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

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

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

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

Preconception Health indicators

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

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

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

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

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

Health Insurance Status, Pregnancy Intention, 2002–2010—Texas PRAMS Prevalence (%) No health insurance before pregnancy 48% Unintended Pregnancy 46% Medicaid paid for delivery 59%

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.

Smoking Three Months Before Pregnancy 2002–2010—Texas PRAMS

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

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

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

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

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

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

Predictors of preterm birth

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

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

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

Medicaid Payment for Delivery 2004–2008—Texas PRAMS

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

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

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

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

Reported Stress by Race/Ethnicity

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

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

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)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Contact Information Rochelle Kingsley, MPH PRAMS Coordinator email: rochelle.kingsley@dshs.state.tx.us Noha H. Farag, MD, PhD EIS Officer email: iym0@cdc.gov