Estimating Uncertainty of Alcohol-Attributable Fractions for Diseases
Author Information
Author(s): Gerrit Gmel, Kevin D. Shield, Hannah Frick, Tara Kehoe, Gerhard Gmel, Jürgen Rehm
Primary Institution: Centre for Addiction and Mental Health (CAMH)
Hypothesis
This article aims to present a method to calculate confidence intervals for alcohol-attributable fractions (AAFs) derived from different meta-analyses.
Conclusion
The method yielded very accurate values for variances of alcohol-attributable fractions within reasonable computation time.
Supporting Evidence
- Alcohol is a major risk factor for disease burden globally.
- The method allows for accurate estimation of variances for alcohol-attributable fractions.
- 150,000 samples provided sufficient accuracy for confidence intervals.
- Variances indicate that some disease categories require more research on dose-response relationships.
Takeaway
The study shows how to calculate the uncertainty of health risks from alcohol consumption, helping us understand its impact on diseases better.
Methodology
The study used a Monte Carlo approach to derive variances for alcohol-attributable fractions by generating random sets of parameters.
Potential Biases
There is a risk of bias due to reliance on adjusted relative risks and potential undercoverage of alcohol consumption.
Limitations
The use of adjusted relative risks may lead to biased results due to undercoverage of alcohol consumption in studies.
Participant Demographics
The study focused on men aged 15 to 34 years in five Asian regions.
Statistical Information
Confidence Interval
95%
Digital Object Identifier (DOI)
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