Advertisement

International Journal of Public Health

, Volume 64, Issue 1, pp 135–145 | Cite as

Socioeconomic gradients in chronic disease risk behaviors in a population-based study of older adults in rural South Africa

  • Lindsay C. KobayashiEmail author
  • Sarah Frank
  • Carlos Riumallo-Herl
  • David Canning
  • Lisa Berkman
Original Article
  • 102 Downloads

Abstract

Objectives

To investigate the associations between household wealth, household consumption, and chronic disease risk behaviors among older adults in rural South Africa.

Methods

Data were from baseline assessments of 5059 adults aged ≥ 40 in the population-based “Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa” in 2015. Confounder-adjusted prevalence ratios were estimated for the associations between each of household wealth and household consumption quintiles with low moderate-to-vigorous physical activity (MVPA), current smoking, frequent alcohol intake, and overweight/obese body mass index (BMI).

Results

Low MVPA and overweight/obese BMI were common (57% and 58%, respectively), and linearly increased in prevalence across household wealth quintiles. Low MVPA decreased and overweight/obese BMI increased in prevalence across household consumption quintiles. Smoking and frequent alcohol intake were rare (9% and 6%, respectively); they decreased in prevalence across wealth quintiles, but did not vary by consumption quintile.

Conclusions

Chronic disease risk behaviors are socioeconomically graded among older, rural South African adults. The high prevalence of overweight and obesity in rural South Africa is a public health concern requiring urgent attention.

Keywords

South Africa Aging Rural Physical activity Smoking Alcohol Body mass index Socioeconomic inequalities 

Notes

Funding

This work was funded by a Grant from the National Institute on Aging of the National Institutes of Health (P01 AG041710). The funder had no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the article; or in the decision to submit it for publication.

Compliance with ethical standards

Conflict of interest

The authors have no conflicts of interest to declare.

Ethical approval

Ethical approval was granted by the University of Witwatersrand Human Research Ethics Committee (M141159), the Harvard T. H. Chan Harvard School of Public Health, Office of Human Research Administration (C13-1608-02), and the Mpumalanga Provincial Research and Ethics Committee. Informed consent was obtained from all individual participants included in the study. All procedures involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.

Supplementary material

38_2018_1173_MOESM1_ESM.docx (18 kb)
Supplementary material 1 (DOCX 18 kb)

References

  1. Akinyemiju T, Ogunsina K, Okwali M, Sakhuja S, Braithwaite D (2017) Lifecourse socioeconomic status and cancer-related risk factors: analysis of the WHO study on global ageing and adult health (SAGE). Int J Cancer 140:777–787CrossRefGoogle Scholar
  2. Allen L, Williams J, Townsend N, Mikkelsen B, Roberts N, Foster C, Wickramasinghe K (2017) Socioeconomic status and non-communicable disease behavioural risk factors in low-income and lower-middle-income countries: a systematic review. Lancet Glob Health 5:e277–e289.  https://doi.org/10.1016/S2214-109X(17)30058-X CrossRefGoogle Scholar
  3. American Cancer Society (2017) Alcohol use and cancer. https://www.cancer.org/cancer/cancer-causes/diet-physical-activity/alcohol-use-and-cancer.html. Accessed 24 Mar 2018
  4. Arokiasamy P, Bloom D, Lee J, Feeney K, Ozolins M (2012) Longitudinal aging study in india: vision, design, implementation, and preliminary findings. In: Smith JP, Majmundar M (eds) Aging in Asia: findings from new and emerging data initiatives. National Academies Press, Washington, pp 36–76Google Scholar
  5. Bull FC, Maslin TS, Armstrong T (2009) Global physical activity questionnaire (GPAQ): nine country reliability and validity study. J Phys Act Health 6:790–804CrossRefGoogle Scholar
  6. Caldwell TM, Rodgers B, Clark C, Jefferis BJ, Stansfeld SA, Power C (2008) Lifecourse socioeconomic predictors of midlife drinking patterns, problems and abstention: findings from the 1958 British Birth Cohort Study. Drug Alcohol Depend 95:269–278CrossRefGoogle Scholar
  7. Christie P, Collins C (1982) Bantu education: apartheid ideology or labour reproduction? Comp Educ 18:59–75CrossRefGoogle Scholar
  8. Deaton A, Grosh M (2000) Consumption. In: Grosh M, Glewwe P (eds) Designing household survey questionnaires for developing countries: lessons from 15 years of the living standards measurement study. The World Bank, Washington, pp 91–134Google Scholar
  9. Ford ES, Zhao G, Tsai J, Li C (2011) Low-risk lifestyle behaviors and all-cause mortality: findings from the National Health and Nutrition Examination Survey III Mortality Study. Am J Public Health 101:1922–1929CrossRefGoogle Scholar
  10. Gómez-Olivé FX, Montana L, Wagner RG, Kabdula CW, Rohr JK, Kahn K, Barnighausen T, Canning D, Gaziano T, Salomon JA, Payne CF, Wade A, Tollman SM, Berkman L (2018) Cohort profile: health and ageing in africa: a longitudinal study of an INDEPTH community in South Africa (HAALSI). Int J Epidemiol.  https://doi.org/10.1093/ije/dyx247 Google Scholar
  11. Grundy E, Holt G (2011) The socioeconomic status of older adults: how should we measure it in studies of health inequalities? J Epidemiol Community Health 55:895–904.  https://doi.org/10.1136/jech.55.12.895 CrossRefGoogle Scholar
  12. Grundy E, Sloggett A (2003) Health inequalities in the older population: the role of personal capital, social resources and socio-economic circumstances. Soc Sci Med 56:935–937.  https://doi.org/10.1016/S0277-9536(02)00093-X CrossRefGoogle Scholar
  13. Headey B (2008) Poverty is low consumption and low wealth, not just low income. Soc Indic Res 89:23–39.  https://doi.org/10.1007/s11205-007-9231-2 CrossRefGoogle Scholar
  14. Hentschel J, Lanjouw P (1996) Constructing an indicator of consumption for the analysis of poverty: principles and illustrations with reference to Ecuador. World Bank, Washington, LSMS Working Paper Number 124Google Scholar
  15. Howe LD, Galobardes B, Maijasevic A, Gordon D, Johnson D, Onwujekwe O, Patel R, Webb EA, Lawlor DA, Hargreaves JR (2012) Measuring socio-economic position for epidemiological studies in low-and middle-income countries: a methods of measurement in epidemiology paper. Int J Epidemiol 41:871–886.  https://doi.org/10.1093/ije/dys037 CrossRefGoogle Scholar
  16. Jin M, Cai S, Guo J, Zhu Y, Li M, Yu Y, Zhang S, Chen K (2013) Alcohol drinking and all cancer mortality: a meta-analysis. Ann Oncol 24:807–816.  https://doi.org/10.1093/annonc/mds508 CrossRefGoogle Scholar
  17. Kabudula CW, Houle B, Collinson MA, Kahn K, Gómez-Olivé FX, Clark SJ, Tollman S (2017) Progression of the epidemiological transition in a rural South African setting: findings from population surveillance in Agincourt, 1993–2013. BMC Public Health 17:424.  https://doi.org/10.1186/s12889-017-4312-x CrossRefGoogle Scholar
  18. Katzmarzyk PT, Mason CJ (2009) The physical activity transition. Phys Act Health 6:269–280CrossRefGoogle Scholar
  19. Khaw KT, Wareham N, Bingham S, Welch A, Luben R, Day N (2008) Combined impact of health behaviours and mortality in men and women: the EPIC-Norfolk prospective population study. PLOS Med 5:e12.  https://doi.org/10.1371/journal.pmed.0050012 CrossRefGoogle Scholar
  20. Kobayashi LC, Glymour MM, Kahn K, Payne CF, Wagner RG, Montana L, Mateen FJ, Tollman SM, Berkman LF (2017) Childhood deprivation and later-life cognitive function in a population-based study of older, rural South Africans. Soc Sci Med 190:20–28.  https://doi.org/10.1016/j.socscimed.2017.08.009 CrossRefGoogle Scholar
  21. Kvaavik E, Batty D, Ursin G, Huxley R, Gale C (2011) Influence of individual and combined health behaviors on total and cause-specific mortality in men and women: the United Kingdom Health and Lifestyle Survey. Arch Intern Med 170:711–719CrossRefGoogle Scholar
  22. McCullough ML, Patel AV, Kushi LH, Patel R, Willett WC, Doyle C, Thun MJ, Gapstur SM (2011) Following cancer prevention guidelines reduces risk of cancer, cardiovascular disease, and all-cause mortality. Cancer Epidemiol Biomark Prev 20:1089–1097CrossRefGoogle Scholar
  23. National Department of Health (2017) South African demographic and health survey 2016: key indicators report. https://www.statssa.gov.za/publications/Report%2003-00-09/Report%2003-00-092016.pdf. Accessed 5 May 2018
  24. Pampel F (2008) Tobacco use in sub-Sahara Africa: estimates from the demographic health surveys. Soc Sci Med 66:1772–1783CrossRefGoogle Scholar
  25. Popkin BM, Adair LS, Ng SW (2012) NOW AND THEN: the global nutrition transition: the pandemic of obesity in developing countries. Nutr Rev 70:3–21.  https://doi.org/10.1111/j.1753-4887.2011.00456.x CrossRefGoogle Scholar
  26. Prince M, Wimo A, Guerchet M, Ali G-C, Wu Y-T, Prina M, Alzheimer’s Disease International (2015) World alzheimer report 2015: the global impact of dementia: an analysis of prevalence, incidence, cost, and trends. https://www.alz.co.uk/research/WorldAlzheimerReport2015.pdf. Accessed 5 May 2018
  27. Riumallo-Herl C, Canning D, Wagner R, Kabudula C, Collinson M (2017) Health gradients in South Africa: inequalities in the measure of the beholder. PGDA Working Paper 139. https://cdn1.sph.harvard.edu/wp-content/uploads/sites/1288/2012/11/Health-Gradients-in-South-Africa-Inequalities-in-the-Measure-of-the-Beholder-May_3_2017.pdf. Accessed 5 May 2018
  28. Roerecke M, Rehm J (2010) Irregular heavy drinking occasions and risk of ischemic heart disease: a systematic review and meta-analysis. Am J Epidemiol 171:633–644.  https://doi.org/10.1093/aje/kwp4515 CrossRefGoogle Scholar
  29. Rutstein SO, Johnson K (2004) DHS comparative reports no 6: the DHS wealth index. https://dhsprogram.com/pubs/pdf/cr6/cr6.pdf. Accessed 7 May 2018
  30. Sartorius K, Sartorius B, Tollman S, Schatz E, Kirsten J, Collinson M (2013) Rural poverty dynamics and refugee communities in south africa: a spatial-temporal model. Popul Space Place 19:103–123.  https://doi.org/10.1002/psp.697 CrossRefGoogle Scholar
  31. Shisana O et al (2013) South African national health and nutrition examination survey (SANHANES-1). HSRC Press, Cape Town. http://www.hsrc.ac.za/uploads/pageNews/72/SANHANES-launch%20edition%20(online%20version).pdf. Accessed 7 May 2018
  32. Statistics South Africa (2014) Census 2011: Profile of older persons in South Africa (Report no. 03-01-60). https://www.statssa.gov.za/publications/Report-03-01-60/Report-03-01-602011.pdf. Accessed 7 May 2018
  33. Tehranifar P, Liao Y, Ferris JS, Terry MB (2009) Life course socioeconomic conditions, passive tobacco exposures and cigarette smoking in a multiethnic birth cohort of U.S. women. Cancer Causes Control 20:867–876CrossRefGoogle Scholar
  34. Tucker JS (2002) Health-related social control within older adults’ relationships. J Gerontol B Psychol Sci Soc Sci 57:3873995CrossRefGoogle Scholar
  35. United Nations (1963) Apartheid in South Africa: summary of the report of the special committee on the policies of apartheid of the government of South Africa. United Nations, GenevaGoogle Scholar
  36. Wiseman M (2008) The second World Cancer Research Fund/American Institute for Cancer Research expert report. Food, nutrition, physical activity, and the prevention of cancer: a global perspective. Proc Nutr Soc 67:253–256CrossRefGoogle Scholar
  37. World Health Organization (2010) Global recommendations on physical activity for health. http://www.who.int/dietphysicalactivity/global-PA-recs-2010.pdf. Accessed 7 May 2018
  38. World Health Organization (2017a) Countries: South Africa. http://www.afro.who.int/countries/south-africa. Accessed 7 May 2018
  39. World Health Organization (2017b) Obesity and Overweight Fact Sheet. http://www.who.int/mediacentre/factsheets/fs311/en/. Accessed 7 May 2018
  40. World Health Organization (2018) Tobacco fact sheet. http://www.who.int/mediacentre/factsheets/fs339/en/. Accessed 7 May 2018
  41. Zou G (2004) A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol 159:702–7066CrossRefGoogle Scholar

Copyright information

© Swiss School of Public Health (SSPH+) 2018

Authors and Affiliations

  • Lindsay C. Kobayashi
    • 1
    • 2
    Email author
  • Sarah Frank
    • 2
  • Carlos Riumallo-Herl
    • 2
    • 3
  • David Canning
    • 2
    • 4
  • Lisa Berkman
    • 2
  1. 1.Lombardi Comprehensive Cancer CenterGeorgetown UniversityWashingtonUSA
  2. 2.Harvard Center for Population and Development StudiesHarvard T.H. Chan School of Public HealthCambridgeUSA
  3. 3.Department of Applied EconomicsErasmus School of EconomicsRotterdamThe Netherlands
  4. 4.Department of Global Health and PopulationHarvard T.H. Chan School of Public HealthBostonUSA

Personalised recommendations