+ Preconception Health and Racial/Ethnic Disparities in Birth Weight: A National Study Kelly L. Strutz, MPH Liana J. Richardson, PhD, MPH Jon M. Hussey, PhD, MPH University of North Carolina at Chapel Hill 3 rd National Summit on Preconception Health and Health Care June 13, 2011

+ Introduction: Evidence regarding the relationship between preconception health and birth outcomes is limited. Even less is known about the contribution of preconception health to racial/ethnic disparities in birth outcomes. This represents a critical gap in the knowledge base needed to inform MCH policy and practice.

+ Study Questions: How does preconception health impact birth weight? Does preconception health contribute to racial/ethnic disparities in birth weight? Does preconception health impact all racial/ethnic groups equally?

+ Data and Analytic Sample: National Longitudinal Study of Adolescent Health (Add Health), a nationally representative probability sample of US adolescents in the school year Respondent interviews Wave I ( ): Adolescents in 7 th -12 th grades Wave III ( ): Young Adults aged Wave IV ( ): Adults aged Analytic sample 3046 singleton births conceived after Wave III and reported at Wave IV to non-Hispanic White, non-Hispanic Black, Mexican- Origin Latina, and Asian/Pacific Islander mothers

+ Measures and Analysis: Infant birth weight Reported by respondent Adjusted for preterm birth Preconception Health Indicators Cigarette smoking, alcohol consumption, physical activity, and obesity status Measured prospectively at Waves I and III

+ Measures and Analysis: Confounders Respondent’s age and parity at birth, nativity, and early life SES Mediators Respondent’s prenatal smoking and alcohol consumption, and trimester began prenatal care Statistical Analysis Univariate and bivariate analyses Linear regression Accounted for complex survey design

+ Results: Mean Birth Weight (g)

+ Results: Any Smoking

+ Results: Heavy Drinking

+ Results: Overweight/Obese

+ Results: Physically Active

+ Results: Contribution to Disparities Model 1: Race/Ethnicity Model 2: R/E + Smoking Model 3: R/E + Smoking + Prenatal Latina-- Black Asian Any Smoking Wave I Only Wave III Only-- Both Waves

+ Results: Contribution to Disparities Model 1: Race/Ethnicity Model 3: R/E + Obesity Model 4: R/E + Obesity + Prenatal Latina-- Black Asian-- Overwt/Obese Wave I Only-- Wave III Only Both Waves

+ Results: Contribution to Disparities Model 1: Race/Ethnicity Model 6: R/E + Activity Model 7: R/E + Activity + Prenatal Latina-- Black Asian Physically Active Wave I Only-- Wave III Only Both Waves

+ Effects by Racial/Ethnic Group: Racial/Ethnic GroupEffects White Overweight/Obese Wave III Only ↑ Physically Active Either or Both Waves ↑ Black Any Smoking Wave I Only ↓ Overweight/Obese Both Waves ↑ Latina Heavy Drinking Both Waves ↓ Asian Any Smoking Wave III Only ↓ Overweight/Obese Wave III Only ↑ Heavy Drinking Wave I Only ↓

+ Discussion: Findings Overall associations between birth weight and preconception health indicators Varied by racial/ethnic group Effects of adjusting for preconception factors on Black/White and Asian/White disparities in birth weight

+ Discussion: Strengths Prospective measures of preconception health and subsequent birth weight Diverse national cohort Limitations Adequacy of available data and measures Public Health Significance Utility of applying a life course perspective Further research is needed to identify modifiable preconception factors

+ Acknowledgments Alexis Dennis and Chirayath Suchindran This work was supported by the Eunice Kennedy Shriver National Institute of Child Health & Human Development (grant numbers R01-HD057073, R01-HD058535, and T32-HD ) This research used data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website ( No direct support was received from grant P01-HD31921 for this analysis.

+ Contact Kelly Strutz University of North Carolina at Chapel Hill Carolina Population Center CB# 8120, University Square 123 West Franklin Street Chapel Hill, NC