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Acknowledgements AG was funded by the National Centre for Population Health and Wellbeing Research Wales (WCPHWR), and SP, DF, and JG are members of the NCPHWR team in Cardiff University. We would like to thank the Brecon Group (which comprises all paediatricians and paediatric diabetes healthcare staff in Wales with an interest in Diabetes and endocrinology). The Brecon Group was supported initially by grants from NovoNordisk and subsequently the Welsh Government. Funds from the Economic and Social Research Council, the Medical Research Council, and Alcohol Research UK supported the establishment of the ELASTiC data platform.This study used anonymised data held in the Secure Anonymised Information Linkage (SAIL) Databank. We would like to acknowledge all the data providers who enable SAIL to make anonymised data available for research. Data sharing The datasets used in this study are available in the SAIL Databank at Swansea University, Swansea, UK, but as restrictions apply, they are not publicly available. All proposals to use SAIL data are subject to review by an independent Information Governance Review Panel (IGRP). Before any data can be accessed, approval must be given by the IGRP. The IGRP gives careful consideration to each project to ensure proper and appropriate use of SAIL data. When access has been granted, it is gained through a privacy-protecting safe haven and remote access system referred to as the SAIL Gateway. SAIL has established an application process to be followed by anyone who would like to access data via SAIL at https://www.saildatabank.com/application-process. Funding information: Alcohol Research UK; Medical Research Council; Economic and Social Research Council; Welsh Government; Novo Nordisk; Brecon Group; National Centre for Population Health and Wellbeing Research Wales ; Peer reviewed ; Postprint ; Publisher PDF

Recent studies found evidence of health selective migration whereby healthy people move to less deprived areas and less healthy people move to or stay in more deprived areas. There is no consensus, however, on whether this influences health inequalities. Measures of socio-economic inequalities in mortality and life expectancy are widely used by government and health services to track changes over time but do not consider the effect of migration. This study aims to investigate whether and to what extent migration altered the observed socioeconomic gradient in mortality. Data for the population of Wales (3,136,881) registered with the National Health Service on 01/01/2006 and follow-up for 24 quarters were individually record-linked to ONS mortality files. This included moves between lower super output areas (LSOAs), deprivation quintiles and rural-urban class at each quarter, age, sex, and date of death. Cox regression models were used to estimate the hazard ratios for the deprivation quintiles in all-cause mortality, as well as deprivation change between the start and end of the study. We found evidence of health selective migration in some groups, for example people aged under 75 leaving the most deprived areas having a higher mortality risk than those they left behind, suggesting widening inequalities, but also found the opposite pattern for other migration groups. For all ages, those who lived in the most deprived quintile had a 57% higher risk of death than those in the least deprived quintile, allowing deprivation to vary with moves over time. There was little change in this risk when people were artificially kept in their deprivation quintile of origin (54% higher). Overall, migration during the six year window did not substantially alter the deprivation gradient in mortality in Wales between 2006 and 2011.

Funding Funding for this work was received from Public Health Wales NHS Trust as part of a report on migration and health. Support for the report was also received from the National Centre for Population Health and Wellbeing Research (NCPHWR). The eCATALYsT multiagency dataset and the baseline survey was supported by the Wales Office of Research and Development (SCC99/1/105 and R00/1/017). The follow-up survey was supported by a Welsh Assembly Government/Medical Research Council Health Research Partnership Award (H07-3-030), and the electronic cohort is supported by a National Institute for Social Care and Health Research Welsh Assembly Government Translational Health Research Platform Award (TPR08-020). Data availability statement Data may be obtained from a third party and are not publicly available. The electronic cohort is securely stored and maintained on the Secure Anonymised Information Linkage (SAIL) databank at Swansea University Medical School. The authors welcome general enquiries and ideas for new collaborations. Readers with an interest in further details should contact Professor Shantini Paranjothy, Principal Investigator. ; Peer reviewed ; Publisher PDF

IntroductionExcessive alcohol consumption has adverse effects on health and there is a recognised need for thelongitudinal analysis of population data to improve our understanding of the patterns of alcohol use,harms to consumers and those in their immediate environment. The UK has a number of linkable,longitudinal databases that if assembled properly could support valuable research on this topic.
Aims and objectivesThis paper describes the development of a broad set of cross-linked cohorts, e-cohorts, surveys andlinked electronic healthcare records (EHRs) to construct an alcohol-specific analytical platform inthe United Kingdom using datasets on the population of Wales.
The objective of this paper is to provide a description of existing key datasets integrated withexisting, routinely collected electronic health data on a secure platform, and relevant derived variablesto enable population-based research on alcohol-related harm in Wales. We illustrate our use of thesedata with some exemplar research questions that are currently under investigation.
MethodsRecord-linkage of routine and observational datasets. Routine data includes hospital admissions,general practice, and cohorts specific to children. Two observational studies were included. Routinesocioeconomic descriptors and mortality data were also linked.
ConclusionWe described a record-linked, population-based research protocol for alcohol related harm on a secureplatform. As the datasets used here are available in many countries, ELAStiC provides a templatefor setting up similar initiatives in other countries. We have also defined a number of alcohol specificvariables using routinely-collected available data that can be used in other epidemiological studiesinto alcohol related outcomes. With over 10 years of longitudinal data, it will help to understandalcohol-related disease and health trajectories across the lifespan.