How PRAMS Can Inform Healthy Texas Babies Initiative

1. How PRAMS Can Inform Healthy Texas Babies Initiative Rochelle Kingsley, MPHOffice of Program Decision Support Texas Department of State Health Services Noha H. Farag, MD, PhD CDC EIS Field Assignments Branch Birth Defects Surveillance and Epidemiology, DSHS Office of Surveillance, Epidemiology, and Laboratory Services Scientific Education and Professional Development Program Office

2. Healthy Texas Babies (HTB) • Initiative to decrease infant mortality • Goals: • Use evidence-based interventions • Provide local partnerships and coalitions with major roles in shaping programs in their communities • Decrease preterm birth rate by 8% over two years • Save $7.2 million in Medicaid costs over two years

3. Pregnancy Risk Assessment Monitoring System (PRAMS) • CDC and DSHS-funded, state-based complex survey • Monthly stratified random sample of moms pulled from birth certificate • Stratified on birth weight and race/ethnicity • Moms surveyed 2-3 months after delivery • Maternal behaviors and experiences before, during, and after pregnancy • Population estimates representative of all women in Texas who recently delivered a live birth

4. Significance of Texas PRAMS Data • Source of detailed state-level information on risk factors relevant to birth outcomes • Behavioral factors: smoking, alcohol use • Psychosocial factors: stress, social support • Medical conditions: diabetes, hypertension, pregnancy complications • Not only during pregnancy, but also preconception and postpartum • 50% of Texas births are to Hispanics

5. Preconception Health indicators

6. Early Prenatal Care is Too Late • First few weeks after conception are the most critical for fetal development • Many risk factors that can affect fetal development have greatest effect 17-56 days of pregnancy • Most women not aware they are pregnant until after this period • Important to deliver interventions before pregnancy to reduce risks of adverse outcomes: • Preterm delivery, low birthweight, birth defects

7. Preconception Health and Health Care • Preconception Health refers to the health of women during their reproductive years • Important for men too • Everyone benefits, regardless of pregnancy intention • Preconception Care refers to interventions designed to lower preconception risks that contribute to adverse maternal and infant outcomes

8. PRAMS Data Analysis • Birth year 2002-2010 combined • 15,386 respondents (weighted estimate: 3,292,432) • Aged 13-47 years

9. Preconception Health Indicators • Health Behaviors • Smoking • Alcohol consumption • Binge drinking • Physical Activity • Multivitamin use • Health Conditions • Weight status (underweight, overweight, obese) • Diabetes • Hypertension • Anemia

10. Indicators Broken Down By: • Health insurance before pregnancy • Pregnancy intention • Medicaid paid for delivery (proxy for socioeconomic status) • Race/ethnicity • Age • Education

11. Health Insurance Status, Pregnancy Intention, 2002–2010—Texas PRAMS

12. No Daily Multivitamin*2002–2010—Texas PRAMS *During the month before pregnancy did not take a multivitamin at all, or took multivitamins but not every day of the week.

13. Smoking Three Months Before Pregnancy 2002–2010—Texas PRAMS

14. Prepregnancy Obesity*2002–2010—Texas PRAMS BMI of 30 or higher.

15. Indicators by Pregnancy Intention and Insurance, 2002–2010—Texas PRAMS

16. Indicators by Pregnancy Intention and Insurance, 2002–2010—Texas PRAMS

17. Indicators by Pregnancy Intention and Insurance, 2002–2010—Texas PRAMS

18. Implications • Significant racial/ethnic disparities among all indicators • Even among those with intended pregnancy and health care coverage, rates could use improvement • Missing link?

19. Take-Home Message • Preconception health of women in Texas is less than optimal • To accomplish HTB goal of reducing infant mortality by 8%, analysis of gaps in preconception care is important • This is just a small snapshot of the wealth of data available from PRAMS

20. Predictors of preterm birth

21. Preterm Birth (PTB) in Texas PTB: deliveries at < 37 weeks gestation

22. National Facts • PTB leading cause of neonatal mortality • Disparities in PTB persistent public health problem • Low education and poverty associated with higher PTB risk • Blacks have ≥ 50% higher PTB risk

23. How Are We Doing in Texas? • PRAMS 2004–2008 • Socioeconomic disparity • Race/ethnic disparity

24. Medicaid Payment for Delivery 2004–2008—Texas PRAMS

25. Race/Ethnic Disparity in PTB 2004–2008—Texas PRAMS < 34 weeks gestation

26. Race/Ethnic Disparity in PTB 2004–2008—Texas PRAMS < 34 weeks gestation 34–36 weeks gestation

27. Reasons for Race/Ethnic Disparity Theories • Early-life programming • Weathering Hypothesis • Racism • Stress Facts • Stress associated with increased PTB risk • Stress higher in blacks

28. Original Research Question • Does stress explain the observed race/ethnic disparity in PTB in Texas?

29. Reported Stress by Race/Ethnicity Stress

30. Stress and PTB • No difference by race/ethnicity

31. Selected Risk Factors for PTB • No difference by race/ethnicity

32. Beyond Traditional Risk Factors • Look further upstream at causal pathway • Consider contextual factors (neighborhood characteristics) • Proportion of residents in census tract: • Poverty (income < 150% of federal poverty level) • Race/ethnic composition (proportion black residents)

33. Revised Research Question • Do neighborhood characteristics explain race/ethnic disparity in PTB in Texas?

34. Data Source for Neighborhood Characteristics • American Community Survey • Component of census • Provides updated population estimates • Neighborhood factors: • Proportion less than high school education • Proportion non-Hispanic black

35. Statistical Considerations • PRAMS data not random sample • Need survey procedures • SUDAAN or SAS survey procedures • Neighborhood data • Individuals in same census tract have more in common with one another than they do with those in others census tracts • Account for correlation using multilevel models • Combining neighborhood data with complex survey data problematic • Published methods do not account for both neighborhood characteristics and survey design

36. What Texas Did • Modified multilevel methods to account for design factors in PRAMS • Existing multilevel models accounted for neighborhood effects, NOT design factors • Accurately estimate associations between neighborhood characteristics, individual-level risk factors, and PTB

37. Effect of Revised Method on Conclusions Proportion black in neighborhood and PTB among blacks Referent: black women living in predominantly white neighborhoods

38. Effect of Revised Method on Conclusions Proportion black in neighborhood and PTB among blacks Referent: black women living in predominantly white neighborhoods

39. Effect of Proportion Black in Neighborhood on PTB Risk High Proportion Black Medium Proportion Black Referent: women living in predominantly white neighborhood

40. Effect of Proportion Black in Neighborhood on PTB Risk High Proportion Black Medium Proportion Black Referent: women living in predominantly white neighborhood

41. Effect of Proportion Black in Neighborhood on PTB Risk High Proportion Black Medium Proportion Black Referent: women living in predominantly white neighborhood

42. Effect of Proportion Black in Neighborhood on PTB Risk High Proportion Black Medium Proportion Black Referent: women living in predominantly white neighborhood

43. Effect of Neighborhood Education on PTB Risk Medium Education Low Education Referent: women living in predominantly white neighborhood

44. Effect of Neighborhood Education on PTB Risk Medium Education Low Education Referent: women living in predominantly white neighborhood

45. Effect of Neighborhood Education on PTB Risk Medium Education Low Education Referent: women living in predominantly white neighborhood

46. Summary • Neighborhood factors did not explain excess PTB risk among black women • However, they did have an effect on risk in Hispanic women • Non-response among black women problematic

47. Public Health Significance • First study of neighborhood effects among Hispanic women • Previous studies compared black and white women • In Texas, Hispanic women represented 50% of weighted sample • In 2010, three published PRAMS studies used analytic methods inappropriately • Revising statistical methods ensured public health policies based on sound statistical evidence

48. Future Directions • Develop neighborhood deprivation index • Target communities and individuals within them with highest PTB risk • Risk factors for early versus late PTB

49. PRAMS Can Inform Healthy Texas Babies • Funds for community interventions can target highest risk communities • Evaluate effectiveness of interventions • On outcome, PTB • On risk factors, preconception indicators • Reducing PTB is not equal to reducing disparity

50. Acknowledgments Office of Surveillance, Epidemiology, and Laboratory Services Scientific Education and Professional Development Program Office The findings and conclusions in this report are those of the authors and do not represent the official position of the Centers for Disease Control and Prevention