Patterns of Age Mixing and Sexually Transmitted Infections
- Slides: 26
Patterns of Age Mixing and Sexually Transmitted Infections Julie Kraut-Becher University of Pennsylvania Sevgi O. Aral Division of STD Prevention, CDC
Age Mixing n Population-level determinant – Spread of HIV n Africa n Gay n men Individual-level risk factor – Risky behavior n Unprotected vaginal sex n Lack of consistent condom use
Age Mixing n Increase STI incidence – Directly n Exposure to partner pools with higher STI prevalence – Indirectly n Partnerships marked by power imbalance – Practice of safer sex is difficult
Objectives n Describe age mixing patterns – Nationally representative sample of reproductive age, sexually-active U. S. women n Relate these patterns to self-reported STI history – STI diagnosis or testing or treatment
Methods n Data – 1995 National Survey of Family Growth (NSFG) n Sample – N = 9, 272 sexually-active women 15 -44 years of age n Valid birth date information for themselves and their partner
Methods n Age Difference – Computed for current or most recent partnership – Age difference < 0 n Younger male partner – Age difference > 0 n Older male partner
Methods n Assess extent of age mixing n Describe patterns of age mixing n Examine association between age mixing and STI test, treatment, and diagnosis n Nationally representative sample – Sociodemographic and socioeconomic characteristics – STI history – Sample weights
Results
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Results n 15 -17 year-old females
Results n 18 -19 year-old females
Results n 20 -24 year-old females
Results n 25 -29 year-old females
Results n 30 -34 year-old females
Results n 35 -39 year-old females
Results n 40 -44 year-old females
Limitations n Self reports of STI information n STI diagnoses not temporally defined – Cannot determine the causal nature of association between partnership characteristics and STI
Conclusions n Large extent of age mixing n Age mixing varies over the life course n The effect of age mixing on STI varies over the life course
Conclusions n Future research – – – n Biomarkers vs. self-reports Specific infections Race/ethnicity specific Program – Ask about age mixing with current sex partners n n Screening parameter Target interventions
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