Abstract
BackgroundNeighborhood characteristics are robust predictors of overall health and mortality risk for residents. Though there has been some investigation of the role that molecular indicators may play in mediating neighborhood exposures, there has been little effort to incorporate newly developed epigenetic biomarkers into our understanding of neighborhood characteristics and health outcomes.MethodsUsing 157 participants of the Detroit Neighborhood Health Study with detailed assessments of neighborhood characteristics and genome-wide DNA methylation profiling via the Illumina 450K methylation array, we assessed the relationship between objective neighborhood characteristics and a validated DNA methylation-based epigenetic mortality risk score (eMRS). Associations were adjusted for age, race, sex, ever smoking, ever alcohol usage, education, years spent in neighborhood, and employment. A secondary model additionally adjusted for personal neighborhood perception. We summarized 19 neighborhood quality indicators assessed for participants into 9 principal components which explained over 90% of the variance in the data and served as metrics of objective neighborhood quality exposures.ResultsOf the nine principal components utilized for this study, one was strongly associated with the eMRS (β = 0.15; 95% confidence interval = 0.06–0.24; P = 0.002). This principal component (PC7) was most strongly driven by the presence of abandoned cars, poor streets, and non-art graffiti. Models including both PC7 and individual indicators of neighborhood perception indicated that only PC7 and not neighborhood perception impacted the eMRS. When stratified on neighborhood indicators of greenspace, we observed a potentially protective effect of large mature trees as this feature substantially attenuated the observed association.ConclusionObjective measures of neighborhood disadvantage are significantly associated with an epigenetic predictor of mortality risk, presenting a potential novel avenue by which neighborhood-level exposures may impact health. Associations were independent of an individual’s perception of their neighborhood and attenuated by neighborhood greenspace features. More work should be done to determine molecular risk factors associated with neighborhoods, and potentially protective neighborhood features against adverse molecular effects.
Highlights
Neighborhood characteristics are robust predictors of overall health and mortality risk for residents
Of the nine principal component (PC), only one (PC7) was associated with the epigenetic mortality risk score (eMRS) (Fig. 1) in a model adjusted for age, sex, race, smoking status, alcohol usage, years residing in the neighborhood, education, and employment after correcting for the nine associations performed in the primary analysis
To evaluate the impact of greenspace, we examined if associations between PC7 and the eMRS were attenuated in individuals residing in neighborhoods where the percentage of street segments with large mature trees was above the median (> 84.2%) or in neighborhoods with at least one community garden observed
Summary
Neighborhood characteristics are robust predictors of overall health and mortality risk for residents. Though much of the existing research on the relationship between neighborhood characteristics and health has focused on overt health outcomes, like chronic disease and mortality, there is an increasing appreciation of the molecular alterations that may accompany residence in socioeconomically and built environment disadvantaged neighborhoods and that may explain the biological process through which exogenous factors like neighborhood characteristics “get under the skin.”. Multiple studies have reported that allostatic load is increased for those living in stressful and socioeconomically disadvantaged neighborhoods [12, 13]. In the reverse of these studies, neighborhood factors associated with positive health outcomes, e.g., greenspace, have been associated with improved levels of molecular biomarkers for allostatic load and inflammation [18], demonstrating that both positive and negative neighborhood characteristics might impact molecular indicators of health
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