Socioeconomic Factors and Adherence to CPAP
2021; Elsevier BV; Volume: 160; Issue: 4 Linguagem: Inglês
10.1016/j.chest.2021.04.064
ISSN1931-3543
AutoresAndreas Palm, Ludger Grote, Jenny Theorell‐Haglöw, Mirjam Ljunggren, Josefin Sundh, Bengt Midgren, Magnus Ekström,
Tópico(s)Cardiovascular and Diving-Related Complications
ResumoBackgroundEarly identification of poor adherence to CPAP treatment is of major clinical importance to optimize treatment outcomes in patients with OSA.Research QuestionHow do socioeconomic factors influence CPAP adherence?Study Design and MethodsNationwide, population-based cohort study of patients with OSA receiving CPAP treatment reported to the Swedish quality registry Swedevox between 2010 and 2018 was cross-linked with individual socioeconomic data from Statistics Sweden. Socioeconomic factors associated with CPAP adherence were identified using a multivariate linear regression model, adjusted for age and sex.ResultsIn total, 20,521 patients were included: 70.7% men; mean age ± SD, 57.8 ± 12.2 years; BMI, 32.0 ± 6.1 kg/m2; apnea-hypopnea index, 36.9 ± 22.1; Epworth Sleepiness Scale, 10.4 ± 5.0; and median nocturnal CPAP use, 355 min (interquartile range, 240-420 min). Adherence after 1.3 ± 0.8 years of CPAP use was significantly (all P < .001) associated with civil status (married vs unmarried: +20.5 min/night), education level (high, ≥ 13 years vs low, ≤ 9 years: +13.2 min/night), total household income (highest/third/second vs lowest quartile: +15.9 min/night, +10.4 min/night, and +6.1 min/night, respectively), and country of birth (born in Sweden with one native parent/born in Sweden with two native parents vs being born abroad: +29.0 min/night and +29.3 min/night, respectively).InterpretationCivil status, educational level, household income, and foreign background predict CPAP adherence in a clinically significant manner and should be considered when treating OSA with CPAP. Early identification of poor adherence to CPAP treatment is of major clinical importance to optimize treatment outcomes in patients with OSA. How do socioeconomic factors influence CPAP adherence? Nationwide, population-based cohort study of patients with OSA receiving CPAP treatment reported to the Swedish quality registry Swedevox between 2010 and 2018 was cross-linked with individual socioeconomic data from Statistics Sweden. Socioeconomic factors associated with CPAP adherence were identified using a multivariate linear regression model, adjusted for age and sex. In total, 20,521 patients were included: 70.7% men; mean age ± SD, 57.8 ± 12.2 years; BMI, 32.0 ± 6.1 kg/m2; apnea-hypopnea index, 36.9 ± 22.1; Epworth Sleepiness Scale, 10.4 ± 5.0; and median nocturnal CPAP use, 355 min (interquartile range, 240-420 min). Adherence after 1.3 ± 0.8 years of CPAP use was significantly (all P < .001) associated with civil status (married vs unmarried: +20.5 min/night), education level (high, ≥ 13 years vs low, ≤ 9 years: +13.2 min/night), total household income (highest/third/second vs lowest quartile: +15.9 min/night, +10.4 min/night, and +6.1 min/night, respectively), and country of birth (born in Sweden with one native parent/born in Sweden with two native parents vs being born abroad: +29.0 min/night and +29.3 min/night, respectively). Civil status, educational level, household income, and foreign background predict CPAP adherence in a clinically significant manner and should be considered when treating OSA with CPAP. OSA with excessive daytime sleepiness is common, affecting at least 6% of men and 4% of women,1Franklin K.A. Lindberg E. Obstructive sleep apnea is a common disorder in the population: a review on the epidemiology of sleep apnea.J Thorac Dis. 2015; 7: 1311-1322PubMed Google Scholar and is associated with increased risk of cardiovascular mortality and morbidity.2Young T. Finn L. Peppard P.E. et al.Sleep disordered breathing and mortality: eighteen-year follow-up of the Wisconsin sleep cohort.Sleep. 2008; 31: 1071-1078PubMed Google Scholar,3Punjabi N.M. Caffo B.S. Goodwin J.L. et al.Sleep-disordered breathing and mortality: a prospective cohort study.PLoS Med. 2009; 6e1000132Crossref PubMed Scopus (941) Google Scholar CPAP treatment improves daytime sleepiness and daily functioning,4Weaver T.E. Maislin G. Dinges D.F. et al.Relationship between hours of CPAP use and achieving normal levels of sleepiness and daily functioning.Sleep. 2007; 30: 711-719Crossref PubMed Scopus (637) Google Scholar mitigates an elevated risk of motor vehicle accidents,5Karimi M. Hedner J. Habel H. Nerman O. Grote L. Sleep apnea-related risk of motor vehicle accidents is reduced by continuous positive airway pressure: Swedish Traffic Accident Registry data.Sleep. 2015; 38: 341-349Crossref PubMed Scopus (86) Google Scholar and reduces BP.6Bratton D.J. Stradling J.R. Barbe F. Kohler M. Effect of CPAP on blood pressure in patients with minimally symptomatic obstructive sleep apnoea: a meta-analysis using individual patient data from four randomised controlled trials.Thorax. 2014; 69: 1128-1135Crossref PubMed Scopus (122) Google Scholar In observational studies, CPAP has been shown to improve cardiovascular outcomes.7Marin J.M. Carrizo S.J. Vicente E. Agusti A.G. Long-term cardiovascular outcomes in men with obstructive sleep apnoea-hypopnoea with or without treatment with continuous positive airway pressure: an observational study.Lancet. 2005; 365: 1046-1053Abstract Full Text Full Text PDF PubMed Scopus (2688) Google Scholar,8Campos-Rodriguez F. Martinez-Garcia M.A. de la Cruz-Moron I. Almeida-Gonzalez C. Catalan-Serra P. Montserrat J.M. Cardiovascular mortality in women with obstructive sleep apnea with or without continuous positive airway pressure treatment: a cohort study.Ann Intern Med. 2012; 156: 115-122Crossref PubMed Google Scholar However, this association was not shown in intention-to-treat analyses of randomized controlled trials,9Barbe F. Duran-Cantolla J. Sanchez-de-la-Torre M. et al.Effect of continuous positive airway pressure on the incidence of hypertension and cardiovascular events in nonsleepy patients with obstructive sleep apnea: a randomized controlled trial.JAMA. 2012; 307: 2161-2168Crossref PubMed Scopus (556) Google Scholar, 10McEvoy R.D. Antic N.A. Heeley E. et al.CPAP for prevention of cardiovascular events in obstructive sleep apnea.N Engl J Med. 2016; 375: 919-931Crossref PubMed Scopus (1022) Google Scholar, 11Peker Y. Glantz H. Eulenburg C. Wegscheider K. Herlitz J. Thunstrom E. Effect of positive airway pressure on cardiovascular outcomes in coronary artery disease patients with nonsleepy obstructive sleep apnea. The RICCADSA randomized controlled trial.Am J Respir Crit Care Med. 2016; 194: 613-620Crossref PubMed Scopus (313) Google Scholar, 12Sanchez-de-la-Torre M. Sanchez-de-la-Torre A. Bertran S. et al.Effect of obstructive sleep apnoea and its treatment with continuous positive airway pressure on the prevalence of cardiovascular events in patients with acute coronary syndrome (ISAACC study): a randomised controlled trial.Lancet Respir Med. 2020; 8: 359-367Abstract Full Text Full Text PDF PubMed Scopus (104) Google Scholar but rather in the subgroup of patients with high adherence to CPAP.10McEvoy R.D. Antic N.A. Heeley E. et al.CPAP for prevention of cardiovascular events in obstructive sleep apnea.N Engl J Med. 2016; 375: 919-931Crossref PubMed Scopus (1022) Google Scholar, 11Peker Y. Glantz H. Eulenburg C. Wegscheider K. Herlitz J. Thunstrom E. Effect of positive airway pressure on cardiovascular outcomes in coronary artery disease patients with nonsleepy obstructive sleep apnea. The RICCADSA randomized controlled trial.Am J Respir Crit Care Med. 2016; 194: 613-620Crossref PubMed Scopus (313) Google Scholar, 12Sanchez-de-la-Torre M. Sanchez-de-la-Torre A. Bertran S. et al.Effect of obstructive sleep apnoea and its treatment with continuous positive airway pressure on the prevalence of cardiovascular events in patients with acute coronary syndrome (ISAACC study): a randomised controlled trial.Lancet Respir Med. 2020; 8: 359-367Abstract Full Text Full Text PDF PubMed Scopus (104) Google Scholar Four hours of mean nightly CPAP use have been identified as the cutoff point for the above-mentioned beneficial CPAP effects. Adherence to CPAP treatment often is insufficient and a major clinical problem. As many as 29% to 83% of patients with OSA who are receiving CPAP treatment have a nocturnal CPAP use of less than 4 h.13Weaver T.E. Grunstein R.R. Adherence to continuous positive airway pressure therapy: the challenge to effective treatment.Proc Am Thorac Soc. 2008; 5: 173-178Crossref PubMed Scopus (956) Google Scholar Excessive daytime sleepiness and a high apnea-hypopnea index (AHI), indicating more severe OSA, are associated with better adherence to CPAP therapy.14Sin D.D. Mayers I. Man G.C. Pawluk L. Long-term compliance rates to continuous positive airway pressure in obstructive sleep apnea: a population-based study.Chest. 2002; 121: 430-435Abstract Full Text Full Text PDF PubMed Scopus (311) Google Scholar Only a handful of studies, many of those small and with short follow-up duration, have evaluated the association between socioeconomic factors and adherence. Income,15Simon-Tuval T. Reuveni H. Greenberg-Dotan S. Oksenberg A. Tal A. Tarasiuk A. Low socioeconomic status is a risk factor for CPAP acceptance among adult OSAS patients requiring treatment.Sleep. 2009; 32: 545-552Crossref PubMed Scopus (112) Google Scholar,16Brin Y.S. Reuveni H. Greenberg S. Tal A. Tarasiuk A. Determinants affecting initiation of continuous positive airway pressure treatment.Isr Med Assoc J. 2005; 7: 13-18PubMed Google Scholar educational level,17Bakker J.P. O'Keeffe K.M. Neill A.M. Campbell A.J. Ethnic disparities in CPAP adherence in New Zealand: effects of socioeconomic status, health literacy and self-efficacy.Sleep. 2011; 34: 1595-1603Crossref PubMed Scopus (55) Google Scholar socioeconomic status in neighborhood,16Brin Y.S. Reuveni H. Greenberg S. Tal A. Tarasiuk A. Determinants affecting initiation of continuous positive airway pressure treatment.Isr Med Assoc J. 2005; 7: 13-18PubMed Google Scholar, 17Bakker J.P. O'Keeffe K.M. Neill A.M. Campbell A.J. Ethnic disparities in CPAP adherence in New Zealand: effects of socioeconomic status, health literacy and self-efficacy.Sleep. 2011; 34: 1595-1603Crossref PubMed Scopus (55) Google Scholar, 18Platt A.B. Field S.H. Asch D.A. et al.Neighborhood of residence is associated with daily adherence to CPAP therapy.Sleep. 2009; 32: 799-806Crossref PubMed Scopus (96) Google Scholar number of household members, and civil status18Platt A.B. Field S.H. Asch D.A. et al.Neighborhood of residence is associated with daily adherence to CPAP therapy.Sleep. 2009; 32: 799-806Crossref PubMed Scopus (96) Google Scholar,19Lewis K.E. Seale L. Bartle I.E. Watkins A.J. Ebden P. Early predictors of CPAP use for the treatment of obstructive sleep apnea.Sleep. 2004; 27: 134-138Crossref PubMed Scopus (173) Google Scholar have been associated with adherence in ,some but not all, studies.20Gulati A. Ali M. Davies M. Quinnell T. Smith I. A prospective observational study to evaluate the effect of social and personality factors on continuous positive airway pressure (CPAP) compliance in obstructive sleep apnoea syndrome.BMC Pulm Med. 2017; 17: 56Crossref PubMed Scopus (16) Google Scholar, 21Billings M.E. Auckley D. Benca R. et al.Race and residential socioeconomics as predictors of CPAP adherence.Sleep. 2011; 34: 1653-1658Crossref PubMed Scopus (101) Google Scholar, 22Ye L. Pack A.I. Maislin G. et al.Predictors of continuous positive airway pressure use during the first week of treatment.J Sleep Res. 2012; 21: 419-426Crossref PubMed Scopus (46) Google Scholar, 23Campbell A. Neill A. Lory R. Ethnicity and socioeconomic status predict initial continuous positive airway pressure compliance in New Zealand adults with obstructive sleep apnoea.Intern Med J. 2012; 42: e95-e101Crossref PubMed Scopus (22) Google Scholar The aim of this large population-based study with extended follow-up was to evaluate the association between socioeconomic factors and long-term adherence to CPAP in patients with OSA. The study was an analysis of the CPAP subcohort in the prospective, longitudinal cohort study Course of Disease in Patients Reported to the Swedish CPAP Oxygen and Ventilator Registry. A detailed description of the study protocol was published previously.24Palm A. Ågren K. Grote L. et al.Course of DISease In patients reported to the Swedish CPAP Oxygen and VEntilator RegistrY (DISCOVERY) with population-based controls.BMJ Open. 2020; 10e040396Crossref PubMed Scopus (2) Google Scholar Patients with OSA treated with CPAP reported to the Swedevox registry between July 1, 2010, and March 12, 2018, were included, and data were cross-linked with several other quality and governmental registries. In this study, socioeconomic data from Statistics Sweden were used. The total cohort comprised 66,265 patients, and those with complete data regarding CPAP adherence at the scheduled 1-year follow-up visit were analyzed further (n = 20,521) (Fig 1). Patients lacking reported data on nocturnal CPAP use or who claimed no further need of CPAP at the follow-up visit were excluded from subsequent analysis. Potential explanation for ceased need for CPAP can be significant weight loss with decreased symptoms of OSA or other successful sleep hygienic intervention. The procedure for reporting to the Swedevox registry has been detailed elsewhere.25Palm A. Midgren B. Theorell-Haglow J. et al.Factors influencing adherence to continuous positive airway pressure treatment in obstructive sleep apnea and mortality associated with treatment failure—a national registry-based cohort study.Sleep Med. 2018; 51: 85-91Crossref PubMed Scopus (23) Google Scholar In brief, CPAP-related data were reported manually to a web-based case report format by 39 sleep centers. The geographical coverage is estimated to be 90% (www.ucr.uu.se/swedevox/rapporter/arsrapporter) (e-Fig 1). Since 2015, up to 17 centers reported data via automated data transfer from the Swedish Sleep Apnea Registry (www.sesar.se). Information about sex, age, height, weight, AHI, oxygen desaturation index, excessive daytime sleepiness using the Epworth Sleepiness Scale (ESS) score,26Johns M.W. A new method for measuring daytime sleepiness: the Epworth sleepiness scale.Sleep. 1991; 14: 540-545Crossref PubMed Scopus (10876) Google Scholar and the presence of hypertension as well as information about the use of a humidifier were reported to the registry when CPAP therapy was initiated. At follow-up, data regarding nocturnal CPAP use time (hours per total number of nights) from the CPAP's data log were reported. Individual data on civil status and country of birth were based on data from the nationwide Swedish Civil Registry supplied to Statistics Sweden, a government-based agency that brings official statistics to the public (www.scb.se/en). Civil status was categorized as: married or in a civil partnership, unmarried, divorced, and widow or widower. National origin was categorized as: born in Sweden with two native parents, born in Sweden with one native and one foreign parent, born in Sweden with two foreign parents, and born abroad. Total household income at year of inclusion in the Swedevox registry or control group was obtained from the Swedish Tax Agency and was index-linked and categorized into quantiles.27EkonomifaktaReal löneutveckling. July 20, 2020. Ekonomifakta website.https://www.ekonomifakta.se/Fakta/Arbetsmarknad/Loner/Loneutveckling-och-inflation/?graph=/20419/1/all/Date accessed: February 5, 2021Google Scholar,28Statistics SwedenIncome and tax registry. Statistics Sweden website.https://www.scb.se/vara-tjanster/bestalla-mikrodata/vilka-mikrodata-finns/individregister/inkomst-och-taxeringsregistret-iot/Date accessed: February 5, 2021Google Scholar The Swedish Longitudinal Integrated Database for Health Insurance and Labour Market Studies provided data on length of education.29Ludvigsson J.F. Svedberg P. Olen O. Bruze G. Neovius M. The longitudinal integrated database for health insurance and labour market studies (LISA) and its use in medical research.Eur J Epidemiol. 2019; 34: 423-437Crossref PubMed Scopus (241) Google Scholar Education was categorized into three levels: low (≤ 9 years), medium (10-12 years), and high (≥ 13 years), corresponding to compulsory school, secondary school, and postsecondary school (college and university), respectively. The study was approved by the Ethical Board of Lund University (Identifier: Log No. 2018/51). Reporting to a National Quality Registry in Sweden requires careful information and verbal consent, but does not require written informed consent. Normal distributed continuous data were expressed as mean ± SD, and skewed distributed continuous data were expressed as median with interquartile range. Categorical data were presented as frequencies and percentages. The t test was used for comparisons of continuous variables, and the χ 2Young T. Finn L. Peppard P.E. et al.Sleep disordered breathing and mortality: eighteen-year follow-up of the Wisconsin sleep cohort.Sleep. 2008; 31: 1071-1078PubMed Google Scholar test was used for comparisons of categorical variables. The associations between adherence to CPAP therapy as a dependent variable and covariates were evaluated in multivariate linear and logistic regression models. Direct acyclic graphs were created using the browser-based environment DAGitty (www.dagitty.net)30Lederer D.J. Bell S.C. Branson R.D. et al.Control of confounding and reporting of results in causal inference studies. Guidance for authors from editors of respiratory, sleep, and critical care journals.Ann Am Thorac Soc. 2019; 16: 22-28Crossref PubMed Scopus (283) Google Scholar and identified age and sex as the main confounding factors (Fig 2). In the fully adjusted linear regression model all covariates (socioeconomic factors, age, sex, BMI, AHI, ESS score, and use of humidifier) were included to make effect sizes comparable and interpretable in a clinical context. To make a comparison of effect size between classic variables associated with CPAP adherence and socioeconomic variables possible and interpretable in a clinical context, the continuous variables age, BMI, AHI, and ESS score were transformed to categorical variables using widely accepted clinical severity thresholds. Age was stratified into young (< 40 years), middle-aged (40-< 60 years), and elderly (≥ 60 years) and total household income was stratified into quartiles to make the variable understandable for international readers. A sensitivity analysis was conducted comparing counties with reported follow-up data on more than 50% of patients with counties reporting lower follow-up rates. A P value of < .05 was considered statistically significant. Statistical analyses were conducted using Stata version 16.0 software (StataCorp LP). In total, 20,521 patients were included in the analysis after a mean of 1.3 ± 0.8 years of CPAP use; 70.7% were men with a mean age of 57.8 ± 12.2 years, BMI of 32.0 ± 6.1 kg/m2, AHI of 36.9 ± 22.1 events/h, and ESS score of 10.4 ± 5.0. Nocturnal CPAP use of ≥ 4 h was reported in 15,511 patients (76%), whereas lower adherence was reported in 5,010 patients (Table 1, Fig 1). The median nocturnal CPAP use time was 355 min (interquartile range, 240-420 min). CPAP-adherent patients were slightly older, showed higher AHI levels at baseline, and showed a slightly lower BMI. Patients nonadherent to CPAP were less frequently married, had lower levels of education, and more frequently had a foreign background.Table 1Baseline CharacteristicsCharacteristicAllFully Adherent to CPAP (≥ 4 h/night)Nocturnal CPAP Use < 4 h/nightNo. of patients20,52115,5115,010Men14,501 (70.7)11,029 (71.1)3,472 (69.3)Nocturnal CPAP use, min355 (240-420)386 (328-432)69 (0-180)Age, y57.8 ± 12.258.2 ± 11.956.6 ± 12.7 <401,632 (8.0)1,137 (7.3)495 (9.9) 40-608,938 (43.6)6,604 (42.6)2,334 (46.6) ≥609,951 (48.5)7,770 (50.1)2,181 (53.5)BMI, kg/m232.0 ± 6.132.0 ± 6.032.3 ± 6.6 < 251,667 (8.41,227 (8.2)440 (9.2) 25-< 306,565 (33.2)5,031 (33.6)1,534 (32.0) 30-< 356,305 (31.9)4,850 (32.4)1,455 (30.3) ≥ 355,241 (26.5)3,874 (25.9)1,367 (28.5)AHI, events/h36.9 ± 22.138.3 ± 22.232.6 ± 21.3 < 5202 (1.0)118 (0.8)84 (1.7) 5-< 152,491 (12.3)1,579 (10.3)912 (18.5) 15-< 306,287 (31.1)4,652 (30.4)1,635 (33.1) ≥ 3011,252 (55.6)8,944 (58.5)2,308 (46.7)ESS10.4 ± 5.010.5 ± 4.99.9 ± 5.0 < 74,557 (24,3)3,309 (23.2)1,248 (27.8) 7-105,118 (27.3)3,859 (27.1)1,259 (28.0) 11-155,982 (31.9)4,669 (32.8)1,313 (29.2) > 163,072 (16.4)2,396 (16.8)676 (15.0)Use of humidifier10,028 (49.3)7,686 (49.9)2,342 (47.4)Civil status Unmarried4,736 (23.1)3,366 (21.7)1,370 (27.4) Married11,509 (56.1)9,046 (58.4)2,462 (49.3) Divorced3,319 (16.292,396 (15.5)923 (18.5) Widower or widow935 (4.6)696 (4.5)239 (4.8)Educational level Low, ≤ 9 y4,392 (22.2)3,256 (21.7)1,140 (23.9) Medium, 10-12 y10,222 (51.7)7,669 (51.1)2,550 (53.5) High, > 12 y5,168 (26.1)4,088 (27.2)1,082 (22.6)Households total income, index-linked gross pay, €32,270 ± 18,92132,861 ± 19,05630,437 ± 18,540 1st quartile (lowest)5,129 (25.0)3,674 (23.7)1,455 (29.1) 2nd quartile5,128 (25.0)3,853 (24.8)1,275 (25.5) 3rd quartile5,130 (25.0)3,905 (25.2)1,225 (24.5) 4th quartile (highest)5,128 (25.0)4,078 (26.3)1,050 (21.0)Birth country Born abroad2,335 (11.4)1,617 (10.4)718 (14.3) Born in Sweden, two foreign parents427 (2.1)298 (1.9)129 (2.6) Born in Sweden, one native parent1,149 (5.6)864 (5.6)285 (5.7) Born in Sweden, two native parents16,610 (80.9)12,732 (82.1)3,878 (77.4)Data are presented as No. (%), mean ± SD, or median (interquartile range). AHI = apnea-hypopnea index; ESS = Epworth Sleepiness Scale. Open table in a new tab Data are presented as No. (%), mean ± SD, or median (interquartile range). AHI = apnea-hypopnea index; ESS = Epworth Sleepiness Scale. In multivariate linear regression analysis (Table 2), independent predictors of higher nocturnal CPAP use were female sex, age of ≥ 60 years, BMI of 25 to 35 kg/m2, AHI of ≥ 15 events/h, ESS of > 10, and use of a humidifier. Among the socioeconomic factors, being married, having a high educational level exceeding 13 years, having a total household income exceeding the lowest quartile, and being born in Sweden with one or two native parents all were associated independently with longer nocturnal CPAP use (Table 2, Fig 3).Table 2Multiple Linear Regression Models With Minutes of Nightly CPAP Use as Dependent VariableVariableModel 2A: β-Coefficient for Minutes of Nightly CPAP Use (95% CI)aAdjusted for sex and age.P ValueModel 2B: β-Coefficient for Minutes of Nightly CPAP Use (95% CI)bAdjusted for sex, age, and socioeconomic factors.P ValueModel 2C: β-Coefficient for Minutes of Nightly CPAP Use (95% CI)cAdjusted for all variables in the table.P ValueSex Male1...1...1... Female–1.7 (–6.2 to 2.8).4603.1 (–1.7 to 7.9).2087.3 (2.3-12.4).005Age, y < 401...1...1... 40-6013.6 (5.7-21.4).0017.5 (–0.8 to 15.7).0767.6 (–0.9 to 16.2).079 ≥ 6033.8 (26.0-41.6)< .00126.3 (17.6-34.9)< .00127.0 (18.0-36.0)< .001BMI, kg/m2 < 25............1... 25-< 30............10.0 (1.7-18.4).018 30-< 35............10.8 (2.3-19.2).012 ≥ 35............6.5 (–2.3 to 15.2).146AHI, events/h < 5............1... 5-< 15............25.8 (3.2-48.4).025 15-< 30............62.9 (40.8-85.0)< .001 ≥ 30............84.4 (62.4-106.4)< .001ESS score.................. < 7............1... 7-10............6.5 (0.5-12.5).032 11-15............13.7 (7.9-19.5)< .001 > 16............17.2 (10.3-24.1)< .001Use of humidifier............8.4 (4.1-12.7)< .001Civil status Unmarried......1...1... Married......20.5 (14.8-25.6)< .00120.6 (14.9-26.3)< .001 Divorced......–6.8 (–13.7 to 0.2).056–5.2 (–12.4 to 2.0).415 Widower or widow......3.9 (–7.2 to 15.1).4890.1 (–11.6 to 11.8).984Educational level Low (≤ 9 y)......1...1... Medium (10-12 y)......3.1 (–2.2 to 8.4).2562.3 (–3.2 to 7.9).415 High (≥ 13 y)......13.2 (7.0-19.4)< .00112.8 (6.3-19.2)< .001Household total income (index-linked) Quartile 1 (lowest income)......1...1... Quartile 2......6.1 (0.2-12.0).0438.5 (2.3-14.6).007 Quartile 3......10.4 (4.3-16.5).00112.1 (5.8-18.5)< .001 Quartile 4 (highest income)......15.9 (9.5-22.3)< .00117.0 (10.3-23.7)< .001Birth country Born abroad......1...1... Born in Sweden, two foreign parents......10.7 (–4.9 to 26.3).1793.2 (–12.9 to 19.3).698 Born in Sweden, one native parent......29.0 (18.3-39.8)< .00125.5 (14.4-36.6)< .001 Born in Sweden, two native parents......29.3 (22.7-36.0)< .00127.2 (20.2-34.2)< .001AHI = apnea-hypopnea index; ESS = Epworth Sleepiness Scale.a Adjusted for sex and age.b Adjusted for sex, age, and socioeconomic factors.c Adjusted for all variables in the table. Open table in a new tab AHI = apnea-hypopnea index; ESS = Epworth Sleepiness Scale. In a sensitivity analysis addressing a potential reporting bias, all socioeconomic factors remained significant as independent predictors of CPAP adherence in counties with more than 50% of patients with reported follow-up data (8 counties; 13,138 patients). In counties with less than 50% of patients with a reported follow-up visit (11 counties; 7,383 patients), all factors except education level and total household income for counties with < 50% follow-up remained significant (e-Table 1). The impact of socioeconomic factors on adherence to CPAP treatment was confirmed in a multivariate logistic regression analysis adjusting for the same covariates (Table 3). Patients lost to follow-up (n = 39,949) showed a slightly lower AHI at baseline compared with the analysis population (34.6 ± 22.7 vs 36.9 ± 22.1 events/h; P < .001); otherwise, no clinically significant differences at baseline were identified (e-Table 2).Table 3OR for Having Nocturnal CPAP Use of ≥ 4 hVariableOR (95% CI)P ValueCivil status Unmarried1... Married1.36 (1.25-1.48)< .001 Divorced0.96 (0.87-1.07).498 Widower or widow1.06 (0.88-1.27).547Education Low (≤ 9 y)1... Medium (10-12 y)1.08 (0.99-1.17).079 High (≥13 y)1.26 (1.14-1.39)< .001Household total income Quartile 1 (lowest income)1... Quartile 21.15 (1.05-1.26).004 Quartile 31.26 (1.14-1.38)< .001 Quartile 4 (highest income)1.43 (1.29-1.59)< .001Birth country Born abroad1... Born in Sweden, two foreign parents1.09 (0.86-1.38).476 Born in Sweden, one native parent1.38 (1.17-1.63)< .001 Born in Sweden, two native parents1.37 (1.24-1.52)< .001Adjusted for sex, age, and all variables in the table. AHI = apnea-hypopnea index; ESS = Epworth Sleepiness Scale. Open table in a new tab Adjusted for sex, age, and all variables in the table. AHI = apnea-hypopnea index; ESS = Epworth Sleepiness Scale. The main finding of this longitudinal population-based study is that civil status, educational level, household income, and foreign background can be established as strong predictors for CPAP adherence in OSA. As illustrated in the regression analysis, the effect sizes of socioeconomic factors are equivalent to those often used for the indication of CPAP therapy like the degree of daytime sleepiness or OSA severity. To the best of our knowledge, the impact of socioeconomic factors on adherence to CPAP therapy have not been analyzed in a large population-based cohort. Previous studies are based on small clinical cohorts consisting of 70 to 330 patients,15Simon-Tuval T. Reuveni H. Greenberg-Dotan S. Oksenberg A. Tal A. Tarasiuk A. Low socioeconomic status is a risk factor for CPAP acceptance among adult OSAS patients requiring treatment.Sleep. 2009; 32: 545-552Crossref PubMed Scopus (112) Google Scholar, 16Brin Y.S. Reuveni H. Greenberg S. Tal A. Tarasiuk A. Determinants affecting initiation of continuous positive airway pressure treatment.Isr Med Assoc J. 2005; 7: 13-18PubMed Google Scholar, 17Bakker J.P. O'Keeffe K.M. Neill A.M. Campbell A.J. Ethnic disparities in CPAP adherence in New Zealand: effects of socioeconomic status, health literacy and self-efficacy.Sleep. 2011; 34: 1595-1603Crossref PubMed Scopus (55) Google Scholar, 18Platt A.B. Field S.H. Asch D.A. et al.Neighborhood of residence is associated with daily adherence to CPAP therapy.Sleep. 2009; 32: 799-806Crossref PubMed Scopus (96) Google Scholar, 19Lewis K.E. Seale L. Bartle I.E. Watkins A.J. Ebden P. Early predictors of CPAP use for the treatment of obstructive sleep apnea.Sleep. 2004; 27: 134-138Crossref PubMed Scopus (173) Google Scholar, 20Gulati A. Ali M. Davies M. Quinnell T. Smith I. A prospective observational study to evaluate the effect of social and personality factors on continuous positive airway pressure (CPAP) compliance in obstructive sleep apnoea syndrome.BMC Pulm Med. 2017; 17: 56Crossref PubMed Scopus (16) Google Scholar, 21Billings M.E. Auckley D. Benca R. et al.Race and residential socioeconomics as predictors of CPAP adherence.Sleep. 2011; 34: 1653-1658Crossref PubMed Scopus (101) Google Scholar, 22Ye L. Pack A.I. Maislin G. et al.Predictors of continuous positive airway pressure use during the first week of treatment.J Sleep Res. 2012; 21: 419-426Crossref PubMed Scopus (46) Google Scholar and follow-up times generally were short.20Gulati A. Ali M. Davies M. Quinnell T. Smith I. A prospective observational study to evaluate the effect of social and personality factors on continuous positive airway pressure (CPAP) compliance in obstructive sleep apnoea syndrome.BMC Pulm Med. 2017; 17: 56Crossref PubMed Scopus (16) Google Scholar Because of the small sample size in previous studies, multivariate analysis is statistically challenging, rendering the results inconsistent. To estimate the impact of socioeconomic status despite small sample sizes, different compound socioeconomic variables were created. Such compound variables were able to show associations with CPAP adherence in some studies,17Bakker J.P. O'Keeffe K.M. Neill A.M. Campbell A.J. Ethnic disparities in CPAP adherence in New Zealand: effects of socioeconomic status, health literacy and self-efficacy.Sleep. 2011; 34: 1595-1603Crossref Pub
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