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Rochelle Kingsley, MPH Office of Program Decision Support Texas Department of State Health Services Noha H. Farag, MD, PhD CDC EIS Field Assignments Branch.

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Presentation on theme: "Rochelle Kingsley, MPH Office of Program Decision Support Texas Department of State Health Services Noha H. Farag, MD, PhD CDC EIS Field Assignments Branch."— Presentation transcript:

1 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 How PRAMS Can Inform Healthy Texas Babies Initiative 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, 2002–2010Texas PRAMS Prevalence (%) No health insurance before pregnancy 48% Unintended Pregnancy46% Medicaid paid for delivery59%

12 No Daily Multivitamin * 2002–2010Texas 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 2002–2010Texas PRAMS

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

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

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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 2004–2008Texas PRAMS

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

26 Race/Ethnic Disparity in PTB 2004–2008Texas PRAMS < 34 weeks gestation34–36 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 StressOR (95% CI) Financial1.3 (1.1–1.5) Traumatic1.3 (1.1–1.6) Emotional1.2 (0.9–1.4) Partner-related1.1 (0.9–1.4) No difference by race/ethnicity

31 Selected Risk Factors for PTB OR (95% CI) Age 35 yrs1.3 (1.03–1.7) Unmarried1.2 (1.03–1.4) Medicaid paid for delivery1.3 (1.1–1.5) Obesity1.4 (1.1–1.7) Pregestational Diabetes3.7 (2.4–5.7) Preconception smoking1.4 (1.1–1.7) Infections1.3 (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 High Proportion Black ORP Published Method0.70.001 Proportion black in neighborhood and PTB among blacks Referent: black women living in predominantly white neighborhoods

38 Effect of Revised Method on Conclusions High Proportion Black ORP Published Method0.70.001 Revised Method0.70.3 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 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 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 CDC/EFAB Betsy Cadwell Diana Bensyl Julie Magri CDC/PRAMS Indu Ahluwalia Texas DSHS Mark Canfield Rebecca Martin Chris Webb

51 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


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