Dataset Information

Estimating alcohol-attributable fractions for injuries based on data from emergency department and observational studies: a comparison of two methods.

ABSTRACT:

Aim

To compare the injury alcohol-attributable fractions (AAFs) estimated using emergency department (ED) data to AAFs estimated by combining population alcohol consumption data with corresponding relative risks (RRs).

Design

Comparative risk assessment.

Setting and participants

ED studies in 27 countries (n = 24 971).

Measurements

AAFs were estimated by means of an acute method using data on injury cases from 36 ED studies combined with odds ratios obtained from ED case-cross-over studies. Corresponding AAFs for injuries were estimated by combining population-level data on alcohol consumption obtained from the Global Information System on Alcohol and Health, with corresponding RRs obtained from a previous meta-analysis.

Findings

ED-based injury AAF estimates ranged from 5% (Canada 2002 and the Czech Republic) to 40% (South Africa), with a mean AAF among all studies of 15.4% (18.9% for males and 8.4% for females). Population-based injury AAF estimates ranged from 21% (India) to 51% (Spain and the Czech Republic), with a mean AAF among all country-years of 36.8% (42.5% for males and 22.5% for females). The Pearson correlation coefficient for the two types of injury AAF estimates was 0.09 for the total, 0.06 for males and 0.32 for females.

Conclusions

Two methods of estimating the injury alcohol-attributable fractions-emergency department data versus population method-produce widely differing results. Across 36 country-years, the mean AAF using the population method was 36.8%, more than twice as large as emergency department data-based acute estimates, which average 15.4%.

SUBMITTER: Ye Y

PROVIDER: S-EPMC6384006 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Estimating alcohol-attributable fractions for injuries based on data from emergency department and observational studies: a comparison of two methods.

Ye Yu Y Shield Kevin K Cherpitel Cheryl J CJ Manthey Jakob J Korcha Rachael R Rehm Jürgen J

Addiction (Abingdon, England) 20181121 3

<h4>Aim</h4>To compare the injury alcohol-attributable fractions (AAFs) estimated using emergency department (ED) data to AAFs estimated by combining population alcohol consumption data with corresponding relative risks (RRs).<h4>Design</h4>Comparative risk assessment.<h4>Setting and participants</h4>ED studies in 27 countries (n = 24 971).<h4>Measurements</h4>AAFs were estimated by means of an acute method using data on injury cases from 36 ED studies combined with odds ratios obtained from ED ...[more]

PMID: 30347115

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Project description:BACKGROUND: Alcohol consumption is a major risk factor for injuries; however, international data on this burden are limited. This article presents new methods to quantify the burden of injuries attributable to alcohol consumption and quantifies the number of deaths, potential years of life lost (PYLL), and disability-adjusted life years (DALYs) lost from injuries attributable to alcohol consumption for 2004. METHODS: Data on drinking indicators were obtained from the Comparative Risk Assessment study. Data on mortality, PYLL, and DALYs for injuries were obtained from the World Health Organization. Alcohol-attributable fractions were calculated based on a new risk modeling methodology, which accounts for average and heavy drinking occasions. 95% confidence intervals (CIs) were calculated using a Monte Carlo simulation method. RESULTS: In 2004, 851,900 (95% CI: 419,400 to 1,282,500) deaths, 19,051,000 (95% CI: 9,767,000 to 28,243,000) PYLL, and 21,688,000 (95% CI: 11,097,000 to 32,385,000) DALYs for people 15?years and older were due to injuries attributable to alcohol consumption. With respect to the total number of deaths, harms to others were responsible for 15.1% of alcohol-attributable injury deaths, 14.5% of alcohol-attributable injury PYLL, and 11.35% of alcohol-attributable injury DALYs. The overall burden of injuries attributable to alcohol consumption corresponds to 17.3% of all injury deaths, 16.7% of all PYLL, and 13.6% of all DALYs caused by injuries, or 1.4% of all deaths, 2.0% of all PYLL, and 1.4% of all DALYs in 2004. CONCLUSIONS: The novel methodology described in this article to calculate the burden of injuries attributable to alcohol consumption improves on previous methodology by more accurately calculating the burden of injuries attributable to one's own drinking, and for the first time, calculates the burden of injuries attributable to the alcohol consumption of others. The burden of injuries attributable to alcohol consumption is large and is entirely avoidable, and policies and strategies to reduce it are recommended.

Project description:ObjectivesThe objective was to compare the effectiveness of physician judgment and an electronic algorithmic alert to identify pediatric patients with severe sepsis/septic shock in a pediatric emergency department (ED).MethodsThis was an observational cohort study of patients older than 56 days with fever or hypothermia. All patients were evaluated for potential sepsis in real time by the ED clinical team. An electronic algorithmic alert was retrospectively applied to identify patients with potential sepsis independent of physician judgment. The primary outcome was the proportion of patients correctly identified with severe sepsis/septic shock defined by consensus criteria. Test characteristics were determined and receiver operating characteristic (ROC) curves were compared.ResultsOf 19,524 eligible patient visits, 88 patients developed consensus-confirmed severe sepsis or septic shock. Physician judgment identified 159 and the algorithmic alert identified 3,301 patients with potential sepsis. Physician judgment had sensitivity of 72.7% (95% confidence interval [CI] = 72.1% to 73.4%) and specificity of 99.5% (95% CI = 99.4% to 99.6%); the algorithmic alert had sensitivity of 92.1% (95% CI = 91.7% to 92.4%) and specificity of 83.4% (95% CI = 82.9% to 83.9%) for severe sepsis/septic shock. There was no significant difference in the area under the ROC curve for physician judgment (0.86, 95% CI = 0.81 to 0.91) or the algorithm (0.88, 95% CI = 0.85 to 0.91; p = 0.54). A combination method using either positive physician judgment or an algorithmic alert improved sensitivity to 96.6% and specificity to 83.3%. A sequential approach, in which positive identification by the algorithmic alert was then confirmed by physician judgment, achieved 68.2% sensitivity and 99.6% specificity. Positive and negative predictive values for physician judgment versus algorithmic alert were 40.3% versus 2.5% and 99.88% versus 99.96%, respectively.ConclusionsThe electronic algorithmic alert was more sensitive but less specific than physician judgment for recognition of pediatric severe sepsis and septic shock. These findings can help to guide institutions in selecting pediatric sepsis recognition methods based on institutional needs and priorities.

Project description:BACKGROUND AND AIMS:To assess the burden of excessive alcohol use, researchers estimate alcohol-attributable fractions (AAFs) routinely. However, under-reporting in survey data can bias these estimates. We present an approach that adjusts for under-reporting in the estimation of AAFs, particularly within subgroups. This framework is a refinement of a previous method conducted by Rehm et al. METHODS:We use a measurement error model to derive the 'true' alcohol distribution from a 'reported' alcohol distribution. The 'true' distribution leverages per-capita sales data to identify the distribution average and then identifies the shape of the distribution with self-reported survey data. Data are from the National Alcohol Survey (NAS), the National Household Survey on Drug Abuse (NHSDA) and the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). We compared our approach with previous approaches by estimating the AAF of female breast cancer cases. RESULTS:Compared with Rehm et al.'s approach, our refinement performs similarly under a gamma assumption. For example, among females aged 18-25 years, the two approaches produce estimates from NHSDA that are within a percentage point. However, relaxing the gamma assumption generally produces more conservative evidence. For example, among females aged 18-25 years, estimates from NHSDA based on the best-fitting distribution are only 19.33% of breast cancer cases, which is a much smaller proportion than the gamma-based estimates of approximately 28%. CONCLUSIONS:A refinement of Rehm et al.'s approach to adjusting for underreporting in the estimation of alcohol-attributable fractions provides more flexibility. This flexibility can avoid biases associated with failing to account for the underlying differences in alcohol consumption patterns across different study populations. Comparisons of our refinement with Rehm et al.'s approach show that results are similar when a gamma distribution is assumed. However, results are appreciably lower when the best-fitting distribution is chosen versus gamma-based results.

Dataset Information

Estimating alcohol-attributable fractions for injuries based on data from emergency department and observational studies: a comparison of two methods.

Aim

Design

Setting and participants

Measurements

Findings

Conclusions

Publications

Estimating alcohol-attributable fractions for injuries based on data from emergency department and observational studies: a comparison of two methods.

Similar Datasets

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