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      Arthritis diagnosis and symptoms are positively associated with specific physical job exposures in lower- and middle-income countries: cross-sectional results from the World Health Organization’s Study on global AGEing and adult health (SAGE)

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          Abstract

          Background

          In higher income countries, work-related squatting and heavy lifting have been associated with increased arthritis risk. Here, we address the paucity of data regarding associations between arthritis and work-related physical stressors in lower- and middle-income countries.

          Methods

          Data were extracted from the Study on global AGEing and adult health (SAGE) Wave 1 (2007–10) for adults (aged ≥50 years) from Ghana, India, Russia and South Africa for whom detailed occupation data was available ( n = 21,389; 49.2% women). Arthritis cases were identified using a symptom-defined algorithm (current) and self-reported doctor-diagnosis (lifetime). A sex-specific Job Exposure Matrix was used to classify work-related stressors: heavy physical work, kneeling/squatting, heavy lifting, arm elevation and awkward trunk posture. Using the International Standard Classification of Occupations, we linked SAGE and the Job Exposure Matrix. Logistic regression was used to investigate associations between arthritis and work-related stressors, adjusting for age (10 year age groupings), potential socioeconomic-related confounders, and body mass index. Excess exposure risk due to two-way interactions with other risk factors were explored.

          Results

          Doctor-diagnosed arthritis was associated with heavy physical work (adjusted odds ratios [OR] 1.12, 95%CI 1.01–1.23), awkward trunk posture (adjusted OR 1.23, 95%CI 1.12–1.36), kneeling or squatting (adjusted OR 1.25, 95%CI 1.12–1.38), and arm elevation (adjusted OR 1.66, 95%CI 1.37–2.00). Symptom-based arthritis was associated with kneeling or squatting (adjusted OR 1.27, 95%CI 1.08–1.50), heavy lifting (adjusted OR 1.33, 95%CI 1.11–1.58), and arm elevation (adjusted OR 2.16, 95%CI 1.63–2.86). Two-way interactions suggested excess arthritis risk existed for higher body mass index, and higher income or education.

          Conclusions

          Minimization of occupational health risk factors is common practice in higher income countries: attention should now be directed toward reducing work-related arthritis burden in lower- and middle-income countries.

          Electronic supplementary material

          The online version of this article (10.1186/s12889-018-5631-2) contains supplementary material, which is available to authorized users.

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          Most cited references22

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          Socioeconomic Inequalities in Non-Communicable Diseases Prevalence in India: Disparities between Self-Reported Diagnoses and Standardized Measures

          Background Whether non-communicable diseases (NCDs) are diseases of poverty or affluence in low-and-middle income countries has been vigorously debated. Most analyses of NCDs have used self-reported data, which is biased by differential access to healthcare services between groups of different socioeconomic status (SES). We sought to compare self-reported diagnoses versus standardised measures of NCD prevalence across SES groups in India. Methods We calculated age-adjusted prevalence rates of common NCDs from the Study on Global Ageing and Adult Health, a nationally representative cross-sectional survey. We compared self-reported diagnoses to standardized measures of disease for five NCDs. We calculated wealth-related and education-related disparities in NCD prevalence by calculating concentration index (C), which ranges from −1 to +1 (concentration of disease among lower and higher SES groups, respectively). Findings NCD prevalence was higher (range 5.2 to 19.1%) for standardised measures than self-reported diagnoses (range 3.1 to 9.4%). Several NCDs were particularly concentrated among higher SES groups according to self-reported diagnoses (Csrd) but were concentrated either among lower SES groups or showed no strong socioeconomic gradient using standardized measures (Csm): age-standardised wealth-related C: angina Csrd 0.02 vs. Csm −0.17; asthma and lung diseases Csrd −0.05 vs. Csm −0.04 (age-standardised education-related Csrd 0.04 vs. Csm −0.05); vision problems Csrd 0.07 vs. Csm −0.05; depression Csrd 0.07 vs. Csm −0.13. Indicating similar trends of standardized measures detecting more cases among low SES, concentration of hypertension declined among higher SES (Csrd 0.19 vs. Csm 0.03). Conclusions The socio-economic patterning of NCD prevalence differs markedly when assessed by standardized criteria versus self-reported diagnoses. NCDs in India are not necessarily diseases of affluence but also of poverty, indicating likely under-diagnosis and under-reporting of diseases among the poor. Standardized measures should be used, wherever feasible, to estimate the true prevalence of NCDs.
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            Prevalence of arthritis according to age, sex and socioeconomic status in six low and middle income countries: analysis of data from the World Health Organization study on global AGEing and adult health (SAGE) Wave 1

            Background In higher income countries, social disadvantage is associated with higher arthritis prevalence; however, less is known about arthritis prevalence or determinants in low to middle income countries (LMICs). We assessed arthritis prevalence by age and sex, and marital status and occupation, as two key parameters of socioeconomic position (SEP), using data from the World Health Organization Study on global AGEing and adult health (SAGE). Methods SAGE Wave 1 (2007–10) includes nationally-representative samples of older adults (≥50 yrs), plus smaller samples of adults aged 18-49 yrs., from China, Ghana, India, Mexico, Russia and South Africa (n = 44,747). Arthritis was defined by self-reported healthcare professional diagnosis, and a symptom-based algorithm. Marital status and education were self-reported. Arthritis prevalence data were extracted for each country by 10-year age strata, sex and SEP. Country-specific survey weightings were applied and weighted prevalences calculated. Results Self-reported (lifetime) diagnosed arthritis was reported by 5003 women and 2664 men (19.9% and 14.1%, respectively), whilst 1220 women and 594 men had current symptom-based arthritis (4.8% and 3.1%, respectively). For men, standardised arthritis rates were approximately two- to three-fold greater than for women. The highest rates were observed in Russia: 38% (95% CI 36%–39%) for men, and 17% (95% CI 14%–20%) for women. For both sexes and in all LMICs, arthritis was more prevalent among those with least education, and in separated/divorced/widowed women. Conclusions High arthritis prevalence in LMICs is concerning and may worsen poverty by impacting the ability to work and fulfil community roles. These findings have implications for national efforts to prioritise arthritis prevention and management, and improve healthcare access in LMICs. Electronic supplementary material The online version of this article (doi:10.1186/s12891-017-1624-z) contains supplementary material, which is available to authorized users.
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              Are estimates of socioeconomic inequalities in chronic disease artefactually narrowed by self-reported measures of prevalence in low-income and middle-income countries? Findings from the WHO-SAGE survey

              Background The use of self-reported measures of chronic disease may substantially underestimate prevalence in low-income and middle-income country settings, especially in groups with lower socioeconomic status (SES). We sought to determine whether socioeconomic inequalities in the prevalence of non-communicable chronic diseases (NCDs) differ if estimated by using symptom-based or criterion-based measures compared with self-reported physician diagnoses. Methods Using population-representative data sets of the WHO Study of Global Ageing and Adult Health (SAGE), 2007–2010 (n=42 464), we calculated wealth-related and education-related concentration indices of self-reported diagnoses and symptom-based measures of angina, hypertension, asthma/chronic lung disease, visual impairment and depression in three ‘low-income and lower middle-income countries’—China, Ghana and India—and three ‘upper-middle-income countries’—Mexico, Russia and South Africa. Results SES gradients in NCD prevalence tended to be positive for self-reported diagnoses compared with symptom-based/criterion-based measures. In China, Ghana and India, SES gradients were positive for hypertension, angina, visual impairment and depression when using self-reported diagnoses, but were attenuated or became negative when using symptom-based/criterion-based measures. In Mexico, Russia and South Africa, this distinction was not observed consistently. For example, concentration index of self-reported versus symptom-based angina were: in China: 0.07 vs −0.11, Ghana: 0.04 vs −0.21, India: 0.02 vs −0.16, Mexico: 0.19 vs −0.22, Russia: −0.01 vs −0.02 and South Africa: 0.37 vs 0.02. Conclusions Socioeconomic inequalities in NCD prevalence tend to be artefactually positive when using self-report compared with symptom-based or criterion-based diagnostic criteria, with greater bias occurring in low-income countries. Using standardised, symptom-based measures would provide more valid estimates of NCD inequalities.
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                Author and article information

                Contributors
                +61 03 8395 8114 , sbrennan@unimelb.edu.au
                svetlana.solovieva@ttl.fi
                eira.viikari-juntura@ttl.fi
                ilana.ackerman@monash.edu
                s.bowe@deakin.edu.au
                kowalp@who.int
                naidoon@who.int
                chatterjis@who.int
                anita.wluka@monash.edu
                michelle.leech@monash.edu
                richard.page@deakin.edu.au
                ksanders@unimelb.edu.au
                gomez.montes@ucaldas.edu.co
                gustavo.duque@unimelb.edu.au
                darci.green@unimelb.edu.au
                m.mohebbi@deakin.edu.au
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                8 June 2018
                8 June 2018
                2018
                : 18
                : 719
                Affiliations
                [1 ]ISNI 0000 0001 2179 088X, GRID grid.1008.9, Australian Institute for Musculoskeletal Science (AIMSS), , The University of Melbourne and Western Health, ; Level 3, WHCRE Building, C/- Sunshine Hospital, 176 Furlong Road, St Albans, Melbourne, VIC 3021 Australia
                [2 ]ISNI 0000 0004 0645 2884, GRID grid.417072.7, Department of Medicine-Western Health, ; St Albans, Australia
                [3 ]ISNI 0000 0004 0410 5926, GRID grid.6975.d, Finnish Institute of Occupational Health, ; Helsinki, Finland
                [4 ]ISNI 0000 0004 1936 7857, GRID grid.1002.3, Department of Epidemiology and Preventive Medicine, , Monash University, ; Melbourne, Australia
                [5 ]ISNI 0000 0001 0526 7079, GRID grid.1021.2, Deakin University, ; Geelong, Australia
                [6 ]ISNI 0000000121633745, GRID grid.3575.4, Department of Health Statistics and Information Systems, , World Health Organization, ; Geneva, Switzerland
                [7 ]ISNI 0000 0000 9039 7662, GRID grid.7132.7, Research Institute for Health Sciences, , Chiang Mai University, ; Chiang Mai, Thailand
                [8 ]ISNI 0000 0004 1936 7857, GRID grid.1002.3, Monash University, ; Melbourne, Australia
                [9 ]ISNI 0000 0004 0540 0062, GRID grid.414257.1, Barwon Centre for Orthopaedic Research and Education, Barwon Health, ; Geelong, Australia
                [10 ]GRID grid.7779.e, Health Faculty, , University of Caldas, ; Manizales, Colombia
                Article
                5631
                10.1186/s12889-018-5631-2
                5994040
                29884171
                357062ef-4974-4a28-8a52-2c83b1dfe510
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the 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.

                History
                : 17 October 2017
                : 29 May 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;
                Award ID: 1107510
                Award ID: 1063574
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2018

                Public health
                arthritis,lower- and middle-income countries,obesity,occupation,social factors
                Public health
                arthritis, lower- and middle-income countries, obesity, occupation, social factors

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