International Journal of Population Data Science (May 2019)

Electronic Longitudinal Alcohol Study in Communities (ELAStiC) Wales – protocol for platform development

  • Laszlo Trefan,
  • Ashley Akbari,
  • Shantini Paranjothy,
  • Daniel Mark Farewell,
  • Andrea Gartner,
  • David Fone,
  • Giles Jeremy Greene,
  • Anette Evans,
  • Ann Smith,
  • Victor Adekanmbi,
  • Jonathan Kennedy,
  • Ronan Anthony Lyons,
  • Simon Moore

DOI
https://doi.org/10.23889/ijpds.v4i1.581
Journal volume & issue
Vol. 4, no. 1

Abstract

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Introduction Excessive alcohol consumption has adverse effects on health but there is a recognised need for longitudinal analysis of population data to improve our understanding of the patterns of alcohol use, harms to consumers and those in their immediate environment. This paper describes the protocol for the project “Electronic Longitudinal Alcohol Study in Communities” (ELAStiC) that aims to leverage the value of a broad set of cross-linked cohorts, e-cohorts, surveys and data linkage facilities to construct an alcohol-specific analytical platform in the United Kingdom. Aims and objectives ELAStiC aims to address four aims: (a) the effect on children’s’ health and educational achievement of living in household in which one or more adults experience alcohol-related harm; (b) the longitudinal relationship between alcohol consumption, physical and mental health in adults in a Welsh county (Caerphilly); (c) the patterns of Welsh alcohol-related hospital admissions across 16 years; (d) the socioeconomic patterns in alcohol-related hospital admission in adults in Wales, considering individual alcohol consumption and other factors. Methods Datasets containing routinely collected electronic healthcare records including data from hospital admissions, general practice, cohorts specific to children as well as data from project specific observational studies. In addition, socioeconomic descriptors and mortality data were linked to these datasets. Conclusion The data used represent either Welsh population or county level. This level of representativeness could offer robust confidence for future analyses. In excess of 10 years of longitudinal data will help to understand alcohol-related disease and health trajectories across the lifespan.

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