Using non-parametric Bayes shrinkage to assess relationships between multiple environmental and social stressors and neonatal size and body composition in the Healthy Start cohort.

BACKGROUND: Both environmental and social factors have been linked to birth weight and adiposity at birth, but few studies consider the effects of exposure mixtures. Our objective was to identify which components of a mixture of neighborhood-level environmental and social exposures were driving associations with birth weight and adiposity at birth in the Healthy Start cohort. METHODS: Exposures were assessed at the census tract level and included air pollution, built environment characteristics, and socioeconomic status. Prenatal exposures were assigned based on address at enrollment. Birth weight was measured at delivery and adiposity was measured using air displacement plethysmography within three days. We used non-parametric Bayes shrinkage (NPB) to identify exposures that were associated with our outcomes of interest. NPB models were compared to single-predictor linear regression. We also included generalized additive models (GAM) to assess nonlinear relationships. All regression models were adjusted for individual-level covariates, including maternal age, pre-pregnancy BMI, and smoking. RESULTS: Results from NPB models showed most exposures were negatively associated with birth weight, though credible intervals were wide and generally contained zero. However, the NPB model identified an interaction between ozone and temperature on birth weight, and the GAM suggested potential non-linear relationships. For associations between ozone or temperature with birth weight, we observed effect modification by maternal race/ethnicity, where effects were stronger for mothers who identified as a race or ethnicity other than non-Hispanic White. No associations with adiposity at birth were observed. CONCLUSIONS: NPB identified prenatal exposures to ozone and temperature as predictors of birth weight, and mothers who identify as a race or ethnicity other than non-Hispanic White might be disproportionately impacted. However, NPB models may have limited applicability when non-linear effects are present. Future work should consider a two-stage approach where NPB is used to reduce dimensionality and alternative approaches examine non-linear effects.

Combined environmental and social exposures during pregnancy and associations with neonatal size and body composition: the Healthy Start study.

BACKGROUND: Prenatal environmental and social exposures have been associated with decreased birth weight. However, the effects of combined exposures in these domains are not fully understood. Here we assessed multi-domain exposures for participants in the Healthy Start study (Denver, CO) and tested associations with neonatal size and body composition. METHODS: In separate linear regression models, we tested associations between neonatal outcomes and three indices for exposures. Two indices were developed to describe exposures to environmental hazards (ENV) and social determinants of health (SOC). A third index combined exposures in both domains (CE = ENV/10 × SOC/10). Index scores were assigned to mothers based on address at enrollment. Birth weight and length were measured at delivery, and weight-for-length z-scores were calculated using a reference distribution. Percent fat mass was obtained by air displacement plethysmography. RESULTS: Complete data were available for 897 (64%) participants. Median (range) ENV, SOC, and CE values were 31.9 (7.1-63.2), 36.0 (2.8-75.0), and 10.9 (0.4-45.7), respectively. After adjusting for potential confounders, 10-point increases in SOC and CE were associated with 27.7 g (95%CI: 12.4 - 42.9 g) and 56.3 g (19.4 - 93.2 g) decreases in birth weight, respectively. SOC and CE were also associated with decreases in % fat mass. CONCLUSIONS: Combined exposures during pregnancy were associated with lower birth weight and % fat mass. Evidence of a potential synergistic effect between ENV and SOC suggests a need to more fully consider neighborhood exposures when assessing neonatal outcomes.

Population Size, Growth, and Environmental Justice Near Oil and Gas Wells in Colorado.

We evaluated population size and factors influencing environmental justice near oil and gas (O&G) wells. We mapped nearest O&G well to residential properties to evaluate population size, temporal relationships between housing and O&G development, and 2012 housing market value distributions in three major Colorado O&G basins. We reviewed land use, building, real estate, and state O&G regulations to evaluate distributive and participatory justice. We found that by 2012 at least 378,000 Coloradans lived within 1 mile of an active O&G well, and this population was growing at a faster rate than the overall population. In the Denver Julesburg and San Juan basins, which experienced substantial O&G development prior to 2000, we observed a larger proportion of lower value homes within 500 feet of an O&G well and that most O&G wells predated houses. In the Piceance Basin, which had not experienced substantial prior O&G development, we observed a larger proportion of high value homes within 500 feet of an O&G well and that most houses predated O&G wells. We observed economic, rural, participatory, and/or distributive injustices that could contribute to health risk vulnerabilities in populations near O&G wells. We encourage policy makers to consider measures to reduce these injustices.