Differential vulnerability to neighbourhood disorder: a gene×environment interaction study

Abstract

BackgroundType 2 diabetes (T2D) is preventable, it is increasing in prevalence and it is a major risk factor for morbidity and mortality. Importantly, residents of neighbourhoods with high levels of disorder are more likely to develop T2D than those living in less disordered neighbourhoods and neighbourhood disorder may exacerbate genetic risk for T2D.MethodWe use genetic, self-reported neighbourhood, and health data from the Health and Retirement Study. We conducted weighted logistic regression analyses in which neighbourhood disorder, polygenic scores for T2D and their interaction predicted T2D.ResultsGreater perceptions of neighbourhood disorder (OR=1.11, p<0.001) and higher polygenic scores for T2D (OR=1.42, p<0.001) were each significantly and independently associated with an increased risk of T2D. Furthermore, living in a neighbourhood perceived as having high levels of disorder exacerbated genetic risk for T2D (OR=1.10, p=0.001). This significant gene×environment interaction was observed after adjusting for years of schooling, age, gender, levels of physical activity and obesity.ConclusionFindings in the present study suggested that minimising people’s exposure to vandalism, vacant buildings, trash and circumstances viewed by residents as unsafe may reduce the burden of this prevalent chronic health condition, particularly for subgroups of the population who carry genetic liability for T2D.

Genetic risk of obesity as a modifier of associations between neighbourhood environment and body mass index: an observational study of 335 046 UK Biobank participants

“…interact with genetic risk, [9][10][11] despite a number of 'socioecological' environmental factors long being recognised in social epidemiology as potentially important determinants of weight status. The residential neighbourhood environment comprises many features that potentially influence energy balance.…”

Heritable environments: bias due to conditioning on a collider in models with polygenic scores

“…We considered the presence of direct effects from G to Y and E to Y, allowed the G-E correlation to vary from 0 indicating no heritability to 0.5 indicating a highly heritable covariate E, and included an uncontrolled confounder, U, which is positively correlated with both E and Y at a fixed value. Figure 1B consider such environments as relationship status, 22 educational attainment, 23 occupational exposure, 24 neighbourhood characteristics 25 and others. There is ongoing discussion on the implications of non-exogeneity of environments.…”

“…Here, in the same fashion as in additive models, environmental exposures of interest are not usually exogenous. For example, recent studies on gene-environment interaction analysis consider such environments as relationship status, 22 educational attainment, 23 occupational exposure, 24 neighbourhood characteristics 25 and others. There is ongoing discussion on the implications of non-exogeneity of environments.…”

Genetic risk of obesity as a modifier of associations between neighbourhood environment and body mass index: an observational study of 335,046 UK Biobank participants

“…Some recent studies have examined interactions between genetic risk and birth cohort as a means of capturing exposure to an increasingly obesogenic environment in very broad terms, [7][8][9] but there has been limited investigation of specific features of the environment that might plausibly interact with genetic risk, [10][11][12][13][14] despite a number of 'socio-ecological' environmental factors long being recognised in social epidemiology as potentially important determinants of weight status.…”

“…[4,5] For obesity outcomes, the ‘environment’ in GxE studies is often operationalised as the lifestyle or behavioural factors that influence energy balance,[6] rather than more upstream features of the built and social environments; the settings where behavioural ‘choices’ are made and constrained. Some recent studies have examined interactions between genetic risk and birth cohort as a means of capturing exposure to an increasingly obesogenic environment in very broad terms,[7–9] but there has been limited investigation of specific features of the environment that might plausibly interact with genetic risk,[10–14] despite a number of ‘socio-ecological’ environmental factors long being recognised in social epidemiology as potentially important determinants of weight status.…”