Change in alcohol outlet density and alcohol-related harm to population health (CHALICE): a comprehensive record-linked database study in Wales

Abstract

BackgroundExcess alcohol consumption has serious adverse effects on health and results in violence-related harm.ObjectiveThis study investigated the impact of change in community alcohol availability on alcohol consumption and alcohol-related harms to health, assessing the effect of population migration and small-area deprivation.DesignA natural experiment of change in alcohol outlet density between 2006 and 2011 measured at census Lower Layer Super Output Area level using observational record-linked data.SettingWales, UK; population of 2.5 million aged ≥ 16 years.Outcome measuresAlcohol consumption, alcohol-related hospital admissions, accident and emergency (A&E) department attendances from midnight to 06.00 and violent crime against the person.Data sourcesLicensing Act 2003 [Great Britain.Licensing Act 2003. London: The Stationery Office; 2003. URL:www.legislation.gov.uk/ukpga/2003/17/contents(accessed 8 June 2015)] data on alcohol outlets held by the 22 local authorities in Wales, alcohol consumption data from annual Welsh Health Surveys 2008–12, hospital admission data 2006–11 from the Patient Episode Database for Wales (PEDW) and A&E attendance data 2009–11 were anonymously record linked to the Welsh Demographic Service age–sex register within the Secure Anonymised Information Linkage Databank. A final data source was recorded crime 2008–11 from the four police forces in Wales.MethodsOutlet density was estimated (1) as the number of outlets per capita for the 2006 static population and the per quarterly updated population to assess the impact of population migration and (2) using new methods of network analysis of distances between each household and alcohol outlets within 10 minutes of walking and driving. Alcohol availability was measured by three variables: (1) the previous quarterly value; (2) positive and negative change over the preceding five quarters; and (3) volatility, a measure of absolute quarterly changes during the preceding five quarters. Longitudinal statistical analysis used multilevel Poisson models of consumption and Geographically Weighted Regression (GWR) spatial models of binge drinking, Cox regression models of hospital admissions and A&E attendance and GWR models of violent crime against the person, each as a function of alcohol availability adjusting for confounding variables. The impact on health inequalities was investigated by stratifying models within quintiles of the Welsh Index of Multiple Deprivation.ResultsThe main finding was that change in walking outlet density was associated with alcohol-related harms: consumption, hospital admissions and violent crime against the person each tracked the quarterly changes in outlet density. Alcohol-related A&E attendances were not clinically coded and the association was less conclusive. In general, social deprivation was strongly associated with the outcome measures but did not substantially modify the associations between the outcomes and alcohol availability. We found no evidence for an important effect of population migration.LimitationsLimitations included the absence of any standardised methods of alcohol outlet data collation, processing and validation, and incomplete data on on-sales and off-sales. We were dependent on the quality of clinical coding and administrative records and could not identify alcohol-related attendances in the A&E data set.ConclusionThis complex interdisciplinary study found that important alcohol-related harms were associated with change in alcohol outlet density. Future work recommendations include defining a research standard for recording outlet data and classification of outlet type, the methodological development of residence-based density measures and a health economic analysis of model-predicted harms.FundingThe National Institute for Health Research Public Health Research programme. Additional technical and computing support was provided by the Farr Institute at Swansea University, made possible by the following grant:Centre for the Improvement of Population Health through E-records Research (CIPHER) and Farr Institute capital enhancement. CIPHER and the Farr Institute are funded by Arthritis Research UK, the British Heart Foundation, Cancer Research UK, the Chief Scientist Office (Scottish Government Health Directorates), the Economic and Social Research Council, the Engineering and Physical Sciences Research Council, the Medical Research Council, the National Institute for Health Research, the National Institute for Social Care and Health Research (Welsh Government) and the Wellcome Trust (grant reference MR/K006525/1).

Investigation of the Association Between Alcohol Outlet Density and Alcohol-Related Hospital Admission Rates in England: Study Protocol

“…Average populations in the geographic units of analysis were approximately 17,000 and 52,000 in two studies [6,7] and >10,000 in another study (which did not provide further details) [5]. Studies in the United Kingdom used spatial scales similar to the LSOAs that we plan to use [8,9]. …”

“…Regarding evidence on outlet density and harm in the United Kingdom, there are two recent studies of note [8,9]. Fone et al examined the association between alcohol outlet density and alcohol consumption, hospital admissions, accident and emergency attendances, and crime in Wales and found evidence of association with all four of these outcomes.…”

“…Fone et al examined the association between alcohol outlet density and alcohol consumption, hospital admissions, accident and emergency attendances, and crime in Wales and found evidence of association with all four of these outcomes. However, this study did not differentiate between on-trade and off-trade outlets, and did not distinguish between admissions for acute and chronic conditions related to alcohol [8]. Richardson et al examined the association between on-trade and off-trade outlet density, and hospital admissions and mortality in the four largest cities in Scotland [9].…”

The health impacts of energy performance investments in low-income areas: a mixed-methods approach

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