Early age of first sex: a risk factor for HIV infection among women in Zimbabwe

AIDS. 2004 Jul 2;18(10):1435-42. doi: 10.1097/01.aids.0000131338.61042.b8.


Objective: To explore the relationship between early age of coital debut (15 years of age or younger) and risk for HIV infection among sexually active urbanized Zimbabwean women.

Design: Cross-sectional analysis of screening data from a cohort study.

Methods: Sexually active women aged 18-35 years were recruited from public sector family planning clinics in and around Harare, Zimbabwe between November 1999 and September 2002. They received a brief behavioral interview and HIV testing. Of the 4675 women screened, 4393 (94%) had complete data on sexual behaviors and HIV serostatus, and were included in this analysis.

Results: HIV prevalence in this sample was 40.1%. The median age of coital debut was 18 years and 11.8% of women reporting having experienced coital debut at age 15 or younger. Women with early coital debut had a significantly higher risk profile, including multiple lifetime partners and not completing high school. In binary generalized linear regression models HIV risk was increased for women reporting early age of coital debut (relative hazard, 1.30; 95% confidence interval, 1.13-1.50), controlling for duration of sexual activity and current age; this effect was attenuated somewhat after controlling for other factors such as number of sexual partners.

Conclusions: Our results show that early coital debut is a significant predictor of prevalent HIV infection independent of other identified factors in this population. HIV prevention strategies should include delaying the age of first coitus and should address the barriers that may prevent young women from so doing.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Coitus*
  • Cross-Sectional Studies
  • Female
  • HIV Infections / epidemiology
  • HIV Infections / etiology*
  • Humans
  • Logistic Models
  • Multivariate Analysis
  • Prevalence
  • Risk Factors
  • Zimbabwe / epidemiology