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Is education a risk factor or social vaccine against HIV/AIDS in Sub-Saharan Africa? The effect of schooling across public health periods

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Abstract

Early in the 30-year HIV/AIDS pandemic in Sub-Saharan Africa, epidemiological studies identified formal education attainment as a risk factor: educated Sub-Saharan Africans had a higher risk of contracting HIV/AIDS than their less educated peers. Later demographic research reported that by the mid-1990s the education effect had reversed, and education began to function as a social vaccine. Recent counter-evidence finds a curvilinear pattern, with the association between educational attainment and HIV/AIDS infection changing from positive to negative across the education gradient. To reconcile these inconsistent conclusions, a hypothesis is developed and tested that education at early stages functioned as a risk factor and later functioned (and continues to function) as a social vaccine. We reason that this shift in the direction of the education effect was concurrent with changes in the public health environment in SSA that early on heightened material benefits from educational attainment but later heightened cognitive benefits from schooling. Using the 2003/2004 Demographic Health Surveys from four Sub-Saharan African countries (Cameroon, Ghana, Kenya and Tanzania), we tested this hypothesis (differential effects of schooling) using non-linear regression analysis (probit), identifying the different public health periods and controlling for confounding factors. The results support the hypothesis that the education effect shifted historically in the HIV/AIDS pandemic in SSA as we hypothesized.

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Fig. 1

Note: predicted probabilities are calculated by multiplying coefficients from estimation of Eq. (3) by the dummy variables for education attainment and mean values for all control variables included in the model. Darker lines indicate statistically significant relationships at 5%

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Notes

  1. These countries were selected since they were the first four SSA nations to include HIV/AIDS biomarker data in the Demographic Health Survey.

  2. We searched articles related to this issue in different electronic repositories such as EconPapers, EconLit, EBSCO, ERIC, JSTOR, National Bureau of Economic Research (NBER), Oxford University Press Journal, Pro-Quest, PsycINFO, Science Direct, UNESDOC (UNESCO’s documents and reports), and the World Bank Documents and Reports. Additionally, we searched Google Scholar since the search engine has the advantage of including both published and unpublished materials.

  3. This continuous variable aims to capture the educational dispersion given the low levels of educative development in Africa.

  4. To avoid bias on the answers, the questionnaire used the phrase “if ever” at the end of the question “How old were you when you first had sexual intercourse?” to somewhat, soften the phrasing for young teenagers, persons who have never been in a union or do not currently have a sexual partner; also, the question was asked directly to avoid the underreporting of sexual experience among young unmarried persons.

  5. The probit model estimated has as dependent variable being part of the HIV tested sample and as independent variables: age cohort, sex, years of schooling, wealth index, marital status, place of residency, whether has sexual partners other than wife/husband, whether sexually active, knowledge about HIV, whether circumcised, number of children, whether has no religion and fixed effects by regions.

  6. We centered the years of schooling and years of schooling squared terms on the overall mean for each country, because this change of scale reduces any multicollinearity resulting from the inclusion of both years of schooling and years of schooling squared in the same regression models.

  7. We use commonly used thresholds for statistically significant relationships in regression analysis and these are 1, 5 and 10% (Gordon 2015).

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Author information

Authors and Affiliations

  1. Group for the Analysis of Development, and Faculty of Accounting, Economics, and Finance, San Martin de Porres University, Lima, Peru

    Juan Leon

  2. Pennsylvania State University, PA, USA

    David P. Baker

  3. OECD, Paris, France

    Daniel Salinas

  4. Global Schools First Association for Childhood Education International (ACEI), Washington, DC, USA

    Adrienne Henck

  5. Population Research Institute, PA, USA

    David P. Baker

Authors
  1. Juan Leon
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  2. David P. Baker
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  3. Daniel Salinas
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  4. Adrienne Henck
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Correspondence to Juan Leon.

Appendices

Appendix 1: Probit regression coefficients of the control variables included in the final models for each country

See Tables 6 and 7.

Table 6 Probit regression coefficients for the model stated in Eq. (1) for each country
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Table 7 Probit regression coefficients for the final model estimated for each country
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Appendix 2: Hypothesis testing for each informational period

The following table shows the different hypothesis that were tested in order to check the relevance of the linear and quadratic terms (see Table 8).

Table 8 Hypothesis tested using the Wald test
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Leon, J., Baker, D.P., Salinas, D. et al. Is education a risk factor or social vaccine against HIV/AIDS in Sub-Saharan Africa? The effect of schooling across public health periods. J Pop Research 34, 347–372 (2017). https://doi.org/10.1007/s12546-017-9192-5

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