-DB, (HM)MB-B-DL, and Ramfjord teeth. ³6 teeth per quadrant Minimum number of included teeth may limit the external validity of the study. Vettore et al., 2007 (Vettore MV et al., 2007) University setting, Maternity clinic, Brazil 156 subjects, 30-67 years Mean (SD) of periodontitis severity. RHM and CPITN teeth. ³15 teeth Minimum number of included teeth may limit the external validity. Beck et al., 2006 (Beck JD et al., 2006) Population based (ARIC study), 4 states, USA 6793 subjects, 52 to 74 years Prevalence of moderate-severe and severe periodontitis, mean (SD) of periodontitis severity. 84 RSSM, 42 RSSM, 36 RSSM, RHM, MB-B-DB (HM), and Ramfjord teeth. ³1 tooth. Older subjects (52 to 74 years), which may limit the external validity. Susin et al., 2005 (Susin C et al., 2005) General population, Brazil 1460 subjects, 14-103 years Prevalence of moderate-severe and severe periodontitis. (FM)MB-B-DB, (FM)MB-B-DL, RHM, (HM)MB-B-DB, and (HM)MB-B-DL. Not clear Defined periodontitis at least at 1 site with CAL. Did not clarify what was the minimum number of teeth in included subjects. 109 Reference Settings, country Sample size, age Outcomes Partial Recording Protocol Minimum number of teeth/sites Potential concerns Dowsett et al., 2002 (Dowsett SA, Eckert GJ, et al., 2002b) Untreated population, randomly selected or from siblings and spouse pairs of the randomly selected subjects, Guatemala 292 subjects, 18-78 years Prevalence of moderate-severe and severe periodontitis. RHM and Ramfjord teeth. Not clear Did not state what the minimum number of sites considered to define subjects with periodontitis was; there were untreated subjects, which may reduce the external validity; did not describe the selection criteria for the study population. It was not clear what was the inter-examiner reliability since the study uses pooled data from three surveys. CAL: Clinical Attachment Loss, HbA1c: glycated hemoglobin, ARIC: Atherosclerosis Risk In Communities, NHANES: National Health And Nutrition Examination Survey, CDC: Centers for Disease Control and Prevention, AAP: American Academy of Periodontology, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal, DL: Disto-Lingual, (FM): Full-Mouth, (HM): Half-Mouth, RHM: Random-Half-Mouth CPITN: Community Periodontal Index of Treatment Needs, 84 RSSM: 84 sites selected using Random-Site-Selection-Method, 42 RSSM: 42 sites selected using Random-Site-Selection-Method. 36 RSSM: 36 sites selected using Random-Site-Selection-Method. 110 Table 19. Exploratory subgroup analysis using bivariate random effect meta-regression for identifying factors associated with absolute bias in estimating moderate-severe periodontitis prevalence Determinants Number of estimates Absolute bias% (95% CI) Association with absolute bias, p-value Heterogeneity I2 (%) No subgroups -12.3 (-14.8, -9.7) 96.3 Minimum number of sites with CAL ≥1 15 -11.4 (-14.3, -8.4) reference 96.9 ≥2 12 -13.5 (-16.8, -10.1) .352 95.5 PRP types Full mouth at partial sites 8 -8.5 (-5.5, -1.5) reference 80.2 RHM 6 -7.8 (-11.1, -4.6) .784 77.4 Half mouth at partial sites 8 -16.1 (-18.8, -13.3) <.001 89.5 Index teeth 5 -17.1 (-22.7, -11.4) <.001 97.5 PRP total sites 84 sites 7 -7.2 (-10.1, -4.3) reference 84.6 56 sites 7 -9.2 (-12.1, -6.3) .079 13.6 40 to 42 sites 6 -14.3 (-17.3, -11.3) .008 92.2 36 sites 3 -15.8 (-19.9, -11.7) <.001 97.6 24-28 sites 4 -20.7 (-17.1, -1.9) <.001 92.9 Sampling method Random 19 -13.5 (-16.0, -11.1) reference 97.1 Non-random 8 -8.9 (-13.0, -4.8) .055 77.3 Risk of bias Low risk 9 -13.8 (-16.3, -11.2) reference 97.2 Potential or high risk 18 -9.2 (-12.9, -5.6) .048 82.0 CAL: Clinical Attachment Loss, PRP: Partial Mouth Recording Protocol, CI: Confidence Interval. Table 20. Exploratory subgroup analysis using bivariate random effect meta-regression for identifying factors associated with the absolute bias in estimating severe periodontitis prevalence Determinants Number of estimates Absolute bias% (95% CI) Association with absolute bias, p-value Heterogeneity I2 (%) No subgroups -8.9 (-10.9, -7.0) 95.6 Minimum number of sites with CAL ≥1 (reference) 12 -11.4 (-13.7, -9.2) reference 95.1 ≥2 12 -6.3 (-8.6, -4.1) .002 84.9 PRP types Full mouth at partial sites 7 -4.5 (-7.3, -1.8) reference 0.0 RHM 5 -7.8 (-11.3, -4.2) .157 69.3 Half mouth at partial sites 7 -11.2 (-13.8, -8.5) <.001 94.5 Index teeth 5 -12.0 (-15.1, -8.9) <.001 97.6 PRP total sites 84 sites 5 -6.3 (-9.2, -3.5) reference 52.9 56 sites 7 -5.1 (-7.5, -2.7) .522 40.5 40 to 42 sites 5 -11.2 (-13.8, -6.7) .012 96.9 36 sites 3 -16.1 (-19.7, -12.6) <.001 72.6 24-28 sites 4 -8.3 (-11.2, -5.5) .337 94.5 Sampling method Random 19 -8.4 (-10.5, -6.4) reference 96.38 Non-random 5 -11.8 (-16.6, -6.9) .211 78.1 Prevalence <30% 7 -5.5 (-8.3, -2.8) reference 90.35 30-40% 9 -10.4 (-13.1, -7.7) .013 80.1 >40% 8 -10.9 (-13.9, -8.0) .009 95.9 Risk of bias Low risk 17 -8.1 (-10.3, -6.0) reference 96.6 Potential or high risk 7 -11.2 (-14.9, -7.6) .155 83.7 CAL: Clinical Attachment Loss, PRP: Partial Mouth Recording Protocol, CI: Confidence Interval. 111 Table 21. Summary of diabetes mellitus, obesity, and current cigarette smoking associations with periodontitis defined using the case definitions by the Centers for Disease Control and Prevention and the American Academy of Periodontology (CDC/AAP) case definitions (Page RC & Eke PI, 2007). Alawaji 20221 Alshihayb 20202 Akinkugbe 20153 Moderate-severe Severe Moderate Severe Moderate-severe Diabetes mellitus FRP (reference) OR (95%CI) 0.9 (0.3, 2.7) 2.0 (1.1, 3.7) 1.3 (1.1 ,1.5) 1.0 (0.7, 1.5) 1.4 (1.2, 1.6) 42 RSSM OR (95%CI) 1.3 (1.1, 1.6) AB (RB) 0.0 (-0.1) RHM OR (95%CI) 1.6 (0.6, 4.5) 1.9 (0.9, 3.7) 1.2 (1.0, 1.3) 1.0 (0.8, 1.1) AB (RB) 0.6 (-5.0) -0.1 (-0.1) -0.1 (-0.4) -0.1 (-1.8) (FM)MB-DL OR (95%CI) 1.5 (0.5, 4.0) 1.6 (0.8, 3.0) AB (RB) 0.5 (-4.2) -0.2 (-0.3) (HM)MB-B-DL OR (95%CI) 1.2 (1.0, 1.4) AB (RB) -0.1 (-0.4) (HM)MB-DL OR (95%CI) 1.9 (0.8, 4.5) 2.6 (1.3, 5.1) AB (RB) 0.8 (-6.5) 0.3 (0.4) CPITN teeth OR (95%CI) 1.2 (1.0, 1.5) 1.1 (0.8, 1.6) AB (RB) -0.1 (-0.3) 0.1 (-2.3) Ramfjord teeth OR (95%CI) 1.2 (0.8, 1.6) 1.0 (0.6, 1.6) 1.2 (1.0, 1.4) AB (RB) -0.1 (-0.4) -0.1 (-2.0) -0.1 (-0.5) Obesity FRP (reference) OR (95% CI) 1.6 (0.7, 3.7) 1.3 (0.7, 2.4) 1.2 (1.1, 1.4) 42 RSSM OR (95%CI) 1.2 (1.0, 1.4) AB (RB) -0.1 (-0.3) RHM OR (95%CI) 1.6 (0.8, 3.3) 1.1 (0.5, 2.0) AB (RB) 0.0 (0.0) -0.2 (-0.8) (FM)MB-DL OR (95%CI) 1.4 (0.7, 2.9) 1.4 (0.7, 2.6) AB (RB) -0.1 (-0.2) 0.1 (0.3) (HM)MB-B-DL OR (95%CI) 1.2 (1.0, 1.4) AB (RB) -0.1 (-0.3) (HM)MB-DL OR (95%CI) 1.1 (0.6, 2.0) 0.8 (0.4, 1.7) AB (RB) -0.4 (-0.9) -0.5 (-1.9) Ramfjord teeth OR (95%CI) 1.1 (0.9, 1.3) AB (RB) -0.2 (-0.7) Current cigarette smoking FRP (reference) OR (95% CI) 4.2 (1.5, 11.7) 2.3 (1.2, 4.7) 3.4 (2.8, 4.1) 42 RSSM OR (95%CI) 3.3 (2.7, 3.9) AB (RB) 0.9 (2.7) RHM OR (95%CI) 4.0 (1.6, 10.0) 2.5 (1.2, 5.2) AB (RB) -0.1 (0.0) 0.1 (0.1) (FM)MB-DL OR (95%CI) 3.5 (1.5, 8.5) 2.2 (1.1, 4.4) AB (RB) -0.2 (-0.1) -0.1 (-0.1) (HM)MB-B-DL OR (95%CI) 3.5 (2.9, 4.2) 112 Alawaji 20221 Alshihayb 20202 Akinkugbe 20153 Moderate-severe Severe Moderate Severe Moderate-severe AB (RB) 0.9 (2.9) (HM)MB-DL OR (95%CI) 4.1 (1.9, 9.1) 1.9 (0.9, 4.1) AB (RB) -0.1 (0.0) -0.2 (-0.2) Ramfjord teeth OR (95%CI) 3.2 (2.6, 3.9) AB (RB) 0.9 (2.7) FRP: Full-mouth Recording Protocol, OR: Odds Ratio, CI: Confidence Interval, AB: Absolute Bias, RB: Relative Bias, 42 RSSM: 42 sites using Random-Site-Selection-Method, (RHM): Random-Half-Mouth, (FM): Full-Mouth, (HM): Half-Mouth, MB: Mesio-Buccal, B: Mid-Buccal, DL: Disto-Lingual, CPITN: Community Periodontal Index of Treatment Needs. 1. Analyses adjusted for age, sex, level of education, monthly income, diabetes mellitus (for smoking), smoking (for diabetes mellitus), obesity, perceived stress, and perceived social support. 2. Analyses adjusted for age, gender, race/ethnicity, education, smoking, waist to height ratio, and diabetes mellitus. 3. Analyses adjusted for age, study site, race, gender, education, tooth brushing frequency, frequency of dental visits, and number of teeth present in each selection. 113 4.4 Discussion The findings from included studies indicate that use of PRPs had the highest impact on estimating periodontitis prevalence, whereas the impact on periodontitis severity, extent, and associations with exposures was marginal in general. Several concerns and factors specifically impacted the performance of each periodontitis outcome and need to be considered before judging the applicability of PRPs in population-based studies. 4.4.1 Methodological considerations Selection of study participants in individual studies: The majority of included studies used non-representative and non-randomly selected samples (Alawaji Y, Mostafa N, et al., 2022; Chu Y & Ouyang X, 2015; Dowsett SA, Eckert GJ, et al., 2002b; Relvas M et al., 2014; Teixeira F et al., 2020; Vettore MV et al., 2007). The remaining studies used probability sampling without reporting the extent of missingness, non-response rate, or any approaches for managing missingness and non-response despite that such limitations are often encountered in population-based studies using probability sampling (Akinkugbe AA et al., 2015; Alshihayb TS et al., 2020; Beck JD et al., 2006; Kingman A et al., 2008; Romano F et al., 2019; Susin C et al., 2005; Tran DT et al., 2014, 2016). For studies that used non-probability sampling, the use of consecutive recruitment would have been an appropriate approach based on the standards for reporting in diagnostic accuracy studies (Bossuyt PM et al., 2003). Studies that used non-probability and non-consecutive sampling methods were judged to have both potential risk of bias and applicability concerns. In addition, some studies restricted their samples to subjects with periodontitis (Chu Y & Ouyang X, 2015), untreated populations (Alawaji Y, Mostafa N, et al., 2022; Dowsett SA, Eckert GJ, et al., 2002b), or they excluded subjects with 14 to 23 remaining teeth (Chu Y & Ouyang X, 2015; Relvas M et al., 2014; Vettore MV et al., 2007) which can impact their external validity and were judged to have applicability concerns. Studies that did not have clear eligibility criteria or inappropriate exclusions were judged to have potential risk of bias or high risk of bias respectively. The overall risk of bias and the applicability concerns ranged from low to high. Studies with inappropriate gold standard for comparisons were excluded. Despite those studies used random sampling framework were judged to have superior designs (Shi L, 2007; Whiting PF et al., 2011), the fact that non-response rate and missingness of data were unreported can be concerning. Probability sampling does not guarantee having a representative sample since representativeness can depend on several aspects including sample size, degree of heterogeneity of underlying population, and degree of non-response (Shi L, 2007). Non-response rate around ≥30.0% may result in non-response bias; those who respond can be systematically different from respondents; consequently, investigation of non-response bias needed to be conducted (Bose J, 2002). Non-response bias could be considered as a selection bias (Lash TL & Rothman KJ, 2021b). Non-response rate reported by the U.S. CDC on NHANES 2013-2014 ranged from 20.1% to 67.4% based on different age cohorts (National Center for Health Statistics, 2014). Though, such potentially high rate of non-response were 114 not reported in studies that used NHANES data. Having a large-scale study may increase the probability of being representative of the underlying population but there might be a higher chance of having missing data. The fact that studies rarely report the percentage of missingness can be also concerning. Many included studies used non-probability samplings such as convenience and purposive sampling. In contrast to studies using probability sampling with issues with non-response that could bias some of the findings, using non-probability sampling frameworks can result in biased findings of all study populations; consequently, the external validity can be limited. In addition to the limited external validity that could result from selection bias, unreasonable exclusions or selection of study subjects based on having periodontitis can compromise the internal validity of these studies. Thus, within the context of evaluation of PRP performance, selection bias either compromised the external validity, internal validity, or both. Measurement errors of periodontal examinations: Overall intra-examiner agreements using intraclass correlation coefficients for CAL ranged from 0.72 to 0.99; intraclass correlation coefficients for PPD ranged from 0.60 to 0.99. Weighted kappa for CAL or PPD ranged from 0.76 to 0.87. The overall inter-examiner agreement for CAL and PPD ranged from 0.65 to 0.86 using Cohen’s Kappa. Clinical examinations were done by hygienists (Tran DT et al., 2014, 2016), dentists (Kingman A et al., 2008; Susin C et al., 2005), periodontists (Alawaji Y, Mostafa N, et al., 2022; Romano F et al., 2019), or unspecified examiners for the rest of the studies (Akinkugbe AA et al., 2015; Beck JD et al., 2006; Teixeira F et al., 2020). Studies either had a single examiner who conducted all clinical examinations (Akinkugbe AA et al., 2015; Alawaji Y, Mostafa N, et al., 2022; Beck JD et al., 2006; Chu Y & Ouyang X, 2015; Relvas M et al., 2014; Romano F et al., 2019), a single examiner conducted measurements for specific clinical parameter in each original survey: CAL or PPD (Dowsett SA, Eckert GJ, et al., 2002b), or multiple examiners ranging from 2 to 6 examiners (Alshihayb TS et al., 2020; Kingman A et al., 2008; Susin C et al., 2005; Tran DT et al., 2014, 2016; Vettore MV et al., 2007). Studies that used multiple examiners reported undergoing a period of training and calibration. A study that did not report the inter-examiner agreements of pooled clinical data from 3 surveys was judged to have an unclear risk of information bias (Dowsett SA, Eckert GJ, et al., 2002b). Studies that used multiple examiners had an overall lower measurement agreement compared with studies used single examiners; studies that had periodontists conducting clinical examinations reported the highest clinical measurement agreement where the intraclass correlation coefficients for both CAL and PPD were ≥90; these findings were consistent to what was previously reported (Hefti AF & Preshaw PM, 2012). Studies used multiple examiners may potentially added up their measurements’ errors: intra-examiner and inter-examiner measurement errors. The lowest reported intra-examiner measurement agreement was ≥0.60 calculated using intraclass correlation coefficient for mean PPD at 6 sites and were conducted by dental hygienists in NHANES 2009-2011 survey (Dye BA et al., 2014). However, the intraclass correlation coefficients for measurement of mean CAL at 6 sites were ≥0.80 by the same examiners. Considering that measurements of CAL are more relevant and reliable 115 indicators for population-based studies, overall judgment on information loss based on clinical examinations for all included studies appear to be within acceptable limits. Methodological heterogeneity: In addition to the heterogeneity in sampling, included studies had methodological differences including case definitions that used PPD and CAL or CAL alone; minimum number of sites with CAL was different or unclear; most of the studies restricted their inclusion to subjects with ≥6 teeth or had specific eligibility criteria ensuring having adequate number of teeth/sites per quadrant; operational definitions for exposures associated with periodontitis were defined differently between studies. Diabetes mellitus was either defined as present/absent (Akinkugbe AA et al., 2015; Alshihayb TS et al., 2020) or based on self-reported glycemic control (Alawaji Y, Mostafa N, et al., 2022). Obesity was defined as present/absent (Alawaji Y, Mostafa N, et al., 2022) or based on BMI (Akinkugbe AA et al., 2015; Alshihayb TS et al., 2020). Current smoking was defined as currently smoking any number of cigarettes daily (Alawaji Y, Mostafa N, et al., 2022) or smoking ≥100 cigarettes during the lifetime (Akinkugbe AA et al., 2015). The exposures associations with periodontitis were mainly self-reported without validation using objective measurements such as HbA1c for glycemic control. Although the judgment on measurements of exposures were not evaluated as part of QUADAS-2 tool, the limited number of studies had several concerns regarding the assessments of exposures. Furthermore, inherent limitations of using cross-sectional study designs can be added as potential concerns due to the lack of ascertainment of temporal sequence, direction of associations, or limited control over confounding. Compared with external validity, internal validity can be generally considered more important since internally valid studies might be scientifically generalizable especially when findings are proved to be consistent across different study populations (Elwood JM, 2013; Lash TL & Rothman KJ, 2021b; Nohr E & Olsen J, 2013; Rothman KJ et al., 2013). Although clinical measurements generally had minimum concerns, overall aspects that may compromised the review findings include issues in samplings and selection of study participants, deficient reporting of non-response and missingness proportion, lack of consistency in exposures measurement and operational definitions, and having an overall high methodological heterogeneity. 4.4.2 Periodontitis prevalence Overall importance on measuring periodontitis prevalence can include quantification of population periodontitis burden; consequent to quantification of population’s disease burden can be used to plan population-based strategies for different stakeholders; studying the exposures’ association with periodontitis; comparisons of periodontitis trends across different populations. Since periodontitis prevalence representativeness can be limited by time and place, a more powerful use of periodontitis prevalence can be the assessment of disease trend over time based on series of cross-sectional surveys; consequently, assessment of efficiency of population-based strategies can be evaluated. When the use of PRPs comes into play, the resulted information loss from estimating periodontitis 116 prevalence can have several consequences based on the several implications of such measure. Periodontitis prevalence was found to have the largest impact from using PRPs compared with other periodontitis outcomes; absolute bias ranged from |2.1|% to |26.1|%; sensitivity ranged from 27.9% to 97.7%; negative predictive values ranged from 0.6% to 96.9%. In general, interpretation of sensitivity and negative predictive values of ≥80.0% can indicate high accuracy; a value of ≥60.0% may indicate moderate accuracy; any value less than 60.0% can be unacceptable (Nelson DE et al., 2001). Interpretation of absolute bias, however, can be more subjective and it does not consider the specific population’s prevalence before judging the bias magnitude as previously discussed in Chapter III. The absolute bias, however, can be useful for comparisons since it is widely reported across different studies and for all population-based outcomes. Nevertheless, none of the comparison indicators for PRP performance is perfect and several indicators were used to judge the impact of PRP on periodontitis prevalence since it is the most impacted outcome when using PRP and studies’ findings drastically differed based on many factors. Specificity and positive predictive values were 100.0% for all PRPs because PRPs can only identify positive cases that were already identified using the FRP (Preisser JS et al., 2018). However, the specificity and positive predictive values can have different values when studies used different thresholds in case definitions for PRP and FRP as outlined in Appendix Table 27. The sensitivity for moderate-severe periodontitis were mainly above 80.0% for the following PRPs: RHM and full-mouth assessments at partial sites such as the (FM)MB-B-DL, (FM)MB-DL, (FM)MB-B-DB, (FM)MB-DB, and protocols using randomly selected site method (84 RSSM, 42 RSSM, and 36 RSSM) which can be considered to have high accuracy (Nelson DE et al., 2001). The negative predictive value varied considerably among different studies and ranged from as low as 0.6% to 97.7%, which highlights the fact that the accuracy of PRPs can be different based on the prevalence in specific populations (Tenny S & Hoffman M R, 2021). When the periodontitis threshold increased from moderate (CAL ≥4 mm) to severe (CAL ≥6 mm) the average sensitivity decreased to 70.1%, which is considered only moderately accurate (Nelson DE et al., 2001). The PRPs that resulted in sensitivity above 70.0% were the RHM, 84 RSSM, 42 RSSM, and full mouth assessments at partial sites such as (FM)MB-B-DL, (FM)MB-DL, (FM)MB-B-DB, and (FM)MB-DB. Thus, periodontitis severity and the periodontitis prevalence in the underlying population impacted the PRP performance. The minimum number of sites with CAL used in the included studies was either ≥1 or ≥2 sites. Based on a finding from meta-regression analysis, studies that used ≥2 CAL sites had a lower absolute bias for severe periodontitis compared with studies used ≥1 CAL site. This finding contradicts the results from individual studies where the absolute bias increased when using a minimum of ≥2 CAL sites (Agerholm DM & Ashley FP, 1996; Heaton B, Sharma P, et al., 2018; Teixeira F et al., 2020; Tran DT et al., 2014). The minimum number of sites with CAL finding from meta-regression might be spurious due to presence of unmeasured or residual confounding such as having an overall higher methodological quality in studies used ≥2 CAL sites as a minimum threshold compared to 117 those that used ≥1 CAL site. It is important to consider that the use of CAL measurements at ≥2 sites is generally preferable in order to preclude sites with CAL due to other etiologies such as having a single isolated PPD due to endodontic involvements, external root resorptions, or root fractures. In addition to the minimum sites with CAL, overall factors that may impact the PRP performance in estimating periodontitis prevalence include specific prevalence in study population, where studies with lower prevalence have lower absolute bias; PRP total sites range from 24 to 42 had higher absolute bias compared with PRP total sites range from 56 to 84; severe periodontitis prevalence had lower absolute bias than moderate-severe periodontitis threshold; full mouth at partial sites and RHM protocols had lower absolute bias compared with the half mouth at partial sites and index teeth protocols. When studies were analyzed based on their risk of bias, having a potential or high risk of bias resulted in a lower systematic error when estimating moderate-severe periodontitis prevalence compared with having low risk of bias. Studies that used the CDC/AAP definitions had lower overall sensitivity and higher absolute bias for estimating the prevalence using PRP as compared to studies that used same CAL thresholds of ³4 mm or ³6 mm (Akinkugbe AA et al., 2015; Alawaji Y, Mostafa N, et al., 2022; Alshihayb TS et al., 2020; Romano F et al., 2019; Tran DT et al., 2014). The lower sensitivity for studies used the CDC/AAP for estimating the prevalence using PRP might be explained by the difficulty in of applying such defining criteria; there is need to use minimally two to three sites with CAL and/or PPD at non-adjacent teeth which can be challenging due to the limited number of sites in PRPs. Tran et al. (Tran DT et al., 2014) and Heaton et al. (Heaton B, Sharma P, et al., 2018) tested the CDC/AAP definitions at different thresholds of minimum number of sites with CAL and/or PPD and found that sensitivity can increase up to 40.0% when using a minimum of one site with CAL. Despite that the review included wide age range: 13 to 103 years, only few studies reported comparisons based on different age groups. Impact of using PRPs on periodontitis prevalence was more pronounced in younger individuals compared with older individuals. Younger age group <35 years had a sensitivity ranged from 50.0% to 100.0%; older age group ≥35 years had a sensitivity ranged from 87.4% to 100.0% (Alawaji Y, Mostafa N, et al., 2022; Dowsett SA, Eckert GJ, et al., 2002b). Absolute bias in younger age group ranged from |2.3|% to |27.4|% while older age group had an absolute bias ranged from 0.0% to |18.9|% (Alawaji Y, Mostafa N, et al., 2022; Dowsett SA, Eckert GJ, et al., 2002b). Although age related comparisons based on wide age range were rarely reported, previous studies on young age groups (16-26 years) that did not meet our eligibility criteria had an absolute bias ranged from |7.0|% to |36.0|% (Eaton KA et al., 2001; Thomson WM & Williams SM, 2002). Thus, it can be interpreted that younger age group can have a drastic underestimation of periodontitis prevalence. However, due to having a limited number of studies with heterogenous methodologies, the factors that impact the performance of PRPs in young age group cannot be explored any further. 118 Considering the different uses of periodontitis prevalence, the information loss that may result when using of PRP can potentially impact the interpretation of disease burden in population-based studies, its use for planning of strategies, and the estimation of periodontitis exposures. Reports on periodontitis trends compared across different studies, different countries, or within a population but at different time points have been challenged by the methodological heterogeneity of these studies (Baelum V & Lopez R, 2021; Dye BA, 2012; Hugoson A & Norderyd, 2008). In this review, the methodological heterogeneity was observed despite the selection of studies based on some common criteria. If PRPs are used differently in population-based studies, they could add up to the existing methodological heterogeneity, consequently, creating further challenges in such comparisons. 4.4.3 Periodontitis severity and extent In general, the summarized absolute bias and its heterogeneity were low across different studies, PRPs, and CAL thresholds. The index teeth: Ramfjord teeth, and CPITN protocols overestimated the extent and severity of periodontitis and resulted in the highest absolute bias. The periodontitis extent at different thresholds appears to be skewed in all studies. Due to having relatively large sample sizes of all studies, logarithmic transformation of the individual patient data, to make the data follow a normal-like distribution at the logarithmic scale, may not be necessary (Deeks JJ et al., 2021; Higgins JP et al., 2008). Though, obtaining the individual patient data from adequate number of studies would have allowed us to analyze each PRP type individually to obtain valid compiled estimates. For periodontitis severity, few studies seem to have skewed data such as Relvas et al. and Kingman et al. (Kingman A et al., 2008; Relvas M et al., 2014). In contrast to the periodontitis prevalence and extent, the periodontitis severity had only small variations among heterogeneous study populations; thus, the validity of the severity as a population-based estimate seems to be questionable. A study on untreated population reported lower correlations in younger group (<35 years) for periodontitis extent estimated using PRPs compared with FRP and ranged from 0.00 to 1.00; older group (≥35 years) had intraclass correlation coefficient ranged from 0.76 to 0.98 (Dowsett SA, Eckert GJ, et al., 2002b). Another study compared subjects <35 years of age to an older group ≥35 years of age and found that the accuracy of estimating the prevalence of periodontitis was decreased in younger subjects, while the extent of periodontitis was underestimated or overestimated (Alawaji Y, Mostafa N, et al., 2022). The possibility of overestimating periodontitis extent using PRP in younger age group was also previously reported (Eaton KA et al., 2001). A study that evaluated the periodontitis extent and severity based on different age cohorts in an adult population had unclear pattern based on age; though, both periodontitis outcomes had negligible absolute bias (Tran DT et al., 2016). 119 4.4.4 Associations with periodontitis The three exposures summarized in this review were diabetes mellitus, obesity, and cigarette smoking. In general, the absolute bias ranged from -0.5 to 0.9; a finding that confirms the differential misclassification that results from using PRP on estimating exposures’ OR (Preisser JS et al., 2018). Though, this differential misclassification resulted in an overall trivial bias. Factors that may impact the direction and/or magnitude of bias in estimating periodontitis associations using PRPs may include the periodontitis severity threshold in case definitions where severe periodontitis had a lower systematic error (absolute or relative bias) compared with moderate to severe periodontitis threshold (Alawaji Y, Mostafa N, et al., 2022; Alshihayb TS et al., 2020). The unadjusted associations had slightly lower absolute bias compared with adjusted associations (Akinkugbe AA et al., 2015; Alawaji Y, Mostafa N, et al., 2022); thus, it can be inferred that the magnitude of bias in adjusted association may potentially change based on specific covariates included in multivariate models. In one study, the magnitude of systematic error and the size of association were inversely proportional (Alawaji Y, Mostafa N, et al., 2022) similar to findings from a simulation study (Heaton B, Garcia RI, et al., 2018). Though, based on findings by Akinkugbe et al., the systematic error and the size of associations seem to be directly proportional (Akinkugbe AA et al., 2015). An additional observation, similar to what we previously reported in chapter III, the estimated associations using different PRPs were confined within the 95% CI of the FRP OR. Therefore, the overall interpretation of associations with periodontitis did not seem to be altered by using PRP. Due to the small number of studies that evaluated the PRP performance in estimating periodontitis associations, we were unable to evaluate the impact of other factors such as PRP types and total PRP sites. 4.4.5 Limitations, implications, and future directions Review limitations: The majority of the studies used non-representative and non-randomly selected samples or randomly selected subjects without reporting the extent of the missing data and non-response. Some studies had unjustifiably strict eligibility criteria or selected the study subjects based on having periodontitis; thus, potentially limited their internal and external validity. The overall risk of bias ranged from low to high and the applicability concerns ranged from low to high. Studies had high overall methodological heterogeneity including lack of consistency in exposures measurement and use of operational definitions. Limited number of studies evaluated the performance of using PRPs on periodontitis associations and periodontitis outcomes on younger age groups, consequently, limited the analyses of factors that impact the PRP performance. The assessments of periodontitis trends over time might be challenged by using PRPs, though, the potential impact of using PRPs on the interpretation cannot be estimated based on included studies or current literature. Most of the studies in the literature compared the performance of PRPs to FRPs in terms of accuracy, validity and/or precision. However, there is no published evidence that compares the actual time, effort, and resources needed to conduct any of the PRPs compared to the 120 FRPs. Also, the feasibility of applying some of the PRPs, such as the RSSM at 36, 42, or 84 sites, can be challenging in surveillance studies and have not been tested clinically or in the field (Beck JD et al., 2006). In our review, we do not consider the pooled estimates for different PRPs in the meta-analyses valid because we do not assume that performance of different PRPs could be summarized as a single estimate. We compiled the estimates of different PRPs in order to compare the inherent methodological approaches, and to examine the factors that could impact the performance of PRPs. The pooled estimates from meta-analyses would have been valid if we analyzed each specific PRP separately. However, this approach was not possible due to the deficiency of the reported performance for specific PRP type in the literature. Studies that limited their assessment of periodontitis to measuring the PPD without assessment of CAL were excluded. The use of PPD is an unreliable indicator of periodontitis since it is measured from the gingival margin to the base of the pocket/or sulcus. The gingival margin can fluctuate; having a swelling can increase the measurement without reflecting an actual damage to the tissues (Armitage GC, 2004). Periodontal treatment may reduce the PPD, consequently, can be reversible indicator of the disease (Beltran-Aguilar ED et al., 2012; Leroy R et al., 2010). Measurements of mean PPD had poor reliability compared with mean CAL that had good reliability (Dye BA et al., 2014). Review implications and future directions: PRPs were investigated for their use for population-based studies and are not recommended for clinical use. Therefore, the findings may be relevant for research studies and population-based surveys. The use of PRPs mainly impacted the periodontitis prevalence and several factors may need to be considered before planning population-based surveys using PRPs. We investigated the methodological factors that may impact the performance of PRPs which may guide the selection of protocols in future studies. In addition, our review highlights some of the limitations in the literature and methodological considerations that need to be addressed. We reiterate the previous recommendations for the use of PRPs for population-based studies: Before conducting a national survey using a PRP, pilot studies should first be conducted in a subset sample of a specific population with adequate representation of subgroups (Holtfreter B et al., 2015; Kingman A et al., 2008). In these pilot studies, several accuracy measures should be used, as well as absolute bias and relative bias. If necessary, a correction factor for the PRP can be calculated to acquire valid estimates of disease prevalence in a specific population (Dye BA, 2012; Susin C et al., 2005). The use of CAL measurements at ≥1 interproximal sites to define the periodontitis prevalence increased the sensitivity and slightly decreased the specificity. However, the use of these measurements at ≥2 interproximal sites is preferable to exclude sites with CAL due to other etiologies, such as trauma from brushing or orthodontic treatments that may result in midbuccal or midlingual recessions, isolated sites with endodontic involvements, vertical root fractures, external root resorption, etc. 121 Objective measurements of medical conditions, such as an assessment of glycemic control using the most recent HbA1c is needed to confirm the associations with diabetes mellitus (Lind M et al., 2008). also, both adjusted and unadjusted effects of exposures should be presented in order to compare results of different studies. We suggest for future systematic review to obtain the individual patient data from different populations to properly analyze the systematic error using meta-regression model while controlling for clinical and methodological variations that we outlined in this review. It is important to consider that the evaluation of PRP performance is often done as a secondary analysis of data. Thus, the individual patient data can be obtained from any population-based study rather than being restricted to published studies that specifically evaluated the performance of PRPs. In conclusion, the use of PRPs resulted in the highest impact on estimating periodontitis prevalence; the degree of underestimation varied considerably. Several factors can impact the accuracy of PRPs and may need to be considered before conducting population-based studies, these including the type of PRP, total PRP sites, age of the population, underlying distribution of periodontitis, and severity threshold and use of a minimum number of sites with CAL in periodontitis case definitions. Based on our findings, the PRPs that had the best performance to assess periodontitis prevalence involved a full-mouth recordings at the following partial sites: MB-B-DL, MB-DL, MB-B-DB, MB-DB, 84 RSSM, and the RHM protocol. Studies that were judged to have potential to high risk of bias reported an overall lower systematic error for estimating the moderate-severe periodontitis prevalence. Overall, the PRPs estimated the periodontitis extent and severity with a relatively small bias. Estimations of associations with periodontitis had marginal bias and did not seem to alter the interpretation of these associations regardless of the PRP. However, this evidence was based on a small number of studies. 122 Chapter 5: Concluding remarks The thesis projects (Chapters 2, 3, and 4) found that despite the uniformly high levels of plaque in the study population, several other exposures were associated with untreated periodontitis including increased age (≥35 years), male sex, lower education, lower income, uncontrolled diabetes mellitus, obesity, lower perceived stress, and current cigarette smoking. When PRPs were evaluated for their use to study periodontitis in untreated individuals, (FM)MB-DL had the best performance compared with other protocols, especially in young individuals (13-34 years). In population-based studies, periodontitis prevalence was impacted the most by using PRPs, while periodontitis extent, its severity, and exposure associations with periodontitis had only marginal bias. PRPs that had the best performance in estimating periodontitis included full mouth at the following partial sites: MB-B-DL, MB-DL, MB-B-DB, MB-DB, 84 RSSM, and the RHM protocol. Factors that can impact the performance of PRPs include the selection of PRP (type and number of sites), periodontitis case definitions (severity thresholds selected to define periodontitis and a minimum number of CAL and PPD sites), subjects’ age, and prevalence of periodontitis in a population. Despite the use of wide age ranges in earlier studies focused on periodontal diseases (Baelum V, Fejerskov O, et al., 1988; Loe H, Boysen H, et al., 1978; Timmerman MF et al., 1998), most concurrent studies tend to separate younger from older individuals in reporting their results or even targeted the study population based on narrow age groups (Akinkugbe AA et al., 2015; Beck JD et al., 2006; Califano JV & American Academy of Periodontology, 2003; Goldberg P et al., 1985; Siukosaari P et al., 2012; Susin C et al., 2004, 2011; Thomson WM & Williams SM, 2002). Reporting the periodontitis findings based on narrow age precludes direct age-related comparisons. This age-related restriction may hamper the identification of age thresholds when the periodontitis occur, steeply increases and reaches its peak (in prevalence, severity, or extent), consequently making it difficult to plan periodontitis prevention at early stages; may masks the identification of some exposures if the study group lacks variations in periodontitis distribution or when saturated prevalence is reached (close to 100.0%); can make it challenging to compare the efficiency of methodological strategies, such as the use of PRPs, based on different age cohorts. It can be hypothesized that such an approach of separating study subjects based on age was influenced by having different periodontal diagnoses based on age over the last few decades (American Academy of Periodontology, 2015; Caton J, 1989; Lindhe J et al., 1999). However, the new classification system diagnoses periodontitis under one main category while age is considered in grading based on the patient’s risk profile (Tonetti MS et al., 2018). Unless the study’s aim justifies the need for a narrow age group, such approach could hamper the age-related comparisons by looking through a narrow lens at a time. In the projects I and II, the periodontitis prevalence was found to be high in the older age group (≥35 years) when using shallower thresholds of two different case definitions: CDC/AAP and AAP/EFP. Thus, if the study was restricted to the older age group or to shallower thresholds, it may have not been possible to identify any of the periodontitis-related exposures. 123 It has been reported in the literature that higher information loss can be expected when using PRPs in younger age groups compared with older groups (Papapanou P & Lindhe J, 2015). This was hypothesized based on a possibly higher periodontitis prevalence, its extent, and having a symmetrical distribution in older subjects compared with younger age groups. However, when the overall body of knowledge was evaluated based on actual studies that compared subjects based on age, studies either restricted their sample to narrow age groups (Akinkugbe et al., 2015; J. D. Beck et al., 2006; Eaton et al., 2001; Peres et al., 2012; Thomson & Williams, 2002), or wider age groups without performing any age-based comparisons (Kingman A et al., 2008; Romano F et al., 2019; Susin C et al., 2005). One study by Dowsett et al. provided direct age comparisons on wide age group had similar findings to our project II (Chapter 3) where RHM poorly performed in young age group (Dowsett SA, Eckert GJ, et al., 2002b). In contrast, we found that the (FM)MB-DL protocol had acceptable performance in such young group. These findings may indirectly indicate that the periodontitis distribution appear to non-symmetrical under 35 years. Therefore, it can be assumed that PRPs that consider all teeth at partial sites may be more suitable for such group rather than considering RHM protocol. However, these findings and assumptions need to be confirmed in future studies. Three main summaries of periodontitis that are currently recommended for population-based studies are prevalence, extent, and severity (Holtfreter B et al., 2015). Periodontitis severity is a summary of depth that is measured for individuals at 6 sites per tooth at a total of 28 teeth, then averaged for the whole population. Consequently, periodontitis severity undergoes about three levels of potential information loss before it is used for the population. For example, 10 sites that have CAL ≥7 mm in an individual can be averaged with another 158 sites that have CAL=0 mm then the mean severity becomes 0.42 mm. Thus, the severity estimate can already lose information even when used at an individual level, further loss of information can be expected when individual measures are averaged for the whole study population. In addition, such summary averages both diseased and non-diseased sites for diseased and non-diseased individuals then summarized as a single score. An illustration of how severity is measured and summarized for population is depicted in Figure 25. In our third project (Chapter 4), periodontitis severity summarized for different populations has demonstrated minor variations despite the heterogeneity of the studied populations which ranged from 0.92 to 2.90 mm. When considering some of the major issues that made the periodontal indices abandoned due to attenuation of variations when using mean index scores, discussed in chapter 1, it is unclear how the summary of periodontitis severity measure is doing any better. Another issue related to the summary of periodontitis severity is that it is averaged for a population without adjustment for clustering of sites or teeth at an individual or may be used as an average of an average; thus, it does not properly consider the multi-level nature of the data and the variations at different levels. Due to potential unit of analysis issues when using periodontitis severity, it might be wise to consider multilevel mixed effects models to study associations with periodontitis severity (Cho YI & Kim HY, 2015). Nevertheless, the periodontitis severity in terms of depth of 124 involvement is already incorporated in other summary measures, namely periodontitis prevalence and periodontitis extent which are defined at different severity thresholds. Figure 25. Illustration of multi-levels that are averaged in periodontitis severity as a single summary for the whole population. No adjustment is done for clustering at tooth-level or individual-level when severity is summarized for a population. CAL: Clinical Attachment Loss, PPD: Periodontal Probing Depth. *Figure of Human dental arches–upper and lower: © Kaligula, retrieved from Wikimedia.org and was used under the Creative Commons Attribution-Share Alike 3.0 Unported license. Periodontitis extent is another summary measure used in population-based studies to indicate the proportion of teeth or sites with periodontitis at the individual level, then averaged for a specific population (Holtfreter et al., 2015). Periodontitis extent presents some advantages over the summary of severity measure in terms of accounting for clustering of sites or teeth per individual and potentially avoiding too many levels of attenuation of the variations (Figure 26). However, the issue that is often encountered with the summary of periodontitis extent is its severe skewness. Skewness can occur when periodontitis extent is summarized for the population or when periodontitis extent is used for within-group comparisons. This issue with skewness was demonstrated in all our projects including the systematic review that summarized the extent and compared several populations (Chapters 2, 3, and 4). The standards for reporting population-based periodontitis summaries recommended reporting the periodontitis extent as a mean and its standard error (Holtfreter B et al., 2015). However, such approach was criticized since the standard deviation can provide a better indication regarding the level of skewness compared with standard error (Baelum V & Lopez R, 2021). Skewness of periodontitis extent can be particularly problematic when it is used in statistical analyses such as studying the associations with periodontitis or performing meta-analyses (Deeks JJ et al., 2021; Higgins JP et al., 2008). As previously mentioned in project III (Chapter 4), the skewness may be less of a problem when the sample size is large, however, no specific rule has been suggested for judging how large the 125 actual sample size should be (Deeks et al., 2021; Schmidt A & Finan C, 2018). In clinical case definitions, the periodontitis extent is classified into localized or generalized based on an arbitrary (non-scientifically based) 30.0% cut off (Highfield, 2009). This arbitrary cut-off, however, is rarely questioned or considered to be tested in the literature. Figure 26. Illustration for how periodontitis extent is measured and subsequently summarized for a population. CAL: Clinical Attachment Loss, PPD: Periodontal Probing Depth. *Figure of Human dental arches–upper and lower: © Kaligula, retrieved from Wikimedia.org and was used under the Creative Commons Attribution-Share Alike 3.0 Unported license. The third summary for periodontitis recommended for population-based studies and possibly the most important is the periodontitis prevalence (Holtfreter B et al., 2015). Prevalence can estimate the disease burden in a population, and it is the main summary that may have practical implications for clinicians, public health practitioners and policy makers. Prevalence should ideally be estimated in a representative sample of a specific population using probability sampling (Lash TL & Rothman KJ, 2021b, 2021a; Shi L, 2007). However, the representativeness of disease prevalence in a specific population is often bounded by the place where data is collected and the time of assessment. This means that a measure of periodontitis prevalence in 2019 in a representative Saudi Arabian sample will not be representative of individuals from another geographical area such as the United Arab Emirates, and the 2019 prevalence may or may not be a valid measure for the periodontitis prevalence representing the Saudi population in 2025. The probability sampling can be effective in studying the general population and common characteristics. However, the degree of how the probability sampling can obtain a representative sample may depends on the heterogeneity of the population and the sample size (Shi L, 2007). Probability sampling may become less effective in representing the minority groups (Kalsbeek WD, 2003). 126 Among different suggested strategies for sampling minority groups is a use of cluster sampling or stratified random sampling for the population with oversampling (over representation) of minority groups. However, this sampling approach can be difficult to achieve when total number of the minority group is too small, the proportion of the minority group to the whole population is unknown, the minority group is heterogenous, frequently travels from a place to another, or if the minority group is widely dispersed geographically. Thesis projects I and II (Chapters 2 and 3) focused on subjects with untreated periodontitis and recruitment of this minority population was targeted at a dental school clinic that is located close to residences of nomadic tribes. The fact that little has been known about the nomads or the descendants of nomadic tribes apart from anecdotal evidence made it nearly impossible to obtain a truly representative sample of this minority population. Additional problems making it difficult to study the nomadic tribes is keeping track of people who move too often (unstable living conditions), live in scattered geographical areas across the country, possibly difficulty in reaching this minority group since their residential areas are mostly concentrated in deserts or mountains. The use of purposive sampling and the recruitment of minority groups that are difficult to reach from health care centers has been suggested among the strategies for studying such population groups (Kalsbeek WD, 2003). Another possible sampling method that could help to recruit the minority groups is the use of snowballing sampling (Shi L, 2007). Snowballing sampling might be particularly helpful when recruiting the nomadic tribes where initially recruited subjects can help recruiting their peers from the same minority group. In addition, it was also suggested to combine different sampling methods to have better coverage of the minority groups (Kalsbeek WD, 2003). In epidemiological studies, there is often a trade-off between internal and external validity (Elwood JM, 2013). Studying the periodontitis burden as summarized using prevalence is best to be evaluated using a representative population-based sample. The representativeness can be better achieved when using probability samples, consequently, increase ability to generalize the study findings (external validity) to the underlying population. However, the representativeness can be undermined by the non-response bias since the non-responders can be systematically different from respondents, consequently leading to a selection bias (Bose J, 2002; Shi L, 2007). It has been suggested that bias can result when non-response reaches around 30.0% (Bose J, 2002). Unless some efforts are done to investigate the non-response, the non-response can threaten the study’s validity (Bose J, 2002; Shi L, 2007). The non-response in some population-based studies, including NHANES 2013-2014, ranged from 20.1% to 67.4% (Lorenzo SM et al., 2015; National Center for Health Statistics, 2014). Also, a probability sampling from a population often results in an inadequate representation of minority groups, unless the overrepresentation of subgroups was considered when planning a study (Kalsbeek WD, 2003). Representativeness of prevalence is bounded by place and time; thus, the representativeness of prevalence can be considered a historical concept that can no longer be representative over time (Nohr E & Olsen J, 2013; Rothman KJ et al., 2013). The external validity of a study also depends on the internal validity; an internally invalid study cannot be externally valid (Elwood JM, 2013; Lash TL & Rothman KJ, 2021b; Rothman KJ et al., 2013). Representativeness of the population often requires 127 large-scale studies; consequently, requires multiple examiners, excessive cost, and extended study time. Data missingness can often be an issue in large-scale studies which may decrease both the internal and external validity. Multiple examiners require training and standardization of their measurements, however, the inter-examiner agreements in clinical measurements are often lower than intra-examiner agreement which can impact the internal validity (Andrade R et al., 2012; Hefti AF & Preshaw PM, 2012; Rothman KJ & Lash TL, 2021). In addition, clinical periodontal assessments in large scale studies are often performed by non-specialists which can potentially increase the measurement errors and misclassifications of cases at lower disease thresholds (Beltran-Aguilar ED et al., 2012; Tonetti MS et al., 2018). Besides the fact that compromised internal validity of the study may not have external validity, having a high internal validity can be scientifically generalizable even when the sample is not representative (Elwood JM, 2013; Lash TL & Rothman KJ, 2021b). The meaning of scientific generalizability was described by Hans Reichenbach as follows: As an example of having a high internal validity in non-representative sample is the conduct of high quality randomized controlled trials that often recruit non-probability samples while results of these trials can be scientifically generalizable (Elwood JM, 2013). The scientific generalizability of high quality randomized controlled clinical trials can therefore depend on our understanding or judging what is relevant and what is irrelevant; considering the relevant elements when designing the trial can increase the scientific generalizability. Examples of important elements that may increase the scientific generalizability of clinical trials include recruitment of study subjects from primary care centers rather than secondary or tertiary care centers, considering different rates of susceptibility to disease in study participants, and considering different stages of the natural course of the disease (Rothwell PM, 2005). Although the clinical trial study design is irrelevant to this thesis projects, it was mentioned here to demonstrate a more concrete example of the importance of internal validity which is a prerequisite to scientific generalizability. “The essence of knowledge is generalisation. That rubbing wood in a certain way can produce fire is a knowledge derived by generalisation from individual experiences; the statement means that rubbing wood in this way will always produce fire. The art of discovery is therefore the art of correct generalization. What is irrelevant, such as the particular shape or size of the piece of wood used, is to be excluded from generalization; what is relevant, for example, the dryness of the wood, is to be included in it. The meaning of the term relevant can thus be defined: that is relevant which must be mentioned for the generalisation to be valid. The separation of relevant from irrelevant factors is the beginning of knowledge.” (Reichenbach H, 1951) 128 A distinction can therefore be made between the statistical inference and scientific inference as described by Kenneth J. Rothman et al. “It is true that statistical inference, the process of inferring from a sample to the source from which it was drawn, is greatly aided by having a representative sample. The mistake is to think that statistical inference is the same as scientific inference. Science works on the assumption that the laws of nature are constant, but if we conflate statistical inference with scientific inference we get the reverse principle, in which the results of a study are applicable only in circumstances just like those of the study itself, and applicable only to people who are just like those in the study population” (Rothman KJ et al., 2013). Thus, studies that use probability samples are not always superior to studies which include non-probability samples. The applicability of study findings may depend on the degree of internal validity and the ability to distinguish between what is relevant and irrelevant when drawing conclusions about the study findings that can be generalized beyond the study population. In spite of the tendency to define periodontitis prevalence using different thresholds across studies, most of the periodontitis case definitions used certain severity thresholds at a minimum of 2 sites or teeth (Eke PI et al., 2012; Page RC & Eke PI, 2007; Tonetti MS et al., 2005; van der Velden U, 2000). A possible limitation of using such case definitions is depicted in Figure 27 where one could see that different number of teeth with periodontitis can be diagnosed equally. Thus, reporting only periodontitis prevalence can be limited and possibly needs to be complemented by reporting the periodontitis extent in studies; periodontitis prevalence identifies the proportion of individuals with the disease while the extent identifies the mean proportion of sites or teeth with periodontitis However, the recommended CDC/AAP definitions for periodontitis prevalence use the following severity thresholds: CAL ≥4 mm or CAL ≥6 mm, whereas recommended severity thresholds for extent were CAL ≥3 mm or CAL ≥5 mm (Holtfreter B et al., 2015). Considering that the two population-based measures (prevalence and extent) complement each other, it would have been prudent to define the disease thresholds similarly for both. Figure 27. Illustration of different number of sites or teeth with periodontitis that are diagnosed similarly based on periodontitis case definition for periodontitis prevalence: Clinical attachment loss (CAL) at specific severity threshold in ≥2 non-adjacent teeth or sites. *Figure of Human dental arches–upper and lower: © Kaligula, retrieved from Wikimedia.org and was used under the Creative Commons Attribution-Share Alike 3.0 Unported license. 129 When the impact of using PRPs was evaluated in the thesis projects II and III (Chapters 3 and 4), estimates of the continuous outcomes such as periodontitis extent or and severity had smaller bias compared with bias for the periodontitis prevalence, which is a dichotomous outcome. Despite that the impact of using PRPs on the prevalence was the largest, the corresponding impact on associations with periodontitis, based on limited evidence, was only marginal. Most of the bias that resulted from PRPs on estimating associations was within the 95% CI of FRPs; thus, the use of PRPs did not seem to alter the interpretation of these associations. Estimation of exposures’ findings from studies included in the systematic review (Chapter 4) were similar to the findings from some excluded studies (excluded due to their use of different case definitions based on PPD alone or using FRP based on partial sites) (Peres MA et al., 2012; Thomson WM & Williams SM, 2002). Among the challenges that could arise when using PRPs for estimating periodontitis prevalence: PRPs could potentially make the time trend comparisons more difficult, and comparisons among different populations might be compromised if different PRPs are used (Baelum V & Lopez R, 2021). However, the PRPs impact on studying time trends, based on the current literature, is still unknown. Feasibility of using some PRPs needs to be evaluated clinically before they can be used in the field since their use might be challenging to apply such as random selection of different number of sites protocols (Beck JD et al., 2006; Preisser JS et al., 2017). Since surveillance of periodontitis requires continuous monitoring, several reasons could make the evaluation of time trend in periodontitis challenging. Unless the raw data is used to define then redefine periodontitis cases to accommodate the continuous evolvements of case definitions, time trend may otherwise be hampered by evolvements of case definitions (Baelum V & Lopez R, 2021). In addition, the use of PRPs may lead to different estimations of periodontitis prevalence (projects II and III: chapters 3 and 4), consequently, changes over time would be difficult to interpret given different degrees of misclassifications. Periodontal indices such as the CPITN, continue to be widely used, had several updated versions but did not overcome all previous limitations (Baelum V & Lopez R, 2013). Thus, on top of the challenges in assessment of periodontitis time trends due the continuous evolvements of case definitions and approaches, the CPITN use can be additionally limited due to relying on reversible parameters (PPD and bleeding on probing), and the use of PRP for assessing CAL (World Health Organization, 1977, 1997, 2013). An additional limiting factor for time trend monitoring of periodontitis can be a possible survivorship bias which may result when periodontitis prevalence is estimated in those who have teeth without considering the ones with tooth loss. This can be a potential problem, especially when considering that clinicians may extract periodontally involved teeth at relatively early stage in their natural course of disease to replace them with implants. The prevalence of dental implants in the U.S. has increased from 0.7% in 1999 to 5.7% in 2016; the projected increase in 2026 can be up to 23.0% (Elani HW et al., 2018). Thus, more efforts are needed to inquire about the reasons behind the tooth loss and consider tooth loss when interpreting the decline of periodontitis prevalence. Any assessment of the global trend of periodontitis can also be challenged by adding up all the previously mentioned challenges in monitoring periodontitis trends unless groups of countries are compared 130 separately based on some shared methodologies (Dye BA, 2012). Another approach that can be used when evaluating the periodontitis trends globally can be by obtaining the raw data of individual studies; such approach can overcome some methodological heterogeneity including periodontitis case definitions. However, it is unlikely that obtaining raw data would resolve the methodological heterogeneity if the study relied on using PRPs or specific approaches such as using the modified CPI. Besides the importance of using the periodontitis prevalence in estimating the disease burden and for planning population-based strategies, it is possibly the most suitable to be used for estimating the exposures’ associations with periodontitis. In our first project (Chapter 2), two case definitions were used the CDC/AAP (Eke PI et al., 2012; Page RC & Eke PI, 2007) and the AAP/EFP (Tonetti MS et al., 2018)) and it was demonstrated that using different periodontitis definitions at different disease thresholds could result in different significance levels of associations. This issue was previously discussed in the literature and highlights the need for universally used case definitions, especially when identifying the exposures associated with periodontitis (Manau C et al., 2008; Preshaw PM, 2009). Up to date, there is no universally accepted definition for periodontitis and the definitions proposed by the CDC/AAP were recommended for epidemiological studies for the time being (Holtfreter B et al., 2015). However, having different case definitions and disease thresholds for clinical use and epidemiological use will continue to present issues in identifying the exposures differently in clinical versus epidemiological research; unless the standards for reporting also consider that clinical and epidemiolocal case definitions should be similar. The use of the CDC/AAP definitions for epidemiological studies can offer the advantage of allowing comparisons across multiple studies since their definitions have been the most widely used (Eke PI et al., 2012; Page RC & Eke PI, 2007). However, among potential issues of these definitions can be the potential heterogeneity of the moderate periodontitis category beside having unclear practical implications of such definitions. Moderate category can potentially include lower thresholds of disease based on PPD ≥5 mm that could correspond to CAL ≥3 mm or could have high thresholds of CAL ≥5 mm (but without having the required PPD ≥5 mm). Due to this reason, in our three projects (Chapters II, III and IV) we combined the moderate and severe categories and presented them as total cases. In comparison, authors of the CDC/AAP definitions separated the severe periodontitis category from the non-severe category (combining mild and moderate cases), to report about periodontitis prevalence or analyze the exposures associated with periodontitis (Eke PI et al., 2015, 2016, 2018, 2020). Such approach of presenting the associations with non-severe categories and total periodontitis category could be a better method of reporting the prevalence and its associations, however, this was not suggested when they proposed these case definitions (Eke PI et al., 2012; Page RC & Eke PI, 2007). When the CDC/AAP definitions were evaluated for estimating periodontitis prevalence using PRPs in our systematic review, the overall accuracy was lower than using other case definitions (Chapter 4). This can be due to the need for a minimum of 2 to 3 sites with specific criteria for CAL and/or PPD while PRPs measure reduced number of teeth or sites. 131 Unlike most of other periodontitis definitions, the AAP/EFP definitions explicitly stated the practical implications of periodontitis staging and grading definitions (Tonetti MS et al., 2018). The AAP/EFP has also uniquely adopted the stages of the natural course of periodontitis, though, mainly focused on the latest stages. Some possible limitations of the AAP/EFP definitions can include the complexity of case definitions, having too many categories, and their unclear use for epidemiological studies. The practical implications of stages I and II are similar, though, they are categorized as two separate categories rather than being combined. Periodontitis grading may not be suitable for defining periodontitis in epidemiological studies since it is based on the rate of progression and then modified by two risk factors: smoking status and diabetes. The fact that grading inherently incorporates some risk factors (smoking and diabetes) means that it possibly cannot be used as a dependent variable to study the associations with periodontitis. Furthermore, considering two periodontitis exposures only in the classification can be limited since other periodontitis exposures can have important practical implications in patient management. Grading also requires radiographic assessment in order to assign the rate of progression, but the radiographic assessments are not routinely collected in population-based studies. Evolvements in understanding of the natural history of disease have formed the basis for preventive efforts, contributed to clinical practice, and possibly facilitated the directions of research interests. In general, periodontal treatment can be considered as a preventive measure to minimize tooth loss or loss of masticatory function. However, when different levels of disease prevention are translated to the context of periodontitis, the periodontal research, diagnosis, prevention, and treatment are mainly focused on late stages along the natural course (Kisling LA & das JM, 2022; The Association of Faculties of Medicine of Canada, 2018). Consequently, both primordial and primary prevention levels tend to be out of focus including the prevention of exposures before development of the disease. A recent review evaluating the prevention of periodontitis has also concluded that until nowadays, the actions taken to prevent periodontitis are mostly focused on individuals based on their management by clinicians (Janakiram C & Dye BA, 2020). Undertaking primordial population-based prevention entails the need to understand more about the underlying exposures linking individual-level exposures to the society (Bouchard P et al., 2017). Primordial prevention targets the whole population, and it needs to be applied at the earliest point prior to the development of disease-related exposures (Kisling LA & das JM, 2022; The Association of Faculties of Medicine of Canada, 2018). Primary prevention targets individuals or populations with a previously known exposures/risks for having periodontitis. Since both primordial and primary preventions are done prior to the development of the disease, prevention of periodontitis needs to focus on younger age groups (possibly during adolescence). Some recent recommendations have been suggested for “primary prevention” for periodontitis, though, were mainly based on clinical practice of professionals and are relevant to individual patient care rather than populations (Preshaw PM, 2015; Tonetti MS et al., 2015). 132 Underlying exposures commonly reported in periodontal literature include race/ethnicity, education, and income. Limiting the reporting of these underlying exposures without attempts to contextualize their possible associations with periodontitis in a broader context have been criticized (Baelum V & Lopez R, 2004; Borrell L et al., 2002; Borrell L & Crawford N, 2012; Borrell LN & Crawford ND, 2008; Borrell LN & Papapanou PN, 2005; Lopez R & Baelum V, 2012). Some ethnicities associations with periodontitis have been reported in the U.S. and these associations have been consistent over decades based on NHANES studies; African Americans have the highest prevalence of periodontitis followed by Latin Americans when compared with Caucasians (Borrell L et al., 2002; Borrell L & Crawford N, 2012; Borrell LN & Crawford ND, 2008; Borrell LN & Papapanou PN, 2005; Eke PI et al., 2016). Ethnicities associations with periodontitis or with other health outcomes have been conceptually explained by having ethnic-based disparities in education, income, experience of racism, residential segregation, as well as behavioral differences (Borrell L et al., 2002; Borrell L & Crawford N, 2012; Borrell LN & Crawford ND, 2008; Zambrana RE & Carter-Pokras O, 2010). Thus, ethnicity can be considered as a social construct and it has been suggested that presenting disparities in health outcomes based on ethnicities can be more informative when details are provided regarding their social determinants including education, employment, housing/neighborhoods, and poverty (Borrell L et al., 2002; Borrell L & Crawford N, 2012; Zambrana RE & Carter-Pokras O, 2010). Other commonly reported underlying exposures in periodontal literature include education and income; similar arguments have been made as to the study of studying ethnicity, that is, there is need to provide further details and conceptualize how socioeconomic differences lead to disparities in susceptibility to periodontitis. For example, having higher education and income can be associated with having better living conditions (housings and neighbourhood), broader social networks, health insurance, and better access to professional health care, and consequently leading to better health outcomes (Boillot A et al., 2011; Braveman P et al., 2011; Braveman P & Gottler L, 2014; Dahlan R et al., 2019). In our study population (project I and II: chapters 2 and 3), the ethnicity had no variation, however, disparities in having periodontitis were observed based on education and household income. Despite that the overall socioeconomic status of study population is considered low compared with that of general population, the study population had different occupations and living conditions; some of them had recently settled and living in housings whereas others continue to travel from a place to another and could be living in tents. Having unstable lifestyle and continuous traveling may in part explain the continuous interruptions of their education, inability to obtain higher profile jobs, health insurance, and regular access to dental care; consequently, making it less likely to improve their periodontal health. Access to dental care can be a complex concept since many attributes could impact the actual utilization of dental care and cannot be solely predicted by socioeconomic status (Aday LA & Andersen RM, 1981; Andersen RM, 1995; Institute of Medicine (US) Committee on Monitoring Access to Personal Health Care Services, 1993; McKernan S et al., 2020; Saurman E, 2016). In our projects: I and II (Chapters 2 and 3), despite that dental care is 133 offered in a public dental school clinics at no cost, nearly half of the visitors demanded having symptomatic treatment only; indicating that almost half of the study population were missing the perceived need and motivation for care. Since our sample was limited to individuals who lack history of periodontal treatment, it was not possible to study the associations between barriers to access dental care and the utilization of periodontal care. However, self-reported barriers to access regular dental care included lack of affordability, transportation, trust in dentists, availability of appointments at other public dental centers, and dental anxiety. Lack of awareness can be also added as a barrier since many of those who rated their oral self-care and periodontal health as good to excellent had high levels of plaque and periodontitis. It is expected that the reasons behind lack of access to regular dental care in our study population are still ambiguous and further investigation of the possible barriers relevant to the population’s backgrounds are still needed. Although stress has been reported to be associated with periodontitis (da Silva AM et al., 1995; Genco RJ et al., 1999), there seems to be some missing links related to this association. Some studies suggested that socioeconomic status may contribute to stressful conditions, consequently, may adversely impact periodontal health (Borrell L et al., 2002; Borrell L & Crawford N, 2012; van der Velden U et al., 2006). Another suggestion was that stress can indirectly influence some health-related behaviors such as lack of oral self-care and increase smoking, thus, increasing the susceptibility to periodontitis (da Silva AM et al., 1995; Deinzer R et al., 2001; Genco RJ et al., 1998). Although some studies adjusted for smoking status when testing the association between stress and periodontitis, no adjustment for oral self-care was considered (Genco RJ et al., 1999; Merchant AT et al., 2003). In our first project (Chapter 2), we inquired about the impact of stress on oral self-care and smoking by asking yes/no questions. Although nearly half of the study subjects reported stop brushing in stressful days, this information may not be useful since the study population had uniformly high levels of plaque. Accordingly, it can be assumed that such questions that inquire about oral self-care can lead to misleading findings possibly due to social desirability bias, that is, individuals may report practicing regular oral self-care because they know it is a socially desirable answer instead of reporting the actual behavior (lack of oral self-care). Furthermore, some of the individuals who answered “no” to the question, about stop brushing in stressful days, stated that it does not apply because they do not brush their teeth at all. In addition, only a small proportion of those who smoke reported to increase smoking frequency in stressful days. On the other hand, it has been suggested before that social support could be a moderator that may buffer the effect of stress (Merchant AT et al., 2003; Zimet GD et al., 1988); considering having an overall high perceived social support in our sample, this assumption will be considered to be tested in future. It has been previously suggested that low social support can be associated with periodontitis (Bouchard P et al., 2017). Some of social factors that were assessed for their association with periodontitis in NHANES 2001-2004 included social network (indicated by number of friends and marital status) and social support (indicated by the need for emotional support during the last year) (Sabbah W et al., 2011). This study found that being widowed and 134 having lowest number of friends was associated with higher periodontitis extent. Another study found lower susceptibility to periodontitis in men with at least one friend and in those who participated in religious meetings (Merchant AT et al., 2003). Also, a systematic review found that social support was positively associated with improved oral behaviors, higher oral health literacy, and increased utilization of dental care among immigrants and ethnic minorities (Dahlan R et al., 2019). In our projects I and II (Chapter 2 and 3), despite that our study groups had an overall high social support, it did not seem be associated with a lower periodontitis prevalence, an improved oral self-care, or an increased utilization of dental care. A possibly conceptually relevant construct that was needed to be considered in our study subjects is the subjective norms; having high social support may not be associated with lower periodontitis or improved oral health behaviors in an individual if everyone in the social network has poor oral health behaviors and perceive such behaviors as normal. In addition, these findings may highlight the importance of community level interventions since interventions at the individual level could be less effective if all members of these social networks have poor oral health behaviors. Despite that most of the periodontitis exposures can have practical implications for different stakeholders, recommendations based on too many exposures related to one disease such as periodontitis can be exhaustive and impractical. Therefore, the common risk factor approach to prevent several chronic diseases has been suggested as a helpful approach since it targets simultaneously risk factors/indicators of several chronic diseases such as cardiovascular diseases, diabetes mellitus, respiratory diseases, and obesity when planning population-based strategies (Janakiram C & Dye BA, 2020; Sheiham A & Watt RG, 2000). Common risk factors of chronic diseases may include tobacco consumption, unhealthy diet, sedentary lifestyle, lack of glycemic control, and psychological stress. The common risk factor approach might also be more manageable at the population level rather than suggesting preventive approaches that are disease specific. This can be especially true when considering that periodontitis is not a life-threatening disease and may not be perceived as a priority to be targeted by policymakers compared with other chronic diseases such as cardiovascular diseases. In addition, by using the common risk factor approach, duplication of efforts in combatting diseases can be avoided (Sheiham A & Watt RG, 2000). Another approach that is possibly needed is to integrate dental patient care with medical care providers. Dentists frequently refer their patients to physicians for medical care, but more help is probably required from medical care providers to advice their patients to see the dentists especially when they have diabetes mellitus that is an established risk factor for periodontitis. In project I (Chapter 2), most of the patients reported that they frequently visited the medical care centers (mainly primary care centers), but they lacked dental care beyond symptomatic treatments. Possible explanations for prioritizing medical care visits may include patients perceiving medical care as more important than dental care or due to having dental anxiety that prevent them from seeking dental care. 135 Since the overall practical implications of epidemiological research are currently heavily relying on clinical patient management, it is unclear why periodontitis is defined differently in clinical classifications and research studies. In a previous report that discussed the desirable characteristics of a classification system, it was suggested that all population members should be classifiable; for example, people can be classified for their need for prevention or treatment (Lopez R & Baelum V, 2012). It can be argued, however, that in the case of periodontitis, both prevention and treatment can be considered different levels of preventions along the natural course of disease (Kisling L & Das J, 2022; The Association of Faculties of Medicine of Canada, 2018). As previously stated, “At the end of the day, the purpose of all our activities, whether in research, public health, or clinical practice, is to be able to control disease” (Lopez R & Baelum V, 2012). Thus, using a classification that incorporates early stages of disease as well as its late stages that require clinical patient management may help to integrate both clinical and epidemiological case definitions based on different levels of prevention. Such approach may also reduce the complexity of the current clinical classification system (Tonetti MS et al., 2018). The exposures can be incorporated into all disease stages rather than being separately classified using grading framework since management of exposures/risk factors and prevention of further disease progression are needed at all stages of the disease. A suggestion for framework for defining periodontitis while integrating the clinical and epidemiological use and considering the initial phases of the disease is depicted in Table 22. In the suggested classification framework that is modified from the AAP/EFP staging (Tonetti MS et al., 2018), the “underlying exposure stage” is the first stage in which all members of the population that did not develop periodontitis or do not have any of the disease specific exposures/risk factors can be classified. Underlying exposures, in contrast to disease specific exposures, refer to the non-medical causes of the disease including the social determinants of health. Examples of underlying exposures may include having low income or low perceived social support. The following stage is “stage 0” where an individual or group of individuals have developed periodontitis-related exposures such as smoking, diabetes, or obesity. Stage I and II are combined since the practical implications are similar. Stage III is mainly based on CAL ≥5 mm or having indication for surgical periodontal treatment such as PPD ≥6 mm, osseous defects (vertical bone loss, craters), class II or III furcation involvements. Stage IV is considered the terminal stage along the natural course of the periodontitis; it is mainly diagnosed based on signs of loss of functional periodontal stability including excessive tooth mobility, drifting, loss of masticatory function, and presence of multiple teeth loss due to periodontitis (≥5 missing teeth). This diagnostic framework could assume that diagnosing an individual to a particular stage means that the individual has developed the features described in previous stages; a stage I periodontitis means that the individual has specific underlying exposures and periodontitis related exposures. Similarly, diagnosing an individual at a terminal stage (stage IV) means that the individual has specific underlying and periodontitis related exposures, CAL ≥5 mm, possible need for periodontal surgery, as well as the signs of loss of functional periodontal stability. 136 Table 22. Suggested diagnostic framework for integrated use in epidemiological research and clinical practice/research. Adapted from the AAP/EFP staging by including early phases of the natural course of disease along with different levels of prevention. Susceptibility Stages (Pre-periodontitis) Periodontitis Stages Stage of underlying exposures Stage 0 (Periodontitis risk factors/exposures) Stage I + II periodontitis Stage III periodontitis Stage IV periodontitis (Terminal stage) Staging • Underlying exposures e.g., male sex, low socioeconomic status, barriers to access dental care: accessibility (transportation), lack of accommodation: (dental appointments), lack of affordability, personal barriers (dental anxiety, lack of trust in dentists), and low perceived social support • Underlying exposures • Periodontitis exposures/risk factors e.g., smoking, lack of glycemic control, other chronic medical conditions, and stress disorders. • Underlying exposures • Periodontitis exposures/risk factors • CAL: 1-4 mm • Underlying exposures • Periodontitis exposures/risk factors • CAL: ≥5 mm • Indications for periodontal surgery: PPD ≥6 mm, osseous defects (Vertical bone loss, craters), class II, or III furcation involvements. • Underlying exposures • Periodontitis exposures/risk factors • CAL: ≥5 mm • Indications for periodontal surgery: (PPD ≥6 mm, osseous defects (Vertical bone loss, craters), class II, or III furcation involvements. • Loss of masticatory functional stability, excessive teeth mobility, drifting, and teeth loss due to periodontitis (≥5 teeth). Aims of prevention Reducing underlying exposures of disease. Preventing the development of periodontitis risk factors/exposures (Population-based approach of prevention) Reducing underlying and periodontitis risk factors/exposures, Preventing periodontitis incidence (High-risk approach of prevention) Reducing underlying and periodontitis risk factors/exposures. Preventing disease progression Reducing underlying and periodontitis risk factors/exposures. Preventing disease progression and complications Reducing underlying and periodontitis risk factors/exposures. Preventing further disease deteriorations Stakeholders Mainly policy makers and governments Mainly public health professionals but also includes Dentists/hygienists, integrated care with Periodontists and integrated with Periodontists, other dental specialities, 137 Susceptibility Stages (Pre-periodontitis) Periodontitis Stages Stage of underlying exposures Stage 0 (Periodontitis risk factors/exposures) Stage I + II periodontitis Stage III periodontitis Stage IV periodontitis (Terminal stage) dentists/hygienists and medical professionals medical professionals medical professionals and integrated with medical professionals Prevention strategies Population-based strategies for prevention using common risk factors approach for combatting chronic diseases such as imposing sin tax on tobacco and added sugar containing products, applying strategies for enforcing education for all population, awareness campaigns regarding oral health and general health, facilitating dental insurance for individuals with low socioeconomic status, and increase dental care clinics at rural and underserved areas. Increasing awareness campaigns for promoting periodontal health and general health for combatting chronic diseases in susceptible individuals/population groups using common risk factor approach for chronic diseases including advocating for healthy diet, regular dental visits, regular medical visits, smoking cessations, increase physical activity, and glycemic control by regularly taking medications, management of anxiety/stress reduction protocols, prophylaxis (removal of plaque, and calculus) by dental care provider. Applying common risk factor approach for chronic diseases for patients including advocating for healthy diet, regular dental visits, regular medical visits, smoking cessations, increase physical activity, and glycemic control by regularly taking medications, management of anxiety/stress reduction protocols, promotion of oral-self-care, and prophylaxis (removal of plaque, and calculus) by dental care provider. Applying common risk factor approach for chronic diseases for patients including advocating for healthy diet, regular dental visits, regular medical visits, smoking cessations, increase physical activity, and glycemic control by regularly taking medications, management of anxiety/stress reduction protocols, promotion of oral-self-care, prophylaxis (removal of plaque, and calculus) by dental care provider, and surgical periodontal treatment. Applying common risk factor approach for chronic diseases for patients including advocating for healthy diet, regular dental visits, regular medical visits, smoking cessations, increase physical activity, and glycemic control by regularly taking medications, management of anxiety/stress reduction protocols, promotion of oral-self-care, prophylaxis (removal of plaque, and calculus) by dental care provider, surgical periodontal treatment, and multidisciplinary functional rehabilitation *Periodontitis risk factors/exposures are the ones expected to have more direct biological links with periodontitis such as diabetes mellitus and smoking, while underlying exposures are the upstream exposures that can be the non-medical causes that can be indirectly associated with the disease thought complex pathways including the low socioeconomic status and low social support. CAL: Clinical Attachment Loss, PPD: Periodontal Probing Depth. Possible strengths of the suggested framework: 1. Less complex diagnostic criteria can potentially allow using the framework for both clinical and epidemiological use. Therefore, could potentially increase the knowledge translation from epidemiological research into clinical practice/research and vice versa. 2. Could potentially motivates the investigation of several underlying and periodontitis related exposures at a patient level (for clinicians) or at a population level (epidemiological use). Thus, management of different 138 exposures can be addressed by several stakeholders at all stages rather than being individually graded (using AAP/EFP classification). For example, management of patient’s risk profile using limited risk factors without considering underlying exposures such as dental anxiety and lack of awareness will less likely address possible barriers to access regular dental care. Lack of addressing these underlying exposures could also lead to loss to follow-up and lack of maintenance, consequently, failure of periodontal treatment outcomes. 3. Periodontal therapy can be generally considered preventive from tooth loss and loss of masticatory function. Therefore, using several levels of prevention along the natural course of disease can be suitable framework for diagnosing patients and defining periodontitis while having a clear picture regarding the practical implications based on the different levels of prevention (Kisling LA & das JM, 2022; The Association of Faculties of Medicine of Canada, 2018). 4. The common risk factor approach can be applied at different levels simultaneously. For example, imposing sin tax for tobacco containing products can be a primordial level of prevention and smoking cessation counseling can be done for those who are smokers either before or after development of the adverse health outcomes. Possible limitations of the suggested framework: 1. Gingivitis was not included in this framework despite that gingivitis precedes periodontitis. Gingivitis was eliminated for simplicity reason since gingivitis to some degree tends to be a universal finding, that is, a pristine gingival health may not exist even in subjects with optimal oral self-care (Chapple IL et al., 2018; Karayiannis A et al., 1992; Lang NP et al., 1991; Lang NP & Bartold PM, 2018). When the AAP/EFP defined gingivitis cases, they used a threshold of ≥10.0% of bleeding on probing; assuming that a <10.0% of gingival bleeding represents gingival health (Trombelli L et al., 2018). In addition, gingivitis does not always lead to periodontitis since it can be reversible or self-limited. However, periodontitis staging is assigned with a purpose of being irreversible; once staging is assigned to an individual and depending on the progression of the disease, it can only be upgraded. 2. Plaque was not included as an exposure since presence of plaque per se is a universal finding that needs to be controlled in all members of the population, though, levels of plaque can be different. Findings from study subjects with optimal oral self-care and undergoing frequent supportive periodontal therapy indicated the presence of plaque despite application of stringent plaque control strategies (Axelsson P et al., 2004; Ramfjord SP et al., 1982; Rosling B et al., 1976; Sreenivasan PK et al., 2016). Plaque control approaches generally aim for reducing plaque scores rather than expecting the elimination of plaque. Full mouth plaque scores up to 25.0% may indicate an acceptable level of plaque control (Axelsson P et al., 2004; Rosling B et al., 1976). However, it has been suggested that full mouth plaque scores of ≥40.0% can be considered “tolerable” among 139 patients undergoing supportive periodontal therapy (Lang NP & Tonetti MS, 2003). Another limitation of considering plaque is that such exposure within the diagnostic framework can be a reversible condition, consequently, it is not suitable for periodontitis staging. In contrast to plaque, other modifiable exposures may not be completely reversible. For example, being diagnosed with diabetes mellitus can be modified by achieving glycemic control. However, once the diagnosis of diabetes mellitus is established, it may not be reversed. Another example is smoking where those who quit smoking can still have higher probability of periodontitis compared with never-smokers (Eke PI et al., 2016; Tomar SL & Asma S, 2000). Thus, exposures that tend to be universal and/or reversible may not be suitable to be included in the framework. 3. Stage I and II were combined since they are managed similarly. However, due to a potential difficulty of diagnosing individuals with low disease thresholds (CAL of 1-2 mm), this low disease threshold could potentially lead to a higher degree of misclassifications. This issue can be especially true for examinations conducted by non-specialists or non-experts where measurement errors tend to be higher (Hefti AF & Preshaw PM, 2012; Tonetti MS et al., 2018). Though, this limitation is inherent to the diagnosis of stage I cases in general. An alternative approach that can be considered to reduce the misclassification of periodontitis cases is by limiting the CAL thresholds to 3-4 mm. It is important to consider, however, that diagnosis of individuals at lower thresholds of periodontitis is needed to early manage the periodontitis prior to its further progression; this can be highly important goal in young individuals. 4. Exposures listed in the framework are limited to the ones included in this thesis and the suggested framework can be modified by adding more exposures. In summary, in the thesis projects, several exposures which were associated with untreated periodontitis despite the uniformly high levels of plaque included increased age, male sex, lower socioeconomic status, lower perceived stress, uncontrolled diabetes mellitus, obesity, and current cigarette smoking. The use of PRPs had the highest impact on periodontitis prevalence whereas the overall impact of PRPs on periodontitis extent, severity and associations with periodontitis was trivial. Several factors that could impact the performance of PRPs were identified and may need to be considered before conducting population-based studies to reduce the bias. Among the knowledge gaps in the current literature are assessment of the impact of using PRP on periodontitis time trend interpretations, evaluation of periodontitis underlying exposures, and direct age-based comparisons. Attempts to conceptualize and analyze the periodontitis association with psychosocial exposures appear to be complex and their interactions will be tested further in future using full structural equation models. Periodontitis clinical definitions (AAP/EFP) and epidemiological research definitions (CDC/AAP) presented several pros and cons for their use; thus, an alternative framework combining clinical and epidemiological definitions based on the natural course of periodontitis has been suggested. Practical implications for studying the periodontitis at different stages of the 140 disease was incorporated within the suggested diagnostic framework. 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Definitions of 1st and 2nd projects’ outcomes Study outcomes 1) The total number of missing teeth. 2) Oral hygiene levels • Full mouth plaque scores <25% 3) Periodontitis prevalence using case definitions by CDC/AAP (Eke PI et al., 2012; Page RC & Eke PI, 2007) • Severe periodontitis: CAL ³6 mm at ³2 interproximal sites (not at the same tooth) and PPD ³5 mm (can be at one of the two teeth with CAL). • Moderate periodontitis: CAL ³4 mm at ³2 interproximal sites (not at the same tooth), or PPD ³5 mm at ³2 interproximal sites (not at the same tooth). 4) Periodontitis prevalence using EFP/AAP (Tonetti MS et al., 2018) • Staging was mainly categorized based on the severity of CAL, where Stage I: CAL 1-2mm, Stage II: CAL 3-4 mm, Stage III/IV: CAL ≥5 mm. The staging was then modified by the complexity factors such as periodontal probing depth and tooth loss. • Grading was applied in this study based on the modification of periodontitis risk by the glycemic control of subjects with Diabetes Mellitus and/or by smoking status. Grade A: non-smokers, non-diabetic subjects, Grade B: smokers of <10 cigarettes daily and/or diabetic with glycemic control (HBA1c <7%), Grade C: smokers of ³10 cigarettes daily and/or diabetic subjects without glycemic control (HbA1c ³7%). 5) Periodontitis extent • Percentage of interproximal sites with CAL ³3 mm/total present sites. • Percentage of interproximal sites with CAL ³4 mm/total present sites. • Percentage of interproximal sites with CAL ³5 mm/total present sites. • Percentage of interproximal sites with CAL ³6 mm/total present sites. • Percentage of interproximal sites with PPD ³4 mm/total present sites. • Percentage of interproximal sites with PPD ³5 mm/total present sites. • Percentage of interproximal sites with PPD ³6 mm/total present sites. • Percentage of interproximal sites with PPD ³7 mm/total present sites. EFP: European Federation of Periodontology, AAP: American Academy of Periodontology, CDC: Centers for Disease Control and Prevention, CAL: Clinical Attachment Loss, PPD: Periodontal Probing Depth. 170 A.2 Exposures Table 24. Definition of independent variables. Exposures Definitions Demographic data Age in years Continuous variables, subcategorized into two groups: 13-34 years and 35-80 years based on the mean age of 35.4 years. Sex Male or female. Ethnicity Arabic, African, Caucasian, East Asian, South Asian, other, or preferred not to answer. The ethnicity was categorized into Arabs and other ethnicities. Socioeconomic Status Monthly income of the household In Saudi Riyal (SAR) • Less than SAR 3,000 • SAR 3,001-5,000 • SAR 5,001-10,000 • SAR 10,001-15,000 • SAR more than 15,000 Categorized into two groups: SAR ≥5,000 and SAR <5,000. Number of the family members • 1-2 • 3-6 • > 6 Level of education 1. No formal education 2. Primary school 3. Elementary school 4. High school 5. < University degree 6. Bachelor’s degree 7. Master’s degree 8. PhD degree Subcategorized into >high school, or ≤high school. Behavioral factors Daily brushing of teeth Binary outcome (yes or no) Daily flossing or use of interdental aids Binary outcome (yes or no) Frequency of dental visits Binary outcome (yes or no) Smoking status • Never smoked • Former smokers • Current smoker who smokes <10 cigarettes/day • Current smoker who smokes ³ 10 cigarettes/day Smoking was recategorized into never smoked, former-smoker and non-smoker. 171 Exposures Definitions Psychosocial Factors Perceived Stress Continuous variable subcategorized based on mean score into higher scores (≥42.1) and lower scores (≤42.0). Perceived Social Support Continuous variable subcategorized based on mean score into higher scores (≥69.5) and lower scores (<69.5). Stopping oral self-care in stressful days Binary outcome (yes or no). Smoking more in stressful days Binary outcome (yes or no). Systemic diseases Diabetes Mellitus • Binary outcome (yes or no). • With or without glycemic control. Osteoporosis/Osteopenia Binary outcome (yes or no). Hyperthyroidism Binary outcome (yes or no). Hypothyroidism Binary outcome (yes or no). Hypertension Binary outcome (yes or no). Obesity Binary outcome (yes or no). Allergies Binary outcome (yes or no). Stroke Binary outcome (yes or no). Medications Oral Contraceptives Binary outcome (yes or no). Other medications (specified) Binary outcome (yes or no). SAR: Saudi Riyal (Currency at Saudi Arabia). 172 Study Questionnaire Q1: How old Are you? ______________ Q2: What is your sex? 1. Male 2. Female Q3: Are you pregnant now? 1. Yes 2. No Q4: Which trimester of Pregnancy? 1. 1st trimester 2. 2nd trimester 3. 3rd trimester Q5: Are you a Saudi citizen? 1. No 2. Yes Q6: What is your ethnicity? 1. Arabic 2. African 3. East Asian 4. South Asian 5. Caucasian 6. Other, please specify ____________ 7. I prefer not to answer Q7: For how long have you lived in Saudi Arabia? 1. Less than five years 2. 5-10 years 3. More than 10 years Q8: How often do you visit the dentist? 1. Only when I have pain or discomfort 2. Once a year 3. Every 6 months or less Q9: If you don’t visit the dentist regularly, what can be the reason(s)? 1. Lack of time 2. Lack of transportation 3. Financial reasons 4. Lack of trust in a dentist 5. Fear from dental treatment 6. Unavailable appointments 7. Other, please specify _______________ Q10: for how long have you been treated in this dental centre? 173 1. This is my 1st visit 2. I visit this center regularly Q11: What is the reason behind your visit to the dental clinic today? 1. Dental check-up 2. Fillings, crowns, bridges 3. Root canal treatment 4. Gum treatment 5. Other treatment, please specify ___________ Q12: What is your level of education? 1. No formal education 2. Primary school 3. Elementary school 4. High School 5. Less than a university degree 6. Bachelor’s degree or equivalent 7. Master’s degree or equivalent 8. PhD degree or equivalent Q13: What is the monthly income of your household? 1. Less than SAR 3,000 2. SAR 3,001-5,000 3. SAR 5,001-10,000 4. SAR 10,001-15,000 5. More than SAR 15,001 Q14: What is the total number of family members of your household? 1. One or two 2. Three to six 3. More than six Q15: Do you have any of these long-term illnesses or disorders? Please specify ALL that applies. 1. Diabetes Mellitus 2. Hypothyroidism 3. Hyperthyroidism 4. Rheumatoid Arthritis 5. Osteoporosis/Osteopenia 6. Leukemia 7. Blood Dyscrasia 8. Obesity 9. Hypertension 10. Cardiac disease, please specify ___________ 11. Stroke 12. Allergies, please specify _________ 13. Other conditions, please specify __________ Q16: This question is regarding your Diabetes Mellitus status. Is your blood sugar controlled? 174 1. Yes 2. I don’t know 3. No Q17: Please indicate if you use any of the following medications or show the list of your medication to your examiner. 1. Bisphosphonate (intravenously) 2. Bisphosphonate (orally). 3. Blood pressure medication, please specify _________ 4. Medication to lower your immunity, please specify ________ 5. Anti-tremor medication, please specify _________ 6. Oral contraceptive medication 7. Insulin 8. Pills to regulate blood sugar 9. Other medication, please specify _________ Q18: Do you smoke? 1. I never smoked 2. I smoked, but stopped smoking since __________ 3. I smoke less than 10 cigarettes per day since _________ 4. I smoke more than 10 cigarettes per day since _________ Q19: If you smoke, what type of smoking you use? (Please select ALL that applies) 1. Cigarettes 2. Hookah/Shisha 3. Pipe 4. Cigar 5. Electronic cigarette with Nicotine 6. Electronic cigarette without Nicotine 7. Marijuana 8. Other, please specify _________ Q20: Do you smoke more on stressful days? 1. Yes 2. No Q21: The following questions are about the health of your gum and teeth 1. Do you brush your teeth every day? • No • Yes 2. Do you use any tools to clean between your teeth? • No • Yes 3. Do you receive professional cleaning to your teeth every 6 months or less? • No • Yes 4. Were you diagnosed with gum disease before? • No • Yes 175 5. Have you seen a gum specialist before? • No • Yes 6. Do you stop cleaning your teeth during stressful days? • No • Yes Q22: What is your level of education? 1. No formal education 2. Primary school 3. Elementary school 4. High School 5. Less than a university degree 6. Bachelor’s degree or equivalent 7. Master’s degree or equivalent 8. Ph.D. degree or equivalent Q23: Do you have any missing teeth or teeth that need extraction? 1. Yes 2. No 3. I don’t know Q24: What was the reason you lost your teeth? (Please select ALL that applies) 1. Tooth decay 2. Gum inflammation 3. Pain from root canal 4. Broken tooth 5. Tooth under the gum (impacted) 6. I never had the tooth 7. Recommended by a dentist for braces 8. My teeth were loose (moving) 9. Tooth abscess or swelling 176 Perceived Stress Scale (PSS) Perceived Stress Scale (PSS) The following section of questions is regarding your mental health. Please select the percentage that applies to you. “0” indicates “Never” and “100” indicates “always”. Q1: In the last month, how often have you felt that you were unable to control the important things in your life? Never Always 0% 100% Q2: In the last month, how often have you felt nervous and stressed? Never Always 0% 100% Q3: In the last month, how often have you found that you could not cope with all the things that you had to do? Never Always 0% 100% Q4: In the last month, how often have you been able to control irritations in your life? Never Always 0% 100% Q5: In the last month, how often have you felt that you were on top of things? Never Always 0% 100% Q6: In the last month, how often have you felt that things were going your way? Never Always 0% 100% Q7: In the last month, how often have you felt confident about your ability to handle your personal problems? Never Always 0% 100% Q8: In the last month, how often have you been upset because of something that happened unexpectedly? Never Always 0% 100% Q9: In the last month, how often have you been angered because of things happened that were outside of your control? Never Always 0% 100% Q10: In the last month, how often have you felt difficulties were piling up so high that you could not overcome them? Never Always 0% 100% 177 Multidimensional Scale of Perceived Social Support (MSPSS) Multidimensional Scale of Perceived Social Support (MSPSS) The following section is regarding social support. Please indicate how much social support applies to you by selecting the percentage. “0” indicates “Never” and “100” indicates “always”. 1) There is a special person who is around when I am in need. Never Always 0% 100% 2) I get the emotional help and support I need from my family. Never Always 0% 100% 3) I have a special person who is a real source of comfort to me. Never Always 0% 100% 4) My friends really try to help me. Never Always 0% 100% 5) There is a special person with whom I can share joys and sorrows. Never Always 0% 100% 6) I can count on my friends when things go wrong. Never Always 0% 100% 7) My family really tries to help me. Never Always 0% 100% 8) I can talk about my problems with my family. Never Always 0% 100% 9) I have friends with whom I can share my joys and sorrows. Never Always 0% 100% 10) There is a special person in my life who cares about my feelings. Never Always 0% 100% 11) My family is willing to help me make decisions. Never Always 0% 100% 12) I can talk about my problems with my friends. Never Always 0% 100% 178 Supplementary tables for the systematic review and meta-analyses Table 25. Customization of the QUADAS-2 tool for quality assessment of diagnostic studies Domain Quality assessment Original signaling question Customized signaling questions for the current review 1) Patient selection Risk of bias Could the selection of patients have introduced bias? Did the study use consecutive or random sample? Was a case control design avoided? Excluded question. Did the study avoid inappropriate exclusions? Did the study have clear eligibility criteria, description of baseline characteristics, study settings, and avoided any inappropriate exclusion? Applicability concerns Are there concerns that the included patients and setting do not match the review question? Were the spectrum of subjects, representative of the subjects who will receive the examination in the general population? Added question: Did they include subjects with few remaining teeth? (Studies that excluded subjects with >6 teeth were considered to have high applicability concerns). 2) Index test: Partial-mouth Recording Protocol (PRP) Risk of bias Were the index test results interpreted without knowledge of the results of the reference standard? Excluded question If a threshold was used, was it prespecified? Did the study adequately define the diagnostic thresholds for periodontitis and provided a rationale for using certain diagnostic thresholds? Applicability concerns Are there concerns that the index test, its conduct, or its interpretation differ from the review question? Is there a concern regarding the PRP selection, use or interpretation that differed from the review question? 3) Reference standard: Full-mouth Recording Protocol (FRP) Risk of bias Is the reference standard likely to correctly classify the target condition? Is the reference standard likely to correctly classify the subjects with periodontitis? Were the reference standard results interpreted without knowledge of the results of the index test? Excluded question Applicability concerns Are there concerns that the target condition as defined by the reference standard does not match the question? Could the reference standard, its conduct or interpretation have deviated from the review question? 4) Flow and Timing Risk of bias Was there an appropriate interval between the index test and reference standard? Excluded question Did all patients receive the same reference standard? Did all the patients receive the same FRP examination? Were all patients included in the analysis? Excluded question Added question: Were the clinical examinations conducted by a trained and calibrated examiner/s? Added question: Were there any intra-examiner/ inter-examiner reliability tests reported? QUADAS-2: 2nd version of QUALITY Assessment of Diagnostic accuracy studies, FRP: Full-mouth Recording Protocol, PRP: Partial-mouth Recording Protocol. 179 Table 26. List of excluded studies from the systematic review and the reasons for exclusion First author, date Reasons for exclusion Alshihayb, 2022 (Alshihayb TS & Heaton B, 2022) Simulation study. Numora, 2020 (Nomura et al., 2020) Did not report periodontal outcomes. Botelho, 2020 (Botelho J et al., 2020) Did not report periodontal outcomes and used the National Health And Nutrition Examination Survey (NHANES) dataset that was utilized earlier in other included studies. Heaton, 2018 (Heaton B, Sharma P, et al., 2018) Reported the sensitivity for diagnosing severe cases based on mesiobuccal and distolingual sites only. The severity estimate was provided as mean CAL without reporting the SD. Preisser, 2018 (Preisser JS et al., 2018) Simulation study. Heaton, 2018 (Heaton B, Garcia RI, et al., 2018) Simulation study. Machado, 2017 (Machado ME et al., 2017) Examined the gingivitis only. Preisser, 2017 (Beck JD et al., 2006) The Atherosclerosis Risk in Communities (ARIC) dataset, periodontal outcomes and PRP used in this study were similar to what were reported earlier in Beck's study but used different statistical approach to estimate the prevalence using conditional linear family estimator then compared it to standard estimator. Peres, 2013 (Peres MA et al., 2012) Assessed bleeding on probing, calculus, and PPD. No assessment for CAL. Eke, 2010 (Eke PI et al., 2010) The FRP included data measured using PRP. Bassani, 2006 (Bassani DG et al., 2006) Used CPITN without assessment of CAL. Borges Yane, 2004 (Borges-Yanez SA et al., 2004) FRP excluded the sites included in the PRP. Thus, the mesiobuccal sites of all teeth were not considered as part of the gold standard. Mumghamba, 2004 (Mumghamba EG et al., 2004) Used Ramfjord index. Owens, 2003 (Owens JD et al., 2003) Reported the prevalence and estimates of severity and extent for full mouth only. The estimate of severity (mean CAL) of partial mouth recording was reported without reporting the SD. The number of subjects with disease or without disease for full mouth and partial mouth recordings were not provided. Thomson, 2002 (Thomson WM & Williams SM, 2002) Assessed full mouth at three sites per tooth only. Eaton, 2001 (Eaton KA et al., 2001) Assessed the CAL at different thresholds (3 mm or less). Benigeri, 2000 (Benigeri M et al., 2000) Used CPITN index. Agerholm, 1996 (Agerholm DM & Ashley FP, 1996) Assessed the CAL at different thresholds (3 mm or 5 mm). 180 First author, date Reasons for exclusion Baelum, 1993 (Baelum V, Fejerskov O, et al., 1993) Used CPITN index. Papapanou, 1993 (Papapanou PN et al., 1993) Used ESI index, did not report the prevalence or made information at the individual level, also it did not report the mean (SD) for extent and severity for partial mouth. Diamanti-Kipioti, 1993 (Diamanti-Kipioti A et al., 1993) Half mouth was assessed at two sites only, no CAL was reported. Full mouth was assessed at our sites including midbuccal and midlingual. Rams, 1993 (Rams TE et al., 1993) Examined the periodontal disease progression using CPITN without reporting the CAL. Almas, 1991 (Almas K et al., 1991) Did not assess the CAL and use CPITN. Hunt, 1991 (Hunt RJ & Fann SJ, 1991) Used CPITN and full mouth assessments at two sites only in some of the study subjects. Silness, 1988 Assessed full mouth only at three sites per tooth. Kingman, 1988 Assessed full mouth at four sites (not restricted to interproximal sites) per tooth. Hunt, 1987 (Hunt RJ, 1987) Used CPITN without assessment of CAL. Fleiss, 1987 (Fleiss JL et al., 1987) Used CPITN without assessment of CAL. Goldberg, 1985 (Goldberg P et al., 1985) Examined the gingivitis and plaque in children and young adults. Gettinger, 1982 (Gettinger G et al., 1983) Assessed full mouth only at two sites per tooth. Mills, 1975 (Mills WH et al., 1975) Assessed the correlation between PRP and FRP without reporting the number of subjects, prevalence or estimates of severity for PRP versus FRP. PRP: Partial mouth recording, FRP: Full mouth recording, SD: standard deviation, PPD: Periodontal Probing Depth, CAL: Clinical Attachment Loss. ESI: Extent and Severity Index, CPITN: Community Periodontal Index of Treatment Need. 181 Table 27. Periodontitis prevalence using Partial-mouth Recording Protocol (PRP) versus Full-mouth Recording Protocol (FRP) at different minimum number of sites and disease thresholds defined by Clinical Attachment Loss (CAL) and Periodontal Probing Depth (PPD). Accuracy of the periodontitis prevalence using PRP are reported including the sensitivity, specificity, Positive Predictive Value (PPV), Negative Predictive Value (NPV), and the absolute bias (AB). Study Selected PRP, total sites Minimal Interproximal sites with CAL and/or PPD using PRP Minimal interproximal sites with CAL and/or PPD using FRP Prevalence PRP (%) Prevalence FRP (%) Sensitivity (%) Specificity (%) PPV (%) NPV (%) AB (%) Teixeira 2020 (Teixeira F et al., 2020) (FM)MB-B-DL Total sites: 84 CAL ³4 mm, ³2 site and PPD ³4 mm, ³2 site CAL ³4 mm, ³2 site and PPD ³4 mm, ³2 site 13.1 18.8 69.7 100.0 100.0 93.4 -5.7 CAL ³4 mm, ³1 site and PPD ³4 mm, ³1 site CAL ³4 mm, ³1 site and PPD ³4 mm, ³1 site 17.7 22.0 80.5 100.0 100.0 94.8 -4.3 CAL ³4 mm, ³1 site or PPD ³4 mm, ³1 site CAL ³4 mm, ³1 site or PPD ³4 mm, ³1 site 30.6 34.8 87.7 100.0 100.0 93.8 -4.2 RHM Total sites: 84 CAL ³4 mm, ³2 site and PPD ³4 mm, ³2 site CAL ³4 mm, ³2 site and PPD ³4 mm, ³2 site 10.6 18.8 56.1 100.0 100.0 90.7 -8.2 CAL ³4 mm, ³1 site and PPD ³4 mm, ³1 site CAL ³4 mm, ³1 site and PPD ³4 mm, ³1 site 14.3 22.0 64.9 100.0 100.0 91.0 -7.7 CAL ³4 mm, ³1 site or PPD ³4 mm, ³1 site CAL ³4 mm, ³1 site or PPD ³4 mm, ³1 site 27.1 34.8 77.9 100.0 100.0 89.4 -7.7 (HM)MB-B-DL Total sites: 42 CAL ³4 mm, ³1 site or PPD ³4 mm, ³1 site CAL ³4 mm, ³1 site or PPD ³4 mm, ³1 site 22.4 34.8 63.9 100.0 100.0 83.8 -12.4 CAL ³4 mm, ³1 site and PPD ³4 mm, ³1 site CAL ³4 mm, ³1 site and PPD ³4 mm, ³1 site 10.8 22.0 49.4 100.0 100.0 87.5 11.2 CAL ³4 mm, ³2 site and PPD ³4 mm, ³2 site CAL ³4 mm, ³2 site and PPD ³4 mm, ³2 site 8.3 18.8 43.9 100.0 100.0 88.5 -10.5 Heaton* 2018 (Heaton B, Sharma P, et al., 2018) RHM Total sites: 28 CAL ³6 mm, ³2 sites and PPD ³5 mm, ³1 site CAL ³6 mm, ³2 sites and PPD ³5 mm, ³1 site 9.4 18.1 54.1 100.0 100.0 90.8 -8.7 CAL ³6 mm, ³1 site and PPD ³5 mm, ³1 site CAL ³6 mm, ³2 sites and PPD ³5 mm, ³1 site 13.9 18.1 76.7 95.8 80.2 94.9 -4.2 CAL ³6 mm, ³2 site CAL ³6 mm, ³2 sites and PPD ³5 mm, ³1 site 17.0 18.1 94.0 79.6 50.5 98.3 -1.1 Tran* 2014 (Tran DT et al., 2014) (FM)MB-DL Total sites: 56 CAL ³4 mm, ³2 sites or PPD ³5 mm, ³2 sites CAL ³4 mm, ³2 sites or PPD ³5 mm, ³2 sites 30.5 34.3 88.9 100.0 100.0 94.5 -3.8 CAL ³4 mm, ³1 site or PPD ³5 mm, ³1 site CAL ³4 mm, ³2 sites or PPD ³5 mm, ³2 sites 39.1 34.3 100.0 92.5 87.4 100.0 4.9 CAL ³6 mm, ³2 sites and PPD ³5 mm, ³1 site CAL ³6 mm, ³2 sites and PPD ³5 mm, ³1 site 8.6 11.8 72.8 100.0 100.0 96.5 -3.2 CAL ³6 mm, ³1 site and PPD ³5 mm, ³1 site CAL ³6 mm, ³2 sites and PPD ³5 mm, ³1 site 11.5 11.8 100.0 99.3 95.2 100.0 -0.3 RHM Total sites: 56 CAL ³4 mm, ³2 sites or PPD ³5 mm, ³2 sites CAL ³4 mm, ³2 sites or PPD ³5 mm, ³2 sites 28.1 34.3 81.9 100.0 100.0 91.4 -6.2 CAL ³4 mm, ³1 site or PPD ³5 mm, ³1 site CAL ³4 mm, ³2 sites or PPD ³5 mm, ³2 sites 37.5 34.2 100.0 95.0 91.2 100.0 3.3 182 Study Selected PRP, total sites Minimal Interproximal sites with CAL and/or PPD using PRP Minimal interproximal sites with CAL and/or PPD using FRP Prevalence PRP (%) Prevalence FRP (%) Sensitivity (%) Specificity (%) PPV (%) NPV (%) AB (%) CAL ³6 mm, ³2 sites and PPD ³5 mm, ³1 site CAL ³6 mm, ³2 sites and PPD ³5 mm, ³1 site 7.7 11.8 65.4 100.0 100.0 95.6 -4.1 CAL ³6 mm, ³1 site and PPD ³5 mm, ³1 site CAL ³6 mm, ³2 sites and PPD ³5 mm, ³1 site 10.6 11.8 89.8 100.0 100.0 98.7 -1.2 Agerholm 1996 (Agerholm DM & Ashley FP, 1996) CPITN Total sites: 40 CAL ³3 mm, ³2 site CAL ³3 mm, ³2 site 28.7 36.1 79.5 100.0 100.0 89.6 -7.4 CAL ³3 mm, ³1 site CAL ³3 mm, ³1 site 47.5 53.0 89.7 100.0 100.0 89.6 -5.5 CAL ³5 mm, ³2 site CAL ³5 mm, ³2 site 5.9 6.9 85.7 100.0 100.0 99.0 -1.0 CAL ³5 mm, ³1 site CAL ³5 mm, ³1 site 13.3 14.4 93.1 100.0 100.0 98.9 -1.1 (FM): Full-Mouth, (HM): Half-Mouth, MB: Mesio-Buccal, B: Mid-Buccal, DB: Disto-Buccal sites, RHM: Random-Half-Mouth, CPITN: Community Periodontal Index of Treatment Needs. * Studies used case definitions by the Centers for Disease Control and Prevention and the American Academy of Periodontology (CDC/AAP) (Eke PI et al., 2012; Page RC & Eke PI, 2007). 183 Supplementary figures for the systematic review: PRP performance in estimating periodontitis prevalence defined using the CDC/AAP case definitions -40.0% -30.0% -20.0% -10.0% 0.0% 10.0%PRPSites PRP Studies N AB% (95% CI)PrevalencePRP (%)PrevalenceFRP (%)56 (FM) MB-DB Tran 2014 3667 -9.2 (-11.5, -7.0) 36.9 46.156 (FM) MB-DL Alawaji 2022 431 -9.7 (-15.6, -3.9) 68.7 78.456 (FM) MB-DL Romano 2019 721 -6.9 (-11.4, -2.4) 71.0 77.956 (FM) MB-DL Tran 2014 3667 -7.0 (-9.3, -4.8) 39.1 46.1Subgroup (I2=0.0%, P=0.500) -8.1 (-9.6, -6.7) 53.9 62.156 RHM Alawaji 2022 431 -10.0 (-15.8, -4.1) 68.4 78.456 RHM Romano 2019 721 -12.1 (-16.7, -7.5) 65.9 77.956 RHM Tran 2014 3667 -10.3 (-12.5, -8.1) 35.8 46.1Subgroup (I2=0.0%, P=0.779) -10.6 (-12.5, -8.7) 56.7 67.542 (HM) MB-B-DL Akinkugbe 2015 6259 -23.7 (-25.4, -22.0) 34.0 57.628 (HM) MB-DB Tran 2014 3667 -19.8 (-22.0, -17.6) 21.7 34.328 (HM) MB-DL Alawaji 2022 431 -19.7 (-25.8, -13.7) 58.7 78.428 (HM) MB-DL Tran 2014 3667 -16.9 (-19.1, -14.7) 29.2 46.1Subgroup (I2=87.5%, P=0.000) -20.1 (-23.6, -16.6) 37.0 57.142 42 RSSM Akinkugbe 2015 6259 -9.5 (-11.2, -7.7) 48.2 57.640 CPITN Tran 2014 3667 -12.9 (-15.1, -10.7) 29.2 46.136 Ramfjord Akinkugbe 2015 6259 -33.8 (-35.4, -32.2) 23.8 57.624 Ramfjord Tran 2014 3667 -26.2 (-28.2, -24.1) 19.9 46.1Subgroup (I2=99.4%, P=0.000) -20.6 (-32.6, -8.6) 31.3 51.9Heterogeneity (I2=98.6%, P<0.001) -15.3 (-20.1, -10.5) 35.1 52.6Absolute biasFigure 28. Summary of the Absolute Bias (AB) prevalence of CDC/AAP moderate-severe periodontitis using Partial-mouth Recording Protocols (PRP). Total PRP sites for each PRP are listed. AB prevalence values <0.0 underestimate the prevalence while values >0.0 overestimate it. FRP: Full-mouth Recording Protocol, N: sample size, CI: Confidence Interval, MB: Mesio-buccal, B: Mid-buccal, DB: Disto-buccal, ML: Mesio-lingual, L: Mid-lingual, DL: Disto-lingual, (FM): Full-mouth, (HM): Half-mouth, 84 RSSM: 84 sites selected using Random Site Selection Method, 42 RSSM: 42 sites selected using Random Site Selection Method, 36 RSSM: 36 sites selected using Random Site Selection Method, (RHM): Random half-mouth, CPITN: Community Periodontal Index of Treatment Needs, ?: not clear. 184 Figure 29. Sensitivity of CDC/AAP moderate-severe periodontitis prevalence using Partial-mouth Recording Protocols (PRP). Specificity and positive predictive value were 100% for all PRPs. PRP sites, minimal number of sites with Clinical Attachment Loss (CAL) and Negative Predictive Value (NPV) are listed. FRP: Full-mouth Recording Protocol, N: sample size, CI: Confidence Interval, MB: Mesio-buccal, B: Mid-buccal, DB: Disto-buccal, ML: Mesio-lingual, L: Mid-lingual, DL: Disto-lingual, (FM): Full-mouth, (HM): Half-mouth, 84 RSSM: 84 sites selected using Random Site Selection Method, 42 RSSM: 42 sites selected using Random Site Selection Method, 36 RSSM: 36 sites selected using Random Site Selection Method, (RHM): Random half-mouth, CPITN: Community Periodontal Index of Treatment Needs, ?: not clear. 40.0% 54.0% 69.0% 83.0% 97.0%PRPSites PRP Studies NPrevalencePRP (%)PrevalenceFRP (%)NPV(%)Sensitivity% (95% CI)56 (FM) MB-DB Tran 2014 3667 36.9 46.1 85.4 80.0 (78.0, 81.8)56 (FM) MB-DL Alawaji 2022 431 68.7 78.4 68.9 87.5 (83.5, 90.6)56 (FM) MB-DL Romano 2019 721 71.0 77.9 76.1 91.0 (88.4, 93.1)56 (FM) MB-DL Tran 2014 3667 39.1 46.1 88.5 84.7 (82.9, 86.4)56 RHM Alawaji 2022 431 68.4 78.4 68.4 95.8 (93.0, 97.5)56 RHM Romano 2019 721 65.9 77.9 64.6 84.5 (81.2, 87.2)56 RHM Tran 2014 3667 35.8 46.1 83.9 77.6 (75.6, 79.6)42 (HM) MB-B-DL Akinkugbe 2015 6259 34.0 57.6 64.2 58.9 (57.3, 60.5)28 (HM) MB-DB Tran 2014 3667 26.3 46.1 73.1 57.1 (54.7, 59.4)28 (HM) MB-DL Alawaji 2022 431 58.7 78.4 52.2 74.8 (69.9, 79.1)28 (HM) MB-DL Tran 2014 3667 29.2 46.1 76.1 63.3 (61.0, 65.6)42 42 RSSM Akinkugbe 2015 6259 48.2 57.6 87.9 90.0 (88.9, 90.9)40 CPITN Tran 2014 3667 29.2 46.1 80.7 72.0 (69.8, 74.0)36 Ramfjord Akinkugbe 2015 6259 23.8 57.6 55.6 41.3 (39.7, 42.9)24 Ramfjord Tran 2014 3667 19.9 46.1 67.4 43.5 (41.1, 45.8)Heterogeneity (I2=99.5%, P<0.001) 35.1 52.6 76.8 (68.2, 83.7)Sensitivity 185 Figure 30. Absolute Bias (AB) prevalence of CDC/AAP severe periodontitis using Partial-mouth Recording Protocols (PRP). Total PRP sites for each PRP are listed. AB prevalence values <0.0 underestimate the prevalence while values >0.0 overestimate it. FRP: Full-mouth Recording Protocol, N: sample size, CI: Confidence Interval, MB: Mesio-buccal, B: Mid-buccal, DB: Disto-buccal, ML: Mesio-lingual, L: Mid-lingual, DL: Disto-lingual, (FM): Full-mouth, (HM): Half-mouth, 84 RSSM: 84 sites selected using Random Site Selection Method, 42 RSSM: 42 sites selected using Random Site Selection Method, 36 RSSM: 36 sites selected using Random Site Selection Method, (RHM): Random half-mouth, CPITN: Community Periodontal Index of Treatment Needs, ?: not clear. -20.0% -15.0% -10.0% -5.0% 0.0% 5.0% 10.0%PRPSites PRP Studies N AB% (95% CI)PrevalencePRP (%)PrevalenceFRP (%)56 (FM) MB-DB Tran 2014 3667 -4.2 (-5.6, -2.8) 7.6 11.856 (FM) MB-DL Alawaji 2022 431 -3.5 (-9.6, 2.6) 27.8 31.356 (FM) MB-DL Romano 2019 721 -5.5 (-10.5, -0.6) 32.6 38.156 (FM) MB-DL Tran 2014 3667 -3.2 (-4.6, -1.8) 8.6 11.8Subgroup (I2=0.0%, P=0.680) -3.8 (-4.7, -2.8) 19.1 23.356 RHM Alawaji 2022 431 -7.9 (-13.8, -20.0) 23.4 31.356 RHM Romano 2019 721 -10.4 (-15.2, -5.6) 27.7 38.156 RHM Tran 2014 3667 -4.1 (-5.4, -2.7) 7.7 11.8Subgroup (I2=72.5%, P=0.027) -6.9 (-11.3, -2.6) 19.6 27.128 (HM) MB-DB Tran 2014 3667 -7.2 (-8.4, -6.0) 4.6 11.828 (HM) MB-DL Alawaji 2022 431 -13.0 (-18.7, -7.3) 18.3 31.328 (HM) MB-DL Tran 2014 3667 -6.6 (-7.9, -5.3) 5.2 11.8Subgroup (I2=57.6%, P=0.095) -7.3 (-8.9, -5.7) 9.4 18.340 CPITN Tran 2014 3667 -4.4 (-5.8, -3.1) 7.4 11.824 Ramfjord Tran 2014 3667 -8.9 (-10.1, -7.7) 2.9 11.8Subgroup (I2=95.9%, P=0.000) -6.7 (-11.1, -2.3) 5.1 11.8Heterogeneity (I2=84.9%, P<0.001) -6.1 (-7.5, -4.7) 9.1 14.4Absolute bias 186 21.0% 39.0% 57.0% 75.0% 93.0%SensitivityPRPsites PRP Studies NPrevalencePRP (%)PrevalenceFRP (%)NPV(%)Sensitivity%(95% CI)56 (FM) MB-DB Tran 2014 3667 7.6 11.8 95.5 64.4 (59.8, 68.8)56 (FM) MB-DL Alawaji 2022 431 27.8 31.3 94.9 88.6 (82.1, 93.0)56 (FM) MB-DL Romano 2019 721 32.6 38.1 91.8 85.3 (80.6, 89.0)56 (FM) MB-DL Tran 2014 3667 8.6 11.8 96.5 72.7 (68.3, 76.7)56 RHM Alawaji 2022 431 23.4 31.3 89.4 74.6 (66.7, 81.2)56 RHM Romano 2019 721 27.7 38.1 85.6 72.6 (67.1, 77.6)56 RHM Tran 2014 3667 7.7 11.8 95.6 65.3 (60.7, 69.7)28 (HM) MB-DB Tran 2014 3667 4.6 11.8 92.5 39.1 (34.6, 43.7)28 (HM) MB-DL Alawaji 2022 431 18.3 31.3 84.0 58.5 (50.0, 66.4)28 (HM) MB-DL Tran 2014 3667 5.2 11.8 93.0 57.0 (55.0, 58.9)40 CPITN Tran 2014 3667 7.4 11.8 95.2 62.6 (57.9, 67.0)24 Ramfjord Tran 2014 3667 2.9 11.8 90.8 27.9 (23.9, 32.2)Heterogeneity (I2=97.5%, P<0.001) 9.1 14.4 64.9 (56.0, 72.9)Figure 31. CDC/AAP severe periodontitis prevalence using Partial-mouth Recording Protocols (PRP). Specificity and positive predictive value are 100% for all PRPs. PRP sites, minimal number of sites with Clinical Attachment Loss (CAL) and Negative Predictive Value (NPV) are listed. FRP: Full-mouth Recording Protocol, N: sample size, CI: Confidence Interval, MB: Mesio-buccal, B: Mid-buccal, DB: Disto-buccal, ML: Mesio-lingual, L: Mid-lingual, DL: Disto-lingual, (FM): Full-mouth, (HM): Half-mouth, 84 RSSM: 84 sites selected using Random Site Selection Method, 42 RSSM: 42 sites selected using Random Site Selection Method, 36 RSSM: 36 sites selected using Random Site Selection Method, (RHM): Random half-mouth, CPITN: Community Periodontal Index of Treatment Needs.
Thesis/Dissertation
eng
Craniofacial Science
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Aleksejuniene, Jolanta
Periodontal disease epidemiology : assessment of untreated periodontitis and accuracy of partial mouth recording protocols
Text