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Int J Epidemiol. 2020 Apr 01;49(2):686-699. doi: 10.1093/ije/dyaa006.

Small-area methods for investigation of environment and health.

International journal of epidemiology

Frédéric B Piel, Daniela Fecht, Susan Hodgson, Marta Blangiardo, M Toledano, A L Hansell, Paul Elliott

Affiliations

  1. UK Small Area Health Statistics Unit, Department of Epidemiology & Biostatistics, School of Public Health, Imperial College London, London, UK.
  2. MRC-PHE Centre for Environment & Health, Department of Epidemiology & Biostatistics, School of Public Health, Imperial College London, London, UK.
  3. National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Health Impact of Environmental Hazards, Imperial College London, UK.
  4. Centre for Environmental Health and Sustainability, Medical School, University of Leicester, Leicester, UK.

PMID: 32182344 PMCID: PMC7266556 DOI: 10.1093/ije/dyaa006

Abstract

Small-area studies offer a powerful epidemiological approach to study disease patterns at the population level and assess health risks posed by environmental pollutants. They involve a public health investigation on a geographical scale (e.g. neighbourhood) with overlay of health, environmental, demographic and potential confounder data. Recent methodological advances, including Bayesian approaches, combined with fast-growing computational capabilities, permit more informative analyses than previously possible, including the incorporation of data at different scales, from satellites to individual-level survey information. Better data availability has widened the scope and utility of small-area studies, but has also led to greater complexity, including choice of optimal study area size and extent, duration of study periods, range of covariates and confounders to be considered and dealing with uncertainty. The availability of data from large, well-phenotyped cohorts such as UK Biobank enables the use of mixed-level study designs and the triangulation of evidence on environmental risks from small-area and individual-level studies, therefore improving causal inference, including use of linked biomarker and -omics data. As a result, there are now improved opportunities to investigate the impacts of environmental risk factors on human health, particularly for the surveillance and prevention of non-communicable diseases.

© The Author(s) 2020. Published by Oxford University Press on behalf of the International Epidemiological Association.

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