Álvaro Castillo-Carniglia1, Jay S Kaufman2, Paulina Pino3. 1. Doctoral Program in Public Health, University of Chile, Av. Independencia 939, Santiago, Chile; Research Department, National Service for Prevention and Rehabilitation of Drug and Alcohol Consumption (SENDA), Chile. Electronic address: alvacasti@gmail.com. 2. Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, 1020 Pine Ave. West, Montreal, Quebec, Canada. Electronic address: jay.kaufman@mcgill.ca. 3. Epidemiology Division, School of Public Health, University of Chile, Av. Independencia 939, Santiago, Chile. Electronic address: ppino@med.uchile.cl.
Abstract
OBJECTIVE: To describe the distribution of alcohol-attributable mortality (AAM) at the local level (345 municipalities) in Chile, including fully and partially attributable causes in 2009. METHODS: AAM was estimated for the population 15years of age and older using per capita alcohol consumption combined with survey estimates. The effect of alcohol on each cause of death was extracted from the published scientific literature. We used Bayesian hierarchical models to smooth the Standardized Mortality Ratio for each municipality for six groups of causes related to alcohol consumption (total, neuro-psychiatric, cardiovascular, cancer, injuries and other causes). RESULTS: The percentage of municipalities with high risk for any group of causes in each region ranges from 0% to 87.0%. Municipalities with high risk were concentrated in south-central and southern Chile for all groups of causes related to alcohol. CONCLUSIONS: AAM risk shows marked geographic concentrations, mainly in south-central and southern regions of Chile. This combination of methods for small-area estimates of AAM is a powerful tool to identify high risk regions and associated factors, and may be used to inform local policies and programs.
OBJECTIVE: To describe the distribution of alcohol-attributable mortality (AAM) at the local level (345 municipalities) in Chile, including fully and partially attributable causes in 2009. METHODS: AAM was estimated for the population 15years of age and older using per capita alcohol consumption combined with survey estimates. The effect of alcohol on each cause of death was extracted from the published scientific literature. We used Bayesian hierarchical models to smooth the Standardized Mortality Ratio for each municipality for six groups of causes related to alcohol consumption (total, neuro-psychiatric, cardiovascular, cancer, injuries and other causes). RESULTS: The percentage of municipalities with high risk for any group of causes in each region ranges from 0% to 87.0%. Municipalities with high risk were concentrated in south-central and southern Chile for all groups of causes related to alcohol. CONCLUSIONS: AAM risk shows marked geographic concentrations, mainly in south-central and southern regions of Chile. This combination of methods for small-area estimates of AAM is a powerful tool to identify high risk regions and associated factors, and may be used to inform local policies and programs.
Authors: Jose I Nazif-Muñoz; Brice Batomen; Youssef Oulhote; Jack Spengler; Arijit Nandi Journal: J Epidemiol Community Health Date: 2020-04-01 Impact factor: 3.710