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Original research
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
  1. Kate E Mason1,2,
  2. Luigi Palla3,4,
  3. Neil Pearce3,
  4. Jody Phelan5 and
  5. Steven Cummins6
  1. 1Department of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK
  2. 2Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
  3. 3Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
  4. 4Department of Global Health, University of Nagasaki, Nagasaki, Japan
  5. 5Department of Infection Biology, London School of Hygiene and Tropical Medicine, London, UK
  6. 6Department of Public Health, Environments and Society, London School of Hygiene and Tropical Medicine, London, UK
  1. Correspondence to Dr Kate E Mason, Public Health, Policy and Systems, University of Liverpool, Liverpool L69 3BX, UK; kate.mason{at}liverpool.ac.uk

Abstract

Background There is growing recognition that recent global increases in obesity are the product of a complex interplay between genetic and environmental factors. However, in gene-environment studies of obesity, ‘environment’ usually refers to individual behavioural factors that influence energy balance, whereas more upstream environmental factors are overlooked. We examined gene-environment interactions between genetic risk of obesity and two neighbourhood characteristics likely to be associated with obesity (proximity to takeaway/fast-food outlets and availability of physical activity facilities).

Methods We used data from 335 046 adults aged 40–70 in the UK Biobank cohort to conduct a population-based cross-sectional study of interactions between neighbourhood characteristics and genetic risk of obesity, in relation to body mass index (BMI). Proximity to a fast-food outlet was defined as distance from home address to nearest takeaway/fast-food outlet, and availability of physical activity facilities as the number of formal physical activity facilities within 1 km of home address. Genetic risk of obesity was operationalised by weighted Genetic Risk Scores of 91 or 69 single nucleotide polymorphisms (SNP), and by six individual SNPs considered separately. Multivariable, mixed-effects models with product terms for the gene-environment interactions were estimated.

Results After accounting for likely confounding, the association between proximity to takeaway/fast-food outlets and BMI was stronger among those at increased genetic risk of obesity, with evidence of an interaction with polygenic risk scores (p=0.018 and p=0.028 for 69-SNP and 91-SNP scores, respectively) and in particular with a SNP linked to MC4R (p=0.009), a gene known to regulate food intake. We found very little evidence of gene-environment interaction for the availability of physical activity facilities.

Conclusions Individuals at an increased genetic risk of obesity may be more sensitive to exposure to the local fast-food environment. Ensuring that neighbourhood residential environments are designed to promote a healthy weight may be particularly important for those with greater genetic susceptibility to obesity.

  • dietary patterns
  • malnutrition
https://creativecommons.org/licenses/by/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

https://doi.org/10.1136/bmjnph-2020-000107

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    Footnotes

    • Twitter @ke_mason

    • Contributors SC and KM conceived the idea of the study. KM, LP and SC designed the analysis. KM led the data management, statistical analysis and writing of the manuscript. JP extracted the genetic data from UK Biobank, and JP and LP provided expertise in working with genetic data. SC, LP and NP contributed to the interpretation of results, and all authors contributed to and approved the final manuscript.

    • Funding This work was supported by a Commonwealth Scholarship Commission PhD Scholarship (KM). SC is supported by Health Data Research UK. Our funders had no role in any stage of this study, nor in the preparation of the manuscript for publication.

    • Competing interests None declared.

    • Patient consent for publication Not required.

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

    • Data availability statement Data are not publicly available but access can be requested from UK Biobank https://www.ukbiobank.ac.uk/