1. How PRAMS Can Inform Healthy Texas Babies Initiative
Rochelle Kingsley, MPH Office 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 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 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
Prevalence (%)
No health insurance before pregnancy
48%
Unintended Pregnancy
46%
Medicaid paid for delivery
59%

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

30. Stress and PTB Stress OR (95% CI) Financial 1.3 (1.1–1.5) Traumatic
1.3 (1.1–1.6)
Emotional
1.2 (0.9–1.4)
Partner-related
1.1 (0.9–1.4)
No difference by race/ethnicity

31. Selected Risk Factors for PTB
OR (95% CI)
Age ≥ 35 yrs
1.3 (1.03–1.7)
Unmarried
1.2 (1.03–1.4)
Medicaid paid for delivery
1.3 (1.1–1.5)
Obesity
1.4 (1.1–1.7)
Pregestational Diabetes
3.7 (2.4–5.7)
Preconception smoking
Infections
1.3 (1.1–1.6)
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
High Proportion Black OR P
Published Method
0.7
0.001
Referent: black women living in predominantly white neighborhoods

38. Effect of Revised Method on Conclusions
Proportion black in neighborhood and PTB among blacks
High Proportion Black OR P
Published Method
0.7
0.001
Revised Method
0.3
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
Low Education
Medium Education
Referent: women living in predominantly white neighborhood

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

45. Effect of Neighborhood Education on PTB Risk
Low Education
Medium 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 CDC/EFAB CDC/PRAMS Texas DSHS Betsy Cadwell
Diana Bensyl
Julie Magri
CDC/PRAMS
Indu Ahluwalia
Texas DSHS
Mark Canfield
Rebecca Martin
Chris Webb
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
Office of Surveillance, Epidemiology, and Laboratory Services
Scientific Education and Professional Development Program Office

51. Contact Information
Rochelle Kingsley, MPH PRAMS Coordinator Noha H. Farag, MD, PhD EIS Officer