Research Article of International Research Journal of Public Health
Depression Predictors among Older Persons in a Rural Community in South Africa
Olurinde A. Oni MD, MPH1 and Olorunfemi E. Amoran MD2
1Department of Clinical Research, Kansas City Veterans Affairs Medical Center, Kansas City, Missouri 64128, USA; 2Department of Community Medicine and Primary Care, Olabisi Onabanjo University Teaching Hospital, Sagamu, Nigeria
Background: Depression is a very important part of global mental health concerns. Many of the studies on correlates of depression stopped short of finding the predictors. Predictive models will empower preventative efforts by healthcare providers and policy makers. The purpose of this study was to determine the factors predicting depressive symptoms among a population of older men and women in rural South Africa.
Methods: Data were obtained from “Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa (HAALSI) in the INDEPTH Health and Demographic Surveillance System (HDSS) site of Agincourt” in rural Mpumalanga province, South Africa. Previously validated short-version Center for Epidemiologic Studies Depression Scale (CES-D 8) was used to assess for depressive symptoms. Multivariable logistic regression model with stepwise selection, and receiver operating curve were used to examine the predictors of depression.
Results: Of the 4027 participants included in this study, 743 (18.5%) met the criterion for depression (CES-D 8 score ≥3). Older age (OR 1.025, CI 1.016-1.034), diabetes (OR 1.467, CI 1.152-1.868), and alcohol consumption (OR 1.536, CI 1.261-1.872) predicted depression. Being male (OR 0.734, CI 0.588-0.915) and homemaker rather than not working (OR 0.513, CI 0.372-0.707) were protective. Compared to those who were married, depressive symptoms were significantly higher among the separated/divorced (OR 1.372, CI 1.027-1.834) and the widowed (OR 1.468, CI 1.172-1.839).
Conclusions: It is possible to predict the development of depression in this community, and findings are generalizable to other communities and countries. Healthcare workers and policy makers should use the findings for preventative care and policies.
Keywords: Depression, South Africa, Aging, Predictors, Mental Health
How to cite this article:
Olurinde A. Oni and Olorunfemi E. Amoran.Depression Predictors among Older Persons in a Rural Community in South Africa. International Research Journal of Public Health, 2019; 3:31. DOI:10.28933/irjph-2019-07-0805
1. Whiteford HA, Ferrari AJ, Degenhardt L, Feigin V, Vos T. The global burden of mental, neurological and substance use disorders: an analysis from the Global Burden of Disease Study 2010. PloS one, 2015; 10(2), e0116820.
2. US Burden of Disease Collaborators, Mokdad AH, Ballestros K. Echko M, Glenn S, Olsen HE, et al. The State of US Health, 1990-2016: Burden of Diseases, Injuries, and Risk Factors Among US States. JAMA, 2018; 319(14), 1444–1472.
3. Thakur H, Oni O, Singh V, Sharma R, Sharma M, Maalouf S, et al. Increases in the Service Connection Disability and Treatment Costs Associated with Posttraumatic Stress Disorder and/or Traumatic Brain Injury in United States Veterans Pre- and Post-9/11: The Strong Need for a Novel Therapeutic Approach. Epidemiology (Sunnyvale) 2018; 8: 353.
4. GBD 2015 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet (London, England), 2016; 388(10053), 1545–1602.
5. National Institute of Mental Health: Depression Basics. https://www.nimh.nih.gov/health/publications/depression/index.shtml#pub1. (Accessed 05 May 2019).
6. Ritchie H, Roser M. (2018) Mental Health. https://ourworldindata.org/mental-health#anxiety-disorders. (Accessed 08 May 2019)
7. World Health Organization. The world health report 2001 – Mental Health: New Understanding, New Hope. https://www.who.int/whr/2001/en/ (Accessed 01 May 2019)
8. World Health Organization (2018). Depression. https://www.who.int/en/news-room/fact-sheets/detail/depression. (Accessed 30 April 2019).
9. Yi SW. Depressive Symptoms on the Geriatric Depression Scale and Suicide Deaths in Older Middle-aged Men: A Prospective Cohort Study. Journal of preventive medicine and public health 2016; 49(3), 176–182.
10. Altonen KI, Isometsä E, Sund R, Pirkola,S. Decline in suicide mortality after psychiatric hospitalization for depression in Finland between 1991 and 2014. World psychiatry: official journal of the World Psychiatric Association (WPA), 2018; 17(1), 110–112.
11. Geulayov G, Lipsitz J, Sabar R, Gross R. Depression in primary care in Israel. Israel Medical Association Journal. 2007;9(8):571–578
12. Amoran OE, Lawoyin, TO, Oni OO. Risk factors associated with mental illness in Oyo State, Nigeria: a community-based study. Annals of general psychiatry, 2005; 4, 19.
13. Berkman, Lisa. Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa [HAALSI] Baseline Survey: Agincourt, South Africa, 2015. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2017-10-30.
14. Gómez-Olivé FX, Montana L, Wagner RG, Kabudula CW, Rohr JK, Kahn K, et al. Cohort profile: health and ageing in africa: A longitudinal study of an INDEPTH community in South Africa (HAALSI). Int. J. Epidemiology. 2018; 47, 689–690.
15. Prince SA, LeBlanc AG, Colley RC, Saunders TJ. Measurement of sedentary behaviour in population health surveys: a review and recommendations. PeerJ, 2017; 5, e4130. doi:10.7717/peerj.4130
16. Pengpid S, Peltzer K. High Sedentary Behavior Is Associated with Depression among Rural South Africans. International Journal of Environmental Research and Public Health 2019; 16, 1413.
17. Schane RE, Walter LC, Dinno A, Covinsky KE, Woodruff PG. Prevalence and risk factors for depressive symptoms in persons with chronic obstructive pulmonary disease. Journal of general internal medicine, 2008; 23(11), 1757–1762.
18. Radloff LS. The CES-D Scale: A Self-Report Depression Scale for Research in the General Population. Applied Psychological Measurement, 1997; 1(3), 385–401.
19. Huppert FA, Marks N, Clark A, Siegrist J, Stutzer A, Vitterso J et al. (2008) Measuring well-being across Europe: description of the ESS well-being module and preliminary findings. http://www.pse.ens.fr/document/wp200840.pdf
20. Duncan I, Huynh N. A Predictive Model for Readmissions Among Medicare Patients in a California Hospital. Population Health Management. 2018; 21(4):317-322.
21. Worldatlas. World Facts: Countries Wth The Largest Aging Population In The World. https://www.worldatlas.com/articles/countries-with-the-largest-aging-population-in-the-world.html. (Accessed 05 May 2019).
22. Drapeau CW, & McIntosh JL. (2018). U.S.A. suicide 2017: Official final data (Publication no. http://www.suicidology.org). (Accessed February 27, 2019).
23. Allred CA (2018). Marriage: More than a century of change, 1900-2016. Family Profiles, FP-18-17. Bowling Green, OH: National Center for Family & Marriage Research. https://doi.org/10.25035/ncfmr/fp-18-17.
24. Centers for Disease Control and Prevention (CDC). Provisional number of marriages and marriage rate: United States, 2000-2017. Provisional number of divorces and annulments and rate: United States, 2000-2017. https://www.cdc.gov/nchs/data/dvs/national-marriage-divorce-rates-00-17.pdf. (Accessed 30 April 2019).
25. Organization for Economic Cooperation and Development (OECD). Marriage and divorce rates. https://www.oecd.org/els/family/SF_3_1_Marriage_and_divorce_rates.pdf. (Accessed 30 April 2019).
26. Statistics South Africa. Statistical Release P0307: Marriages and Divorce, 2016. http://www.statssa.gov.za/publications/P0307/P03072016.pdf. (Accessed 30 April 2019).
27. Judith Treas, Tanja van der Lippe, Tsui-o Chloe Tai, The Happy Homemaker? Married Women’s Well-Being in Cross-National Perspective, Social Forces, 2011; 90 (1), 111–132.
28. Townsend A, Gurin P. Re-Examining the Frustrated Homemaker Hypothesis: Role Fit, Personal Dissatisfaction, and Collective Discontent. Sociology of Work and Occupations, 1981; 8(4), 464–488.
29. Grunow, D., Hofmeister, H., & Buchholz, S. Late 20th-Century Persistence and Decline of the Female Homemaker in Germany and the United States. International Sociology, 2006; 21(1), 101–131.
30. The World Bank. Poverty and Equity Data Portal. http://povertydata.worldbank.org/Poverty/Home.. (Accessed 07 May 2019).
31. Trading Economics. South Africa Unemployment Rate. https://tradingeconomics.com/south-africa/unemployment-rate. (Accessed 07 May 2019).
32. 2018 International Bank for Reconstruction and Development / The World Bank: Overcoming Poverty And Inequality In South Africa: An Assessment Of Drivers, Constraints And Opportunities (2018)
http://documents.worldbank.org/curated/en/530481521735906534/pdf/124521-REV-OUO-South-Africa-Poverty-and-Inequality-Assessment-Report-2018-FINAL-WEB.pdf . (Accessed 08 May 2019).
33. Semenkovich K, Brown ME, Svrakic DM, Lustman PJ. Depression in type 2 diabetes mellitus: prevalence, impact, and treatment. Drugs. 2015; 75(6):577–87.
34. Yu M, Zhang X, Lu F, Fang L. (2015). Depression and risk for diabetes: A Meta-analysis. Canadian Journal of Diabetes. 2015; 39:266–272.
35. Davis EC, Rotheram-Borus MJ, Weichle TW, Rezai R, Tomlinson M. Patterns of Alcohol Abuse, Depression, and Intimate Partner Violence Among Township Mothers in South Africa Over 5 Years. AIDS and behavior, 2017; 21(Suppl 2), 174–182.
36. Rochat TJ, Tomlinson M, Newell ML, Stein A. Detection of antenatal depression in rural HIV-affected populations with short and ultrashort versions of the Edinburgh Postnatal Depression Scale (EPDS). Archives of women’s mental health, 2013; 16(5), 401–410.
37. Trangenstein PJ, Morojele NK, Lombard C, Jernigan DH, Parry C. Heavy drinking and contextual risk factors among adults in South Africa: findings from the International Alcohol Control study. Substance abuse treatment, prevention, and policy, 2018; 13(1), 43.