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Mon, Jan 22, 2018, noon: Narayan Sastry

Pregnant teen

Race-ethnic variation in unintended pregnancy

2/23/2015 feature story

Jennifer Barber and Yasamin Kusunoki look at two factors - reproductive knowledge and prevention motivation - in their examination of race/ethnic disparities in unintended pregnancy.

More Information.

Jennifer S. Barber

Project Information:

Distal Determinants of Race-Ethnic Variation in Unintended Fertility

Unintended fertility in the United States has remained stable since 1994, at half of all pregnancies and a third of all births, with young adults having the highest rates. Given the national public health focus on reducing unintended pregnancy since the 1980s, these continued high levels are a persistent empirical puzzle. An equally persistent concern is that unintended fertility is substantially higher among minorities than non-Hispanic whites, which may exacerbate associated health disparities. Although the proximate determinants of unintended fertility are clear (failure to use effective contraception and carrying unintended pregnancies to term), the underlying causes of these behaviors, and of race/ethnic/nativity differences, are not well understood. This project proposes two key distal determinants – reproductive knowledge and fertility motivation – that may explain unintended fertility and race/ethnic/nativity differences. We use three complementary datasets: the Relationship Dynamics and Social Life study (RDSL), the National Longitudinal Study of Adolescent Health (Add Health), and the 2009 National Survey of Reproductive and Contraceptive Knowledge (Fog Zone). Combining these data resources enables us to move beyond prior descriptive work to identify precursors of risky sexual behavior and unintended fertility. We hypothesize that minorities have lower reproductive knowledge and motivation to prevent pregnancy, that disparities widen over time, and that these distal determinants are differentially associated with outcomes across groups. Our goal is to create reliable and valid measures to identify those most at risk for unintended fertility, which can then be applied to future research and interventions.

Jennifer S. Barber, Yasamin Kusunoki

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