Reduced Disparities in Birth Rates Among Teens Aged 15–19 Years — United States, 2006–2007 and 2013–2014

Is Sexual Abuse a Unique Predictor of Sexual Risk Behaviors, Pregnancy, and Motherhood in Adolescence?

“…Moreover, children born to adolescent mothers are at risk for developmental and cognitive deficiencies (Jahromi, Umaña-Taylor, Updegraff, & Zeiders, 2016) underscoring the potent intergenerational impact that young motherhood can confer on offspring. Although adolescent motherhood rates have decreased in recent years in the United States (Martin, Hamilton, Osterman, Driscoll, & Mathews, 2017), primary prevention remains a public health priority due to the fact that U.S. rates are substantially higher than in other Western industrialized nations (Sedgh, Finer, Bankole, Eilers, & Singh, 2015) and that sociodemographic disparities persist (Romero et al, 2016). Increasing the precision of primary prevention efforts involves identifying at-risk groups that would benefit from targeted intervention.…”

Effects of Maternal Age and Age-Specific Preterm Birth Rates on Overall Preterm Birth Rates — United States, 2007 and 2014

“…Reductions in births to teens and preterm birth rates are two recent public health successes in the United States (1,2). From 2007 to 2014, the birth rate for females aged 15-19 years declined 42%, from 41.5 to 24.2 per 1,000 females.…”

Hot spots, cluster detection and spatial outlier analysis of teen birth rates in the U.S., 2003–2012

“…Even after accounting for racial/ethnic composition of the states, this prior report found that teen birth rates were highest in the southern states and lowest in the North Eastern states (Ventura et al, 2014), suggesting that there are other drivers of geographic patterns beyond racial/ethnic composition, such as area-level socioeconomic factors and other social determinants of health and health disparities. (Romero et al, 2016) The hierarchical Bayesian models employed in this analysis to predict TBRs included several county-level factors related to sociodemographic characteristics, socioeconomic factors, and racial/ethnic composition. (Khan et al, 2018) These factors were significantly related to TBRs at the county-level, adding to the body of literature describing the importance of social determinants of health in relation to teen childbearing and related disparities (Penman-Aguilar et al, 2013; Romero et al, 2016).…”

“…(Romero et al, 2016) The hierarchical Bayesian models employed in this analysis to predict TBRs included several county-level factors related to sociodemographic characteristics, socioeconomic factors, and racial/ethnic composition. (Khan et al, 2018) These factors were significantly related to TBRs at the county-level, adding to the body of literature describing the importance of social determinants of health in relation to teen childbearing and related disparities (Penman-Aguilar et al, 2013; Romero et al, 2016). …”

“…Examinations of teen birth rates at the county level have relied on direct estimates aggregated over several years, and are limited by the inability to show county-level estimates based on fewer than 20 births in the numerator due to concerns about the reliability and stability of the direct estimates. (Romero et al, 2016) This study is the first study to describe county-level variation in teen birth rates over the entire U.S., by using estimates derived from Hierarchical Bayesian models and applying spatial statistical tools to identify hot spots, cold spots, and spatial outliers in teen birth rates.…”