Should Our Approach for Reducing Poor Birth Outcomes Differ in Urban and Rural Populations?

Saturday, 29 July 2017: 9:50 AM

Judy Griffin McCook, PhD
East Tennessee State University, Johnson City, TN, USA
Beth A. Bailey, PhD
Department of Family Medicine, College of Medicine, East Tennessee State University, Johnson City, TN, USA

Purpose:  Location of residence has long been recognized to impact maternal-child health disparities. For decades, women residing in urban areas have experienced high rates of poor pregnancy outcomes. More recently, rural disparities in birth outcomes have been recognized, and have been found to occur at rates similar to those reported for urban populations. In order to appropriately address poor birth outcomes in such highly disparate environments, a better understanding of the modifiable factors that may differentially drive these outcomes is needed. The current study had two objectives. First, we examined potential differences between rural and urban women on modifiable factors known to impact birth outcomes. Second, we examined whether these factors differentially predicted two specific adverse birth outcomes, preterm delivery (PTB, 9.6% nationally) and intrauterine growth restriction (IUGR, 9.9% nationally), for urban and rural newborns.

Methods:  Data were extracted from birth certificates for all live births in the state of Tennessee for a 3-year period from 2012-2014. Rural Urban Commuting Area (RUCA) Codes were assigned based on maternal residence zip code, and participants were classified as either urban (Metropolitan, codes 1.0 – 2.1) or rural (Rural, codes 10.0-10.3). Those with micropolitan and small town RUCA codes were eliminated from further analysis. Birth outcomes of interest were PTB (birth prior to 37 weeks gestation) and IUGR (birth weight for gestational age < 10thpercentile). Modifiable dichotomous predictors included maternal weight based on BMI (underweight prior to pregnancy, overweight prior to pregnancy, gained too little weight during pregnancy , gained too much weight during pregnancy ), smoking (smoked cigarettes at any point during pregnancy), time between pregnancies (previous pregnancy ended < 6 months prior to current pregnancy), prenatal care (inadequate based on timing of entry and number of visits, no prenatal care), and existing or emerging chronic health conditions (prepregnancy and gestational hypertension, prepregnancy and gestational diabetes). Chi-square analyses were used to compare the urban-rural groups on the predictors, while logistic regression was used to look at the odds of poor birth outcomes relative to each predictor separately for urban and rural participants, while controlling for possible confounders (maternal age, race, infant gender, and eligibility for income-based government benefits).

Results:  The final sample contained 183,703 maternal-infant dyads (9,385 classified as rural). The urban and rural populations did not differ significantly (p>0.05) in rates of PTB (10.9% vs 11.4%) or IUGR (11.8% vs 11.3%). The two groups differed significantly (p<0.05 – p<0.001) on all predictors of interest. Compared to urban women, rural women had significantly higher rates of being underweight prior to pregnancy, being overweight prior to pregnancy, gaining too little weight, and gaining too much weight. Compared to urban women, rural women were more than twice as likely to have smoked during pregnancy (27.3% vs 12.2%), had a short inter-pregnancy interval, and had substantially higher rates of prepregnancy and gestational hypertension and diabetes. The only predictors for which urban women were worse off than rural women were related to prenatal care – urban women were 10% more likely to have inadequate prenatal care, and almost twice as likely (2.1% vs 1.1%) to have had no prenatal care. Logistic regression analyses revealed similar predictor patterns for urban and rural women for PTB, with gestational hypertension the strongest predictor (aOR=3.39 for urban women, aOR=2.82 for rural women). Prepregnancy hypertension and diabetes were significant predictors for both groups of women, more than doubling the chances of a PTB. While gaining too little weight predicted PTB for both groups, being overweight prepregnancy and inadequate prenatal care were strong predictors for rural women, while no prenatal care and pregnancy smoking were strong predictors for urban women. Prediction models were very different for urban and rural women regarding IUGR, with pregnancy smoking the strongest predictor for urban women, and prepregnancy hypertension the strongest predictor for rural women. Being underweight prepregnancy significantly predicted IUGR for both groups, as did gaining too little weight, with prenatal care factors only marginally important and only for urban women.

Conclusion:  PTB and IUGR are important indicators of not only newborn wellbeing, but of long term growth and development. In our sample, rates of PTB and IUGR in our urban and rural groups were higher than national averages, but not different between the two regions. This is despite the fact that rural women had significantly higher rates of most modifiable predictors of these adverse birth outcomes. Differences in what predicts PTB and IUGR in the two groups emerged, and may suggest avenues for differentially tailored interventions in urban and rural settings, especially with regard to how to better prioritize improved management of chronic health conditions, addressing weight preconception and weight gain during pregnancy, intervening with smokers, and increasing engagement in prenatal care. However, results also show that just because a potential determinant occurs at a higher rate in a specific region does not mean addressing it to the exclusion of other factors will lead to the greatest improvement in birth outcomes, and interventions should consider the predictors of poor birth outcomes in specific populations. Future research should examine potential buffers or resilience factors in rural samples who, based on rates of predictors of adverse birth outcomes, might be expected to have higher rates of PTB and IUGR than even urban women.