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The impact of comorbidities on productivity loss in asthma patients Ehteshami-Afshar, Solmaz; FitzGerald, J. M; Carlsten, Christopher; Tavakoli, Hamid; Rousseau, Roxanne; Tan, Wan C; Rolf, J. D; Sadatsafavi, Mohsen Aug 26, 2016

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RESEARCH Open AccessThe impact of comorbidities onproductivity loss in asthma patientsSolmaz Ehteshami-Afshar1, J. Mark FitzGerald2,3,4,8*, Christopher Carlsten2,3,5, Hamid Tavakoli4, Roxanne Rousseau2,Wan Cheng Tan6, J. Douglass Rolf7 and Mohsen Sadatsafavi2,3,4AbstractBackground: Health-related productivity loss is an important, yet overlooked, component of the economic burdenof disease in asthma patients of a working age. We aimed at evaluating the effect of comorbidities on productivityloss among adult asthma patients.Methods: In a random sample of employed adults with asthma, we measured comorbidities using a validatedself-administered comorbidity questionnaire (SCQ), as well as productivity loss, including absenteeism andpresenteeism, using validated instruments. Productivity loss was measured in 2010 Canadian dollars ($). We used atwo-part regression model to estimate the adjusted difference of productivity loss across levels of comorbidity,controlling for potential confounding variables.Results: 284 adults with the mean age of 47.8 (SD 11.8) were included (68 % women). The mean SCQ score was 2.47 (SD 2.97, range 0–15) and the average productivity loss was $317.5 per week (SD $858.8). One-unit increase inthe SCQ score was associated with 14 % (95 % CI 1.02–1.28) increase in the odds of reporting productivity loss, and9.0 % (95 % CI 1.01–1.18) increase in productivity loss among those reported any loss of productivity. A person witha SCQ score of 15 had almost $1000 per week more productivity loss than a patient with a SCQ of zero.Conclusions: Our study deepens the evidence-base on the burden of asthma, by demonstrating that comorbiditiessubstantially decrease productivity in working asthma patients. Asthma management strategies must be cognizantof the role of comorbidities to properly incorporate the effect of comorbidity and productivity loss in estimatingthe benefit of disease management strategies.Keywords: Asthma, Comorbidities, Productivity loss, Presenteeism, AbsenteeismAbbreviations: BC, British columbia; CAD, Canadian dollars; EBA study, Economic burden of asthma study;ED, Emergency department; GINA, Global initiative for asthma; NOC, National occupation classification; OR, Oddsratio; PDC, Proportion of days covered (by any asthma controller medication); RR, Relative rate; SCQ, Self-administered comorbidity questionnaire; SD, Standard deviation; VOLP, Valuation of Lost Productivity; WPAI, Workproductivity and activity impairmentBackgroundWith increasing life expectancy there has been anincrease in the prevalence of many chronic diseases andthe co-existence of multiple diseases [1–3]. Clinically,comorbidities are relevant given their potential effect onthe index disease in terms of diagnosis, prognosis, andmanagement [4]. Also, comorbid conditions increase theneed for medication, risk of adverse effects and drug inter-actions, and reduce adherence to treatments, quality of lifeand functional status [1, 5, 6]. Patients with multiplecomorbidities tend to use more medical services andimpose a greater burden on the health-care system [2, 6].Asthma is associated with several comorbidities;however, the prevalence varies across studies [5–8]. In astudy from the United States, 26 and 10 % of asthmapatients had at least one or ≥3 comorbidities, respect-ively [7]. In a study from Germany, 26 % of asthma* Correspondence: Mark.Fitzgerald@vch.ca2Department of Medicine, Division of Respiratory Medicine, The University ofBritish Columbia, Vancouver, Canada3Institute for HEART + LUNG Health, Department of Medicine (RespiratoryDivision), The University of British Columbia, Vancouver, CanadaFull list of author information is available at the end of the article© 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Ehteshami-Afshar et al. Respiratory Research  (2016) 17:106 DOI 10.1186/s12931-016-0421-9patients had at least one other comorbidity while 17 %had 2 or more [9]. In a Canadian study, almost 60 % ofasthma patients had at least one comorbidity [6], whilein another study 12.5 % of adult asthma patientsreported having three or more comorbidities, increasingto 20 % for adults 55 years and older [5, 6].It has been well demonstrated that comorbidities areassociated with poor outcomes in asthma patients [10].Asthma patients with comorbidities experience moreasthma exacerbations [6, 11–13] and there is a significantrelationship between asthma control and the presence ofcomorbidities [4, 14, 15]. The reason behind this fact isunclear. It could be because the patient places a higherpriority on other health conditions, which influences theadherence to asthma treatment. Also the nature of comor-bidities like depression may cause the patient to pay lessattention to their general health status and care less [7]. Ina Canadian province, British Columbia (BC), 25 % ofasthma patients have depression [5]. Also, comobiditiescould directly and causally affect the severity of asthma orits responsiveness to treatment; examples include rhinitisand gastroesophageal reflux disease [16].It has been demonstrated that indirect costs of asthmaaccounted for the greater proportion of costs of asthmathan direct costs, however most of the studies unnoticedthis amount [16]. Also despite the documented burdenof comorbidities in asthma, their effect on productivityloss has been overlooked in the past. One reason behindthis status is that asthma patients are a relatively youngpopulation and are assumed to be free of comorbidities[15]. The general increase in longevity and the increasein the retirement age will inevitably result in more andmore working asthma subjects. The aim of the presentstudy was to evaluate the effect of comorbidities onproductivity loss in a population-based sample of adultasthma patients.MethodsStudy design and participantsThis study is based on data from the Economic Burdenof Asthma (EBA), a 1-year prospective cohort study withthe specific aim of estimating the economic and human-istic burden of asthma (University of British ColumbiaHuman Ethics Board H10-01542). In the EBA study, 618patients with self-reported physician diagnosis asthmawho were aged 1–85 were recruited by random digit dial-ing and followed up for a year. The study’s catchmentareas were Vancouver and Central Okanagan census areas,the latter being in the interior of the BC Province with alarge fraction of the population residing in rural areas.The details of this study have been described previously[17, 18] and the inclusion criteria of the present study arethe same as the main EBA, having at least one encounterwith healthcare system because of asthma in the past 5years and having no plan to move out of the region in thenext year, except it was restricted to adult (≥19 years old)patients who were employed at the baseline visit.VariablesComorbidityA comorbidity score was calculated based on the Self-administered Comorbidity Questionnaire (SCQ) admin-istered in the last visit [19]. The recall period of thequestionnaire is 12 months and thus we assumed co-morbidity score was constant across the study period[19]. The SCQ score not only considers the number ofthe comorbidities but also their severity. Each includedcomorbid condition can get a maximum of three pointsbased on the presence of disease, whether receivingtreatment, and any functional limitation due to the con-dition. This questionnaire has been validated and has amoderately strong correlation with the widely popularCharlson comorbidity index [19]. The Charlson index ismainly designed for hospitalized patients and its evalu-ation needs access to medical records [19]. On the otherhand, the SCQ is designed and validated for the out-patient settings by relying on patient self report as theprinciple source of information [19]. The original SCQincludes 13 common comorbidities, but in this study thequestions related to pulmonary disorders were excluded(given that all patients had asthma), leaving the ques-tionnaire with a maximum of 36 scores, three points foreach of the 12 questions. The included comorbiditieswere heart disease, hypertension, diabetes mellitus, ulceror stomach disease, kidney disease, liver disease, anemiaor other blood disease, cancer, depression, osteoarthritisor degenerative arthritis, back pain, and rheumatoidarthritis.Productivity lossProductivity loss was measured at baseline by twovalidated questionnaires: the Work Productivity andActivity Impairment (WPAI) [20], and the Valuation ofLost Productivity (VOLP) [21]. The WPAI recordspatients’ absenteeism (missing work due to health condi-tions) and presenteeism (attending work but not beingfully functional) in the last 7 days by asking about thehours they missed from work because of sick days or thetimes they went in late or left early due to health statusand times they were not functional with limited accom-plishment and unable to concentrate on their tasks dueto the health status respectively [20]. The VOLPquestionnaire collects information about the workenvironment such as time sensitivity of the job, teamwork, and availability of replacement, to calculate acoefficient that measures the contribution of individualto the work place (a coefficient of X indicates that eachEhteshami-Afshar et al. Respiratory Research  (2016) 17:106 Page 2 of 9hour of a person’s absence is equivalent of X hours ofwork loss) [21, 22].The monetary value of productivity loss per week wasthe product of three terms: amount of work time (hours)lost, the VOLP coefficient, and the hourly wage of theindividual. Job titles were matched to the National Occu-pation Classification (NOC) codes [23] to estimate thehourly wage based on sex and age for each NOC fromStatistics Canada for year 2010 [17]. The reported weeklycosts are therefore in 2010 Canadian dollars (CAD).ConfoundersSocio-demographic data collected at the baseline visitwere included in the statistical models as potentialconfounders (factors that can affect both comorbid leveland productivity but are not on the causal pathway).They included: sex, age, household income levels (low v.high at cut-off of CAD$60,000 per year), education (lowv. high at cut-off of 4-year college/university degree),type of residence (urban v. rural), place of birth (Canadav. abroad), drug insurance (having no insurance, beingpartially insured, or being fully insured), and the propor-tion of days covered (PDC) by any asthma controllermedication in past 12 months as an indicator ofadherence (cut-off values <50 %, 50–80 %, ≥80 %).The main analysis did not adjust for asthma control asit cannot be a confounder; rather, it is potentially beingon the causal pathway (that is, part of the impact ofcomorbidity on productivity might be due to the comor-bid conditions’ affecting the likelihood of achievingasthma control. It is also very unlikely for the currentasthma control status to have an effect on comorbidities(thus being confounding factor). But a sensitivity analysiswas performed to assess the effect of adjusting for controlstatus on the outcomes. We defined control status basedon Global Initiative for Asthma (GINA) 2012 definition,which included the presence of symptoms and impair-ment in lung function (all measured at baseline visit).Statistical analysisAll analyses were performed using Stata (version 14;StataCorp, College Station, TX, USA). Two-tailed p-valuesat 0.05 were considered statistically significant. Descriptiveanalysis was performed on the baseline variables. Wereported the hours and costs of both components of prod-uctivity loss (absenteeism and presenteeism), as well astotal productivity loss across different levels of SCQ score.As the productivity loss data were zero-inflated, weused two-part models for statistical inference [24]. Thefirst part was a logistic component and the second partwas a generalized linear model with logarithmic linkfunction and gamma distribution. The first part gener-ates odds ratio (OR) associating covariates with any lossof productivity, and the second component producesrelative rate (RR) associating covariates with the magni-tude of productivity loss among those with any loss ofproductivity. For both components the dependent variablewas the monetary value of productivity loss and the inde-pendent variables were the SCQ score and other covari-ates as previously mentioned. As there were missingvalues among some of the covariates, multiple imputa-tions were first performed, creating 5 imputed datasetswithout missing variables; results of separate analyses onthe imputed datasets were combined. To estimate themarginal effect of SCQ on productivity loss (that is, theweekly loss of productivity associated with any level ofSCQ score), the OR and RR from the two componentswere combined, and p-values and confidence intervalswere estimated using bootstrapping (500 times) asdescribed elsewhere [25]. The procedure was conductedseparately with absenteeism, presenteeism, and total prod-uctivity loss as the dependent variable.ResultsFigure 1 shows the flowchart of sample selection. Thefinal sample consisted of 284 individuals whose baselinecharacteristics are shown in Table 1. The sample was68 % female with a mean age of 47.8 ± 11.8 with gener-ally high levels of education and household income.Most of the subjects (63 %) had at least one comorbidcondition and the overall SCQ score was 2.47 ± 2.97,with a minimum of 0 and a maximum of 15. Only 48 %of patients reported any productivity loss, with 36 % ofthem reporting absenteeism and 64 % reporting present-eeism. Mean weekly hours and costs of productivity losswere 16 ± 17.6 h and $317.49 ± $858.83 respectively.Fig. 1 Flow chart of study populationEhteshami-Afshar et al. Respiratory Research  (2016) 17:106 Page 3 of 9Unadjusted analysisTable 2 shows the results of unadjusted analysis. Thehours of absenteeism increased from 1.26 to 7.14 h asthe SCQ increased from 0 to 15, and for presenteeism itrose from 3.97 to 12.59 h. The costs of absenteeismincreased from $50/week for SCQ of 0 to almost $300/week for SCQ of 15, while the corresponding values forpresenteeism was $140/week and $734/week. The sameincreases were seen for the total productivity loss, from$190/per week to $1036/per week.Adjusted analysisThe results of two-part regression model are demon-strated in Table 3. In the logistic part of the analysis,SCQ was significantly associated with higher odds ofreporting absenteeism, presenteeism and total productiv-ity loss. However, in the second part of the regression,among patients with productivity loss, SCQ was onlysignificantly associated with the total productivity loss(RR = 1.09, CI = 1.01-1.18, P = 0.02) and not presentee-ism or absenteeism separately. The other covariates werenot significantly associated with productivity loss ineither parts of the model.Marginal effect of comorbidity on productivity lossThe marginal effect of each level of SCQ score on totalproductivity loss is demonstrated in Fig. 2. In patientswithout any comorbidity, the productivity loss was$205 week. Total productivity loss was $1685 higherwith a SCQ score of 15 in comparison to a SCQ score ofzero. The margins were significant at all the levels,except SCQ score of 15 (P-value = 0.06). For Absentee-ism, the costs were from $61.87/week (SD = 23.07) forSCQ score of 0 to $612.61/week (SD = 498.06) forthose with the score of 15, and for presenteeism theywere from $160.92/week (SD = 32.57) to $877.33/week(SD = 473) for the SCQ scores of 0 and 15, respect-ively. However the incremental costs for the SCQscore of ≥10 for absenteeism and SCQ score of 15for presenteeism were not significant.Table 1 Characteristics of study sampleStudy population = 284Age, mean ± SDa 47.8 ± 11.8Sex (%)Women 193 (68)Men 91 (32)Household income (%)High (>60,000 CAD) 178 (62.7)Low 96 (33.8)Missing 10 (3.5)Educational level (%)High 229 (80.6)Low 55 (19.4)Place of birth (%)Canada 207 (72.9)Outside Canada 77 (27.1)Ethnicity (%)Caucasian 231 (81.3)Asian 18 (6.3)Other 35 (12.4)Residence type (%)Urban 260 (91.5)Rural 24 (8.5)Asthma medication adherence (%)PDCb < 50 % 171 (60.2)50 %≤ PDC < 80 % 31 (11)PDC≥ 80 % 81 (28.5)Missing 1 (0.3)Asthma control level (%)Controlled 55 (19.4)Partially Controlled 113 (39.8)Uncontrolled 115 (40.5)Missing 1 (0.3)Productivity Loss (%) 136 (48)Absenteeism (%) 49 (17)Presenteeism (%) 127 (45)Hours of overall productivity loss,mean ± SD16 ± 17.6Costsc of overall productivity loss,mean ± SD317.49$ ± 858.83$Overall SCQd comorbidities score,mean ± SD2.47 ± 2.97Heart disease (%) 15 (5.3)Hypertension (%) 35 (12.3)Diabetes (%) 9 (3.2)Ulcer or Stomach Disease (%) 37 (13)Kidney disease (%) 3 (1.1)Table 1 Characteristics of study sample (Continued)Liver disease (%) 2 (0.7)Anemia or other blood disease (%) 21 (7.4)Cancer (%) 6 (2.1)Depression (%) 40 (14.1)Osteoarthritis, degenerative arthritis (%) 62 (21.8)Back pain (%) 99 (34.9)Rheumatoid arthritis (%) 2 (0.7)aStandard deviationbproportions of days coveredc2010 Canadian dollarsdself-administered comorbidity questionnaireEhteshami-Afshar et al. Respiratory Research  (2016) 17:106 Page 4 of 9Sensitivity analysisSensitivity analysis revealed that OR for reportingproductivity loss and adjusted ratio for productivity lossamong those reporting it did not change by addingcontrol status in the model. However, the adjusted RR inthe second part was no longer significant. Addingcontrol status to the model did not have a significantimpact on the estimates of the marginal loss of product-ivity (Appendix).DiscussionIn this study, we have demonstrated that as the SCQ score,a validated quantitative measure of the burden of comor-bidity, increased, the hours of absenteeism and presentee-ism increased significantly to almost 20 h per week. Thiscaused almost $1685/week higher productivity loss inpatients with a score of 15, the maximum score observedin our sample, in comparison to those with a zero score.The average SCQ score in the sample was 2.47 (SD 2.97).Table 2 Unadjusted regression analysisSCQ score Hours ofAbsenteeismCosts ofAbsenteeismaHours ofPresenteeismCosts ofPresenteeismaHours of totalproductivity lossCosts ofproductivity lossa,b0 1.26 50.35 3.97 140.20 5.22 190.18(0.54–1.98) (19.88–80.81) (2.73–5.22) (65.27–215-13) (3.49–6.96) (97.22–283.14)1 1.65 66.91 4.55 179.81 6.20 246.60(0.99–2.32) (40.19–93.63) (3.48–5.62) (118.75–240.87) (4.70–7.70) (169.16–324.03)2 2.04 83.47 5.12 219.41 7.17 303.01(1.22–2.87) (49.80–117.14) (4.00–6.25) (145.85–292.98) (5.52–8.83) (208.30–397.72)3 2.44 100.03 5.70 259.02 8.15 359.43(1.33–3.54) (53.27–146.79) (4.31–7.08) (155.75–362.28) (6.04–10.26) (226.90–491.95)4 2.83 116.59 6.27 298.62 9.13 415.84(1.38–4.27) (54.35–178.83) (4.51–8.03) (159.03–438.21) (6.41–11.85) (237.59–594.10)5 3.22 133.15 6.84 338.22 10.10 472.26(1.41–5.03) (54.45–211.86) (4.65–9.04) (159.70–516.76) (6.70–13.50) (245.10–699.42)6 3.61 149.71 7.42 377.83 11.08 528.67(1.43–5.79) (54.06–245-36) (4.76–10.08) (159.12–596.53) (6.96–15.20) (251.09–806.25)7 4.00 166.27 7.99 417.43 12.05 585.09(1.44–6.56) (53.42–279.13) (4.85–11.13) (157.90–676.97) (7.19–16.91) (256.28–913.90)8 4.39 182.83 8.57 457.04 13.03 641.50(1.45–7.34) (52.61–313.06) (4.94–12.20) (156.28–757.79) (7.42–18.64) (260.97–1022.03)9 4.79 199.39 9.14 496.64 14.01 697.92(1.45–8.12) (51.70–347.09) (5.01–13.27) (154.41–838.87) (7.63–20.38) (265.36–1130.48)10 5.18 215.96 9.72 536.24 14.98 754.33(1.46–8.90) (50.72–381.19) (5.09–14.34) (152.38–920.11) (7.84–22.12) (269.53–1239.14)11 5.57 232.52 10.29 575.85 15.96 810.75(1.46–9.68) (49.69–415.35) (5.16–15.42) (150.23–1001.47) (8.05–23.86) (273.56–1347.94)12 5.96 249.08 10.86 615.45 16.93 867.17(1.46–10.46) (48.62–449.54) (5.23–16.50) (147.98–1082.92) (8.26–25.61) (277.48–1456.86)13 6.35 265.64 11.44 655.06 17.91 923.58(1.46–11.25) (47.52–483.75) (5.29–17.58) (145.68–1164.43) (8.46–27.36) (281.31–1565.85)14 6.74 282.20 12.01 694.66 18.88 979.99(1.45–12.03) (46.41–517.99) (5.36–18.67) (143.32–1246) (8.66–29.11) (285.08–1674.91)15 7.14 298.76 12.59 734.26 19.86 1036.41(1.45–12.82) (45.27–552.25) (5.42–19.75) (140.93–1327.60) (8.86–30.86) (288.80–1784.03)All the p-values <0.05a2010 CADbThe sum of the costs of absenteeism and presenteeism are not exactly equal to the costs of total productivity loss, because the exact distribution of error termsaround each component is inevitably different in regression modelsEhteshami-Afshar et al. Respiratory Research  (2016) 17:106 Page 5 of 9Table 3 Results of the adjusted regression analysis of productivity loss on SCQa scoreAbsenteeism Presenteeism Total ProductivityLossFemale v. male Adjusted OR for reporting productivity loss 1.72 1.08 0.99(0.53–2.57) (0.61–2.35) (0.56–1.76)(P = 0.7) (P = 0.77) (P = 0.99)Adjusted ratio of productivity loss amongthose who reported productivity loss0.42 0.88 0.79(0.15–1.18) (0.52–2.18) (0.46–1.37)(P = 0.1) (P = 0.63) (P = 0.41)Age (per 1 year increase) Adjusted OR for reporting productivity loss 0.98 0.98 0.98(0.95–1.01) (0.96–1.04) (0.96–1.01)(P = 0.31) P = (0.13) (P = 0.23)Adjusted ratio of productivity loss amongthose who reported productivity loss0.98 0.99 0.98(0.94–1.03) (0.96–1.04) (0.96–1.01)(P = 0.5) (P = 0.49) (P = 0.18)High v. urban education Adjusted OR for reporting productivity loss 1.16 0.68 0.52(0.41–3.27) (0.34–2.84) (0.25–1.1)(P = 0.73) (P = 0.27) (P = 0.09)Adjusted ratio of productivity loss amongthose who reported productivity loss0.92 1.50 1.44(0.29–2.96) (0.84–2.40) (0.76–2.72)(P = 0.9) (P = 0.17) (P = 0.26)Rural residence Adjusted OR for reporting productivity loss 0.47 0.38 0.41(0.13–1.75) (0.11–6.17) (0.13–1.35)(P = 0.26) (P = 0.11) (P = 0.14)Adjusted ratio of productivity loss amongthose who reported productivity loss0.99 0.42 0.44(0.05–20.88) (0.21–2.88) (0.16–1.15)(P = 0.99) (P = 0.1) (P = 0.1)Foreign Born v.Canadian-bornAdjusted OR for reporting productivity loss 0.95 1.00 1.21(0.41–2.19)) (0.56–2.42) (0.67–2.17)(P = 0.92) (P = 0.99) (P = 0.53)Adjusted ratio of productivity loss amongthose who reported productivity loss0.41 0.84 0.72(0.12–1.39) (0.52–2.08) (0.43–1.19)(P = 0.16) (P = 0.5) (P = 0.2)PDCb Level(Reference: PDC < 50 %)50–80 % Adjusted OR for reporting productivity loss 2.75 1.27 1.34(0.98–7.73) (0.54–3.66) (0.58–3.10)(P = 0.07) (P = 0.59) (P = 0.49)Adjusted ratio of productivity loss amongthose who reported productivity loss1.49 2.50 2.72(0.33–6.64) (0.70–6.77) (0.91–8.10)(P = 0.6) (P = 0.15) (P = 0.07)>80 % Adjusted OR for reporting productivity loss 1.11 0.86 0.97(0.48–2.59) (0.47–2.50) (0.52–1.80)(P = 0.8) (P = 0.6) (P = 0.93)Adjusted ratio of productivity loss amongthose who reported productivity loss0.95 1.13 1.13(0.40–2.29) (0.69–2.08) (0.68–1.86)(P = 0.91) (P = 0.62) (P = 0.64)Ehteshami-Afshar et al. Respiratory Research  (2016) 17:106 Page 6 of 9At this level, productivity loss was almost 1.5 times higherthan in individuals without any comorbidity (SCQ= 0). Inthe full two-part regression, SCQ increased the odds ofreporting productivity loss, absenteeism and or presentee-ism by 14–17 %. In addition, among those with prod-uctivity loss, one-unit increase in SCQ increasedproductivity loss by 9 %. Overall, our results demon-strate the substantial effect of comorbidity on prod-uctivity loss in patients with asthma.Previous studies assessing the impact of comorbiditieson asthma patients mostly focused on direct costs orhealth services use [7, 12, 15, 26]. For example, theyhave demonstrated that the rate of hospitalization dueto asthma and Emergency Department (ED) visits inasthma patients increased in the presence of comorbidi-ties [7, 12, 15, 26]. It has also been shown that the pres-ence of some comorbidities increase the risk of mortality[10, 26]. The relationship between comorbidities andasthma exacerbations has also been demonstrated [6]. Astudy conducted in Finland showed that the presence ofone and more than two comorbidities increased the riskof work disability with hazard ratios of 2.2 and 4.5,respectively [27]. In that study, work disability wasdefined as long-term sickness absence (≥90 days) andreceiving a disability pension. Results of current study areinline with our previous study that demonstrated thepresence of comorbid psychological conditions in asthmapatients will increase productivity loss significantly [28].To the best of our knowledge, there is no other studyassessing the general impact of comorbidities on product-ivity loss in asthma patients including both absenteeismand presenteeism and transforming the productivity lossinto its monetary value. The use of validated instrumentsenabled us to transform productivity loss time to itsmonetary value, incorporating the impact of the affectedindividual on team productivity, and the use of a robuststatistical method enabled us to properly handle statisticalissues around zero-inflated and skewed costs data.Besides these strengths, our study has several limitationsworth mentioning. First, the final sample size (284) mighthave underpowered the results and our sample were mostlyhighly educated with high income, which could manifestTable 3 Results of the adjusted regression analysis of productivity loss on SCQa score (Continued)Drug Insurance (Reference: full insurance)Partial Adjusted OR for reporting productivity loss 1.36 1.03 1.11(0.41–4.49) (0.45–3.44) (0.47–2.63)(P = 0.59) (P = 0.94) (P = 0.8)Adjusted ratio of productivity loss amongthose who reported productivity loss0.84 0.60 0.73(0.20–3.53) (0.24–3.99) (0.30–1.80)(P = 0.82) (P = 0.17) (P = 0.5)None Adjusted OR for reporting productivity loss 0.82 0.91 0.86(0.20–3.43) (0.36–4.07) (0.33–2.25)(P = 0.82) (P = 0.86) (P = 0.76)Adjusted ratio of productivity loss amongthose who reported productivity loss1.09 0.66 0.76(0.16–7.33) (0.24–4.58) (0.28–2.11)(P = 0.93) (P = 0.42) (P = 0.61)High v. low income Adjusted OR for reporting productivity loss 0.84 0.87 0.88(0.37–1.88) (0.48–2.47) (0.47–1.66)(P = 0.54) (P = 0.66) (P = 0.7)Adjusted ratio of productivity loss amongthose who reported productivity loss1.47 1.27 1.27(0.55–3.93) (0.74–2.25) (0.69–2.32)(P = 0.44) (P = 0.38) (P = 0.44)SCQ (per 1 unit increase) Adjusted OR for reporting productivity loss 1.17 1.14 1.14(1.04–1.32) (1.03–1.17) (1.02–1.28)(P = 0.01) (P = 0.01) (P = 0.01)Adjusted ratio of productivity loss amongthose who reported productivity loss1.04 1.05 1.09(0.90–1.21) (0.98–1.11) (1.01–1.18)(P = 0.56) (P = 0.14) (P = 0.02)aSelf-administered comorbidity questionnairebproportion of days covered by medicationEhteshami-Afshar et al. Respiratory Research  (2016) 17:106 Page 7 of 9the healthy volunteer bias. Second, our sample onlyincluded employed asthma patients. None of the partici-pants in the original study reported being unemployedbecause of asthma. As such, we could not incorporate theloss of productivity for asthma patients who lose their jobdue to the asthma-related or comorbidity-related impair-ment. Third, self-reported physician diagnosis of asthmaand self-reported comorbidities and productivity loss mightreduce the accuracy of the data we used. Fourth, the per-centage of patients with higher scores of SCQ was limitedsuch that the results for the patients with SCQ scores of≥10 should be interpreted cautiously. Ultimately, the aspectof the burden of a disease that is the most relevant forclinical practice and policy-making is the component thatcan be prevented by disease management. Having docu-mented a significant association between comorbidity andproductivity loss, the research agenda should move forwardto studying specific comorbid conditions as well as the im-pact of treatment on preventing such loss of productivity.ConclusionsTaking the limitations into account, our study hashighlighted the important associations of comorbidities withproductivity loss in working asthma patients. This is demon-strated by almost $1685/week higher productivity loss inpatients with a SCQ score of 15 in comparison to those witha zero score. Productivity loss is a disregarded aspect of theeconomic burden of asthma [16]. Thus this study is areminder for health care providers to pay greater attentionto comorbidities in the management of asthma in order toreduce the burden of this common disease that dispropor-tionately affects individuals in their productive years of life.AppendixFig. 2 Incremental Costs of productivity loss based on comorbidity scoresTable 4 Costs of productivity loss per week (CAD)b, comparingthe main model with alternative model adding control statusas confounderSCQ score Main Model Alternative modela0 205.12 ± 42.09 215.05 ± 50.511 244.42 ± 45.46 253.10 ± 53.852 290.07 ± 51.73 296.62 ± 59.653 342.81 ± 62.54 346.31 ± 69.404 403.47 ± 79.29 402.74 ± 84.455 472.90 ± 103.02 466.56 ± 105.916 552.02 ± 134.70 538.45 ± 134.697 641.82 ± 175.39 619.12 ± 171.698 743.35 ± 226.39 709.36 ± 217.949 857.74 ± 289.24 809.96 ± 274.6910 986.20 ± 365.75 921.82 ± 343.3911 1130.04 ± 458.03 1045.86 ± 425.7212 1290.72 ± 568.50 1183.12 ± 523.6013 1469.79 ± 699.91 1334.70 ± 639.2214 1669.0 ± 855.37 1501.83 ± 775.04*15 1890.27 ± 1038.37* 1685.85 ± 933.81**P value is not significantaAlternative model: two part model regression analysis on the main modelafter adding control statusb2010 Canadian dollarsEhteshami-Afshar et al. Respiratory Research  (2016) 17:106 Page 8 of 9Acknowledgments and fundingWe acknowledge the financial support through the Collaborative InnovativeResearch Fund (CIRF), an investigator initiated, peer-reviewed competitionsponsored by GlaxoSmithKline Canada. None of the sponsors played a rolein the study design, data analysis, or interpretation of the results.Authors’ contributionJMF, MS, WT and DR designed the Economic Burden of Asthma (EBA) study,whose data are used in the present research. MS and RR designed the casereport forms. JMF and SEA proposed the research question. SEA conceptualizedthe study design, was the main analyst, and wrote the first draft of themanuscript. JMF, MS, CC and HT were involved in the acquisition of the data.JMF, CC and MS critically revised the manuscript. JMF and SEA are guarantorsof the paper. All authors approved the final version of the manuscript.Competing interestThe authors declare that they have no competing interests.Consent for publicationAll authors approved the final version of the manuscript and agreed to itscontent and are accountable for all aspects of the accuracy and integrity of themanuscript in accordance with ICMJE criteria and agree to the terms of theBioMed Central Copyright and License Agreement, and Open Data policy.The article is original, has not already been published in a journal, and is notcurrently under consideration by another journal.Informed consent was obtained from all individual participants included inthe study.Ethics approval and consent to participateThe Human Ethics board of the University of British Columbia (University ofBritish Columbia Human Ethics No. H10-01542) approved this study. Allprocedures performed in studies involving human participants were inaccordance with the ethical standards of the institutional and/or nationalresearch committee and with the 1964 Helsinki declaration and its lateramendments or comparable ethical standard.Author details1Experimental Medicine Program, Department of Medicine, Faculty ofMedicine, The University of British Columbia, Vancouver, Canada.2Department of Medicine, Division of Respiratory Medicine, The University ofBritish Columbia, Vancouver, Canada. 3Institute for HEART + LUNG Health,Department of Medicine (Respiratory Division), The University of BritishColumbia, Vancouver, Canada. 4Centre for Clinical Epidemiology andEvaluation, The University of British Columbia, Vancouver, Canada.5Department of Medicine, Centre for Occupational and Environmental LungDisease, Vancouver, BC, Canada. 6Centre for Heart Lung Innovation, TheUniversity of British Columbia, Vancouver, Canada. 7Kelowna Allergy &Respirology Research, Kelowna, Canada. 8Institute of Heart and Lung Health,The Lung Centre, 2775 Laurel Street, Vancouver, BC V5Z 1 M9, Canada.Received: 10 June 2016 Accepted: 17 August 2016References1. 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