Medicine, Faculty of
Medicine, Department of
DSpace
UBCV
Shayegi-Nik, Sara
Master of Science - MSc
University of British Columbia
Introduction: Substance use disorder (SUD), mood, and anxiety disorders disproportionately affect people living with HIV (PLWH). However, comprehensive research on the effects of these disorders on HIV care engagement and healthcare utilization of PLWH is lacking. This thesis aimed to assess the impact of the syndemic between SUD and mood/anxiety disorders on the HIV continuum of care for PLWH in British Columbia (BC), Canada, and identify the stage with the highest attrition in the continuum. Additionally, this thesis intended to examine the effects of SUD, mood/anxiety disorders, and disengagement from HIV care (at the stage with the highest attrition) on healthcare utilization of PLWH. Methods: This retrospective population-based cohort study utilized data from the Comparative Outcomes And Service Utilization Trends (COAST) study that contains data on all diagnosed PLWH in BC. Eligible individuals were ≥19 years of age and were followed during 2001-2019. First, I identified the stage with the highest attrition in the HIV continuum of care. Using statistical models, I measured the associations between SUD and mood/anxiety disorders and the achievement of each stage of the continuum. I then measured the effects of these disorders and disengagement from HIV care (at the stage with the highest attrition) on counts of physician visits, hospitalization, and length of stay (LOS). Results: The stage of sustained viral suppression exhibited the highest attrition. SUD was associated with incomplete antiretroviral therapy adherence (adjusted Odds Ratio (aOR) 0.47, 95% CI: 0.42-0.53) and unsustained suppression (aOR 0.58, 95% CI: 0.53-0.63). Mood/anxiety disorders were also associated with incomplete adherence (aOR 0.78, 95% CI: 0.71-0.87) and unsustained suppression (aOR 0.82, 95% CI: 0.77-0.88). Having both disorders was associated with over four times more acute care hospitalizations, three times longer length of stay and almost twice the physician visits. Unsustained suppression was strongly and independently associated with more physician visits, hospitalizations and longer LOS. Conclusion: SUD and mood/anxiety disorders contribute to attritions across the HIV continuum of care and high healthcare utilization among PLWH. Therefore, this thesis emphasizes the need for integrated mental health and substance use services to support HIV care.
Impact of Mood/Anxiety and Substance Use Disorders on the HIV Continuum of Care and Healthcare Utilization of People Living With HIV by Sara Shayegi-Nik B.Sc., Simon Fraser University, 2020 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Experimental Medicine) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) July 2024 © Sara Shayegi-Nik, 2024 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Impact of Mood/Anxiety and Substance Use Disorders on the HIV Continuum of Care and Healthcare Utilization of People Living With HIV submitted by Sara Shayegi-Nik in partial fulfilment of the requirements for the degree of Master of Science in Experimental Medicine Examining Committee: Viviane Dias Lima, Associate Professor, Medicine, UBC Supervisor Robert S. Hogg, Professor, Health Sciences, Simon Fraser University Supervisory Committee Member William G. Honer, Professor, Psychiatry, UBC Supervisory Committee Member Melanie Murray, Associate Professor, Medicine, UBC Additional Examiner iii Abstract Introduction: Substance use disorder (SUD), mood, and anxiety disorders disproportionately affect people living with HIV (PLWH). However, comprehensive research on the effects of these disorders on HIV care engagement and healthcare utilization of PLWH is lacking. This thesis aimed to assess the impact of the syndemic between SUD and mood/anxiety disorders on the HIV continuum of care for PLWH in British Columbia (BC), Canada, and identify the stage with the highest attrition in the continuum. Additionally, this thesis intended to examine the effects of SUD, mood/anxiety disorders, and disengagement from HIV care (at the stage with the highest attrition) on healthcare utilization of PLWH. Methods: This retrospective population-based cohort study utilized data from the Comparative Outcomes And Service Utilization Trends (COAST) study that contains data on all diagnosed PLWH in BC. Eligible individuals were ≥19 years of age and were followed during 2001-2019. First, I identified the stage with the highest attrition in the HIV continuum of care. Using statistical models, I measured the associations between SUD and mood/anxiety disorders and the achievement of each stage of the continuum. I then measured the effects of these disorders and disengagement from HIV care (at the stage with the highest attrition) on counts of physician visits, hospitalization, and length of stay (LOS). Results: The stage of sustained viral suppression exhibited the highest attrition. SUD was associated with incomplete antiretroviral therapy adherence (adjusted Odds Ratio (aOR) 0.47, 95% CI: 0.42-0.53) and unsustained suppression (aOR 0.58, 95% CI: 0.53-0.63). Mood/anxiety iv disorders were also associated with incomplete adherence (aOR 0.78, 95% CI: 0.71-0.87) and unsustained suppression (aOR 0.82, 95% CI: 0.77-0.88). Having both disorders was associated with over four times more acute care hospitalizations, three times longer length of stay and almost twice the physician visits. Unsustained suppression was strongly and independently associated with more physician visits, hospitalizations and longer LOS. Conclusion: SUD, and mood/anxiety disorders contribute to attritions across the HIV continuum of care and high healthcare utilization among PLWH. Therefore, this thesis emphasizes the need for integrated mental health and substance use services to support HIV care. v Lay Summary Substance use disorders (SUD) and mood/anxiety disorders are common health conditions among people living with HIV (PLWH). However, the impacts of these disorders on HIV care uptake, treatment outcomes, and healthcare service usage of PLWH have not been thoroughly investigated. Therefore, this thesis assessed the effects of SUD and mood/anxiety disorders on the completion of each treatment step that PLWH go through to manage HIV infection and found that these disorders increase the chance of disengagement from HIV care. This thesis found maintenance of viral suppression (i.e., an undetectable amount of HIV in the blood) as the most challenging step in HIV management. This thesis also assessed the impacts of SUD, mood/anxiety disorders, and unmaintained suppression on healthcare service usage of PLWH and determined that PLWH with these disorders and/or unmaintained suppression have more frequent physician visits, increased hospitalizations and longer hospitalization periods. vi Preface This thesis was completed by Sara Shayegi-Nik, under the supervision of Dr. Viviane Dias Lima, and with input from thesis committee members, Drs. Robert S. Hogg and William Honer. This thesis’s concept development, methodological design, statistical interpretations, drafting and critical revisions were performed by SSN. All steps of the research were performed under the guidance of the supervisory committee. Chapter 2 has been published, and Chapter 3 has been submitted to a peer-reviewed journal. The details of the publication and knowledge dissemination efforts are as follows: Chapter 2: Shayegi-Nik S, Wang L, Li J, Budu M, Kooij K, Honer WG, Hogg RS, Montaner JSG, Lima VD. Impact of Substance Use and Mood/Anxiety Disorders on the HIV Continuum of Care in British Columbia, Canada, from 2001 to 2019. International Journal of Mental Health and Addiction. 2024/03/21 2024;doi:10.1007/s11469-024-01272-6. A version of Chapter 2 was presented at the 33rd Canadian Conference on HIV/AIDS Research (CAHR 2024). LW and LJ performed the analytical acquisition and statistical analyses. VDL also provided analytical and statistical guidance. MB, KK, WGH, RSH, MJSG and VDL critically assessed the content of the manuscript and provided editorial and intellectual input. All co-authors approved the final version of the manuscript. Chapter 3: Shayegi-Nik S, Wang L, Magee C, Li J, Budu M, Kooij K, Honer WG, Hogg RS, Montaner JSG, Lima VD. Impact of Substance Use, Mood/Anxiety Disorders and Unsustained Suppression on Healthcare Utilization of People Living with HIV in British Columbia, Canada, from 2001 to 2019. (under review). LW and LJ performed the analytical acquisition and statistical analyses. VDL also provided analytical and statistical guidance. MB, KK, WGH, RSH, MJSG and VDL critically assessed the manuscript and vii provided editorial and intellectual input. All co-authors approved the final version of the manuscript that was submitted to the peer-reviewed journal. The studies in this thesis have received ethics approval from the University of British Columbia/Providence Health Care Research Ethics Board (H22-02875, H09-02905, H16-02036, and H20-03165). These studies comply with the BC Freedom of Information and Protection of Privacy Act (FIPPA) and did not require informed consent as they were conducted retrospectively for research and statistical purposes only using anonymized data. This thesis utilized data from the ongoing Comparative Outcomes and Health Service Utilization (COAST) study based at the British Columbia Centre for Excellence in HIV/AIDS (BC-CfE). Access to data provided by the Data Stewards is subject to approval but can be requested for research projects through the Data Stewards or their designated service providers. The following data sets were used in this study: BC Cancer, Pharmanet, Consolidation, Hospital Separations (Discharge Abstract Database), Mental Health, Medical Service Plan (MSP), PharmaCare, Vital Statistics (VS)-Deaths, National Ambulatory Care Reporting Systems (NARCS). You can find further information regarding these data sets by visiting the PopData project webpage at: https://my.popdata.bc.ca/project_listings/18-223/collection_approval_dates All inferences, opinions, and conclusions drawn in this publication are those of the author(s), and do not reflect the opinions or policies of the Data Steward(s). viii Table of Contents Abstract ......................................................................................................................................... iii Lay Summary ................................................................................................................................ v Preface ........................................................................................................................................... vi Table of Contents ....................................................................................................................... viii List of Tables ................................................................................................................................. x List of Figures .............................................................................................................................. xii List of Abbreviations ................................................................................................................. xiii Acknowledgements .................................................................................................................... xiv Chapter 1: Introduction ........................................................................................................... 1 1.1. Problem Statement ...................................................................................................... 1 1.2. Definitions and Framework ........................................................................................ 2 1.3. Study Justification ....................................................................................................... 6 1.4. Study Setting ............................................................................................................... 7 1.5. Research Objectives and Hypotheses ......................................................................... 8 1.6. Empirical Evidence ..................................................................................................... 9 1.7. Thesis Summary........................................................................................................ 18 Chapter 2: The Impact of Substance Use and Mood/Anxiety Disorders on the HIV Continuum of Care in British Columbia, Canada, from 2001 to 2019 .............................. 19 2.1. Introduction ............................................................................................................... 19 2.2. Methods..................................................................................................................... 20 2.3. Results ....................................................................................................................... 25 2.4. Discussion ................................................................................................................. 45 ix 2.5. Conclusion ................................................................................................................ 48 Chapter 3: The Impact of Substance Use, Mood/Anxiety Disorders and Unsustained Viral Suppression on Healthcare Utilization of People Living with HIV in British Columbia, Canada, from 2001 to 2019.................................................................................. 49 3.1. Introduction ............................................................................................................... 49 3.2. Methods..................................................................................................................... 50 3.3. Results ....................................................................................................................... 56 3.4. Discussion ................................................................................................................. 81 3.5. Conclusion ................................................................................................................ 84 Chapter 4: Conclusion ............................................................................................................ 86 4.1. Overview ................................................................................................................... 86 4.2. Summary of Findings ................................................................................................ 86 4.3. Strengths and Limitations ......................................................................................... 90 4.4. Public Health Implications ........................................................................................ 91 4.5. Final Remarks ........................................................................................................... 93 References .................................................................................................................................... 94 Appendices ................................................................................................................................. 125 Appendix A List of diseases and respective case-finding algorithms ................................ 125 Appendix B Estimated Annual Number and Percentage of People Living with HIV at Each Stage of the HIV Continuum of Care ................................................................................. 128 Appendix C Original Distribution for the Annual Counts of Healthcare Utilizations ....... 132 Appendix D Adjusted predicted mean counts of healthcare utilization with 95% confidence intervals ............................................................................................................................... 135 x List of Tables Table 2.1. Annual estimates of attrition at each stage of the HIV continuum of care for PLWH with neither SUD nor mood/anxiety disorders in British Columbia, Canada, from 2001-2019. . 30 Table 2.2. Annual estimates of attrition at each stage of the HIV continuum of care for PLWH with SUD in British Columbia, Canada, from 2001-2019............................................................ 31 Table 2.3. Annual estimates of attrition at each stage of the HIV continuum of care for PLWH with mood/anxiety disorders in British Columbia, Canada, from 2001-2019. ............................. 32 Table 2.4. Annual estimates of attrition at each stage of the HIV continuum of care for PLWH with both SUD and mood/anxiety disorders in British Columbia, Canada, from 2001-2019. ..... 33 Table 2.5. Comparison of PLWH included and excluded in the study. ....................................... 34 Table 2.6. Clinical and sociodemographic characteristics of the study population ..................... 35 Table 2.7. Clinical and sociodemographic characteristics of PLWH in British Columbia, Canada, from 2001-2019, stratified by SUD and mood/anxiety disorder diagnosis status at (a) index year and (b) end of follow-up. .............................................................................................................. 39 Table 2.8. A multivariable model of the association between substance use and mood/anxiety disorders and the achievement of each stage of the HIV continuum of care. ............................... 44 Table 3.1. Distribution of the study population’s follow-up per year from index date to end of follow-up. ...................................................................................................................................... 55 Table 3.2. Comparison of people living with HIV included and excluded in the study. ............. 57 Table 3.3. Clinical and Sociodemographic characteristics of the overall study population. ....... 59 xi Table 3.4. Sociodemographic and clinical characteristics of people living with HIV and sustained suppression, stratified by diagnosis status of SUD and mood/anxiety disorder at (a) index year and (b) end of follow-up. ............................................................................................ 62 Table 3.5. Sociodemographic and clinical characteristics of people living with HIV and unsustained suppression, stratified by diagnosis status of SUD and mood/anxiety disorder at (a) index year and (b) end of follow-up. ............................................................................................ 66 Table 3.6. Median annual counts of healthcare utilizations among people living with HIV in British Columbia, Canada, stratified by the diagnosis status of SUD and mood/anxiety disorders in (a) 2001, (b) 2010, and (c) 2019. .............................................................................................. 72 Table 3.7. Median annual counts of healthcare utilizations among people living with HIV in British Columbia, Canada, stratified by sustained suppression in (a) 2001, (b) 2010, and (c) 2019............................................................................................................................................... 74 Table 3.8. Percentage of zeros observed in healthcare utilization. .............................................. 79 Table 3.9. Distribution of the number of viral load measurements per year for people living with HIV who had sustained and unsustained suppression. ................................................................. 79 xii List of Figures Figure 2.1. Flowchart outlining the process for including a sample of 14,398 PLWH in British Columbia, Canada, from 2001-2019. ............................................................................................ 26 Figure 2.2. The HIV continuum of care for PLWH with and without SUD and mood/anxiety disorders in British Columbia, Canada, from 2001-2019. ............................................................ 27 Figure 3.1. Flowchart outlining the process for including a sample of 9,757 people living with HIV in British Columbia, Canada, from 2001-2019..................................................................... 58 Figure 3.2. Adjusted predicted mean counts of healthcare utilization outcomes with 95% confidence intervals, stratified by diagnosis status of SUD and mood/anxiety disorders and sustained suppression. ................................................................................................................... 76 xiii List of Abbreviations ART = antiretroviral therapy BC = British Columbia BC-CA = BC Cancer Agency BC-CfE = BC Centre for Excellence in HIV-AIDS BC-MoH = BC Ministry of Health CI = confidence interval COAST = Comparative Outcome and Service Utilization Trends DTP = Drug Treatment Plan gbMSM = gay, bisexual, and other men who have sex with men ICD = International Classification of Disease LOS = length of stay MSP = Medical Services Plan PWID = people who inject drugs Q1-Q3 = 25th-75th percentile SUD = substance use disorder UNAIDS = United Nations Programme on HIV/AIDS VL = Viral Load xiv Acknowledgements COAST is funded by the Canadian Institutes of Health Research through an Operating Grant (#130419), a Foundation Award to RSH (#143342), and support from the BC Centre for Excellence in HIV/AIDS. Dr. Viviane Dias Lima is funded by a grant from the Canadian Institutes of Health Research (PJT-148595, #130419, #143342), and the Canadian Foundation for AIDS Research (CANFAR Innovation Grant – 30-101). I would like to express my appreciation to my research supervisor, Dr. Viviane Lima. I am grateful for her guidance, support and mentorship. I also would like to thank my thesis committee members, Drs. Robert S. Hogg and William Honer, for sharing their expertise with me and providing me with valuable feedback throughout the course of my studies. I am grateful to my colleagues in the EMBARC research group at the BC-CfE with special thanks to Nance Cunningham and Carly Magee for their help and support. I want to extend my appreciation to Clara Wang for her time, statistical expertise and ongoing support. I would like to thank the COAST study participants, BC Cancer Agency, BC Centre for Excellence in HIV/AIDS, BC Ministry of Health, BC Vital Statistics Agency, PharmaNet and the institutional data stewards for granting access to the data, and Population Data BC for facilitating the data linkage process. Finally, I was fortunate to have the support and encouragement of my parents, siblings and partner throughout this journey. I am grateful to them for always believing in me. 1 Chapter 1: Introduction 1.1. Problem Statement With the widespread availability of advanced antiretroviral therapy (ART), human immunodeficiency virus (HIV) has become a manageable life-long condition.1-3 Life expectancy among ART-treated people living with HIV (PLWH) is now similar to HIV-negative individuals.4 However, due to an excess burden of chronic comorbidities and socio-economic disparities, many PLWH disengage from HIV care and experience suboptimal health outcomes.5,6 Consequently, PLWH often have complex medical needs which promote high usage of healthcare services, especially in hospital settings.7-9 The resulting high healthcare utilization and associated costs for PLWH are a rising concern as healthcare costs among PLWH are greater than HIV-negative counterparts.7,10 Mental health and substance use disorders are some of the most burdensome comorbidities disproportionately affecting PLWH.5,6,11-13 In British Columbia (BC), Canada, approximately 54% of PLWH are diagnosed with at least one mental health disorder, and 30% are diagnosed with at least two during their lifetime.14 Mood and anxiety disorders are the most prevalent mental health conditions among PLWH; they account for up to 85% and 65% respectively of all mental health disorders within this population.14-16 The prevalence of substance use disorder (SUD), the problematic use of alcohol or drugs, is also substantially elevated among PLWH.17-21 For instance, alcohol use disorder, the most prevalent SUD, affects approximately 42% of PLWH in developed countries.18 The high prevalence of mood, anxiety and substance use disorders among PLWH calls for a thorough investigation of their effects on HIV care uptake, treatment outcomes, and healthcare utilization within this population. 2 Previous findings indicate that these disorders are linked to delayed HIV testing and diagnosis, delayed ART initiation, missed healthcare appointments, incomplete ART adherence, adverse health outcomes, and high healthcare utilization and costs.22-27 The adverse effects of mood, anxiety and substance use disorders on HIV care uptake and treatment outcomes can also impede global control of the HIV/AIDS epidemic. To control the HIV epidemic, the Joint United Nations Programme on HIV/AIDS (UNAIDS) has set the 95-95-95 by 2025 Target. To meet this globally mandated target, all countries must ensure that by 2025, 95% of all their PLWH are diagnosed with HIV, 95% of their diagnosed PLWH are receiving ART, and 95% of their PLWH are virally suppressed (i.e., having an undetectable/untransmittable viral load [VL]).28 According to UNAIDS, achieving the 95-95-95 by 2025 Target will bring the end of the AIDS epidemic as a global health concern by 2030.29,30 Thus, determining the effects of mood and anxiety disorders and SUD on HIV care engagement and treatment outcomes is essential for ending HIV/AIDS as a public health threat. 1.2. Definitions and Framework This section defines mood, anxiety, and substance use disorders and provides an overview of their risk factors in the context of PLWH. As the main framework of this study, the HIV continuum of care is also described in detail to provide a better understanding of HIV care engagement and treatment process. Mood and Anxiety Disorders Mood disorders, which include depressive and bipolar disorders, are characterized by fluctuations in mood and disturbance in the emotional state that cause extreme lows (depression) and highs 3 (mania).31,32 Anxiety disorders, defined by excessive and persistent worry and fear, encompass generalized anxiety, social anxiety, obsessive-compulsive, panic, post-traumatic stress, and phobia-related disorders.33 Mood and anxiety disorders are distinct categories of psychiatric conditions. However, they frequently occur together such that having either mood or anxiety disorder significantly increases the risk of having the other.34 In BC’s health records data, mood and anxiety disorders are coded under one BC-specific diagnostic code (50B).35 Therefore, in this thesis, mood and anxiety disorders are studied as one category of disorders and are henceforth referred to as mood/anxiety disorders. The high prevalence of mood/anxiety disorders among PLWH is attributed to experiences of HIV-related stigma,36 discrimination, internalized stigma and shame,37 histories of trauma, adverse childhood experiences,38 unemployment or low income,39 reduced functioning, and other mental and physical health concerns.14,39 Findings suggest that among PLWH, females,39-46 younger individuals,5,14,39,41,46,47 those with Indigenous ancestry,14 gay, bisexual, and other men who have sex with men (gbMSM),41,44,48,49 and people who inject drugs (PWID)15,46,50,51 are disproportionately affected by mood/anxiety disorders. Substance Use Disorder Substance use disorder (SUD) is a treatable medical condition that impacts a person’s cognition and behaviour, leading to the compulsive use of illicit or legal substances, alcohol or medications.52 According to 2015 estimates, 21% (approximately 6 million) of Canadians suffer from SUD throughout their lifetime.53 In 2019, it was reported that among Canadians 15 years and older, over 18% (5.4 million) engaged in problematic drinking, and 3% (1.1 million) used at least one of the following illegal drugs: cocaine, crack, heroin, speed, methamphetamines, ecstasy, hallucinogens, 4 inhalants and salvia.54 The prevalence of SUD is exceptionally high among PLWH.18,21 A longitudinal cohort study of PLWH in the United States (US) has estimated a prevalence of 48% for SUD.21 A meta-analysis study has estimated that alcohol use disorder affects 42% of PLWH in developed countries.18 Furthermore, in a cross-sectional Canadian survey, approximately 22% of women living with HIV reported having a substance use disorder.19 Alcohol, marijuana, opioid, benzodiazepine and stimulant use disorders are some of the most common SUDs among PLWH.17,55,56 The high prevalence of SUD among PLWH is a significant concern, given its strong associations with high morbidity and mortality.57 People with SUD are at a high risk for chronic comorbidities, infectious diseases, and mental disorders.57 For example, alcohol and tobacco use are significant risk factors for cardiovascular diseases, diabetes and cancers (e.g., liver and breast cancers).57-59 The use of other substances, such as heroin, stimulants, methamphetamine, and cocaine, is also highly associated with cardiovascular diseases.57 As another example, the risk of hepatitis C infection substantially increases with injection drug use.57 It is worth noting that people with SUD experience socioeconomic disparities, such as poverty, food insecurities and homelessness, that further increase their risk for adverse health outcomes and chronic diseases.57,60 Comorbid Mood/Anxiety Disorders and SUD Comorbidity (the co-occurrence) of mental health disorders and SUD, also referred to as concurrent disorders and dual diagnosis, is common.61 According to the Canadian Centre on Substance Use, about 50% of people with SUD also have a mental health disorder, and 15-20 % of people with mental health disorders also have SUD.62 The prevalence of comorbid mental health disorders and SUD is also substantially high among PLWH.5,63 It is estimated that 10-28% of PLWH have comorbid mental health disorder and SUD.63 A study of women living with HIV 5 found that 68% of those ever diagnosed with a mood disorder also had at least one SUD diagnosis, while 40% of women with SUD also had a mood disorder diagnosis.5 The same study found that over 60% of those with SUD also had an anxiety disorder and vice versa.5 The literature provides several reasons for the co-occurrence of mood/anxiety disorders and SUD. First, mood/anxiety disorders and SUD are risk factors for each other, and one may be directly or indirectly caused by the other.63-65 For instance, heavy alcohol consumption may directly lead to depression among people with alcohol use disorder.64 Also, SUD may indirectly arise when individuals use substances to relieve symptoms of mental health disorders as a way of coping or self-medicating.64-66 It is estimated that in 75% of people with both SUD and anxiety disorders, the anxiety disorder occurred first.65 Drugs of choice among people who experience certain psychiatric symptoms also support the self-medication pathway.66 For instance, individuals with symptoms, such as rage and aggression, may use opioids (depressants), while those with depression are more likely to use cocaine (stimulant).66 The co-occurrence of SUD and mood/anxiety disorders may also be due to several hereditary and socio-economic (e.g., poverty and traumatic experiences) risk factors that these disorders share.63-65 The HIV Continuum of Care Framework This study uses the HIV continuum of care framework to determine the impact of mood/anxiety disorders on HIV care engagement. The HIV continuum of care outlines the sequential stages of HIV care that PLWH go through, from the diagnosis of HIV to the latter stages of achieving and sustaining viral suppression.67-70 The continuum of care allows us to identify attritions in the process of treating PLWH and achieving viral suppression. Attritions are marked by the stages at which PLWH disengage from HIV care. The continuum of care model, also referred to as the 6 cascade of care model, is utilized to monitor public health outcomes of PLWH, evaluate HIV programs, and compare progress through time and across different settings. However, the continuum stages included in other studies and their corresponding definitions vary depending on data availability and jurisdictions.70,71 Some data sources include diagnosis as the earliest stage of the continuum.68,71 However, this stage is excluded in many studies that develop the HIV continuum of care for people already diagnosed with HIV.72-74 As a result, these variations often prevent meaningful comparisons across settings.70 Therefore, UNAIDS calls for a unified HIV continuum of care definition which is consistent with the 95-95-95 target, and includes the stages of HIV diagnosis, receiving ART and achieving viral suppression.75 Worldwide, studies have used the continuum of care framework to reveal deficiencies in HIV care delivery. In Europe and Central Asian countries, the highest attrition in the HIV continuum of care was found at HIV diagnosis, and attrition at subsequent stages of the continuum after HIV diagnosis is less of a concern.71 However, in North America, engaging diagnosed PLWH in HIV care and achieving viral suppression seems to be more of a challenge.68,72,74,76,77 From 1996 to 2011, although the proportion of PLWH who reached each consecutive stage of the HIV continuum of care in BC increased significantly, attritions still existed; the largest appeared to be at the stages of retention in HIV care and viral suppression.68,72,74,76,77 According to the BC Centre for Excellence in HIV/AIDS (BC CfE)’s annual reports, from 2019 to 2023, less than 59% of diagnosed PLWH in BC achieved viral suppression.73,78-81 1.3. Study Justification Previous studies have identified mental health and substance use disorders as factors contributing to delayed HIV diagnosis and ART initiation, suboptimal ART adherence, and increased 7 healthcare utilization and costs.82-96 There is also evidence suggesting that mood/anxiety disorders and SUD can synergically interact with each other to impede progress through the HIV continuum of care.89-91 Although some studies have examined the relationship between mood/anxiety disorders and SUD on various HIV care outcomes and healthcare usage and expenditures,89-91,94-96 comprehensive longitudinal research examining the separate and combined effects of these disorders on the HIV continuum of care and healthcare utilization of PLWH is lacking. The relationship between attrition in the HIV continuum of care and healthcare utilization of PLWH with mood/anxiety disorders and SUD has also not been thoroughly assessed. Therefore, this thesis addresses some gaps in the literature by examining the HIV continuum of care for PLWH with and without mood/anxiety disorders and SUD and identifying the points of highest attrition for these individuals. In addition, this thesis assesses the impacts of mood/anxiety disorders and SUD on the healthcare utilization of PLWH who disengage from HIV care at the critical point of attrition, and of PLWH who remain in care. 1.4. Study Setting The studies in this thesis are population-based retrospective cohort studies that utilized longitudinal data from all diagnosed PLWH in BC, Canada, from 2001 to 2019. In BC, PLWH have free-of-charge access to ART and laboratory monitoring (e.g., VL measurements) through the Drug Treatment Plan (DTP). The DTP, administered by the BC-CfE,97 provides HIV treatment in accordance with BC’s HIV therapeutic guidelines,98 while also collecting demographic, clinical, and treatment data on its clients.97 Furthermore, all BC residents are medically insured by the Medical Services Plan (MSP), which covers the cost of all necessary medical services.99 8 The data used in this thesis were obtained from the ongoing Comparative Outcome And Service Utilization Trends (COAST) study, which contains linkages to the DTP registry and other administrative databases held by Population Data BC.100 These administrative databases capture individual-level health records data from real-time clinical practices. COAST contains healthcare utilization and mortality data from all diagnosed PLWH in BC from April 1st, 1992, to March 31st, 2020.100 Additional PLWH not enrolled in the DTP were identified using a validated highly specific case-finding algorithm which requires one of the following: 1) five HIV-related healthcare practitioner visits within a 12 month period, (2) two HIV-related hospitalizations within a 12-month period, or (3) one hospitalization with HIV as the most responsible diagnosis.101 1.5. Research Objectives and Hypotheses The purpose of this thesis is to assess the impact of mood/anxiety disorders and SUD on the HIV continuum of care and healthcare utilization of PLWH. The specific aims and hypotheses of this investigation are as follows: Aim 1: To assess the impact of the syndemic between mood/anxiety disorders and SUD on the HIV continuum of care for PLWH in BC, and to identify the stage with the highest attrition in the continuum. Chapter 2 will develop separate HIV continua of care for PLWH with mood/anxiety disorder, SUD, both disorders and neither disorder, will identify the point of highest attrition for each group, and will measure the association between these disorders and the achievement of each stage of the HIV continuum of care. I hypothesized that, for PLWH with mood/anxiety disorder, SUD or both, the highest attrition in the HIV continuum of care occurs at the stage of ART adherence and that mood/anxiety disorders and SUD are associated with attritions at each stage of the HIV continuum of care. 9 Aim 2: To examine the impact of mood/anxiety disorders and SUD on the utilization of different healthcare services among PLWH in BC, Canada, who disengage from HIV care at the point of highest attrition identified in Aim 1, and among PLWH who remain in care. Chapter 3 measures the separate and combined impacts of mood/anxiety disorders, SUD, and both disorders, and disengagement from HIV care on counts of physician visits, laboratory visits, hospitalizations and length of hospital stays among PLWH. My hypothesis was that having both disorders while disengaging from HIV care at the point of highest attrition identified in Aim 1 is associated with the highest increase in the healthcare utilization of PLWH. 1.6. Empirical Evidence This section summarizes the literature related to (a) key HIV care and treatment outcomes among PLWH who have mood/anxiety disorders, SUD, or both, (b) attritions in the HIV continuum of care and correlates of attrition for PLWH, (c) healthcare utilization of PLWH who have mood/anxiety disorder, SUD or both and PLWH who disengage from HIV care and experience poor HIV outcomes. Mood/Anxiety Disorder, SUD and ART Initiation ART initiation is an early stage of the HIV continuum and an essential step toward viral suppression and optimal health outcomes. Previous studies examining the effects of mood/anxiety disorders on ART initiation have yielded mixed results depending on their study population and the type and severity of the mood/anxiety disorders studied. In a study of Canadian women living with HIV, depression was mildly associated with increased odds of ART initiation.92 Similarly, 10 some studies of PLWH in low and middle-income countries found that individuals with depression and anxiety symptoms were more likely to initiate ART.102,103 It is suggested that PLWH may be encouraged to initiate ART when they seek medical care for their depressive symptoms.92 On the contrary, a few South African studies have identified depression and anxiety symptoms as barriers to ART initiation, especially if the symptoms are more severe.22,82 The literature has identified SUD as a barrier to ART initiation among PLWH. For instance, a study in the United Kingdom (UK) found that injection drug use was associated with delayed or non-initiation of ART.104 Similarly, a Russian study identified significant associations between opioid use and reduced odds of ART initiation.105 Furthermore, a few studies in the US found that PLWH with high alcohol consumption were less likely to be prescribed with ART.106-108 Factors inhibiting ART initiation may be patient or provider-related. Providers are sometimes hesitant to prescribe ART for PLWH with SUD due to their concern about incomplete ART adherence causing ART drug resistance.109 Additionally, the stigma associated with SUD often prevents people from receiving appropriate healthcare.109 Alternately, various individual-level barriers may lead to delayed or non-ART initiation among PLWH. According to a systematic review, fearing the risk of HIV status disclosure, financial barriers, housing instability, transportation costs, low education and awareness about HIV, misconceptions about ART, internalized stigma, perceived health status, lack of social support, challenges with scheduling appointments and long waiting times are individual-level barriers to ART initiation.110 Mood/Anxiety Disorder, SUD and ART Adherence Adherence to ART medication is a stage of the HIV continuum of care necessary for viral suppression.111 The majority of studies have concluded that mood/anxiety disorders are associated 11 with incomplete ART adherence among PLWH.84,93,112-122 Among some groups of PLWH, including gbMSM and women, depression and anxiety symptoms have been identified as barriers to ART adherence.114-119 Overall, positive associations between depression and sub-optimal ART adherence are consistently evident within the literature.84,120,123 In a qualitative study of PLWH in Canada and France, PLWH and their healthcare providers listed depressive symptoms as barriers to ART adherence.112 Studies indicate that the probability of suboptimal ART adherence is even higher when depressive and anxiety symptoms are more severe.113,122,123 While the relationship between depression and suboptimal ART adherence is consistent across country income levels and study designs (cross-sectional studies, cohort studies, and randomized trials), the strength of the association has decreased in recent publications and with the use of larger sample sizes.84 However, it is also worth noting that ART drugs used in earlier years were associated with more adverse psychiatric side effects, which may have induced symptoms of mood and anxiety disorders.124 Previous studies have also identified SUD as a significant predictor of incomplete ART adherence.85,125,126 Studies have identified strong associations between alcohol, cocaine, and heroin use and reduced ART adherence.85,125,126 One study has found a dose-response relationship between alcohol consumption and non-adherence to ART.125 Although a large body of literature did not find significant associations between cannabis use and increased risk of non-adherence,125 a recent prospective study of PLWH aged 40 years and older found that cannabis use was associated with suboptimal ART adherence.127 It is suggested that non-adherence among PLWH with SUD may be intentional or non-intentional. For instance, the adverse effects of substances on cognition and memory may lead to unintentional non-adherence, while interactive toxicity beliefs (i.e., believing that the interaction of substances and ART causes toxicities) can cause intentional 12 non-adherence.85 It is worth noting that the definition of ART adherence varies across the literature since the percentage of ART adherence required to achieve optimal health outcomes has changed over time with advancements in the available ART treatments.85,111,125,126,128 Mood/Anxiety Disorder, SUD and Viral Suppression The objective of ART is the later stage of the HIV continuum of care, viral suppression, which promotes immune function for PLWH and prevents the transmission of HIV.129 As the final measure of the UNAIDS’ 95-95-95 Target, the percentage of virally suppressed PLWH within a population is a crucial indicator of success in controlling the HIV epidemic.129 Therefore, determining the relationship between mood/anxiety disorders and SUD and viral suppression is crucial. It is important to note that the VL threshold used to define viral suppression varies across the literature.90 130,131 Thus, caution is needed for study comparisons. Research examining the relationship between mood/anxiety disorders and viral suppression has yielded mixed results depending on the type of mood/anxiety disorder examined and the severity and treatment status of these disorders. Studies suggest that mood disorders, such as depressive and bipolar disorders, are significantly associated with having an unsuppressed VL.90,130,132 One study has estimated that the risk of having a detectable VL of ≥75 copies/mL is 28% higher among PLWH who experience depressive symptoms.130 Another study indicates that PLWH with bipolar disorders are more likely to have a detectable VL of ≥ 400 copies/mL, compared to PLWH with major depressive disorders or PLWH without mood disorders.131 Studies have also suggested that although untreated depression is associated with a higher risk of non-suppression, the association is weaker and insignificant for treated depression.90,132 13 While mood disorders are generally associated with higher VLs, the relationship between anxiety disorders and viral suppression is unclear. One study has found that those with moderate to severe anxiety are more likely to have an unsuppressed VL of ≥400 copies/mL.133 However, another study found that anxiety disorders were associated with less time spent with a VL of ≥200 copies/mL.90 This protective effect, which is more substantial among those with treated anxiety disorders, can be due to better ART adherence and attentiveness to treatment regimens among people with non-disabling anxiety disorders.90 Therefore, viral suppression may become more likely with the proper management of anxiety disorders among PLWH. The literature has established that SUD is associated with viral non-suppression.134,135 For instance, a retro-respective cohort study of PLWH in Maryland, US, found strong associations between cocaine and opioid use disorder and viral non-suppression. However, this study found weaker associations after adjusting for mental health symptoms.135 In another study of PLWH in the US, alcohol use disorder was associated with unsuppressed VLs.136 According to the literature, factors impeding viral suppression among PLWH with SUD include incomplete ART adherence and direct effects of substances on ART metabolism and HIV disease progression, which can prevent viral suppression.137,138 Mood/Anxiety Disorders, SUD and Sustained Viral Suppression The ultimate goal of HIV care is not only the achievement of viral suppression but also its sustainment since long-term suppression is essential for optimizing health outcomes for PLWH and minimizing the risk of HIV transmission.137,139 Hence, in this thesis, sustained suppression is included as the final stage of the HIV continuum of care and is defined as having a suppressed (undetectable) VL for all documented VL measurements within a calendar year.69,140 14 The literature suggests that mood/anxiety disorders are associated with viral rebound (i.e., having detectable VL after a period of suppression). For example, a few studies in the US have found significant associations between mood and anxiety disorders and reduced likelihood of sustained viral suppression.46,141 In a cohort study of PLWH in the US who had achieved viral suppression, depression and other mental disorders were associated with earlier virologic failure.142 Likewise, in a study of PLWH in the UK, mood and anxiety disorders were identified as strong predictors of viral rebound.143 However, one older study did not find significant associations between depression and sustained suppression.144 Previous studies have identified SUD as a barrier to sustained suppression. A prospective cohort study of PLWH in Canada found that heroin injection, crack use and heavy alcohol use were significant risk factors for viral rebound.138 Another Canadian cohort study also found that PLWH with a history of injection drug use were at a higher risk of viral rebound.137 Similarly, studies in the US have identified cocaine use, alcohol consumption, and stimulant use as factors associated with a lack of durable viral suppression.126,134,135 In the literature, the associations between SUD and unsustained viral suppression have been mainly attributed to the impeding effects of these disorders on ART adherence.126,134,135 Other Correlates of Attrition in the HIV Continuum of Care In addition to mood/anxiety disorders and SUD, other socio-demographic factors can impede ART initiation, adherence and viral suppression among PLWH and can contribute to attritions in the HIV continuum of care. Therefore, other correlates of attrition must be identified and considered to allow for a more accurate estimate of the contribution of SUD and mood/anxiety disorders. 15 Previous Canadian studies suggest that females, younger individuals and PLWH with low household income and housing instability experience the highest attrition across the HIV continuum of care.76,77,83,145 According to survey reports, Canadian women and transgender women living with HIV experience the highest attritions at the stages of ART initiation and adherence.83,145 In Ontario, differences in attrition estimates between males and females were minor, while the differences between age groups were considerable, with younger individuals experiencing higher attritions across the continuum of care.77 Regardless of sex or gender, estimates of attritions across the continuum of care have been the highest among younger age groups, particularly those less than 30 years old.101, 104, 146 However, some studies in BC suggest that older age is associated with delayed ART initiation.147 Studies have also identified associations between HIV acquisition risk categories and attritions in the HIV continuum of care. Recent evaluations of the HIV continuum of care in BC show that compared to other sub-populations of PLWH, gbMSM experience the highest attrition across the HIV continuum of care.148 However, in an older study of PLWH in BC, PWID were more likely to experience attritions than gbMSM, particularly at the stages of receiving ART and viral suppression.76 In a study of women living with HIV, those with injection drug use were less likely to be on ART.149 Study findings are also indicative of geographic heterogeneity in HIV care continuity.76,146 For instance, compared to those living in the more urbanized Vancouver Coastal regions, the likelihood of experiencing attrition at every stage of the HIV continuum of care is higher among those living in Northern BC.76 Impacts of disengagement from HIV care on Healthcare Utilization 16 A substantial number of studies have identified suboptimal ART adherence and viral non-suppression as factors contributing to high healthcare utilization among PLWH.26,27,150-152 Findings suggest that non-adherence to ART is associated with more frequent emergency department visits, hospitalizations, hospital readmissions, and extended hospital stays.26,27,150 One study of PLWH in the US has estimated that PLWH with optimal ART adherence were 43% less likely to be hospitalized than those with suboptimal adherence.151 Similarly, a study in BC estimated that non-adherent PLWH were 1.88 times more likely to be hospitalized than adherent individuals.153 Overall, studies suggest that adherence to ART and achieving viral suppression are associated with less frequent usage of medical services and reduced healthcare costs among PLWH.27,154 It is estimated that this reduction in healthcare costs compensates for the medical expenses of sustained ART use and reduces the overall healthcare costs for PLWH.154 However, one Canadian study suggests that the ART-induced reduction in medical expenses does not counterbalance the higher healthcare costs associated with earlier initiation and long-term use of ART.155 Nevertheless, timely ART initiation is considered cost-effective due to its ability to improve the quality of life for PLWH and prevent the transmission of HIV.156,157 Impact of Mood/Anxiety Disorder and SUD on Healthcare Utilization A large body of literature has examined the impact of SUD and mood/anxiety disorders on healthcare utilization and costs within the general population. The majority of the literature has concluded that SUD and mood/anxiety disorders are associated with increased use of primary care services, higher risks of hospitalizations, longer hospital stays and higher medical costs.158-164 However, some of the studies examining the impacts of anxiety disorders on healthcare utilization have yielded mixed results. There are a few studies indicating that some anxiety disorders, such as 17 social and general anxiety disorders or medical fear-related anxiety disorders, may lead to decreased use of healthcare services.159 It is explained that characteristics of anxiety disorders, such as reassurance-seeking and avoidant behaviours, can lead to both increased and reduced use of healthcare services. For example, people with health-related anxiety disorders may excessively seek reassurance from healthcare professionals and have higher primary healthcare utilizations, while those with anxiety disorders related to fear of medical procedures (e.g., injection) may avoid healthcare.159 Although the impact of mood/anxiety disorders and SUD on the healthcare utilization of PLWH is not as widely studied as in the general population, there is evidence suggesting that these disorders are also correlated with high healthcare utilization and costs among PLWH.94-96 For instance, a study of PLWH in California, US, found that mood/anxiety disorders were associated with increased mental and non-mental health related healthcare costs.96 Furthermore, in a longitudinal prospective cohort study of PLWH in Ontario, depression alone and depression combined with recreational drug use were significantly associated with an increased hazard for hospital admissions.94 According to a systematic review, alcohol use disorder among PLWH has been associated with increased use of hospital services, especially in more marginalized groups of PLWH, such as individuals experiencing homelessness.165 In addition to SUD and mood/anxiety disorders, socio-economic and structural barriers are significant determinants of healthcare utilization among PLWH. Previous studies have identified low income, housing instability, homelessness, and food insecurity as factors contributing to the high utilization of emergency and acute care hospital services among people with HIV and SUD.166-168 Other structural barriers such as transportation issues, distance to healthcare facilities, treatment delays, inadequacy of care, refusal of care by healthcare providers, and stigma associated 18 with HIV and SUD in healthcare settings often prevent PLWH from seeking healthcare until they have to seek care for medical emergencies.169 1.7. Thesis Summary This thesis consists of four chapters. This current chapter provides the rationale for the studies conducted in this thesis and outlines their aims. Furthermore, this chapter offers an overview of the current literature related to the effects of mood/anxiety disorders and SUD on key HIV care and treatment outcomes and healthcare utilization of PLWH. Chapter 2 addresses the first aim of this thesis by identifying the point of highest attrition in the HIV continuum of care for PLWH with mood/anxiety disorder, SUD, and both disorders, and by examining the association between these disorders and the achievement of each stage of the HIV continuum of care. Chapter 3 addresses the second aim of this thesis by comparing the healthcare utilization of PLWH with mood/anxiety disorders, SUD, both disorders and neither disorder who disengage at the stage of high attrition identified in Aim 1, and of those who remain in care at that stage. Chapter 4 summarizes the key findings and the strengths and limitations of the studies presented in Chapter 2, and Chapter 3 and outlines the public health implications of these studies for public health policies and interventions. 19 Chapter 2: The Impact of Substance Use and Mood/Anxiety Disorders on the HIV Continuum of Care in British Columbia, Canada, from 2001 to 2019 2.1. Introduction Despite the availability of highly effective antiretroviral therapy (ART) and improved health outcomes for people living with HIV (PLWH), this population is disproportionately affected by mental health and substance use disorders that hinder their sustained engagement with HIV care.5,6 In British Columbia (BC), Canada, approximately 54% of PLWH are diagnosed with at least one and 30% with at least two mental health disorders during their lifetime.14 Mood and anxiety disorders are the most common mental health disorders, accounting for approximately 85% and 65% of all psychiatric diagnoses within this population respectively.14 The prevalence of substance use disorder (SUD), the problematic use of alcohol or drugs, is also substantially high among PLWH.18,170 The most common SUD, alcohol use disorder, affects approximately 40% of PLWH in Canada and other developed countries.17,18 Besides alcohol, opioid, benzodiazepine and stimulant use disorders are some of the most prevalent SUDs among PLWH.17,55,56 In particular, injection drug use is estimated to affect approximately 17% of PLWH in Canada.171 Moreover, SUD, mood, and anxiety disorders often occur as comorbid conditions since they are risk factors for each other and share genetic and socio-economic risk factors such as poverty.64 Previous studies suggest that mood and/or anxiety disorders (hereafter referred to as mood/anxiety disorders) and SUD contribute to delayed HIV testing and diagnosis, late ART initiation, incomplete ART adherence, hospitalizations, increased healthcare utilization costs, and mortality among PLWH.82-88 The adverse impacts of these disorders on ART uptake can also impede achieving the globally mandated target to end AIDS as a public health threat. In 2021, the 20 Joint United Nations Programme on HIV/AIDS (UNAIDS) introduced the 95-95-95 by 2025 Target, recommending that, by 2025, all countries ensure that 95% of all their PLWH are diagnosed, 95% of those diagnosed are receiving ART, and 95% of those receiving ART are virally suppressed (i.e., undetectable viral load [VL]). UNAIDS predicts that achieving the 95-95-95 by 2025 Target will bring about the “end of the HIV/AIDS pandemic” as a global public health concern.29,30 Thus, determining the impact of mood/anxiety disorders and SUD on HIV care uptake and success is essential for meeting the UNAIDS Target and ending the global AIDS epidemic. Numerous studies have examined the relationship between mood/anxiety disorders, SUD, and HIV-related outcomes separately.89-91 There is also literature suggesting that these disorders synergistically interact with each other (i.e., syndemic) to hinder progress through the HIV continuum care.172 However, comprehensive research on the impact of these disorders on the HIV continuum of care is lacking. The HIV continuum of care is a framework that outlines the dynamic and subsequent stages of HIV care, from HIV diagnosis to the final stages of achieving and sustaining viral suppression.68,70 This study aims to assess the impact of the syndemic between SUD and mood/anxiety disorders on the HIV continuum of care for PLWH in BC and to identify the stage with the highest attrition in the continuum. 2.2. Methods Study Setting and Data Source In BC, people diagnosed with HIV have free-of-charge access to ART and routine laboratory (VL and CD4 blood markers) monitoring through the Drug Treatment Program (DTP) registry operated by the BC Centre for Excellence in HIV/AIDS (BC-CfE).97 Besides providing HIV treatment 21 according to BC’s HIV therapeutic guidelines, the DTP collects demographic, clinical, and treatment data.97 This retrospective population-based cohort study utilizes longitudinal individual-level data from the ongoing Comparative Outcomes And Service Utilization Trends (COAST) study developed through linkages between BC-CfE's DTP and various province-wide health administrative datasets held by Population Data BC.100 The COAST study provides healthcare utilization and mortality data on all diagnosed PLWH from April 1992 to March 2020. Diagnosed PLWH are identified using a previously validated, highly specific case-finding algorithm.101 COAST also contains data on a 10% random sample of BC's general adult population, but I did not use this dataset in this study. The COAST cohort profile describes the study cohort and the linked datasets in detail.100 Study Population Eligible individuals were 19 years and older. The index date was the latest of the following dates: HIV seropositive status defined by the first HIV-related record (i.e., VL test, ART initiation, HIV-related International Classification of Disease [ICD] codes in BC's Medical Services Plan [MSP] or hospitalization records), 19th birthday or January 1, 2001. Eligible individuals were followed until the earliest of the following dates: death, last healthcare contact, or December 31, 2019. Individuals who participated in clinical trials were censored during their participation. Exposure Variable Cases of mood/anxiety disorders and SUD were identified in health administrative records using the BC Ministry of Health's case-finding algorithms that include the ICD codes for mood/anxiety 22 disorders and SUD (Appendix A).35,173 Note that, since in BC's MSP data, mood and anxiety disorders are coded under one BC-specific diagnostic code (50B),35 these disorders had to be combined into one disease category. Some studies have considered mood/anxiety disorders and SUD as syndemic conditions, suggesting that their interaction amplifies their adverse impacts on HIV outcomes.113,172 Hence, I used a categorical exposure variable to assess the individual and combined effects of mood/anxiety disorders and SUD on the HIV continuum of care. For each calendar year, the exposure variable was: (1) having neither SUD nor mood/anxiety disorders, (2) having only SUD, (3) having only mood/anxiety disorders, and (4) having both SUD and mood/anxiety disorders. Cases of these disorders were ascertained yearly by using a five-year look-back window, which was selected as per previous studies.174 Thus, these disorders were assumed to be present if they had a record of diagnosis in the five years before the year of interest. Study Outcomes Our outcome variables included the achievement (yes/no) of the following stages of the HIV continuum of care: (1) ART initiation, (2) On-ART, (3) ART adherence, (4) Viral suppression, and (5) Sustained suppression. I determined the number of individuals at each stage of the HIV continuum of care annually, from 2001 to 2019, using ART dispensation records and VL measurements. The continuum stages were defined in accordance with the criteria used in previous studies. ART initiation was defined as having any record of ART dispensation during or at any point before the calendar year of interest.83 Being on-ART was described as being on ART for at least 30 days per year.69 The number of days on ART is equivalent to the number of days an individual was dispensed ART medications. The proportion of days in a calendar year that a person was on ART was used to determine ART adherence.68,69 Before 2014, adherence to ART was 23 defined as having 95% adherence in a calendar year since this level of adherence was required to achieve viral suppression.128 From 2014 onwards, the adherence level for viral suppression was reduced to a minimum of 80% due to the introduction and widespread use of more effective ART.111 The fourth continuum stage was viral suppression, defined by having the last VL in the calendar year <200 copies/mL.140 Since the goal of ART is long-term viral suppression, examining one VL within a calendar year to define suppression is too liberal. Therefore, the fifth stage, sustained suppression, was added to the continuum and was defined by having all VLs in the calendar year <200 copies/mL.69 In the annual estimates, PLWH who met the criterion of a later stage without records of achieving its preceding stages in the same year were assumed to have also completed the previous stages for that particular year. I assumed that individuals with missing ART dispensation records and VL measurements in a particular year did not meet the criteria for that specific year. Potential Confounders Potential sociodemographic confounders were age (19-29, 30-39, 40-49 and 50+ years), gender (women, men), use of income assistance in the past five years (no, yes, unknown), regional Health Authority of residency (Vancouver Coastal, Fraser, Vancouver Island, Interior, Northern, and unknown), and residency in the Vancouver Downtown Eastside (DTES) (no, yes, unknown). In BC, regional Health Authorities are responsible for delivering health services to the population residing within their geographic regions.175 DTES is a neighbourhood within the city of Vancouver characterized by social and economic inequities and is one of the epicentres of the HIV epidemic among people who have ever injected drugs.176,177 Use of income assistance was determined based on records of drug dispensation (excluding ART) under the PharmaCare Plan C, a BC-wide 24 program covering 100% of prescription costs for low-income residents of BC.178 A sensitivity analysis was performed to identify the optimum number of years for the look-back observation period of the income assistance variable, and a five-year look-back window was selected. Other confounders were index year or ART initiation year (continuous, depending on the outcome) and HIV transmission group (people who inject drugs [PWID], gay, bisexual, and other men who have sex with men [gbMSM], PWID/gbMSM, heterosexual/other, unknown). HIV transmission group was reported by the individual or a physician. For the stage of ART initiation, the index year represented the cohort effect; for the proceeding stages, ART initiation year was selected to measure the cohort effect. The HIV transmission group variable was excluded from the multivariable analysis due to having a high proportion of unknowns and multicollinearity with residency in the DTES and diagnosis of SUD. Data Analysis As part of the descriptive analysis, I calculated the number of people who met the definition of each stage of the HIV continuum of care annually from 2001 to 2019. I estimated attrition at each stage of the continuum by dividing the number of people who did not meet the criteria for each stage by the number of people who completed the previous stage. I also calculated the proportion of PLWH who sustained suppression each year by dividing the number of people with sustained suppression by the total number of PLWH. I stratified the number of PLWH at each stage of the HIV continuum of care, the percentage of attrition at each stage, and the overall percentage of PLWH who sustained suppression by mood/anxiety disorders and SUD diagnosis status. Categorical and continuous covariates were compared using the χ2 and Kruskal-Wallis tests, respectively.179 I used a generalized linear mixed effects model, assuming a binomial 25 distribution, logit link function and a random intercept, to assess the association between SUD and mood/anxiety disorders and the achievement of each stage of the HIV continuum of care while controlling for potential confounders.180,181 In the multivariable analyses, individuals with missing ART dispensation records or VL measurements were excluded. Confounders for the final model were selected through a backward elimination approach, as described in previous publications.88 I started with the full model and omitted confounding variables one at a time until the change in the coefficient for the exposure variable was ≥ 5%. All statistical analyses were conducted using SAS version 9.4. 2.3. Results The HIV continuum of care was annually evaluated for 14,398 diagnosed PLWH enrolled in COAST from 2001-2019. Figure 2.1 presents the step-by-step inclusion process. Figure 2.2 displays the estimated stages of the HIV continuum of care for PLWH with (a) neither SUD nor mood/anxiety disorders, (b) only SUD, (c) only mood/anxiety disorders, and (d) both SUD and mood/anxiety disorders. The annual estimated numbers and percentages of PLWH at each stage of the HIV continuum of care for all four groups are presented in Appendix B. Over time, progress to all stages of the HIV continuum of care has drastically improved for PLWH, regardless of their SUD and mood/anxiety disorder diagnosis status. However, PLWH who had SUD or both SUD and mood/anxiety disorders have been consistently less successful in achieving the stages of ART adherence and sustained suppression. 26 Figure 2.1. Flowchart outlining the process for including a sample of 14,398 PLWH in British Columbia, Canada, from 2001-2019. 27 Figure 2.2. The HIV continuum of care for PLWH with and without SUD and mood/anxiety disorders in British Columbia, Canada, from 2001-2019. 28 29 The percentages of attrition at each step of the HIV continuum of care from 2001 to 2019 are presented in Tables 2.1-2.4. Annual trends also show that, over time, attrition at each stage of the HIV continuum of care has decreased for all PLWH regardless of their SUD and mood/anxiety disorder diagnosis status. However, attrition at the stage of sustained suppression remains high for all PLWH and is the highest for PLWH with SUD. In 2019, for example, for all PLWH, achieving viral suppression after adherence was the most successful step, with only 1-3% attrition. In contrast, for all PLWH, sustained suppression was the most challenging stage of the continuum of care, attrition at this stage being the highest for PLWH with SUD (23%) and both SUD and mood/anxiety disorders (21%). 30 Table 2.1. Annual estimates of attrition at each stage of the HIV continuum of care for PLWH with neither SUD nor mood/anxiety disorders in British Columbia, Canada, from 2001-2019. Year Attrition at ART Initiation (%) Attrition at On-ART (%) Attrition at ART Adherence (%) Attrition at Viral Suppression (%) Attrition at Sustained Suppression (%) 2001 25 19 22 11 28 2002 26 22 21 8 26 2003 26 26 21 6 29 2004 26 24 15 5 26 2005 26 23 10 5 23 2006 25 19 10 3 20 2007 23 16 8 2 19 2008 21 14 7 2 20 2009 19 13 6 2 16 2010 16 12 6 2 15 2011 15 10 5 2 14 2012 13 10 5 1 13 2013 11 10 4 1 14 2014 10 9 4 1 13 2015 9 8 3 1 14 2016 7 9 3 1 12 2017 6 8 3 1 12 2018 6 8 3 1 12 2019 5 7 2 1 12 31 Table 2.2. Annual estimates of attrition at each stage of the HIV continuum of care for PLWH with SUD in British Columbia, Canada, from 2001-2019. Year Attrition at ART Initiation (%) Attrition at On-ART (%) Attrition at ART Adherence (%) Attrition at Viral Suppression (%) Attrition at Sustained Suppression (%) 2001 36 28 39 12 41 2002 36 30 41 10 38 2003 35 32 35 10 39 2004 38 30 30 6 38 2005 37 26 29 4 42 2006 36 26 26 6 34 2007 34 19 27 3 36 2008 31 15 23 3 35 2009 25 12 18 4 30 2010 22 12 17 3 28 2011 17 10 13 2 28 2012 14 8 11 3 26 2013 12 8 13 2 25 2014 10 6 11 2 24 2015 8 6 12 2 23 2016 9 6 11 2 22 2017 8 7 12 2 25 2018 7 8 10 3 21 2019 7 6 11 3 22 32 Table 2.3. Annual estimates of attrition at each stage of the HIV continuum of care for PLWH with mood/anxiety disorders in British Columbia, Canada, from 2001-2019. Year Attrition at ART Initiation (%) Attrition at On-ART (%) Attrition at ART Adherence (%) Attrition at Viral Suppression (%) Attrition at Sustained Suppression (%) 2001 21 20 24 11 29 2002 22 24 25 7 32 2003 22 22 24 5 31 2004 23 22 17 4 28 2005 23 18 12 3 25 2006 22 14 10 2 20 2007 21 11 8 2 21 2008 19 9 7 2 19 2009 15 8 5 1 18 2010 14 7 5 1 15 2011 11 6 4 1 17 2012 9 6 5 1 13 2013 8 5 5 1 14 2014 6 5 4 0 13 2015 5 5 3 0 14 2016 5 5 3 0 13 2017 4 5 3 1 13 2018 4 5 2 0 12 2019 3 4 2 0 11 33 Table 2.4. Annual estimates of attrition at each stage of the HIV continuum of care for PLWH with both SUD and mood/anxiety disorders in British Columbia, Canada, from 2001-2019. Year ART Initiation (%) Attrition at ART Initiation (%) Attrition at On-ART (%) Attrition at ART Adherence (%) Attrition at Viral Suppression (%) Attrition at Sustained Suppression (%) 2001 70% 30 31 39 10 46 2002 71% 29 31 43 8 45 2003 69% 31 32 39 8 48 2004 68% 32 30 33 6 46 2005 69% 31 27 31 7 40 2006 70% 30 23 29 5 36 2007 73% 27 20 24 5 37 2008 75% 25 15 20 3 38 2009 79% 21 12 16 4 32 2010 81% 19 10 14 4 29 2011 85% 15 9 15 3 29 2012 88% 12 8 14 4 25 2013 89% 11 7 12 1 26 2014 91% 9 6 12 2 25 2015 92% 8 7 9 2 25 2016 93% 7 7 11 1 21 2017 93% 7 7 11 2 21 2018 93% 7 6 10 1 22 2019 93% 7 6 10 1 21 34 A total of 12,076 eligible PLWH were included in this study's bivariable and multivariable analyses; 2,322 PLWH were excluded due to missing information for at least one of the confounding variables. Table 2.5 compares PLWH included and excluded from the analyses. Compared to PLWH included, individuals excluded were more likely to be younger and to have never initiated ART. Table 2.5. Comparison of PLWH included and excluded in the study. Variable Excluded N=2322 N (Row %) Included N=12076 N (Row%) P-value Gender 0.7512 Women 438 (16) 2312 (84) Men 1884 (16) 9764 (84) Age <0.0001 19 to 29 506 (23) 1656 (77) 30 to 39 867 (18) 3967 (82) 40 to 49 601 (13) 3944 (87) 50 or more 348 (12) 2509 (88) Dispensed ART ever <0.0001 No 1079 (18) 4766 (82) Yes 1243 (14) 7310 (86) Continuous Variables Median (Q1-Q3) Median (Q1-Q3) P-value Index Year 2011 (2004-2016) 2003 (2001-2009) <0.0001 Age 37 (31-45) 40 (34-48) <0.0001 Q1-Q3: 25th to 75th Percentile Table 2.6 describes the clinical and sociodemographic characteristics of the study population at the index year and at the end of follow-up. At the index year, 2,514 (21%) of people had mood/anxiety disorders, 2,236 (19%) had both SUD and mood/anxiety disorders, and 1,325 (11%) had SUD only. At the end of follow-up, the prevalence of these disorders was 2,417 (20%), 2,657-2,661 (22%), and 1,854 (15%), respectively. The participants were 81% men, 27% gbMSM, and 35 23% PWID. At the index year, the median age was 40 years (25th-75th percentile [Q1-Q3]: 34-48), and at the end-of-follow-up, the median age increased to 52 years (Q1-Q3: 44-60). At the index year and end of follow-up, over 50 % of the population resided in the Vancouver Coastal Health Authority, and over 20% lived in the Fraser Health Authority, the two most urbanized regions in BC. At the index year and end of follow-up, over 44% of participants were on income assistance, and over 8% were residents of the DTES. The median index year was 2003 (Q1-Q3: 2001-2009), and the median year of ART initiation for the 10,881 PLWH who initiated ART was 2005 (Q1-Q3:1998-2011). For the 10,235 PLWH who achieved viral suppression during the study, the median time from ART initiation to first viral suppression was four months (Q1-Q3: 2-24). Table 2.6. Clinical and sociodemographic characteristics of the study population (a) Time-varying characteristics Categorical Variables At Index Year N = 12076 N (%) At End of Follow-up N = 12076 N (%) Presence of SUD or mood/anxiety disorder Neither 4257 (35) 5144 (43) SUD 1325 (11) 1854 (15) Mood/anxiety disorders 2514 (21) 2417 (20) Both 2236 (19) 2657-2661 (22)* < 5 years of medical history 1744 (14) <5† Age (years) 19 to 29 1656 (14) 328 (3) 30 to 39 3967 (33) 1612 (13) 40 to 49 3944 (33) 3069 (25) 50+ 2509 (21) 7067 (59) Income Assistance 36 No 6385 (53) 6335 (53) Yes 5291 (44) 5454 (45) Unknown 400 (3) 287 (2) Health Authority of Residence Vancouver Coastal 6401 (53) 6161 (51) Fraser 2589 (21) 2782 (23) Vancouver Island 1395 (12) 1548 (13) Interior 775 (6) 885 (7) Northern 448 (4) 431 (4) Unknown 468 (4) 269 (2) Residency in the DTES No 10520 (87) 10854 (90) Yes 1109 (9) 997 (8) Unknown 447 (4) 225 (2) Continuous Variables Median (Q1-Q3) Median (Q1-Q3) Age (years) 40 (34-48) 52 (44-60) (b) Time-fixed Characteristics Categorical Variables N=12076 N (%) Gender Women 2312 (19) Men 9764 (81) HIV Transmission Group PWID 2819 (23) gbMSM 3306 (27) PWID/gbMSM 796 (7) Heterosexual/Other 1060 (9) Unknown 4095 (34) Continuous Variables Median (Q1-Q3) 37 Index Year 2003 (2001-2009) Year of ART Initiation‡ 2005 (1998-2011) Time between ART Initiation and Viral Suppression (Months)§ 4 (2-24) PWID: People with a history of injecting drugs, gbMSM: gay, bisexual and other men who have sex with Men, DTES: Downtown Eastside, Q1-Q3: 25th to 75th Percentile * Due to privacy concerns, small cell counts (<5) were protected by displaying a number range † Due to data privacy, I replaced exact numbers if cells contained <5 participants ‡Estimated for 10881 PLWH who initiated ART during the study § Estimated for 10235 PLWH who achieved viral suppression during the study 38 Table 2.7 displays the sociodemographic and clinical characteristics of PLWH stratified by the presence of SUD and mood/anxiety disorders at (a) index year and (b) end of follow-up. Those with SUD, mood/anxiety disorder, or both had a significantly earlier index and ART initiation year than those without these disorders. Those with SUD or both SUD and mood/anxiety disorders were likelier to be women, PWID, younger, on income assistance, and residing in a less urbanized (northern) health region and the DTES. Those with neither SUD nor mood/anxiety disorders and those with only mood/anxiety disorders were more likely to be men, gbMSM, older, not on income assistance, residents of more urbanized (Vancouver Coastal and Fraser) health regions, and not residents of the DTES. 39 Table 2.7. Clinical and sociodemographic characteristics of PLWH in British Columbia, Canada, from 2001-2019, stratified by SUD and mood/anxiety disorder diagnosis status at (a) index year and (b) end of follow-up. (a) At index year (N= 10039) Categorical Variables Neither N=4045 N (Row %) SUD N=1302 N (Row %) Mood/Anxiety Disorders N=2478 N (Row%) Both N=2214 N (Row %) P-values Gender Women 475 (24) 377 (19) 361 (18) 747 (38) <0.0001 Men 3570 (44) 925 (11) 2117 (26) 1467 (18) HIV Transmission Group PWID 415 (16) 734 (29) 225 (9) 1177 (46) gbMSM 1455 (54) 73 (3) 998 (37) 169 (6) <0.0001 PWID/gbMSM 241 (35) 83 (12) 181 (27) 176 (26) Heterosexual/Other 415 (50) 46 (6) 281 (34) 87 (10) Unknown 1519 (46) 366 (11) 793 (24) 605 (18) Age Category 19 to 29 486 (39) 197 (16) 255 (20) 309 (25) <0.0001 30 to 39 1152 (37) 486 (15) 740 (24) 774 (25) 40 to 49 1288 (38) 403 (12) 854 (25) 818 (24) 50+ 1119 (49) 216 (10) 629 (28) 313 (14) 40 Income Assistance No 2915 (55) 332 (6) 1543 (29) 470 (9) <0.0001 Yes 1130 (24) 970 (20) 935 (20) 1744 (37) Residency in the DTES No 3831 (42) 1002 (11) 2408 (27) 1805 (20) <0.0001 Yes 214 (22) 300 (30) 70 (7) 409 (41) Health Authority of Residence Vancouver Coastal 2223 (41) 725 (13) 1420 (26) 1094 (20) Fraser 974 (43) 274 (12) 511 (23) 485 (22) Vancouver Island 461 (37) 151 (12) 299 (24) 321 (26) <0.0001 Interior 262(40) 57 (9) 175 (26) 169 (25) Northern 119 (28) 94 (22) 66 (16) 143 (34) Unknown 6 (38) 1 (6) 7 (44) 2 (13) Continuous Variables Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) P-Value Age 42 (35-50) 39 (33-46) 42 (36-50) 40 (33-46) <0.0001 Index Year 2003 (2001-2010) 2001 (2001-2008) 2001 (2001-2008) 2001 (2001-2007) <0.0001 Year of ART Initiation* 2006 (1997-2012) 2004 (1998-2010) 2003 (1996-2010) 2004 (1998-2010) <0.0001 (b) At the end of follow-up (N=11520) 41 Categorical Variables Neither N=4715 N (Row%) SUD N=1818 N (Row%) Mood/Anxiety Disorders N=2378 N (Row%) Both N=2609 N (Row%) P-values Gender <0.0001 Women 700 (32) 461 (21) 337 (15) 709 (32) Men 4015 (43) 1357 (15) 2041 (22) 1900 (20) HIV Transmission Group PWID 412 (15) 956 (35) 204 (7) 1186 (43) gbMSM 1706 (53) 169 (5) 931 (29) 385 (12) <0.0001 PWID/gbMSM 210 (27) 158 (20) 145 (19) 262 (34) Heterosexual/Other 611 (60) 70 (7) 234 (23) 105 (10) Unknown 1776 (47) 465 (12) 864 (23) 671 (18) Age (years) <0.0001 19 to 29 134 (43) 43 (14) 66 (21) 70 (22) 30 to 39 526 (35) 286 (19) 242 (16) 467 (31) 40 to 49 995 (34) 523 (18) 524 (18) 860 (30) 50+ 3060 (45) 966 (14) 1546 (23) 1212 (18) Income Assistance No 3468 (56) 506 (8) 1541 (25) 643 (10) <0.0001 Yes 1247 (23) 1312 (25) 837 (16) 1966 (37) Residency in the DTES 42 No 4555 (43) 1451 (14) 2321 (22) 2228 (21) <0.0001 Yes 160 (17) 367 (38) 57 (6) 381 (39) Health Authority of Residence Vancouver Coastal 2245 (38) 1085 (18) 1229 (21) 1416 (24) Fraser 1323 (49) 332 (12) 548 (20) 506 (19) Vancouver Island 623 (41) 202 (13) 320 (21) 365 (24) <0.0001 Interior 367 (43) 86 (10) 201 (24) 201 (24) Northern 135 (32) 108 (26) 61 (15) 114 (27) Unknown 22 (42) 5 (9) 19 (36) 7 (13) Continuous Variables Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) P-value Age 54 (45-62) 50 (42-57) 54 (46-61) 49 (41-56) <0.0001 Index Year 2004 (2001-2010) 2001 (2001-2007) 2002 (2001-2010) 2002 (2001-2008) <0.0001 Year of ART Initiation† 2006 (1998-2011) 2005 (1998-2010) 2005 (1997-2011) 2005 (1998-2011) 0.0067 P-value estimates exclude “Unknown” categories; p-value significance is set at 0.05 Patients with missing/unknown variables were excluded SUD: Substance use disorder, PWID: people with a history of injecting drugs, gbMSM: gay, bisexual and other men who have sex with Men, DTES: Downtown Eastside, Q1-Q3: 25th to 75th Percentile For transgender PLWH, gender was determined based on the last sex specified in administrative health records *Estimated based on a total of 8938 PLWH who had initiated ART at index year †Estimated based on a total of 10491 PLWH who had initiated ART at the end of follow-up 43 Table 2.8 presents the multivariable model of the effect of SUD and mood/anxiety disorders on the achievement of each stage of the HIV continuum of care with their respective adjusted odds ratio (aOR). Compared to those with neither of the disorders, those with only SUD or both SUD and mood/anxiety disorders had significantly reduced odds of achieving all stages of the HIV continuum of care, except for the stage of on-ART. Having SUD had the strongest association with lower odds of ART adherence (aOR 0.47, 95% CI [confidence interval]: 0.42-0.53) and lower odds of sustained suppression (aOR 0.58, 95% CI: 0.53-0.63). Having only mood/anxiety disorders was also associated with failure to achieve ART adherence (aOR 0.78, 95% CI: 0.71-0.87) and sustained suppression (aOR 0.82, 95% CI: 0.77-0.88), but their impacts were more moderate. Although the effect was minor, having only mood/anxiety disorders was associated with increased odds of ART initiation. The achievement of the on-ART stage was not significantly associated with the presence of mood/anxiety disorders, SUD, or both. 44 Table 2.8. A multivariable model of the association between substance use and mood/anxiety disorders and the achievement of each stage of the HIV continuum of care. Presence of SUD and Mood/Anxiety Disorders ART Initiation* aOR (95%CI) On-ART † aOR (95%CI) ART Adherence ‡ aOR (95%CI) Viral Suppression § aOR (95%CI) Sustained Suppression ‖ aOR (95%CI) Neither Reference Reference Reference Reference Reference Only SUD 0.74 (0.62-0.88) 0.96 (0.81-1.14) 0.47 (0.42-0.53) 0.67 (0.53-0.85) 0.58 (0.53-0.63) Mood/Anxiety Disorders 1.19 (1.04-1.36) 1.04 (0.91-1.20) 0.78 (0.71-0.87) 1.13 (0.92-1.39) 0.82 (0.77-0.88) Both 0.80 (0.68-0.93) 0.97 (0.83-1.14) 0.47 (0.42-0.52) 0.65 (0.53-0.80) 0.56 (0.52-0.60) SUD: Substance use disorder, aOR: adjusted odds ratio, CI: confidence interval, ART: Antiretroviral therapy * Adjusted for gender, age, income assistance, residency in the Downtown Eastside, and index year † Adjusted for gender, age, income assistance, residency in the Downtown Eastside, and ART initiation year ‡ Adjusted for age, income assistance and ART initiation year § Adjusted for gender, age, income assistance, residency in the Downtown Eastside, and ART initiation year ‖ Adjusted for age, income assistance, residency in the Downtown Eastside, and ART initiation year 45 2.4. Discussion Despite reduced overall attrition across the HIV continuum of care in the past two decades, attrition at sustained suppression remains relatively high, especially for PLWH with SUD. High attrition at this stage raises a challenge for achieving optimal health outcomes among PLWH since long-term viral suppression is necessary to protect immune function and reduce morbidity and mortality risk.137 Also, given that viral rebound increases the risk of HIV transmission, sustained viral suppression among PLWH is crucial in preventing new HIV infections.137 In agreement with the literature, I found that SUD alone, and in combination with mood/anxiety disorders, was associated with reduced odds of ART initiation, ART adherence, viral suppression and sustained suppression.83,85,113,137,138 However, the magnitude and the significance of the association between combined SUD and mood/anxiety disorders and achieving these steps of the HIV continuum of care was similar to that of SUD alone. The literature indicates that several psychological, socio-economic, and biological factors associated with SUD contribute to attrition across the HIV continuum of care. For example, mental health issues, stigma, and housing instability are barriers to ART initiation.83,182 Cognitive impairment (e.g., memory loss) and ART neurotoxicity induced by SUD are some of the factors leading to intentional or unintentional incomplete ART adherence.85 In turn, incomplete ART adherence and the adverse impacts of substances on ART metabolism and HIV disease progression can increase the risk of viral rebound.137,138 Thus, various interrelated factors contribute to the association between SUD and attrition across the HIV continuum of care. Similar to previous findings, I observed that women, younger and low-income individuals, and residents of the DTES were more likely to have SUD.5,55 Considering the vulnerability to SUD, these subpopulations of PLWH require targeted interventions to reduce the burden of this 46 disorder. The literature also indicates that some SUDs, such as alcohol and illicit drug use disorders, are more detrimental to HIV care continuity than others.138 Thus, understanding the impact of specific SUDs on the HIV continuum of care is essential to identifying the most vulnerable groups of PLWH and designing targeted interventions for reducing the burden of SUD among PLWH. In this study, mood/anxiety disorders were associated with higher odds of ART initiation but lower odds of ART adherence. PLWH with diagnosed mood/anxiety disorders may be encouraged to initiate ART when they receive health services for their mental illness,92 but are not adherent to ART due to psychosocial and clinical factors such as stigma, lack of social support and motivation, mood dysregulation, and use of substances that are associated with incomplete ART adherence.84,113,183 However, it is worth noting that PLWH who initiate ART with mood/anxiety disorders are more likely to have their mood/anxiety disorder diagnosed since they are engaged with healthcare services.184 According to my results, mood/anxiety disorders were not significantly associated with viral suppression. The literature examining the relationship between mood/anxiety disorders and viral suppression has yielded mixed results depending on the definition of viral suppression and the type of mood/anxiety disorder, its severity and the treatment status. For instance, untreated depressive disorders and both treated and untreated bipolar disorders were associated with having an unsuppressed VL, while treated depressive disorders and anxiety disorders were not.90,91 The lack of association in my results could also be due to the liberal definition of viral suppression that I selected, the one most widely used in the literature.140 However, using a more stringent definition, mood/anxiety disorders were associated with reduced odds of sustained suppression.143 The most likely factor contributing to the higher risk of viral rebound among PLWH with mood/anxiety disorders is incomplete ART adherence since the 47 symptoms of these disorders can lead to treatment interruption or withdrawal. However, independent of adherence, mood/anxiety disorders are associated with altered immune functions that can also lead to virologic failure.143 Strengths and Limitations To my knowledge, this is the first population-based cohort study that examines the impact of SUD and mood/anxiety disorders on a comprehensive multistage HIV continuum of care while including a measure for sustained viral suppression. As another strength, this analysis consists of a large study population with 19 years of follow-up in a setting where access to ART, as well as medical and laboratory monitoring, are all fully subsidized. Additionally, the BC-CfE has complete data capture of ART use, refills, and VL for all PLWH in BC. Nonetheless, this study has some limitations that must be considered. First, administrative health record data were not collected for research purposes and may be prone to diagnostic coding errors and misclassifications that may be a source of bias. Second, due to using a single diagnostic code encompassing both mood and anxiety disorders in BC health records, I could not examine the separate effects of mood and anxiety disorders on the HIV continuum of care. Also, due to combining mood and anxiety disorders into one diagnosis category, I could not assess the effect of their separate interactions with SUD on HIV outcomes. Likewise, SUD was included as a general category of disease, and I was not able to examine the effect of specific substances and their severity on the HIV continuum of care. Third, the stage of HIV diagnosis was eliminated from the HIV continuum of care since data was restricted, by design, to PLWH who were already diagnosed. Fourth, I excluded PLWH with missing or insufficient medical records from the bivariable and multivariable analysis to reduce bias and enhance the interpretability of my results. Lastly, I could not control for ethnicity 48 since I had a high proportion of PLWH with missing information. Due to a lack of data availability, I also could not control for other potential sociodemographic confounders such as housing stability, education, employment, social support, and food security. 2.5. Conclusion Attritions across the HIV continuum of care have decreased for PLWH from 2001 to 2019. Currently, some PLWH still experience attritions, highest at sustaining suppression. The results in this chapter demonstrate that PLWH with SUD are more likely to experience attrition across the HIV continuum of care and they suggest that addressing the socio-economic and clinical correlates of SUD and providing effective SUD treatment may be crucial to achieving sustained viral suppression and optimal public health outcomes for this population. My findings also indicate that treating mood/anxiety disorders and improving mental health among PLWH may enhance ART adherence and prevent viral rebound. Therefore, this study supports the need for integrated mental health and substance use services as an essential component of comprehensive HIV care. 49 Chapter 3: The Impact of Substance Use, Mood/Anxiety Disorders and Unsustained Viral Suppression on Healthcare Utilization of People Living with HIV in British Columbia, Canada, from 2001 to 2019 3.1. Introduction The widespread use of modern antiretroviral therapy (ART) has transformed HIV from a fatal disease to a chronic, manageable condition. As a result, the life expectancy of people living with HIV (PLWH) is almost as long as their HIV-negative counterparts.4 However, due to an excess burden of chronic-non-infectious comorbidities and socioeconomic disparities, PLWH often have complex healthcare needs.7,8 In addition, high healthcare utilization among PLWH is a critical concern as medical expenditures within this population have exceeded those of the general population.7 Longitudinal reports from 2001 to 2012 show that healthcare expenditures among PLWH have been higher than HIV-negative counterparts.7,10 Mental health and substance use disorders disproportionately affect PLWH.5,6,17 Recent studies have estimated that over 54% of PLWH in Canada and the US are diagnosed with a mental health disorder and have identified mood and anxiety disorders as the most prevalent mental health conditions.14,19,91 Likewise, it is estimated that substance use disorder (SUD), the problematic use of alcohol and drugs, affects more than 20% of PLWH in Canada and other developed countries.17-20 Studies of the general population suggest that mood and anxiety disorders and SUD are associated with increased healthcare utilization and costs, especially in primary care and hospital settings.158-160 In 2018, it was estimated that depression alone added an average annual cost of $7,232 per person to Canada's healthcare expenditures.185 The healthcare burden of mood and anxiety disorders and SUD within the general population and the high prevalence of these 50 disorders among PLWH call for a thorough investigation of their effects on the healthcare utilization of PLWH. Notably, among PLWH, these disorders are risk factors for incomplete ART adherence and unsuppressed (i.e., detectable) viral loads (VLs) , which are also predictors of poor health outcomes and high healthcare utilization and costs within this population.137,138,143,154,186,187 A few previous studies have identified mental health and substance use disorders as independent factors contributing to increased healthcare utilization and high medical costs among PLWH.94-96 However, there is a lack of comprehensive longitudinal research examining the separate and combined effects of these disorders while taking into account the role of sustained HIV control (viral suppression). Therefore, this study examined the impact of mood and anxiety disorders (hereafter referred to as mood/anxiety disorders) and SUD on the utilization of different healthcare services among PLWH with sustained and unsustained viral suppression in BC, Canada. 3.2. Methods Study Setting and Data Source In BC, the Drug Treatment Program (DTP) administered by the BC Centre for Excellence in HIV/AIDS (BC-CfE) provides free-of-charge ART and routine laboratory (e.g., VL and CD4 cell count) monitoring to all diagnosed PLWH ever on ART.97 In addition to delivering HIV treatment according to BC's therapeutic guidelines,98 the DTP collects demographic, clinical, and treatment data on its clients. PLWH in BC are also covered by the Medical Services Plan (MSP), a public health insurance plan that pays the cost of medically essential services for all residents of BC.99 This retrospective population-based cohort study utilized individual-level longitudinal data from the Comparative Outcome and Service Utilization Trends (COAST) study that consists of linkages between BC-CfE's DTP and various provincial administrative databases hosted by 51 Population Data BC.100 COAST contains healthcare utilization and mortality data on all diagnosed PLWH from April 1, 1992, to March 31, 2020. Diagnosis of HIV was determined using a previously validated, highly specific case-finding algorithm.101 Study Population Eligible participants were PLWH (i) 19 years and older, who (ii) achieved viral suppression at least once during follow-up, and (iii) had more than one VL measurement during at least one calendar year in which they achieved viral suppression. Viral suppression was defined as having a VL of <200 copies/mL.140 The index date was the latest of the following dates: HIV seropositive status, defined by the first HIV-related record (VL test, ART initiation, HIV-related International Classification of Disease [ICD] codes in MSP or hospitalization records),101 19th birthday or January 1, 2001. The end of the follow-up date for study participants was the earliest of the following dates: last healthcare contact, death, or December 31, 2019. Individuals who participated in clinical trials were censored during their trial participation. Exposure Variable I had two exposure variables: (1) diagnosis status of SUD and/or mood/anxiety disorders and (2) sustainment of viral suppression (hereafter called sustained suppression), which was assessed annually from 2001 to 2019. Sustained suppression was defined by having all VLs in the calendar year <200 copies/mL,69,139 and categorized as no, yes, only one VL measured, or no VL measured. The diagnosis status of SUD and mood/anxiety disorders was categorized as (1) neither disorder, (2) only SUD, (3) only mood/anxiety disorders, and (4) both disorders. Considering that syndemic interactions between SUD and mood/anxiety disorders often exacerbate their impact on health 52 outcomes,113,172 I used this categorical exposure variable to capture both their distinct and combined effects. For the multivariable analyses, I combined the diagnosis status of the disorders and sustained suppression into a single exposure variable to capture their distinct and combined effects. Hence, the exposure variable was categorized as follows: (1) sustained suppression with neither disorder, (2) sustained suppression with only mood/anxiety disorders, (3) sustained suppression with only SUD, (4) sustained suppression with both disorders, (5) unsustained suppression with neither disorder, (6) unsustained suppression with only mood/anxiety disorders, (7) unsustained suppression with only SUD, and (8) unsustained suppression with both disorders. Cases of SUD and mood/anxiety disorders were identified in health administrative records using the BC Ministry of Health’s case-finding algorithms that include the ICD codes for these diseases (Appendix A).35,173 Note that, in BC's MSP data, mood and anxiety disorders are coded under one BC-specific diagnostic code (50B).35 Hence, these disorders had to be combined into one category. SUD and mood/anxiety disorder cases were annually ascertained using a five-year lookback window.174 Thus, these disorders were assumed to be present if there was a record of diagnosis in the five years before the year of interest. However, diagnoses of these disorders were reversible, meaning that I assumed that they were no longer present if there were no records of their diagnosis for five years. A look-back window was implemented to minimize misclassification bias when using administrative data. These databases do not collect data for research purposes; they only capture data from real-time clinical practices when individuals interact with specific healthcare services.174 As a result, people engaged in care for longer durations are more likely to have their new and pre-existing conditions documented in these databases. To mitigate bias, individual records were systematically reviewed, and the same standardized look-back window 53 was applied across all individuals. Per previous studies, five years was selected as the optimum length for minimizing bias and maximizing sample size and follow-up time.174 Outcome Variables Our outcomes included annual counts of primary care physician visits, specialist physician (here onwards referred to as specialist) visits, laboratory visits, day surgery episodes, acute care hospitalizations, and hospital length of stay (LOS). All physician and laboratory visits were identified using the MSP billing database, which holds records of essential physician services, laboratory and diagnostic procedures.188,189 Acute care hospitalizations, day surgery episodes and LOS were determined using the Discharge Abstract Database, which contains hospital discharge and death records from acute care hospitals in BC.190 Hospital LOS was calculated as the number of inpatient days per year. For day surgery episodes, LOS was assumed to be one day. Confounders Potential sociodemographic confounders included age (categorical [19-29, 30-39, 40-49, and 50+ years] or continuous), gender (woman, man), use of income assistance (no, yes, unknown), Regional Health Authority (HA) of residency (Vancouver Coastal, Fraser, Vancouver Island, Interior, Northern and unknown), and residency in the Vancouver Downtown Eastside (DTES) (no, yes, unknown). In BC, each regional HA delivers healthcare services to the population within its geographic region.175 The most urbanized areas in BC are located within the Vancouver Coastal HA, while Northern HA covers the most rural areas. DTES is a neighbourhood in the city of Vancouver that is disproportionately affected by HIV, drug use, mental disorders and socioeconomic inequities such as homelessness, poverty and crime.176,177 Use of income assistance 54 was determined based on records of non-ART drug dispensation under the PharmaCare Plan C, a BC-wide program covering 100% of prescription costs for low-income residents of BC.191 For this variable, a 5-year lookback observation window was selected as the optimum number of years after conducting a sensitivity analysis. HIV-related potential confounders included ART initiation year (continuous; as the cohort effect), and HIV transmission group (people who inject drugs [PWID], gay, bisexual, and other men who have sex with men [gbMSM], PWID/gbMSM, heterosexual/other, unknown) which was reported by the individual or a physician. Index year (year of study entry) and follow-up time (in years) were reported for descriptive purposes. Age, use of income assistance, regional HA and residency in the DTES were time-varying variables, whereas gender, HIV transmission group, and ART initiation year were time-fixed variables. All potential confounders were chosen based on data availability, literature and relevance to my outcomes of interest.9,55,95,168,192,193 Statistical Analysis Descriptive statistics (frequencies and proportions for categorical variables, medians and 25th-75th percentiles [Q1-Q3] for continuous variables) were calculated for all study variables at the index date and the end of follow-up if the variables were time-varying. Initially, the study population was stratified by the presence of sustained suppression and diagnosis status of SUD and/or mood/anxiety disorders. Characteristics of stratified groups were compared using the χ2 and Kruskal-Wallis tests for categorical and continuous covariates, respectively.179 Next, the median annual counts of each type of healthcare utilization outcome was calculated for each exposure group. Median annual counts were determined for the starting (2001), mid (2010), and ending (2019) years of the study period for illustrative purposes. Individuals with fewer than two VL 55 measures per year were excluded. Counts of healthcare utilizations were reported instead of rates as I had complete follow-up for the vast majority of the final study population (median follow-up time in each year was 364 days; Q1-Q3: 364-364) (Table 3.1). This phenomenon is likely due to the inclusion of only individuals who achieved viral suppression and had a minimum of two VL measures per year. I also reported the distribution of the number of VL measures per year for PLWH with sustained and unsustained suppression. Table 3.1. Distribution of the study population’s follow-up per year from index date to end of follow-up. Quantiles Value 100% Max 365 99% 365 95% 365 90% 365 75% Q3 364 50% Median 364 25% Q1 364 10% 364 5% 364 1% 211 0% Min 30 Multivariable models were used to examine associations between SUD, mood/anxiety disorders and sustained suppression with each healthcare utilization outcome. I adjusted for the following confounders: age category, gender, use of income assistance, residency in the DTES, and ART initiation year. The HIV transmission group and the HA variables were excluded from 56 the multivariable analysis due to multicollinearity with SUD diagnosis and residency in the DTES. For each healthcare utilization outcome, the following models were considered for the multivariable analysis: generalized linear mixed effect negative binomial (NB), zero-inflated NB (ZINB), and hurdle (two-part) models.194,195 NB models, suitable for count data, account for the overdispersion,194 and the inflated NB and hurdle models account for excessive zeros in healthcare utilization data.195 The negative binomial model was selected for specialist visits, acute care hospitalization and LOS. The zero-inflated and the two-part (hurdle) negative binomial models were used for primary care physician visits and laboratory visits, respectively. The selected model for each outcome was the model with the lowest Akaike Information Criterion and the smallest percentage of change between the number of zeros estimated by the model and the observed number of zeros in the outcome variable.195 For interpretation purposes, the adjusted predicted mean count with a 95% confidence interval (CI) was computed for each outcome using the ggpredict function (in the ggeffects package in R) that holds all confounding variables constant while varying the exposure variable.196 All statistical analyses were performed using SAS version 9.4 and R version 4.0.3. 3.3. Results The final study population consisted of 9,757 eligible PLWH. Compared to those included, PLWH excluded due to insufficient VL counts or missing information for confounding variables were more likely to be women, younger and to have never initiated ART (Table 3.2). Figure 3.1 displays the step-by-step inclusion process. 57 Table 3.2. Comparison of people living with HIV included and excluded in the study. Variable Excluded N=4641 N (Row %) Included N=9757 N (Row%) P-value Gender Woman 1084 (39) 1666 (61) <0.0001 Man 3557 (30) 8091 (70) Age 19 to 29 792 (37) 1370 (63) 30 to 39 1581 (33) 3253 (67) <0.0001 40 to 49 1331 (29) 3214 (71) 50 or more 937 (33) 1920 (67) Dispensed ART ever No 2522 (43) 3323 (57) <0.0001 Yes 2119 (25) 6434 (75) Continuous Variables Median (Q1-Q3) Median (Q1-Q3) P-value Age (Years) 39 (32-47) 40 (33-47) 0.0013 Note: Q1-Q3: 25th to 75th Percentile, ART: antiretroviral therapy 58 Figure 3.1. Flowchart outlining the process for including a sample of 9,757 people living with HIV in British Columbia, Canada, from 2001-2019. 59 The median index year was 2003 (Q1-Q3: 2001-2009), and the median follow-up time was 13 years (Q1-Q3:8-19). The study population was 83% men, 32% gbMSM, and 25% PWID (Table 3.3). The median age increased from 40 (25th-75th percentile [Q1-Q3]: 33-47) years at index year to 53 (Q1-Q3: 45-60) years at the end of follow-up. At the index year, 41% of PLWH were on income assistance, 52% resided in the Vancouver Coastal Health region, and 8% were residents of the DTES. The median ART initiation was 2006 (Q1-Q3: 1998-2011). At index year, 37% of PLWH had neither disorder and 22% had only mood/anxiety disorders. Table 3.3. Clinical and Sociodemographic characteristics of the overall study population. (a) Time-varying characteristics Categorical Variables At Index Year At End of Follow-up N = 9757 N = 9757 N (%) N (%) Diagnosis of SUD and Mood/Anxiety Disorder Neither Disorder 3610 (37) 4307 (44) Only SUD 912 (9) 1389 (14) Only Mood/Anxiety disorder 2168 (22) 2098 (22) Both Disorders 1571 (16) 1958-1962 (20)* < 5 years of medical history 1496 (15) <5† Achieved Viral Suppression No 4856 (50) 658 (7) Yes 4125 (42) 8197 (84) No VL measure 776 (8) 902 (9) Sustained Suppression No 5628 (58) 1162 (12) Yes 1668 (17) 6708 (69) Only one VL measure 1685 (17) 985 (10) No VL measure 776 (8) 902 (9) 60 Age Category 19 to 29 1370 (14) 227 (2) 30 to 39 3253 (33) 1088 (11) 40 to 49 3214 (33) 2291 (24) 50+ 1920 (20) 6151 (63) Income Assistance No 5419 (55) 5410 (56) Yes 3989 (41) 4208 (43) Unknown 349 (4) 139 (1) Health Authority Vancouver Coastal 5260 (54) 5042 (52) Fraser 2059 (21) 2272 (23) Vancouver Island 1119 (12) 1260 (13) Interior 597 (6) 691 (7) Northern 327 (3) 312 (3) Unknown 395 (4) 180 (2) Residency in the DTES No 8577 (88) 8894 (91) Yes 801 (8) 700 (7) Unknown 379 (4) 163 (2) Continuous Variables Median (Q1-Q3) Median (Q1-Q3) Age (years) 40 (33-47) 53 (45-60) (b) Time-Fixed Characteristics Categorical Variables Overall N=9757 N (%) Gender Woman 1666 (17) Man 8091 (83) 61 HIV Transmission Group PWID 2434 (25) gbMSM 3110 (32) PWID/gbMSM 735 (8) Heterosexual/Other 987 (10) Unknown 2491 (25) Continuous Variables Median (Q1-Q3) Year of ART Initiation 2006 (1998-2011) Index Year 2003 (2001-2009) Follow-up Time (Years) 13 (8-19) Note: SUD: substance use disorder, VL: viral load, PWID: people with a history of injecting drugs, gbMSM: gay, bisexual, and other men who have sex with Men, DTES: Downtown Eastside, ART: antiretroviral therapy, Q1-Q3: 25th to 75th percentile * Due to privacy concerns, small cell counts (<5) were protected by displaying a range † Due to data privacy, I replaced exact numbers if cells contained <5 participants Table 3.4 and 3.5 display the characteristics of PLWH with sustained and unsustained suppression, stratified by the presence of SUD and mood/anxiety disorders as (a) index year and (b) end of follow-up. Among PLWH with sustained and unsustained suppression, those with both disorders or only SUD were significantly more likely to be women, younger, PWID, on income assistance, residents of the Northern Health region, and residents of the DTES. 62 Table 3.4. Sociodemographic and clinical characteristics of people living with HIV and sustained suppression, stratified by diagnosis status of SUD and mood/anxiety disorder at (a) index year and (b) end of follow-up. (a) At index year (N = 1394 ) SUD and Mood/Anxiety Disorder Diagnoses Neither SUD Mood/Anxiety Disorders Both Categorical Variables N=682 N=105 N=431 N=176 N (Row %) N (Row %) N (Row %) N (Row %) P-value Gender <0.0001 Woman 45 (29) 18 (12) 45 (29) 46 (30) Man 637 (51) 87 (7) 386 (31) 130 (10) Age 0.0002 19 to 29 31-35 (52-58)† <5* 13 (22) 11 (18) 30 to 39 191 (50) 29-33 (8-9)† 110 (29) 49 (13) 40 to 49 240 (43) 41 (7) 181 (33) 92 (17) 50 or more 218 (55) 30 (8) 127 (32) 24 (6) Income assistance <0.0001 No 464 (60) 15 (2) 271 (35) 30 (4) Yes 218 (36) 90 (15) 160 (26) 146 (24) Residency in the DTES <0.0001 63 No 656 (50) 82 (6) 421 (32) 143 (11) Yes 26 (28) 23 (25) 10 (11) 33 (36) HIV Transmission Group <0.0001 PWID 49 (20) 74 (30) 27 (11) 96 (39) gbMSM 353 (54) 15 (2) 255 (39) 26 (4) PWID/gbMSM 70-74 (50-53) † <5* 42 (30) 23 (16) Heterosexual/Other 67-71(48-51)† <5* 57 (41) 10 (7) Unknown 137 (62) 12 (5) 50 (23) 21 (10) Health Authority of Residence 0.3729 Vancouver Coastal 423 (49) 68 (8) 273 (31) 105 (12) Fraser 144 (52) 22 (8) 70 (25) 39 (14) Vancouver Island 75 (49) 11 (7) 52 (34) 15 (10) Interior 30-34 (38-43) † <5* 31 (39) 14 (18) Northern 3-7 (21-50) † <5* <5* <5* Unknown <5* <5* <5* <5* Continuous Variables Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) P-value Age 44 (38-52) 44 (38-51) 44 (39-51) 42 (38-47) 0.0049 Follow-up Time (Years) 19 (12-19) 13 (5-19) 19 (15-19) 19 (8-19) <0.0001 Index Year 2001 (2001-2001) 2001 (2001-2001) 2001 (2001-2001) 2001 (2001-2001) <0.0001 ART Initiation Year 1997 (1994-1999) 1998 (1996-1999) 1996 (1994-1998) 1997 (1996-1999) <0.0001 (b) At the end of follow-up (N=6637) 64 SUD and Mood/Anxiety Disorder Diagnoses Neither SUD Mood/Anxiety Disorders Both Categorical Variables N=3144 N=775 N=1579 N=1139 N (Row %) N (Row %) N (Row %) N (Row %) P-value Gender <0.0001 Woman 403 (40) 160 (16) 182 (18) 254 (25) Man 2741 (49) 615 (11) 1397 (25) 885 (16) Age <0.0001 19 to 29 61 (46) 10 (8) 37 (28) 24 (18) 30 to 39 299 (45) 83 (12) 142 (21) 146 (22) 40 to 49 590 (43) 167 (12) 310 (23) 309 (23) 50 or more 2194 (49) 515 (12) 1090 (24) 660 (15) Income assistance <0.0001 No 2414 (59) 246 (6) 1107 (27) 329 (8) Yes 730 (29) 529 (21) 472 (19) 810 (32) Residency in the DTES <0.0001 No 3053 (49) 640 (10) 1541 (25) 998 (16) Yes 91 (22) 135 (33) 38 (9) 141 (35) HIV Transmission Group <0.0001 PWID 260 (20) 424 (32) 113 (9) 509 (39) 65 gbMSM 1304 (55) 120 (5) 699 (29) 254 (11) PWID/gbMSM 151 (31) 84 (17) 103 (21) 153 (31) Heterosexual/Other 445 (64) 35 (5) 163 (23) 57 (8) Unknown 984 (56) 112 (6) 501(28) 166 (9) Health Authority of Residence <0.0001 Vancouver Coastal 1600 (44) 496 (14) 866 (24) 655 (18) Fraser 890 (54) 148 (9) 372 (23) 227 (14) Vancouver Island 387 (49) 70 (9) 201 (25) 134 (17) Interior 201 (46) 35 (8) 119 (27) 82 (19) Northern 61-65 (41-44) 21-25 (14-17)† 16-20 (11-14)† 37-41 (25-28)† Unknown <5* <5* <5* <5* Continuous Variables Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) P-value Age 56 (47-63) 53 (47-59) 55 (47-61) 52 (44-58) <0.0001 Follow-up Time (Years) 15 (9-19) 15 (9-19) 15 (8-19) 14 (8-19) 0.117 Index Year 2004 (2001-2010) 2002 (2001-2008) 2003 (2001-2010) 2003 (2001-2009) 0.0003 ART Initiation Year 2007 (1998-2011) 2006 (1999-2011) 2006 (1998-2012) 2007 (1999-2011) 0.3043 Note: SUD: substance use disorder, DTES: Downtown Eastside, PWID: people with a history of injecting drugs, gbMSM: gay, bisexual, and other men who have sex with Men, ART: antiretroviral therapy, Q1-Q3: 25th to 75th percentile P-value estimates exclude "Unknown" categories; p-value significance is set at 0.05 * Due to data privacy, I replaced exact numbers if cells contained <5 participants † Due to privacy concerns, small cell counts (<5) were protected by displaying a range 66 Table 3.5. Sociodemographic and clinical characteristics of people living with HIV and unsustained suppression, stratified by diagnosis status of SUD and mood/anxiety disorder at (a) index year and (b) end of follow-up. (a) At index year (N =1904) SUD and Mood/Anxiety Disorder Diagnoses Neither Disorder Only SUD Only Mood/Anxiety Disorders Both Disorders Categorical Variables N=924 N=156 N=507 N=317 P-value N (Row %) N (Row %) N (Row %) N (Row %) Gender <0.0001 Woman 81 (30) 28 (10) 69 (26) 92 (34) Man 843 (52) 128 (8) 438 (27) 225 (14) Age <0.0001 19 to 29 111 (47) 21 (9) 65 (27) 41 (17) 30 to 39 250 (49) 43 (8) 112 (22) 110 (21) 40 to 49 276 (45) 55 (9) 171 (28) 117 (19) 50 or more 287 (54) 37 (7) 159 (30) 49 (9) Income Assistance <0.0001 No 748 (60) 58 (5) 356 (29) 86 (7) Yes 176 (27) 98 (15) 151 (23) 231 (35) 67 Residency in the DTES <0.0001 No 879 (49) 127 (7) 502 (28) 273 (15) Yes 45 (37) 29 (24) 5 (4) 44 (36) HIV Transmission Group <0.0001 PWID 61 (18) 81 (24) 32 (9) 169 (49) gbMSM 401 (59) 23 (3) 213 (31) 49 (7) PWID/gbMSM 38 (34) 16 (14) 23 (21) 35 (31) Heterosexual/Other 139 (54) 13 (5) 78 (30) 28 (11) Unknown 285 (57) 23 (5) 161 (32) 36 (7) Health Authority of Residence 0.0809 Vancouver Coastal 500 (49) 82 (8) 268 (26) 173 (17) Fraser 231 (49) 38 (8) 127 (27) 79 (17) Vancouver Island 105 (50) 10 (5) 63 (30) 33 (16) Interior 57 (49) 14 (12) 33 (28) 12 (10) Northern 26-30 (34-43)* 7-11 (9-14)* 12-16 (16-21)* 16-20 (21-26)* Unknown <5† <5† <5† <5† Continuous Variables Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) P-value Age (Years) 43 (35-52) 41 (34-49) 44 (36-51) 40 (33-47) <0.0415 Follow-up Time (Years) 7 (4-13) 8 (4-14) 9 (4-16) 7 (4-14) <0.0001 Index Year 2011 (2003-2015) 2007 (2000-2013) 2010 (2001-2015) 2008 (2001-2015) <0.0001 ART Initiation Year 2011 (2003-2015) 2007 (2000-2013) 2010 (2001-2015) 2008 (1998-2015) <0.0001 68 (b) At the end of follow-up (N=694) SUD and Mood/Anxiety Disorder Diagnoses Neither Disorder Only SUD Only Mood/Anxiety Disorders Both Categorical Variables N=209 N=148 N=111 N=226 P-value N (Row %) N (Row %) N (Row %) N (Row %) Gender 0.0014 Woman 30 (19) 42 (27) 22 (14) 64 (41) Man 179 (33) 106 (20) 89 (17) 162 (30) Age 0.0047 19 to 29 19 (41) 5 (11) 10 (22) 12 (26) 30 to 39 30 (27) 20 (18) 17 (15) 43 (39) 40 to 49 38 (21) 44 (24) 27 (15) 75 (41) 50 or more 122 (34) 79 (22) 57 (16) 96 (27) Income Assistance <0.0001 No 152 (49) 38 (12) 62 (20) 56 (18) Yes 57 (15) 110 (28) 49 (13) 170 (44) Residency in the DTES <0.0001 No 203 (32) 115 (18) 111 (18) 197 (31) Yes 6 (9) 33 (49) 0 (0) 29 (43) 69 HIV Transmission Group <0.0001 PWID 25 (10) 88 (35) 12 (5) 123 (50) gbMSM 91 (50) 11 (6) 48 (26) 33 (18) PWID/gbMSM 12 (20) 19 (32) 5 (8) 24 (40) Heterosexual/Other 26 (43) 12 (20) 10 (16) 13 (21) Unknown 55 (55) 18 (13) 36 (25) 33 (23) Health Authority of Residence 0.0505 Vancouver Coastal 90 (26) 90 (26) 53 (15) 116 (33) Fraser 65 (39) 26 (16) 26 (16) 50 (30) Vancouver Island 26 (27) 14 (15) 19 (20) 36 (38) Interior 19 (39) 8 (16) 6 (12) 16 (33) Northern 5-9 (15-27)* 5-9 (15-27)* 3-7 (9-21)* 4-8 (12-24)* Unknown <5† <5† <5† <5† Continuous Variables Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) P-value Age 52 (41-60) 50 (42-56) 50 (40-58) 46 (40-55) 0.0050 Follow-up Time (Years) 10 (1-19) 13 (6-19) 7 (2-15) 10 (5-16) 0.0090 Index Year 2006 (2001-2016) 2001 (2001-2007) 2005 (2001-2006) 2004 (2001-2010) <0.0001 ART Initiation Year 2010 (2001-2017) 2005 (1998-2010) 2006 (1998-2017) 2007 (2001-2012) 0.0019 Note: SUD: substance use disorder, DTES: Downtown Eastside, PWID: people with a history of injecting drugs, gbMSM: gay, bisexual, and other men who have sex with Men, ART: antiretroviral therapy, Q1-Q3: 25th to 75th percentile 70 P-value estimates exclude "Unknown" categories; p-value significance is set at 0.05 * Due to data privacy, I replaced exact numbers if cells contained <5 participants † Due to privacy concerns, small cell counts (<5) were protected by displaying a range 71 Table 3.6 displays the median annual counts of healthcare utilizations, stratified by the diagnosis status of SUD and mood/anxiety disorders in (a) 2001, (b) 2010, and (c) 2019. Annual median counts excluded zeros for all healthcare utilization outcomes in the descriptive analyses. Compared to PLWH with neither disorder, PLWH with both disorders or only SUD had significantly more primary care physician and specialist visits and longer LOS. For example, in 2019, PLWH with both disorders had seven days longer median LOS (eight vs. one) and more than double the median counts of primary care physician visits (11 vs. four). I observed subtle but statistically significant differences between those with both disorders and those with only SUD, especially in recent years. For instance, in 2019, the median count of primary care physician visits for PLWH with both disorders was only one more (11 vs. 10), and LOS was only two days longer (eight vs. six) than for PLWH with only SUD. 72 Table 3.6. Median annual counts of healthcare utilizations among people living with HIV in British Columbia, Canada, stratified by the diagnosis status of SUD and mood/anxiety disorders in (a) 2001, (b) 2010, and (c) 2019. Diagnosis Status of SUD and Mood/Anxiety Disorders Neither Disorder N=799 Only SUD N=155 Only Mood/Anxiety Disorder N=563 Both Disorders N=288 a) 2001 Variable Total N Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) P-value Primary Care Physician Visits 1643 8 (5-13) 12 (5-27) 12 (8-19) 22 (11-44) <0.0001 Specialist Visits 1627 6 (3-13) 5 (3-12) 10 (5-19) 10 (5-22) <0.0001 Laboratory Visits 1796 6 (4-10) 8 (5-15) 7 (5-10) 8 (5-13) <0.0001 Acute Care Hospitalization 251 1 (1-2) 1 (1-2) 1 (1-2) 1 (1-3) 0.002 Day Surgery Episodes 128 1 (1-1) 1 (1-2) 1 (1-1) 1 (1-1) 0.5706 LOS (days) 349 4 (1-8) 7 (2-30) 2 (1-9) 12 (3-34) <0.0001 b) 2010 N=2127 N=490 N=1276 N=824 Variable Total N Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) P-value Primary Care Physician Visits 4384 5 (3-9) 10 (4-22) 8 (5-13) 14 (7-31) <0.0001 Specialist Visits 4127 4 (2-8) 6 (3-16) 6 (3-12) 9 (4-20) <0.0001 Laboratory Visits 4693 5 (4-8) 8 (5-13) 6 (4-9) 8 (5-12) <0.0001 Acute Care Hospitalization 623 1 (1-2) 1 (1-2) 1 (1-2) 2 (1-3) <0.0001 73 Day Surgery Episodes 490 1 (1-1) 1 (1-1) 1 (1-1) 1 (1-1) 0.8913 LOS (days) 1021 1 (1-5) 9 (3-31) 1 (1-4) 8 (3-26) <0.0001 c) 2019 N=3092 N=714 N=1508 N=1081 Variable Total N Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) P-value Primary Care Physician Visits 5895 4 (3-7) 10 (4-25) 6 (3-10) 11 (5-32) <0.0001 Specialist Visits 5837 5 (2-10) 7 (3-17) 7 (4-13) 10 (5-22) <0.0001 Laboratory Visits 6361 5 (4-6) 5 (4-9) 2-235 (4-7) 6 (4-10) <0.0001 Acute Care Hospitalization 810 1 (1-2) 1 (1-2) 1 (1-1) 1 (1-2) <0.0001 Day Surgery Episodes 768 1 (1-1) 1 (1-1) 1 (1-2) 1 (1-1) 0.7514 LOS (days) 1435 1 (1-4) 6 (2-17) 1 (1-6) 8 (2-23) <0.0001 Note: SUD: substance use disorder, LOS: length of stay, Q1-Q3: 25th to 75th percentile Counts restricted to values > 0 due to the presence of excess zero P-value estimates exclude “Unknown” categories; p-value significance is set at 0.05 74 Table 3.7 displays the median annual counts of healthcare utilizations of PLWH, stratified by sustained suppression in (a) 2001, (b) 2010, and (c) 2019. Compared to PLWH with sustained suppression, PLWH with unsustained suppression consistently had significantly higher median counts of all healthcare utilization outcomes except for acute care hospitalization. The most significant difference was observed for median LOS, which was eight days longer (10 vs. two days) in 2019. The original distributions of healthcare utilization counts (including zeros) are presented in Appendix C. All results for day surgery episodes were not statistically significant. Table 3.7. Median annual counts of healthcare utilizations among people living with HIV in British Columbia, Canada, stratified by sustained suppression in (a) 2001, (b) 2010, and (c) 2019. Sustained Suppression No Yes a) 2001 N=518 N=1287 Variable Total N Median (Q1-Q3) Median (Q1-Q3) P-value Primary Care Physician Visits 1643 14 (8-23) 9 (6-16) <0.0001 Specialist Visits 1627 11 (5-19) 7 (3-14) <0.0001 Laboratory Visits 1796 9 (6-13) 6 (4-9) <0.0001 Acute Care Hospitalization 251 1 (1-2) 1 (1-2) 0.0004 Day Surgery Episodes 128 1 (1-1) 1 (1-1) 0.8913 LOS (days) 349 9 (3-30) 3 (1-8) <0.0001 b) 2010 N=716 N=4001 Variable Total N Median (Q1-Q3) Median (Q1-Q3) P-value Primary Care Physician Visits 4384 10 (5-18) 7 (4-13) <0.0001 Specialist Visits 4127 7 (3-18) 5 (2-11) <0.0001 Laboratory Visits 4693 8 (5-12) 6 (4-9) <0.0001 75 Acute Care Hospitalization 623 1 (1-2) 1 (1-2) 0.1669 Day Surgery Episodes 490 1 (1-1) 1 (1-1) 0.8913 LOS (days) 1021 8 (2-28) 2 (1-9) <0.0001 c) 2019 N=506 N=5889 Variable Total N Median (Q1-Q3) Median (Q1-Q3) P-value Primary Care Physician Visits 5895 7 (4-20) 6 (3-10) <0.0001 Specialist Visits 5837 9 (4-21) 6 (3-12) <0.0001 Laboratory Visits 6361 6 (4-9) 5 (4-7) <0.0001 Acute Care Hospitalization 810 1 (1-3) 1 (1-2) 0.003 Day Surgery Episodes 768 1 (1-1) 1 (1-1) 0.7514 LOS (days) 1435 10 (3-30) 2 (1-8) <0.0001 Note: LOS: length of stay, Q1-Q3: 25th to 75th percentile Counts restricted to values > 0 due to the presence of excess zeros P-value significance is set at 0.05 Figure 3.2 displays the adjusted predicted mean counts for each healthcare utilization outcome, stratified by disorder diagnosis status and sustained suppression (see Appendix D for exact numbers). Due to a high proportion of zeros (Table 3.8), counts of acute care hospitalization were less than one. The model for LOS excluded zeros. 76 Figure 3.2. Adjusted predicted mean counts of healthcare utilization outcomes with 95% confidence intervals, stratified by diagnosis status of SUD and mood/anxiety disorders and sustained suppression. 77 78 Note: Each healthcare utilization outcome was modelled separately using a single, eight-level exposure variable that combined the diagnosis status of the disorders and sustained suppression. The negative binomial model was selected for specialist visits, acute care hospitalization and LOS. The zero-inflated and the two-part (hurdle) negative binomial models were used for primary care physician visits and laboratory visits, respectively. All counts were adjusted for age, gender, income assistance, residency in the Downtown Eastside, and ART initiation year. Length of stay restricted to values > 0. Scales of the horizontal axes differ for each plot for illustration purposes. 79 Table 3.8. Percentage of zeros observed in healthcare utilization. Healthcare Utilization Outcome # of Zeros % of Zeros Primary Care Physician Visits 6927 8.30% Specialist Visits 9479 11.30% Laboratory Visits 397 0.50% Acute Care Hospitalization 72522 86.50% Day Surgery 75021 89.50% Length of Stay 65461 78.10% Pharmacy Dispensations 5601 6.70% Note: Total Number of Observations = 83,804 There were subtle differences between the median number of VL measures per year for PLWH with sustained and unsustained suppression (4; Q1-Q3:3-4 vs. 5; Q1-Q3:4-7) (Table 3.9). Table 3.9. Distribution of the number of viral load measurements per year for people living with HIV who had sustained and unsustained suppression. Quantiles Unsustained Suppression Sustained Suppression N = 12334 N = 71470 100% Max 27 21 99% 12 10 95% 10 7 90% 9 6 75% Q3 7 4 50% Median 5 4 25% Q1 4 3 10% 3 2 80 5% 2 2 1% 2 2 0% Min 2 2 Note: Q1-Q3: 25th to 75th percentile In the presence of sustained suppression, having both disorders was significantly associated with almost double the estimated number of primary care physician (13.1 vs. 6.9) and specialist (7.9 vs. 4.0) visits, over four times more acute care hospitalizations (0.28 vs. 0.05) and three times longer LOS (9.1 vs. 3.0 days), compared to PLWH with neither disorder. Having only SUD was significantly associated with four times more acute care hospitalization (0.22 vs. 0.05) and twice longer LOS (7.8 vs. 3.0). Although having only SUD was also associated with significantly more primary care physician, specialist and laboratory visits, the magnitude of its association was smaller than with having both disorders. Having only mood/anxiety disorders was significantly associated with higher numbers of primary care physician and specialist visits. However, the increases associated with having only mood/anxiety disorders were much lower than that of having only SUD. There were no significant associations between having only mood/anxiety disorders and acute care hospitalization and LOS. Regardless of disorder diagnosis, unsustained suppression was significantly associated with more primary care physician, specialist and laboratory visits, acute care hospitalizations and longer LOS. For example, among those with both disorders, unsustained suppression was significantly associated with double the estimated number of acute care hospitalizations (0.28 vs. 0.55), six days longer LOS (15.5 vs. 9.1), five more primary care physician visits (17.8 vs. 13.1), and four more specialist visits (11.8 vs. 7.9). 81 3.4. Discussion In this study, SUD (alone or combined with mood/anxiety disorders) was associated with the highest counts of acute care hospitalizations and the most extended LOS. SUD alone was associated with increased use of primary care and specialist physician services, acute care hospitalization, and LOS. Although mood/anxiety disorders alone were not significantly associated with increased acute care hospitalization and LOS, they were associated with more frequent primary care physician and specialist visits. The associations between SUD and mood/anxiety disorders and increased healthcare utilization were independent of sustained suppression. For all PLWH, unsustained suppression was also independently associated with increased utilization of all healthcare services (except day surgery). Our finding that SUD alone or in combination with mood/anxiety disorders was associated with the highest number of primary care and specialist physician visits is consistent with most studies of the general population.160,161,197 However, some research examining the effects of SUD on primary care utilization has yielded mixed results.165,198 For example, in a comparative study, alcohol use disorder was significantly associated with lower utilization of outpatient healthcare services among an underserved group of PLWH, but not among PLWH engaged in HIV care.165 Similarly, another study found reduced primary care utilization among marginalized PWID.198 My results may be inconsistent with these studies due to differences in populations (e.g. PLWH vs. PWID), outcome definitions (e.g. primary care vs. outpatient care), and healthcare systems. Plausibly, my study population may have higher primary care utilization than marginalized individuals in other studies since they are engaged with HIV care and have free-of-charge access to healthcare services.99 Considering that I studied SUD as a general category of disease, 82 differences in results may also be due to variations in the type and severity of the SUD examined by other studies. SUD was also significantly associated with increased acute care hospitalization and longer LOS. These findings agree with studies of the general population and PLWH.94,150,161,163-165,199 Factors contributing to this association may include chronic comorbidities and SUD-induced medical conditions common among PLWH with SUD.160 Chronic comorbidities, such as kidney, respiratory and cardiovascular diseases, cancers, and acute SUD-related conditions (e.g. non-fatal overdose, intoxication-related injuries and skin infections), often increase the need for urgent and extensive medical care.164,200,201 It is worth noting that PLWH with SUD were more likely to be women, on income assistance and residents of the DTES. These results agree with other studies suggesting that among people with HIV and SUD, women and individuals with socio-economic disadvantages, such as low income, housing instability, food insecurities and experiences of violence, have a higher risk of hospitalization.9,55,95,168,192,193 I did not find significant associations between mood/anxiety disorders and increased hospitalization and LOS. My findings contrast with prior research of the general population and a cohort study in Ontario, Canada, that found an elevated risk of hospital admission among PLWH meeting the criteria for depression in the past four weeks.94,159,162,202,203 Some studies have identified a higher risk for hospitalization and prolonged stays among individuals with specific types of mood/anxiety disorders, such as general anxiety and bipolar disorders.94,159,162,202 However, I measured mood/anxiety disorders as a broad category of disease, ascertained with administrative health data, over a 5-year lookback window. The episodic nature of the more common mood/anxiety disorders, such as depression, may have also affected my results. Thus, the 83 disparity in results may be due to the type, chronicity and severity of the disorders examined and to the ascertainment methods. In the results, episodes of day surgeries were not associated with SUD or mood/anxiety disorder. Nonetheless, this lack of association may be due to treatment bias in healthcare settings since the stigma associated with SUD often prevents patients with SUD from receiving appropriate diagnoses and surgery referrals.204 I found that, independent of sustained suppression, SUD and mood/anxiety disorders contributed to higher healthcare utilization among PLWH. While the absence of sustained suppression combined with the diagnosis of both disorders or of only SUD was associated with the highest increase in healthcare utilization, the increase associated with these disorders was also significant in the presence of sustained suppression. Nevertheless, aligned with previous studies, unsustained suppression was associated with a consistent increase in healthcare utilization for the entire population.154,186,187 Therefore, this study highlights the importance of long-term suppression as a crucial determinant of healthcare utilization among PLWH. Strengths and limitation To my knowledge, this is the first population-based cohort study of ART-treated PLWH that examined the impact of SUD and mood/anxiety disorders on various healthcare utilization outcomes in the absence and presence of sustained suppression. As a strength, this study was conducted in a setting where ART and HIV laboratory monitoring are accessible free of charge, and public health insurance covers all residents' medically necessary expenses. In addition, this study analyzed counts of healthcare encounters instead of financial costs, allowing for comparability of results across different settings. Nonetheless, this study has some limitations 84 worth considering. First, administrative health record data were not collected for research purposes and may be prone to diagnostic coding errors and misclassifications that may be a source of bias. Second, due to using a single diagnostic code encompassing both mood and anxiety disorders in BC health records, I could not examine the separate effects of these disorders on the usage of healthcare services. Likewise, I was not able to explore the impact of specific SUDs. Third, the sustained suppression variable may have been subjected to bias due to varying numbers of VL measurements per year across individuals since PLWH with fewer measurements are more likely to be classified as having sustained suppression. However, I observed that the number of VL measurements per year for PLWH with sustained suppression was slightly less than those with unsustained suppression. Lastly, I did not include other healthcare utilization indicators, such as ambulatory and emergency department visits, due to a lack of available data. I also could not control for other potential sociodemographic confounders, such as ethnicity, housing stability, education, employment, social support, and food insecurity. However, I tried to address this limitation by using income assistance and residency in the DTES variables as proxy variables for these sociodemographic factors. 3.5. Conclusion In this study, SUD, mood/anxiety disorders, and unsustained suppression, individually and in combination, contributed to higher healthcare utilization. However, it is evident that independent of their effect on viral suppression, SUD and mood/anxiety disorders were associated with increased healthcare utilization among PLWH. Hence, providing integrated care for mental health and SUD for PLWH may be an effective strategy for minimizing the burden associated with these 85 disorders and reducing strains on the healthcare system. The observed associations between unsustained suppression and increased healthcare utilization also re-emphasize the necessity of long-term suppression for optimizing health outcomes and healthcare utilization within this population. Furthermore, the high proportion of women and individuals on income assistance among PLWH with SUD calls for targeted interventions and strategic healthcare resource allocation to reduce the burden of SUD among the most vulnerable groups of PLWH. 86 Chapter 4: Conclusion 4.1. Overview The first aim of the thesis was to examine the impacts of mood/anxiety disorder and SUD on the HIV continuum of care and identify the point of highest attrition in the continuum. Chapter 2 addressed this aim by examining the HIV continuum of care for PLWH with and without mood/anxiety disorders and SUD from 2001 to 2019; the stage of sustained suppression was identified as the continuum stage with the highest attrition. Chapter 2 also addressed the first aim by assessing the association between mood/anxiety disorder, SUD and both disorders and the achievement of each of the stages of the HIV continuum of care. The second aim of this thesis was to examine the effects of mood/anxiety disorders, SUD, and disengagement from HIV care at the point of highest attrition on healthcare utilization of PLWH. Chapter 3 addressed the second aim by measuring the distinct and combined effects of mood/anxiety disorders, SUD, and unsustained suppression on various healthcare utilization outcomes among PLWH who achieved viral suppression. 4.2. Summary of Findings Mood/Anxiety Disorders, SUD on the HIV Continuum of Care This thesis identified SUD as a significant determinant of attrition across the HIV continuum of care. These findings support research conducted in other settings, which have identified SUD as a barrier to ART initiation, ART adherence, and sustained viral suppression.83,85,113,137,138 However, previous studies examining the impact of SUD on separate HIV outcomes were limited since they 87 mostly used cross-sectional designs, relied on self-reported data, or were focused on only certain types of SUD (e.g., injection or illicit drug use) and sub-populations of PLWH such as women and heterosexual men.83,85,113,137,138 Using longitudinal administrative data from COAST, ICD diagnostic codes and previously validated case-finding algorithms, I assessed the impact of SUD on all stages of the HIV continuum of care among a large cohort of PLWH over a 19-year period. Therefore, the results of this thesis strengthen the growing body of evidence suggesting that SUD is a significant barrier to optimal HIV outcomes and calls for public health interventions aimed at reducing the burden of SUD among PLWH. In addition, Chapter 2 identified women, younger and low-income individuals, and residents of the DTES as sub-groups of PLWH in BC who are disproportionately affected by SUD. Such findings suggest that effective strategies for addressing SUD-related issues among PLWH should include targeted interventions for sub-populations of PLWH who are most vulnerable to SUD. Contrary to my hypothesis, in Chapter 2, I observed that PLWH with mood/anxiety disorders were more likely to initiate ART. The positive association between depression and ART initiation is also seen in another Canadian study and a few studies in low and middle-income countries.92,102,103 It is speculated that PLWH with diagnosed mood/anxiety disorders are more likely to initiate ART since they are connected to healthcare services for their psychiatric diagnosis.184 In contrast to the findings of other studies, in this thesis, I did not find significant associations between mood/anxiety disorders and viral suppression.90,91 However, this lack of association may be attributed to mood/anxiety disorder severity and treatment status that were not captured in this thesis and the liberal definition used for viral suppression.140 Furthermore, in this thesis, mood/anxiety disorders did not significantly affect HIV outcomes for PLWH with SUD 88 since the impact of combined SUD and mood/anxiety disorders on the HIV continuum of care was similar to that of SUD alone. Nevertheless, in agreement with studies conducted in other settings, this thesis confirmed that mood/anxiety disorders are significantly associated with incomplete ART adherence and unsustained suppression.46,84,93,112-122,141 Therefore, this thesis provide further evidence suggesting that improving mental health outcomes among PLWH is an effective strategy for optimizing HIV outcomes and achieving HIV control. This thesis determined the sustainment of viral suppression as the stage with the highest attrition in the HIV continuum of care for all PLWH in BC. This finding raises significant concerns since sustained suppression is highly essential for preventing morbidity and mortality among PLWH, minimizing the risk of HIV, and controlling the HIV epidemic.137 Previous studies examining the HIV continuum of care and its correlates of attrition have set viral suppression as the final stage of the continuum.67,68,70,71,74,76,77,83,91,114,145,146,205 Therefore, this thesis is unique in that it includes sustained suppression, an important indicator of HIV control, as an additional stage of the HIV continuum of care. Mood/anxiety disorders, SUD, Unsustained Suppression and Healthcare utilization In Chapter 3, PLWH with SUD or both SUD and mood/anxiety disorders had the highest healthcare utilization. Although the impacts of SUD and mood/anxiety disorders on healthcare utilization have been widely studied within the general population,160,161,163,164,197,199 there is a lack of comprehensive studies examining the effects of these disorders on the healthcare utilization of PLWH. Previous studies investigating the healthcare utilization patterns of PLWH are mostly older, focused on medical expenditures, or did not include important healthcare utilization 89 indicators such as primary care and specialist physician services.94-96,150,165 This thesis identified SUD as a significant determinant of high healthcare utilization among a large cohort of medically insured ART-treated PLWH. This thesis addresses some knowledge gaps within the literature since it found significant associations between SUD and increased primary care physician and specialist physician visits. Furthermore, this thesis supports previous studies that have determined SUD as a factor contributing to increased hospitalizations among PLWH.94,150,165 The high usage of hospital services among PLWH with SUD is partially due to a high prevalence of chronic comorbidities and SUD-induced medical conditions that require more complex care offered within hospital settings.164,200,201 Such findings highlight the necessity of addressing SUD-related issues to reduce the hospital burden associated with SUD and HIV. Contrary to my hypothesis and some study findings, mood/anxiety disorders were not associated with hospitalization and LOS among PLWH.94,159,162,202,203 This lack of association may be because mood/anxiety disorders were measured as a single category of disorder and that I did not account for the type and severity of the disorders. Nonetheless, this thesis found significant associations between mood/anxiety disorder and more frequent physician and specialist physician visits. Plausibly, PLWH with diagnosed mood/anxiety disorders require less hospital care due to routine engagement with primary care and specialist physician services. Such findings suggest that improving mental health outcomes among PLWH can prevent the strained use of healthcare systems. Furthermore, this thesis found unsustained suppression, the most challenging stage of the HIV continuum of care, as an independent factor contributing to high healthcare utilization among PLWH. This finding supports another Canadian study that has found reduced healthcare costs 90 associated with sustained suppression.154 Such results suggest that identifying and removing barriers to sustained suppression is crucial for reducing the healthcare burden associated with HIV. A uniqueness of this thesis is that it controls for the effects of unsustained viral suppression when examining the impacts of SUD and mood/anxiety disorders on healthcare utilization of PLWH. Given that the impacts of SUD and mood/anxiety disorders on healthcare utilizations were independent of sustained suppression, SUD, mood/anxiety disorders, and unsustained suppression as distinct correlates of high healthcare utilization among PLWH. 4.3. Strengths and Limitations The discussion sections of Chapters 2 and 3 list the strengths and limitations specific to each study. Here, I outline the strengths and limitations common to both studies. Strengths As a significant strength, the studies presented in this thesis are retrospective cohort studies that utilize 19 years of data from a large population of PLWH who are medically insured for essential healthcare services and have free-of-charge access to ART and HIV care through the BC-CfE. In addition, the BC-CfE captured all ART dispensations and VL measures among PLWH in BC during the study period. Hence, this thesis utilized a reliable data source to assess the progress of PLWH through the HIV continuum of care. However, the findings of this thesis may not be generalized to contexts where health insurance is a barrier to healthcare access or settings where ART and HIV care are not as widely accessible to PLWH. 91 Limitations The studies in this thesis are subject to limitations that must be accounted for. First, the health record data utilized for these studies were from administrative databases and were not initially collected for research purposes. These administrative databases capture healthcare records data from real-time clinical practices provided by healthcare providers. Thus, the data used are prone to diagnostic coding errors and misclassification bias. Furthermore, I did not assess the distinct effects of mood and anxiety disorders since I used the BC-specific code, 50B, which encompasses both types of disorders. Likewise, I did not examine the impacts of specific types of SUDs since I studied SUD as a general category of disorder. It is also worth considering that perceptions and beliefs about mental health and substance use vary across time, geographic, and cultural settings and can affect healthcare-seeking patterns, diagnosis procedures, willingness to access treatment and the prevalence of these disorders.206,207 Hence, the findings and recommendations in this thesis may not be generalized to all contexts. As another limitation, due to a lack of available data, I did not control for other relevant socio-demographic confounders, such as education, employment, housing and food insecurity. 4.4. Public Health Implications According to this thesis, sustainment of viral suppression is the most challenging stage of the HIV continuum of care and a significant determinant of high healthcare utilization among PLWH. Therefore, identifying and eliminating barriers to sustained suppression is crucial for optimizing HIV outcomes among PLWH and reducing the healthcare burden associated with HIV. 92 In Chapter 2, SUD was a significant determinant of attrition across the HIV continuum of care and mood/anxiety disorders were identified as factors contributing to incomplete ART adherence and unsustained suppression. Such results suggest that integrating mental health and substance use services into HIV care can be beneficial to improving HIV care continuity and achieving HIV control. In Chapter 3, it was also shown that SUD alone and in combination with mood/anxiety are significantly associated with frequent hospitalization and extended hospital stays. This finding implies that allocating healthcare resources to mental health and substance use treatment can help reduce the burden of HIV on the healthcare system and reduce hospitalization costs for this population. Practical strategies for reducing the burden of SUD and mood/anxiety disorder among PLWH may include screening for SUD and mood/anxiety disorders upon HIV diagnosis, providing patient-centred care, and reducing the stigma associated with mental health and substance use disorders in healthcare settings.169,205,207,208 Effective interventions may also include providing psychotherapies (e.g., cognitive behaviour therapy) in addition to pharmacological treatments for mood/anxiety disorders and SUD.11 Allocating resources to building more mental health and substance use care facilities, improving staff training, reducing wait times, and removing transportation barriers can be beneficial for promoting engagement with mental health and substance use services.208,209 Furthermore, raising the awareness of healthcare providers about the experiences and challenges of PLWH with mental health and substance use disorders is also essential for enhancing healthcare delivery to these individuals and improving treatment uptake.207,209 Other effective interventions may include providing community-based mental and substance use services and facilitating peer support.206 Given the gender and socio-economic 93 disparities observed among PLWH with SUD in this thesis, interventions must be targeted at key subpopulations of PLWH who are most affected by SUD. 4.5. Final Remarks In this thesis, the sustainment of viral suppression was identified as the most challenging stage of the HIV continuum of care and as a major determinant of high healthcare utilization, especially for PLWH with SUD and mood/anxiety disorders. Overall, SUD was identified as a significant correlate of attrition in the HIV continuum of care and high healthcare utilization, disproportionately affecting women and those experiencing socio-economic disparities. Therefore, the results of this thesis imply that the integration of mental health and substance use healthcare services is crucial for improving HIV outcomes and optimizing healthcare utilization and costs among PLWH. However, this thesis did not account for mood/anxiety disorder and SUD type and severity. 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Accessed July 7, 2023. https://epidata.shinyapps.io/BC_diagnostic_codes/ 125 Appendices Appendix A List of diseases and respective case-finding algorithms Disease Case Definitions Diagnostic, Procedure, and/ or Drug Codes References Mood/Anxiety Disorders 1 or more hospitalization with a mood or anxiety diagnostic code OR 2 or more medical visits with a mood/anxiety disorder diagnostic code within one year ICD-9: 296: Affective psychoses 300: Neurotic disorders 311: Depressive disorder, not elsewhere classified MSP DX code 50B: Anxiety/Depression ICD-10: F30: Manic episode F31: Bipolar affective disorder F32: Depressive episode F33: Recurrent depressive disorder F34: Persistent mood [affective] disorders F38: Other mood [affective] disorders F39: Unspecified mood [affective] disorder F40: Phobic anxiety disorders F41: Other anxiety disorders F42: Obsessive-compulsive disorder F43: Reaction to severe stress, and adjustment disorders F44: Dissociative (conversion) disorders F45: Somatoform disorders F48: Other neurotic disorders F68: Other disorders of adult personality and behaviour 1, 2 Substance Use Disorder (SUD) 1 or more hospitalization with SUD diagnostic code ICD-9: 291: Alcoholic psychoses 292: Drug psychoses 2,3 126 OR 2 or more physician visits with SUD diagnostic code within one year 303: Alcohol dependence syndrome 304: Drug dependence 305: Nondependent abuse of drugs ICD-10: F10: Mental and behavioural disorders due to use of alcohol F11: Mental and behavioural disorders due to use of opioids F12: Mental and behavioural disorders due to use of cannabinoids F13: Mental and behavioural disorders due to use of sedative or hypnotics F14: Mental and behavioural disorders due to use of cocaine F15: Mental and behavioural disorders due to use of other stimulants including caffeine F16: Mental and behavioural disorders due to use of hallucinogens F17: Mental and behavioural disorders due to use of tobacco F18: Mental and behavioural disorders due to use of volatile solvents F19: Mental and behavioural disorders due to multiple drug use and psychoactive substance use References 1. Chronic Disease Information Working Group. BC Chronic Disease and Selected Procedure Case Definitions, Case Definition – Mood and Anxiety Disorders. BC Ministry of Health. Updated 2020. Accessed 11-Jun-2021, http://www.bccdc.ca/resource-gallery/Documents/Chronic-Disease-Dashboard/mood-anxiety-disorders.pdf 2. Identifying diagnostic codes in BC administrative health data. Accessed July 7, 2023. https://epidata.shinyapps.io/BC_diagnostic_codes/ 127 3. BC Ministry of Health. British Columbia Chronic Disease Registries (BCCDR) Case Definitions - Substance Use Disorder. Accessed Nov 11, 2022. https://zmail.cfenet.ubc.ca/service/home/~/?auth=co&loc=en_US&id=9395&part=2 128 Appendix B Estimated Annual Number and Percentage of People Living with HIV at Each Stage of the HIV Continuum of Care B.1. Annual estimates of the number of PLWH with neither SUD nor mood/anxiety disorders at each stage of the HIV continuum of care in British Columbia, Canada, from 2001-2019. Year Living with HIV (N) ART Initiation (N) ART Initiation (%) On-ART (N) On-ART (%) ART Adherence (N) ART Adherence (%) Viral Suppression (N) Viral Suppression (%) Sustained Suppression (N) Sustained Suppression (%) 2001 2023 1511 75% 1230 81% 963 78% 860 89% 616 72% 2002 2233 1649 74% 1289 78% 1017 79% 933 92% 690 74% 2003 2368 1756 74% 1306 74% 1032 79% 972 94% 691 71% 2004 2473 1835 74% 1396 76% 1184 85% 1129 95% 832 74% 2005 2578 1920 74% 1486 77% 1332 90% 1271 95% 979 77% 2006 2663 1999 75% 1628 81% 1458 90% 1414 97% 1136 80% 2007 2782 2147 77% 1797 84% 1659 92% 1628 98% 1313 81% 2008 2985 2368 79% 2036 86% 1895 93% 1866 98% 1498 80% 2009 3118 2540 81% 2222 87% 2079 94% 2038 98% 1714 84% 2010 3287 2753 84% 2432 88% 2297 94% 2257 98% 1912 85% 2011 3467 2962 85% 2659 90% 2527 95% 2485 98% 2131 86% 2012 3645 3187 87% 2876 90% 2725 95% 2685 99% 2323 87% 2013 3811 3392 89% 3060 90% 2941 96% 2905 99% 2499 86% 2014 3921 3548 90% 3243 91% 3115 96% 3087 99% 2691 87% 2015 3987 3646 91% 3340 92% 3225 97% 3200 99% 2747 86% 2016 4068 3781 93% 3455 91% 3339 97% 3307 99% 2917 88% 2017 4087 3824 94% 3509 92% 3387 97% 3361 99% 2947 88% 2018 4031 3801 94% 3512 92% 3392 97% 3368 99% 2973 88% 2019 3973 3777 95% 3525 93% 3441 98% 3418 99% 2999 88% 129 B.2. Annual estimates of the number of PLWH with SUD at each stage of the HIV continuum of care in British Columbia, Canada, from 2001-2019. Year Living with HIV (N) ART Initiation (N) ART Initiation (%) On-ART (N) On-ART (%) ART Adherence (N) ART Adherence (%) Viral Suppression (N) Viral Suppression (%) Sustained Suppression (N) Sustained Suppression (%) 2001 719 463 64% 332 72% 201 61% 176 88% 104 59% 2002 748 475 64% 333 70% 196 59% 176 90% 109 62% 2003 802 518 65% 354 68% 230 65% 208 90% 126 61% 2004 864 538 62% 376 70% 265 70% 248 94% 153 62% 2005 872 549 63% 408 74% 289 71% 276 96% 159 58% 2006 874 557 64% 412 74% 304 74% 286 94% 190 66% 2007 880 585 66% 474 81% 347 73% 335 97% 215 64% 2008 915 629 69% 532 85% 409 77% 395 97% 258 65% 2009 944 710 75% 624 88% 509 82% 491 96% 343 70% 2010 954 746 78% 658 88% 548 83% 530 97% 381 72% 2011 953 792 83% 716 90% 626 87% 615 98% 440 72% 2012 938 805 86% 737 92% 657 89% 636 97% 468 74% 2013 948 836 88% 768 92% 672 88% 658 98% 496 75% 2014 959 864 90% 810 94% 721 89% 707 98% 539 76% 2015 975 895 92% 841 94% 736 88% 722 98% 554 77% 2016 1017 924 91% 864 94% 767 89% 750 98% 584 78% 2017 1049 962 92% 895 93% 788 88% 772 98% 580 75% 2018 1054 978 93% 902 92% 812 90% 791 97% 626 79% 2019 1054 981 93% 922 94% 822 89% 798 97% 621 78% 130 B.3. Annual estimates of the number of PLWH with mood/anxiety disorders at each stage of the HIV continuum of care and the percentage of attrition at each stage in British Columbia, Canada, from 2001-2019. Year Living with HIV (N) ART Initiation (N) ART Initiation (%) On-ART (N) On-ART (%) ART Adherence (N) ART Adherence (%) Viral Suppression (N) Viral Suppression (%) Sustained Suppression (N) Sustained Suppression (%) 2001 1385 1091 79% 872 80% 660 76% 587 89% 414 71% 2002 1412 1095 78% 835 76% 630 75% 588 93% 399 68% 2003 1467 1146 78% 891 78% 681 76% 645 95% 447 69% 2004 1544 1182 77% 926 78% 773 83% 743 96% 537 72% 2005 1643 1271 77% 1041 82% 911 88% 880 97% 660 75% 2006 1699 1332 78% 1145 86% 1030 90% 1008 98% 802 80% 2007 1722 1364 79% 1209 89% 1118 92% 1099 98% 868 79% 2008 1707 1385 81% 1257 91% 1167 93% 1148 98% 933 81% 2009 1733 1472 85% 1359 92% 1285 95% 1274 99% 1044 82% 2010 1769 1528 86% 1422 93% 1349 95% 1329 99% 1133 85% 2011 1803 1611 89% 1510 94% 1443 96% 1426 99% 1188 83% 2012 1770 1612 91% 1522 94% 1452 95% 1435 99% 1242 87% 2013 1741 1604 92% 1527 95% 1455 95% 1447 99% 1239 86% 2014 1733 1629 94% 1552 95% 1495 96% 1488 100% 1296 87% 2015 1779 1682 95% 1594 95% 1545 97% 1538 100% 1321 86% 2016 1755 1663 95% 1579 95% 1525 97% 1522 100% 1331 87% 2017 1761 1684 96% 1600 95% 1551 97% 1539 99% 1345 87% 2018 1800 1732 96% 1648 95% 1608 98% 1600 100% 1402 88% 2019 1783 1721 97% 1660 96% 1619 98% 1613 100% 1436 89% 131 B.4. Annual estimates of the number of PLWH with both SUD and mood/anxiety disorders at each stage of the HIV continuum of care and the percentage of attrition at each stage in British Columbia, Canada, from 2001-2019. Year Living with HIV (N) ART Initiation (N) ART Initiation (%) On-ART (N) On-ART (%) ART Adherence (N) ART Adherence (%) Viral Suppression (N) Viral Suppression (%) Sustained Suppression (N) Sustained Suppression (%) 2001 1184 833 70% 578 69% 351 61% 316 90% 170 54% 2002 1252 890 71% 610 69% 346 57% 319 92% 174 55% 2003 1326 912 69% 621 68% 377 61% 347 92% 182 52% 2004 1377 940 68% 660 70% 439 67% 411 94% 223 54% 2005 1418 979 69% 712 73% 492 69% 456 93% 274 60% 2006 1435 1003 70% 773 77% 552 71% 522 95% 332 64% 2007 1445 1057 73% 846 80% 647 76% 615 95% 387 63% 2008 1452 1093 75% 932 85% 749 80% 726 97% 447 62% 2009 1459 1149 79% 1011 88% 848 84% 814 96% 557 68% 2010 1463 1178 81% 1063 90% 912 86% 880 96% 624 71% 2011 1447 1230 85% 1124 91% 955 85% 922 97% 653 71% 2012 1448 1275 88% 1171 92% 1011 86% 975 96% 731 75% 2013 1478 1318 89% 1222 93% 1080 88% 1064 99% 785 74% 2014 1477 1339 91% 1253 94% 1108 88% 1084 98% 817 75% 2015 1510 1393 92% 1301 93% 1187 91% 1163 98% 873 75% 2016 1527 1415 93% 1311 93% 1167 89% 1152 99% 911 79% 2017 1484 1380 93% 1280 93% 1141 89% 1115 98% 877 79% 2018 1493 1389 93% 1302 94% 1172 90% 1158 99% 908 78% 2019 1516 1409 93% 1325 94% 1194 90% 1178 99% 933 79% 132 Appendix C Original Distribution for the Annual Counts of Healthcare Utilizations C.1. Original distribution for the annual counts of healthcare utilizations among people living with HIV in British Columbia, Canada, stratified by the diagnosis status of SUD and mood/anxiety disorders in (a) 2001, (b) 2010, and (c) 2019. Diagnosis Status of SUD and Mood/Anxiety Disorders Neither Disorder N=799 Only SUD N=155 Only Mood/Anxiety Disorder N=563 Both Disorders N=288 a) 2001 Variable Total N Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) P-value Primary Care Physician Visits 1805 7 (4-12) 7 (0-18) 11 (7-18) 20 (9-41) <0.0001 Specialist Visits 1805 5 (2-12) 4 (1-10) 9 (3-18) 9 (4-20) <0.0001 Laboratory Visits 1805 6 (4-10) 8 (4-15) 7 (5-10) 8 (5-13) <0.0001 Acute Care Hospitalization 1805 0 (0-0) 0 (0-0) 0 (0-0) 0 (0-1) <0.0001 Day Surgery Episodes 1805 0 (0-0) 0 (0-0) 0 (0-0) 0 (0-0) 0.2493 LOS (days) 1805 0 (0-0) 0 (0-1) 0 (0-0) 0 (0-5) <0.0001 b) 2010 N=2127 N=490 N=1276 N=824 Variable Total N Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) P-value Primary Care Physician Visits 4717 5 (2-8) 8 (2-19) 8 (5-13) 14 (6-30) <0.0001 Specialist Visits 4717 3 (1-7) 5 (1-13) 5 (2-11) 8 (3-19) <0.0001 Laboratory Visits 4717 5 (4-8) 8 (5-13) 6 (4-9) 8 (5-12) <0.0001 Acute Care Hospitalization 4717 0 (0-0) 0 (0-0) 0 (0-0) 0 (0-1) <0.0001 Day Surgery Episodes 4717 0 (0-0) 0 (0-0) 0 (0-0) 0 (0-0) <0.0001 LOS (days) 4717 0 (0-0) 0 (0-0) 0 (0-0) 0 (0-4) <0.0001 c) 2019 N=3092 N=714 N=1508 N=1081 Variable Total N Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) Median (Q1-Q3) P-value Primary Care Physician Visits 6395 4 (2-7) 9 (3-23) 6 (3-9) 10 (4-30) <0.0001 133 Specialist Visits 6395 4 (2-9) 6 (2-16) 6 (3-12) 10 (4-21) <0.0001 Laboratory Visits 6395 5 (4-6) 5 (4-9) 5 (4-7) 6 (4-10) <0.0001 Acute Care Hospitalization 6395 0 (0-0) 0 (0-0) 0 (0-0) 0 (0-1) <0.0001 Day Surgery Episodes 6395 0 (0-0) 0 (0-0) 0 (0-0) 0 (0-0) 0.0029 LOS (days) 6395 0 (0-1) 0 (0-1) 0 (0-0) 0 (0-2) <0.0001 Note: SUD: substance use disorder, LOS: length of stay, Q1-Q3: 25th to 75th percentile Counts restricted to values > 0 due to the presence of excess zero P-value estimates exclude "Unknown" categories; p-value significance is set at 0.05 134 C.2. Original distribution for the annual counts of healthcare utilizations among people living with HIV in British Columbia, Canada, stratified by sustained suppression in (a) 2001, (b) 2010, and (c) 2019. Sustained Suppression No Yes a) 2001 N=518 N=1287 Variable Total N Median (Q1-Q3) Median (Q1-Q3) P-value Primary Care Physician Visits 1805 13 (6-22) 9 (5-15) <0.0001 Specialist Visits 1805 10 (4-19) 6 (2-13) <0.0001 Laboratory Visits 1805 9 (6-13) 6 (4-9) <0.0001 Acute Care Hospitalization 1805 0 (0-1) 0 (0-0) <0.0001 Day Surgery Episodes 1805 0 (0-0) 0 (0-0) 0.5209 LOS (days) 1805 0 (0-2) 0 (0-0) <0.0001 b) 2010 N=716 N=4001 Variable Total N Median (Q1-Q3) Median (Q1-Q3) P-value Primary Care Physician Visits 4717 5 (2-8) 8 (5-13) <0.0001 Specialist Visits 4717 3 (1-7) 5 (2-11) <0.0001 Laboratory Visits 4717 5 (4-8) 6 (4-9) <0.0001 Acute Care Hospitalization 4717 0 (0-0) 0 (0-0) <0.0001 Day Surgery Episodes 4717 0 (0-0) 0 (0-0) 0.2148 LOS (days) 4717 0 (0-0) 0 (0-0) <0.0001 c) 2019 N=506 N=5889 Variable Total N Median (Q1-Q3) Median (Q1-Q3) P-value Primary Care Physician Visits 6395 7 (3-19) 5 (2-10) <0.0001 Specialist Visits 6395 8 (3-18) 5 (2-11) <0.0001 Laboratory Visits 6395 6 (4-9) 5 (4-7) <0.0001 Acute Care Hospitalization 6395 0 (0-1) 0 (0-0) 0.0971 Day Surgery Episodes 6395 0 (0-0) 0 (0-0) <0.0001 LOS (days) 6395 0 (0-3) 0 (0-0) <0.0001 Note: LOS: length of stay, Q1-Q3: 25th to 75th percentile Counts restricted to values > 0 due to the presence of excess zeros P-value estimates exclude "Unknown" categories; p-value significance is set at 0.05 135 Appendix D Adjusted predicted mean counts of healthcare utilization with 95% confidence intervals D.1. Primary Care Physician Visits Exposure Category Adjusted Predicted Mean Count* (95% CI) Sustained Suppression and Neither Disorder 6.90 (6.48-7.38) Sustained Suppression and only SUD 11.37 (10.60-12.17) Sustained Suppression and only Mood/Anxiety Disorder 8.97 (8.40-9.56) Sustained Suppression and Both disorders 13.14 (12.29-14.05) Unsustained Suppression and Neither Disorder 9.72 (9.07-10.40) Unsustained Suppression and only SUD 14.77 (13.71-15.88) Unsustained Suppression and only Mood/Anxiety Disorder 12.24 (11.45-13.13) Unsustained Suppression and Both Disorders 17.75 (16.62-18.96) Note: SUD: Substance Use Disorder, CI: Confidence Interval * Zero-Inflated Negative Binomial Model D.2. Specialist Visits Exposure Category Adjusted Predicted Mean Count* (95% CI) Sustained Suppression and Neither Disorder 3.98 (3.69-4.30) Sustained Suppression and only SUD 6.24 (5.76-6.77) Sustained Suppression and only Mood/Anxiety Disorder 5.26 (4.87-5.69) Sustained Suppression and Both disorders 7.86 (7.26-8.50) Unsustained Suppression and Neither Disorder 6.41 (5.92-6.95) 136 Unsustained Suppression and only SUD 9.11 (8.34-9.95) Unsustained Suppression and only Mood/Anxiety Disorder 8.12 (7.47-8.82) Unsustained Suppression and Both Disorders 11.80 (10.86-12.81) Note: SUD: Substance Use Disorder, CI: Confidence Interval * Negative Binomial Model D.3. Laboratory Visits Exposure Category Adjusted Predicted Mean Count* (95% CI) Sustained Suppression and Neither Disorder 7.69 (7.38-8.01) Sustained Suppression and only SUD 9.22 (8.82-9.64) Sustained Suppression and only Mood/Anxiety Disorder 8.30 (7.96-8.65) Sustained Suppression and Both disorders 9.62 (9.19-10.04) Unsustained Suppression and Neither Disorder 10.90 (10.44-11.39) Unsustained Suppression and only SUD 10.75 (10.25-11.28) Unsustained Suppression and only Mood/Anxiety Disorder 11.50 (10.98-11.98) Unsustained Suppression and Both Disorders 11.30 (10.83-11.79) Note: SUD: Substance Use Disorder, CI: Confidence Interval * Hurdle (two-part) Negative Binomial Model D.4. Acute Care Hospitalization Exposure Category Adjusted Predicted Mean Count* (95% CI) 137 Sustained Suppression and Neither Disorder 0.05 (0.05-0.06) Sustained Suppression and only SUD 0.22 (0.18-0.26) Sustained Suppression and only Mood/Anxiety Disorder 0.08 (0.07-0.09) Sustained Suppression and Both disorders 0.28 (0.24-0.33) Unsustained Suppression and Neither Disorder 0.15 (0.13-0.18) Unsustained Suppression and only SUD 0.43 (0.36-0.52) Unsustained Suppression and only Mood/Anxiety Disorder 0.19 (0.16-0.23) Unsustained Suppression and Both Disorders 0.55 (0.47-0.66) Note: SUD: Substance Use Disorder, CI: Confidence Interval * Negative Binomial Model D.5. Day Surgery Episodes Exposure Category Adjusted Predicted Mean Count* (95% CI) Sustained Suppression and Neither Disorder 0.04 (0.03-0.05) Sustained Suppression and only SUD 0.04 (0.04-0.06) Sustained Suppression and only Mood/Anxiety Disorder 0.05 (0.04-0.06) Sustained Suppression and Both disorders 0.05 (0.04-0.06) Unsustained Suppression and Neither Disorder 0.05 (0.04-0.06) Unsustained Suppression and only SUD 0.04 (0.03-0.05) Unsustained Suppression and only Mood/Anxiety Disorder 0.05 (0.04-0.07) Unsustained Suppression and Both Disorders 0.04 (0.04-0.06) Note: SUD: Substance Use Disorder, CI: Confidence Interval * Negative Binomial Model 138 D.6. Hospital Length of Stay (Number of Days) Exposure Category Adjusted Predicted Mean Count* (95% CI) Sustained Suppression and Neither Disorder 3.01 (2.56-3.53) Sustained Suppression and only SUD 7.83 (6.61-9.28) Sustained Suppression and only Mood/Anxiety Disorder 3.76 (3.20-4.42) Sustained Suppression and Both disorders 9.08 (7.72-10.68) Unsustained Suppression and Neither Disorder 7.64 (6.42-9.09) Unsustained Suppression and only SUD 13.62 (11.41-16.27) Unsustained Suppression and only Mood/Anxiety Disorder 8.74 (7.30-10.47) Unsustained Suppression and Both Disorders 15.50 (13.14-18.28) Note: SUD: Substance Use Disorder, CI: Confidence Interval Length of stay was restricted to values <0. For each episode of day surgery, LOS was assumed to be one day. * Negative Binomial Model
Thesis/Dissertation
eng
Experimental Medicine
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Lima, Viviane Dias
Impact of mood/anxiety and substance use disorders on the HIV continuum of care and healthcare utilization of people living with HIV
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