Format

Send to

Choose Destination
Nat Hum Behav. 2019 Apr 8. doi: 10.1038/s41562-019-0562-1. [Epub ahead of print]

Genetics and the geography of health, behaviour and attainment.

Author information

1
Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA. db3275@cumc.columbia.edu.
2
Robert N. Butler Columbia Aging Center, Columbia University, New York, NY, USA. db3275@cumc.columbia.edu.
3
Department of Psychology and Neuroscience, Duke University, Durham, NC, USA.
4
Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA.
5
Center for Genomic and Computational Biology, Duke University, Durham, NC, USA.
6
MRC Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
7
Stanford Graduate School of Education, Stanford University, Palo Alto, CA, USA.
8
Carolina Population Center and Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
9
Complex Disease Epigenetics Group, University of Exeter Medical School, Exeter, UK.
10
Department of Psychological Science, University of California at Irvine, Irvine, CA, USA. codgers@uci.edu.
11
Sanford School of Public Policy, Duke University, Durham, NC, USA. codgers@uci.edu.

Abstract

Young people's life chances can be predicted by characteristics of their neighbourhood1. Children growing up in disadvantaged neighbourhoods exhibit worse physical and mental health and suffer poorer educational and economic outcomes than children growing up in advantaged neighbourhoods. Increasing recognition that aspects of social inequalities tend, in fact, to be geographical inequalities2-5 is stimulating research and focusing policy interest on the role of place in shaping health, behaviour and social outcomes. Where neighbourhood effects are causal, neighbourhood-level interventions can be effective. Where neighbourhood effects reflect selection of families with different characteristics into different neighbourhoods, interventions should instead target families or individuals directly. To test how selection may affect different neighbourhood-linked problems, we linked neighbourhood data with genetic, health and social outcome data for >7,000 European-descent UK and US young people in the E-Risk and Add Health studies. We tested selection/concentration of genetic risks for obesity, schizophrenia, teen pregnancy and poor educational outcomes in high-risk neighbourhoods, including genetic analysis of neighbourhood mobility. Findings argue against genetic selection/concentration as an explanation for neighbourhood gradients in obesity and mental health problems. By contrast, modest genetic selection/concentration was evident for teen pregnancy and poor educational outcomes, suggesting that neighbourhood effects for these outcomes should be interpreted with care.

PMID:
30962612
DOI:
10.1038/s41562-019-0562-1

Supplemental Content

Loading ...
Support Center