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Socioeconomic status has been associated with cardiovascular disease risk factors. However, few studies have examined this relationship among populations in the US Gulf Coast region. We assessed neighborhood deprivation in relation to obesity and diabetes in 9,626 residents participating in the Gulf Long-Term Follow-Up Study (2011–present) who completed a home visit (2011–2013) with height, weight, waist, and hip measurements. Obesity was categorized as body mass index of at least 30, and diabetes was defined by doctor's diagnosis or prescription medication. Participant home addresses were linked to an established Area Deprivation Index and categorized into 4 levels (1 = least deprived). In adjusted, modified Poisson regression models, participants with greatest deprivation were more likely to have obesity compared with those with least deprivation (adjusted prevalence ratio (aPR) = 1.21, 95% confidence interval (CI): 1.08, 1.35), central obesity (aPR = 1.11, 95% CI: 1.04, 1.19), and diabetes (aPR = 1.49, 95% CI: 1.03, 2.14). Repeated analyses among a subgroup of participants (n  = 3,016) whose hemoglobin A1C values were measured 3 years later indicated the association with diabetes (defined as diagnosis, medications, or hemoglobin A1C ≥ 6.5) was similar (aPR = 1.46, 95% CI: 1.14, 1.86). Results suggest neighborhood deprivation is associated with obesity and diabetes in a US region with high baseline prevalence. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) and candidate gene analyses have led to the discovery of several dozen genetic polymorphisms associated with breast cancer susceptibility, many of which are considered well-established risk factors for the disease. Despite attempts to replicate these same variant-disease associations in African Americans, the evaluable populations are often too small to produce precise or consistent results. We estimated the associations between 83 previously identified single nucleotide polymorphisms (SNPs) and breast cancer among Carolina Breast Cancer Study (1993–2001) participants using maximum likelihood, Bayesian, and hierarchical methods. The selected SNPs were previous GWAS hits (n = 22), near-hits (n = 19), otherwise well-established risk loci (n = 5), or located in the same genes as selected variants (n = 37). We successfully replicated 18 GWAS-identified SNPs in whites (n = 2,352) and 10 in African Americans (n = 1,447). SNPs in the fibroblast growth factor receptor 2 gene (FGFR2) and the TOC high mobility group box family member 3 gene (TOX3) were strongly associated with breast cancer in both races. SNPs in the mitochondrial ribosomal protein S30 gene (MRPS30), mitogen-activated protein kinase kinase kinase 1 gene (MAP3K1), zinc finger, MIZ-type containing 1 gene (ZMIZ1), and H19, imprinted maternally expressed transcript gene (H19) were associated with breast cancer in whites, and SNPs in the estrogen receptor 1 gene (ESR1) and H19 gene were associated with breast cancer in African Americans. We provide precise and well-informed race-stratified odds ratios for key breast cancer–related SNPs. Our results demonstrate the utility of Bayesian methods in genetic epidemiology and provide support for their application in small, etiologically driven investigations. [ABSTRACT FROM PUBLISHER]

Air pollution may be a potential cause of congenital heart defects (CHDs), but racial disparities in this association are unexplored. We conducted a statewide population-based cohort study using North Carolina birth data from 2003-2015 (N=1,225,285) to investigate the relationship between air pollution and CHDs (specifically pulmonary valve atresia/stenosis, Tetralogy of Fallot (TOF), and atrioventricular septal defect (AVSD)). Maternal exposure to particulate matter ≤2.5 micrometers in diameter (PM2.5) and ozone during weeks 3-9 of pregnancy were estimated using the Environmental Protection Agency's Downscaler Model. Single- and co-pollutant log-binomial models were created for the entire population and stratified by race to investigate disparities. Positive associations between PM2.5 and CHDs were observed. An increasing concentration-response association was found for PM2.5 and TOF in adjusted, co-pollutant models (Quartile 4 prevalence ratio: 1.46; 95% CI: 1.06, 2.03). Differences in the effect of PM2.5 on CHD prevalence were seen in some models stratified by race, although clear exposure-prevalence gradients were not evident. Positive associations were also seen in adjusted, co-pollutant models of ozone and AVSD. Study results suggest that prenatal PM2.5 and ozone exposure may increase the prevalence of certain CHDs. A consistent pattern of differences in association by race/ethnicity was not apparent., (Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2024.)

Mental health effects are frequently reported following natural disasters. However, little is known about effects of living in a hazard-prone region on mental health. We analyzed data from 9,312 Gulf Long-term Follow-up Study participants who completed standardized mental health questionnaires including the Patient Health Questionnaire-9 (depression=score≥10), Generalized Anxiety Disorder Questionnaire-7 (anxiety=score≥10), and Primary Care PTSD Screen (PTSD=score≥3). Geocoded residential addresses were linked to census-tract level natural hazard risk scores estimated using the National Risk Index (NRI). We considered an overall risk score representing 18 natural hazards, and individual scores for hurricanes, heatwaves, coastal flooding and riverine flooding. Log binomial regression estimated prevalence ratios (PR) and 95% confidence intervals (CI) for associations between risk scores (quartiles) and mental health outcomes. Increasing hurricane and coastal flooding scores were associated with all mental health outcomes in a suggestive exposure-response manner. Associations were strongest for PTSD, with PRs for the highest vs. lowest quartile of hurricane and coastal flooding risks of 2.29(1.74-3.01) and 1.59(1.23-2.05), respectively. High heatwave risk was associated with anxiety (PR=1.25(1.12-1.38)) and depression (PR=1.19(1.04-1.36)) and suggestively with PTSD (PR=1.20(0.94-1.52)). Results suggest that living in areas prone to natural disasters is one factor associated with poor mental health status., (Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2024.)