title: Length of secondary schooling and risk of HIV infection in Botswana: evidence from a natural experiment.
abstract: BACKGROUND
  An estimated 2·1 million individuals are newly infected with HIV every year. Cross-sectional and longitudinal studies have reported conflicting evidence for the association between education and HIV risk, and no randomised trial has identified a causal effect for education on HIV incidence. We aimed to use a policy reform in secondary schooling in Botswana to identify the causal effect of length of schooling on new HIV infection.
  
  
  METHODS
  Data for HIV biomarkers and demographics were obtained from the nationally representative household 2004 and 2008 Botswana AIDS Impact Surveys (N=7018). In 1996, Botswana reformed the grade structure of secondary school, expanding access to grade ten and increasing educational attainment for affected cohorts. Using exposure to the policy reform as an instrumental variable, we used two-stage least squares to estimate the causal effect of years of schooling on the cumulative probability that an individual contracted HIV up to their age at the time of the survey. We also assessed the cost-effectiveness of secondary schooling as an HIV prevention intervention in comparison to other established interventions.
  
  
  RESULTS
  Each additional year of secondary schooling caused by the policy change led to an absolute reduction in the cumulative risk of HIV infection of 8·1 percentage points (p=0·008), relative to a baseline prevalence of 25·5% in the pre-reform 1980 birth cohort. Effects were particularly large in women (11·6 percentage points, p=0·046). Results were robust to a wide array of sensitivity analyses. Secondary school was cost effective as an HIV prevention intervention by standard metrics (cost per HIV infection averted was US$27 753).
  
  
  CONCLUSIONS
  Additional years of secondary schooling had a large protective effect against HIV risk in Botswana, particularly for women. Increasing progression through secondary school could be a cost-effective HIV prevention measure in HIV-endemic settings, in addition to yielding other societal benefits.
  
  
  BACKGROUND
  Takemi Program in International Health at the Harvard T.H.Chan School of Public Health, Belgian American Educational Foundation, Fernand Lazard Foundation, Boston University, National Institutes of Health.
authors.affiliation: Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
authors.forename: Jan-Walter
authors.initials: JW
authors.lastname: De Neve
authors.affiliation: Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Center for Population and Development Studies, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
authors.forename: Günther
authors.initials: G
authors.lastname: Fink
authors.affiliation: Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Center for Population and Development Studies, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
authors.forename: S V
authors.initials: SV
authors.lastname: Subramanian
authors.affiliation: Botswana-Harvard AIDS Institute Partnership, Gaborone, Botswana.
authors.forename: Sikhulile
authors.initials: S
authors.lastname: Moyo
authors.affiliation: Department of Global Health and Center for Global Health and Development, Boston University School of Public Health, Boston, MA, USA. Electronic address: jbor@bu.edu.
authors.forename: Jacob
authors.initials: J
authors.lastname: Bor
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000032:analysis; D001902:Botswana / Q000453:epidemiology; D003362:Cost-Benefit Analysis; D004522:Educational Status; D005260:Female; D015658:HIV Infections / Q000191:economics / Q000453:epidemiology / Q000517:prevention & control*; D006801:Humans; D016018:Least-Squares Analysis; D016014:Linear Models; D008297:Male; D065840:Protective Factors; D011640:Public Policy / Q000639:trends*; D012307:Risk Factors; D012574:Schools / Q000191:economics / Q000639:trends*; D017678:Sex Distribution; D013334:Students / Q000706:statistics & numerical data*; D011795:Surveys and Questionnaires; D055815:Young Adult
chemical_list: D015415:Biomarkers