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The effects of HIV and systolic blood pressure on mortality risk in rural South Africa, 2010–2019: a data note

BMC Research Notes volume 16, Article number: 213 (2023) Cite this article

Abstract

Objectives

South Africa is experiencing both HIV and hypertension epidemics. Data were compiled for a study to identify effects of HIV and high systolic blood pressure on mortality risk among people aged 40-plus in a rural South African area experiencing high prevalence of both conditions. We aim to release the replication data set for this study.

Data description

The research data comes from the 2010-11 Ha Nakekela (We Care) population-based survey nested in the Agincourt Health and socio-Demographic Surveillance System (AHDSS) located in the northeast region of South Africa. An age-sex-stratified probability sample was drawn from the AHDSS. The public data set includes information on individual socioeconomic characteristics and measures of HIV status and blood pressure for participants aged 40-plus by 2019. The AHDSS, through its annual surveillance, provided mortality data for nine years subsequent to the survey. These data were converted to person-year observations and linked to the individual-level survey data using participants’ AHDSS census identifier. The data can be used to replicate Houle et al. (2022) — which used discrete-time event history models stratified by sex to assess differential mortality risks according to Ha Nakekela measures of HIV-infection, HIV-1 RNA viral load, and systolic blood pressure.

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Objective

South Africa is experiencing twin HIV and hypertension epidemics. As antiretroviral therapy has become widespread, resulting survival gains and ageing of people living with HIV have highlighted the importance of understanding emerging morbidity and mortality patterns among people living with HIV [1,2,3]. The South African burden of noncommunicable diseases (NCD) – particularly hypertension – is also high [4, 5]. A 2022 study examined associations between HIV and mortality, blood pressure and mortality, and joint associations between HIV and blood pressure and mortality over an eight-year period [6]. The data set we have released permits replication of the study findings and further investigation of effects of these epidemics, individually and in interaction, on mortality at ages 40-plus.

This data set was constructed as part of a larger project – HIV after 40 in rural South Africa: Aging in the context of an HIV epidemic (HIV40) – that more broadly examines life course and contextual variation in HIV risk and protective behaviors among middle-aged and older adults in a rural sub-Saharan African population [6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]. The website https://hivafter40.princeton.edu contains information on all aspects of the overall study including survey instruments (see Table 1:Data file 1), links to publications, etc. The study includes data from the AHDSS, the nested quantitative Ha Nakekela (“We Care”) Survey and the qualitative longitudinal Izindaba za Badala Study (‘matters that concern older people’), nested within the survey. Please see https://hivafter40.princeton.edu/data for more information.

Data description

Analyses in the paper Twin epidemics: The effects of HIV and systolic blood pressure on mortality risk in rural South Africa, 2010–2019 [6] can be replicated using the data set “HIVafter40_Twin_Epidemics_HIV_NCD.dta” deposited in the DataFirst repository, https://doi.org/10.25828/vr0p-ch08. The Table 1: Data file 2 file describes all available files.

Table 1 Overview of data files/data sets
Full size table

The data set was compiled from two sources.

  • The AHDSS is conducted by the MRC/WITS Agincourt Research Unit which is affiliated with both the University of the Witwatersrand and the South African Medical Research Council [21]. Its website provides information on research, publications, and data access for the extensive range of studies carried out in the research site: https://www.agincourt.co.za. Censuses that have been carried out annually since 1992 provide vital event and sociodemographic information on households and residents. Records for an individual are linked to provide a longitudinal history for each person. The censuses also serve as sampling frames for more detailed studies carried out in the Agincourt study site. For all respondents included in the HIV and NCD Survey (described next), sociodemographic information was extracted from the AHDSS.

  • The Ha Nakekela HIV and NCD Survey, carried out in 2010-11, is based on an age-sex stratified random sample of people aged 15-85-plus selected from the 2009 AHDSS Census. To date, a number of studies have utilized this survey [6, 8,9,10,11,12, 16, 17, 20, 22,23,24,25,26]. HIV and NCD biometric data (see [22, 24] for descriptions of the biometric data collection) and a behavioral survey on sexual behavior and other health practices were collected. Of the 7,662 people originally selected, 4,362, including 3,024 aged 40-plus, consented to be interviewed, tested for HIV and have blood pressure measured. Gómez-Olivé et al. [24] reported extremely high HIV prevalence in this population, and Clark et al. [22] showed a high burden of hypertension.

The HIV40 Study linked information from Ha Nakekela to AHDSS mortality records through mid-2019 (see Data file 3) using respondents’ AHDSS census identifier. For each of the 7,662 people in the Ha Nakekela original sample, we calculated the survey weight as the inverse of the probability that the person was selected for the sample. To adjust for survey nonresponse, we used a logistic regression model of factors from the 2009 census to predict the probability of participation and its inverse, the inverse probability sampling weight (IPSW). Final weights for participants are the product of the IPSW and the survey weight [6, 20]. For the replication data set (Data set 1), some variables were dropped and some variables recoded (see Data file 4 and Data file 5). All observations were converted to person-year observations – yielding one person-year for each age in which respondents were followed in the AHDSS census. Only person-years when the participant was aged 40-plus were retained. We then calculated discrete-time models of the risk of dying based on HIV and blood pressure characteristics, adjusted for 2009 Census covariates (see Data file 4; [6]).

Limitations

HIV status and systolic blood pressure were only measured at baseline. Subsequent follow-up surveys or linkage with other data such as clinic records would permit a more detailed understanding of how risk factors and changes in those risk factors are associated with mortality change over time. While mortality was high in this population, given the limited sample size there were too few deaths (n = 477) to include cause of death information.

Data Availability

The data described in this Data note can be accessed on the DataFirst repository under (https://doi.org/10.25828/vr0p-ch08) [27]. Please see Table 1 for details and links to the data. Access to Data set 1 requires registration with DataFirst and an application for access to a licensed data set. https://www.agincourt.co.za contains information on access to additional studies conducted in the AHDSS and a complete list of publications. https://hivafter40.princeton.edu contains copies of all study protocols and data instruments and a complete list of publications related to the HIVafter40 Study.

Abbreviations

AHDSS:

Agincourt Health and Demographic Surveillance System

NCD:

Noncommunicable disease

References

  1. Bor J, Herbst AJ, Newell M-L, Bärnighausen T. Increases in adult life expectancy in rural South Africa: valuing the scale-up of HIV treatment. Science. 2013;339:961–5.

    Article  CAS  PubMed  Google Scholar 

  2. Kabudula C, Houle B, Ohene-Kwofie D, et al. Mortality transition over a quarter century in rural South Africa: finding from population surveillance in Agincourt 1993–2018. Global Health Action. 2021;14:1990507.

    Article  PubMed  Google Scholar 

  3. Vollmer S, Harttgen K, Alfven T, Padayachy J, Ghys P, Bärnighausen T. The HIV epidemic in sub-saharan Africa is aging: evidence from the demographic and health surveys in sub-saharan Africa. AIDS Behav. 2016;21:101–13.

    Article  Google Scholar 

  4. Lloyd-Sherlock P, Beard J, Minicuci N, Ebrahim S, Chatterji S. Hypertension among older adults in low- and middle-income countries: prevalence, awareness and control. Int J Epidemiol. 2014;43:116–28.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Mayosi BM, Flisher AJ, Lalloo UG, Sitas F, Tollman SM, Bradshaw D. The burden of non-communicable diseases in South Africa. Lancet. 2009;374:934–47.

    Article  PubMed  Google Scholar 

  6. Houle B, Kabudula C, Gomez-Olive FX, et al. Twin epidemics: the effects of HIV and systolic blood pressure on mortality risk in rural South Africa, 2010–2019. BMC Public Health. 2022;22:387.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Angotti N, Mojola SA, Schatz E, Williams JR, Gómez-Olivé FX. Taking care’ in the age of AIDS: older rural South Africans’ strategies for surviving the HIV epidemic. Cult Health Sex. 2018;20:262–75.

    Article  PubMed  Google Scholar 

  8. Gómez-Olivé FX, Houle B, Rosenberg M, et al. HIV incidence among older adults in a rural south african setting: 2010–2015. J Acquir Immune Defic Syndr. 2020;85:18–22.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Houle B, Mojola SA, Angotti N, et al. Sexual behavior and HIV risk across the life course in rural South Africa: trends and comparisons. AIDS Care. 2018;30:1435–43.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Houle B, Yu S-T, Angotti N, et al. Clusters of HIV risk and protective sexual behaviors in Agincourt, rural South Africa: findings from the ha Nakekela population-based study of ages 15 and older. Arch Sex Behav. 2020;49:2057–68.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Houle B, Gaziano T, Angotti N, et al. Hypertension incidence among middle-aged and older adults: findings from a 5-year prospective study in rural South Africa, 2010–2015. BMJ Open. 2021;11:e049621.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Ice E, Mojola SA, Angotti N, Houle B. Making sense of troubled livelihoods: gendered expectations and poor health narratives in rural South Africa. Gend Soc. 2022;36:753–63.

    Article  Google Scholar 

  13. Mojola SA, Angotti N. ‘Sometimes it is not about men’: gendered and generational discourses of caregiving HIV transmission in a rural south african setting. Glob Public Health. 20191–13.

  14. Mojola SA, Angotti N, Denardo D, Schatz E, Xavier Gómez Olivé F. The end of AIDS? HIV and the new landscape of illness in rural South Africa. Glob Public Health. 2022;17:13–25.

    Article  PubMed  Google Scholar 

  15. Mojola SA, Williams J, Angotti N, Gómez-Olivé FX. HIV after 40 in rural South Africa: a life course approach to HIV vulnerability among middle aged and older adults. Soc Sci Med. 2015;143:204–12.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Mojola S, Ice E, Schatz E, Angotti N, Houle B, Gómez-Olivé FX. The meaning of health in rural South Africa: gender, the life course and the socio-epidemiological context. Popul Dev Rev. 2022;48:1061–95.

    Article  Google Scholar 

  17. Mojola SA, Angotti N, Schatz E, Houle B. A nowadays Disease: HIV/AIDS and Social Change in a rural south African Community. Am J Sociol. 2021;127:950–1000.

    Article  Google Scholar 

  18. Schatz E, Knight L, Belli RF, Mojola SA. Assessing the feasibility of a life history calendar to measure HIV risk and health in older South Africans. PLoS ONE. 2020;15:e0226024.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Schatz E, David I, Angotti N, Gómez-Olivé FX, Mojola SA. From secret to sensitive issue: shifting Ideas about HIV Disclosure among Middle-Aged and older Rural South Africans in the era of antiretroviral treatment. J Aging Health. 2021;34:14–24.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Schatz E, Houle B, Mojola SA, Angotti N, Williams J. How to `live a good life’: aging and HIV testing in rural South Africa. J Aging Health. 2019;31:709–32.

    Article  PubMed  Google Scholar 

  21. Kahn K, Collinson MA, Gomez-Olive FX, et al. Profile: Agincourt Health and Socio-demographic Surveillance System. Int J Epidemiol. 2012;41:988–1001.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Clark SJ, Gómez-Olivé FX, Houle B, et al. Cardiometabolic disease risk and HIV status in rural South Africa: establishing a baseline. BMC Public Health. 2015;15:372.

    Article  Google Scholar 

  23. Clark SJ, Houle B. Validation, replication, and sensitivity testing of Heckman-type selection models to adjust estimates of HIV prevalence. PLoS ONE. 2014;9:e112563.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Gómez-Olivé FX, Angotti N, Houle B, et al. Prevalence of HIV among those 15 and older in rural South Africa. AIDS Care. 2013;25:1122–8.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Houle B, Angotti N, Clark SJ, et al. Let’s talk about sex, maybe: interviewers, respondents, and sexual behavior reporting in rural South Africa. Field Methods. 2016;28:112–32.

    Article  PubMed  Google Scholar 

  26. Houle B, Angotti N, Gómez-Olivé FX, Clark SJ. Fieldworker effects on substance use reporting in rural South Africa. Int J Alcohol Drug Res. 2018;7:29–39.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Houle B, Kabudula C, Gomez-Olive FX et al. Twin Epidemics: The effects of HIV and systolic blood pressure on mortality risk in rural South Africa 2010–2019. Cape Town: DataFirst Data Repository; 2022:https://doi.org/10.25828/vr0p

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Acknowledgements

Thanks go, as always, to the people resident in the Agincourt Health and Demographic Surveillance Site and the staff of the Agincourt Health and Socio-Demographic Surveillance System.

Funding

We are grateful for funding support from: the US National Institute on Aging—R01 AG049634 HIV after 40 in rural South Africa: Aging in the Context of an HIV Epidemic (PI Sanyu Mojola); the National Institute on Aging—R24 AG032112-05 Partnership for Social Science AIDS Research in South Africa’s Era of ART Rollout (PI Jane Menken); the University of Colorado, Innovative Seed Grant HIV after 40 in rural South Africa (PI Sanyu Mojola); the Eunice Kennedy Shriver National Institute of Child Health and Human Development—K01 HD057246 (PI Samuel Clark); and the William and Flora Hewlett Foundation 2009‐4060 African Population Research and Training Program (PI Jane Menken). The MRC/Wits Rural Public Health and Health Transitions Research Unit and Agincourt Health and Socio‐Demographic Surveillance System, a node of the South African Population Research Infrastructure Network (SAPRIN), is supported by the Department of Science and Innovation, the University of the Witwatersrand, and the Medical Research Council, South Africa, and previously the Wellcome Trust, UK (Grants 058893/Z/99/A; 069683/Z/02/Z; 085477/Z/08/Z; 085477/B/08/Z). This work has also benefited from research, administrative, and computing support from the Eunice Kennedy Shriver National Institute of Child Health and Human Development–funded University of Colorado Population Center (R24HD066613, P2C HD066613).

Author information

Authors and Affiliations

  1. School of Demography, The Australian National University, Canberra, Australia

    Brian Houle

  2. MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), Faculty of Health Sciences, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa

    Brian Houle, Samuel J Clark, Chodziwadziwa W Kabudula, F Xavier Gómez-Olivé, Nicole Angotti, Enid Schatz & Sanyu A Mojola

  3. Department of Sociology, The Ohio State University, Columbus, OH, USA

    Samuel J Clark

  4. Department of Sociology, American University, Washington, D.C, USA

    Nicole Angotti

  5. Department of Public Health, University of Missouri, Columbia, MO, USA

    Enid Schatz

  6. Leverhulme Centre for Demographic Science, Nuffield Department of Population Health, and Nuffield College, University of Oxford, Oxford, UK

    Andrea M Tilstra

  7. Department of Sociology, School of Public and International Affairs, and Office of Population Research, Princeton University, Princeton, NJ, USA

    Sanyu A Mojola

  8. Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO, USA

    Jane Menken

Authors
  1. Brian Houle
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  2. Samuel J Clark
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  3. Chodziwadziwa W Kabudula
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  4. F Xavier Gómez-Olivé
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Contributions

SC, NA, ES, SM, and JM designed the overall project for the survey data. SC, CK, FXG, NA, and JM were involved in the data collection. BH and JM drafted the article. CK curated the mortality data. AT and JM developed the data scripts. All authors contributed to revision of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Brian Houle.

Ethics declarations

Ethics approval and consent to participate

The project received IRB approvals from the University of Colorado Boulder, the University of Michigan, Princeton University, the University of Witwatersrand Human Research Ethics Committee, and the Department of Health, Mpumalanga Provincial Government, South Africa.

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Not applicable.

Competing interests

The authors declare that they do not have competing interests.

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Houle, B., Clark, S.J., Kabudula, C.W. et al. The effects of HIV and systolic blood pressure on mortality risk in rural South Africa, 2010–2019: a data note. BMC Res Notes 16, 213 (2023). https://doi.org/10.1186/s13104-023-06478-w

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