Article Text

Download PDFPDF
Differential vulnerability to neighbourhood disorder: a gene×environment interaction study
  1. Jennifer Williams Robinette1,
  2. Jason D Boardman2,
  3. Eileen M Crimmins1
  1. 1 Davis School of Gerontology, University of Southern California, Los Angeles, California, USA
  2. 2 Institute of Behavioral Science and Department of Sociology, University of Colorado, Boudler, Colorado, USA
  1. Correspondence to Dr Jennifer Williams Robinette, Department of Gerontology, University of Southern California, Los Angeles, CA 90007, USA; jrobinet{at}usc.edu

Abstract

Background Type 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.

Method We 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.

Results Greater 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.

Conclusion Findings 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.

  • genetics
  • neighborhood/place
  • diabetes

Statistics from Altmetric.com

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Footnotes

  • Contributors JWR contributed to the conception of the study, data analysis and interpretation and drafting of the manuscript. JDB contributed to the data analysis interpretation and drafting of the manuscript. EC contributed to the collection of data and drafting of the manuscript. All authors read and approved the final manuscript. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

  • Funding This research was based on work supported by a National Institutes of Health/National Institute on Aging training grant (T32-AG000037-37) and a National Institutes of Health/National Institute on Aging career development grant (1K99AG055699-01) to JWR, and a National Institutes of Health/National Institute on Aging grant (R25 AG053227). These sources of funding supported the data analysis and writing of this report. The data collection for the Health and Retirement Study is also supported by the National Institute on Aging (U01 AG009740).

  • Competing interests None declared.

  • Ethics approval This study was approved by the Institutional Review Board of the University of Michigan.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement HRS data sets are publicly available. No additional unpublished data were used.

  • Patient consent for publication Not required.