1. Presenting Statistical Aspects of Your Research Analysis of Factors Associated with Pre-term Births in North Carolina

2. 2012 NC Birth Data Factors Related to Preterm Births Goal: Identify factors related to preterm birth (PTB) by using cross-sectional data reported on n = 118,391 birth certificates for live births in North Carolina in 2012. Of primary interest is the potential relationship between maternal smoking and prenatal care with PTB. Other demographic factors such as mother’s race, age, and education level as well physiological factors such as hypertension, previous birth history, and diabetes will also be considered.

3. Mother’s Race – White, Black, Hispanic, American Indian, Other Mother’s Education – mother’s education level (ordinal) Mother’s Age – mother’s age (years) Marital Status – mother’s marital status (1 = married, 2 = single) No Care – mother received no pre-natal care (Y or N) Cig During – mother smoked during pregnancy (Y or N) GDIAB – gestational diabetes (Y or N) GHYPE – gestational hypertension (Y or N) PPB – previous pre-term birth (Y or N) Over+ - mother is overweight or obese prior to pregnancy North Carolina Vital Statistics -- Births 2012 (1/23/2012) http://hdl.handle.net/1902.29/11614 UNF:5:uHpa3Rf5Sx9jFVCGIXkFQg== Odum Institute for Research in Social Science [Distributor] V1 [Version] 2012 NC Birth Data Factors Considered

4. Demographics You can summarize mother demographics for the n = 118,391 live births in North Carolina in 2012. Here I used the Analyze > Tabulate command in JMP to create a table of summary statistics. For putting together a paper or presentation however, copying and pasting output from JMP is unsatisfactory. Creating a table in Word and/or PowerPoint would make for a much cleaner presentation!

5. Demographics – Preterm vs. Full-term As pre-term birth is the outcome of interest demographic comparisons of these two populations can be a nice addition. You can assess statistical significance by using appropriate bivariate tests (here all p-values <.0001).

6. County Level Maps You can use the maps you created to examine potential county differences on theses factors and the PTB rates. These maps could be used in your descriptive analysis or to support your findings & recommendations in the results/discussion sections. Discussions of counties that stand out as you did for homework might add to your conclusions. Some of you did a particularly fine job of this! Map of mean number of prenatal visits by county.

7. Pre-term Birth Rates by County

9. Smoking During Pregnancy by County

10. Crude Odds Ratios and Relative Risks Some papers will report both Crude OR’s and Adjusted OR’s. The adjusted OR’s come from the multiple logistic regression model that all of you are fitting as part of your analysis. The crude OR’s will come by considering each factor marginally (e.g. preterm vs. previous history of premature labor). I am not necessarily advocating this for your analysis, but it is something to consider. Also, as these data are NOT from a case-control study, you can look at relative risks (RR) instead of OR’s to quantify effects marginally. Other epidemiological measures can be examined as well. For example the attributable risk or risk difference, the population attributable risk (PAR), or population attributable risk fraction (PAF).

11. Example: Crude OR’s and RR’s Factor 95% Confidence RR Interval Crude 95% Confidence OR Interval Marital status - single 1.27 (1.22, 1.31) 1.30 (1.25, 1.35) No prenatal care 3.19 (2.98, 3.42) 4.16 (3.77, 4.59) Smoking during pregnancy 1.27 (1.21, 1.34) 1.31 (1.24, 1.39) Gestational diabetes 1.35 (1.27, 1.44) 1.40 (1.30, 1.51) Gestational hypertension 2.73 (2.60, 2.86) 3.31 (3.11, 3.52) Previous history of premature birth 2.90 (2.71, 3.10) 3.63 (3.32, 3.98) Overweight or obese prior to pregnancy 1.11 (1.08, 1.15) 1.13 (1.08, 1.17) Table # – Crude RR’s and OR’s for pre-term birth for factors considered. p <.0001 for all factors

12. Measures of Population Impact

13. PAR & PAF : Smoking and Preterm Birth (NC Births - 2012)

14. PAR & PAF : Prenatal Care and Preterm Birth (NC Births - 2012)

15. Multiple Logistic Regression When fitting a multiple logistic regression model to study potentially relevant factors simultaneously, all effects are adjusted for the other factors in your model. OR’s are again used to quantify the effects, but these will generally differ from the crude OR’s we considered previously. These adjusted OR’s can be put in a table with the crude OR’s shown previously or be placed in a separate table. The paper by Lewis, et al. I sent you does the former.

16. Multiple Logistic Regression Level 1 / Level 2Odds RatioProb>Chisq Lower 95% Upper 95% BlackAm.Ind1.17186850.0490*1.0006787 1.3801187 HispAm.Ind0.6510726<.0001*0.5274443 0.8044058 HispBlack0.5555851<.0001*0.4787285 0.6416147 OtherAm.Ind0.689538<.0001*0.5846837 0.8173755 OtherBlack0.588409<.0001*0.5481531 0.6313537 WhiteAm.Ind. 0.8225018 0.0189*0.7030908 0.967722 WhiteBlack0.7018721<.0001*0.667477 0.7381008 WhiteHisp1.2633027 0.0011*1.0961237 1.4633925 WhiteOther1.1928303<.0001*1.1152479 1.2765049 Am.Ind. Black0.8533381 0.0490*0.7245754 0.9993218 Am.Ind. Hisp1.535927<.0001*1.2431537 1.8959349 BlackHisp1.7999044<.0001*1.5585679 2.0888666 Am.Ind. Other1.4502464<.0001*1.223428 1.7103264 BlackOther1.6994981<.0001*1.5838983 1.824308 Am.InWhite1.2158028 0.0189*1.0333546 1.4222914 BlackWhite1.424761<.0001*1.3548284 1.4981789 HispWhite0.7915759 0.0011*0.6833437 0.9123058 OtherWhite0.8383422<.0001*0.7833891 0.8966617 Adjusted OR’s for Mother’s Race, adjusted for maternal smoking, marital status, mother’s age, gestational diabetes, gestational hypertension, and previous history of premature birth, and mother’s educational level.

17. Multiple Logistic Regression Level 1 / Level 2Odds RatioProb>Chisq Lower 95%Upper 95% 121.12420890.0003*1.0548301.1980772 131.11467270.0008*1.04639471.1872249 230.99151740.7638 0.93785211.0481238 141.2774486<.0001*1.18023271.3827778 241.13630890.0005*1.05790471.2206704 341.1460302<.0001*1.07582571.221146 151.2524747<.0001*1.1406671.3759116 251.11409430.0149*1.02119821.2161394 351.12362550.0041*1.03749271.2178402 1 = Less than HS 2 = HS Grad/GED 3 = Some College 4 = Bachelor’s Degree 5 = Master’s or Ph.D. Adjusted OR’s for Mother’s Education - adjusted for maternal smoking, marital status, mother’s age, gestational diabetes, gestational hypertension, and previous history of premature birth, and mother’s race.

18. Multiple Logistic Regression Level 1 / Level 2 Odds RatioProb>ChisqLower 95% Upper 95% MARITAL STATUS SingleMarried 1.1684874<.0001*1.1116343 1.2282365 PRENATAL CARE NoYes 3.9606617<.0001*3.5588051 4.4022196 MATERNAL SMOKING Smoker Nonsmoker 1.1859801<.0001*1.1131197 1.2629405 GESTATIONAL DIABETES YesNo 1.2558757<.0001*1.1585019 1.3598159 GESTATIONAL HYPERTENSION YesNo 3.1812302<.0001*2.9803234 3.3939524 PREVIOUS HISTORY OF PREMATURE BIRTH YesNo 3.2768289<.0001*2.9771507 3.6026212 OVERWEIGHT OR OBESE NoYes1.0430068 0.0455*1.0008396 1.0869491 MOTHER’S AGE Mother’s Age1.026572 (per 1 yr.) <.0001* 1.02263 1.030519 Adjusted OR’s are adjusted for the other factors in the table and are also adjusted for mothers education and race.

19. Summary of Logistic Regression As previous research has shown, factors such as mother’s race, education level, gestational conditions (e.g. diabetes and hypertension), and previous history of preterm birth are all associated with preterm birth in the directions we would expect. In addition, we see that lack of prenatal care and smoking during pregnancy are associated with an increased risk of preterm birth. We will examine these factors in more detail.

20. Discussion – No Prenatal Care Lack of prenatal care is associated with many of the factors examined in our analysis. We see that in general minority mothers have the highest percentages of mothers with no prenatal care, particularly Blacks and American Indians. Single mothers have the highest percentages with no prenatal care. Less educated women also have the highest percentages with no prenatal care. Those without private insurance have the highest rates of no prenatal care. Same is true for mothers who smoked during pregnancy and unfortunately those with a prior history of preterm birth. Finally we see that over 5% of the women with preterm birth had no prenatal care during the course of their pregnancy.

21. Discussion – Maternal Smoking Smoking during pregnancy is also associated with many of the factors examined in our analysis. We see that American Indians have the highest rates of maternal smoking. Less educated women and single women also have the highest percentages of maternal smoking. Those participating in the WIC program have higher rates of maternal smoking. Those without private insurance have the highest rates of maternal smoking, particularly those on Medicaid. Same is true unfortunately for those with a prior history of preterm birth. Finally we see that over 13% of the women with preterm birth smoked during pregnancy.

22. Discussion – NC Perinatal Association Perinatal Regions in North Carolina

23. Outcomes by Perinatal Region

24. NC AHEC (Area Health Education Centers)

25. AHEC - Regions

26. Birth Outcomes by AHEC Region

27. Urban vs. Rural Counties Are there differences between the birth outcomes and demographics for urban counties vs. rural one?

28. Urban vs. Rural Counties Urban counties have worse birth outcomes and prenatal care in general than rural counties which may seem surprising given that we might expect less access to health care in rural counties. However, we do see that maternal smoking is more prevalent in rural areas.