The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Alcohol and mortality: methodological and analytical issues in aggregate analyses
Abstract
This supplement includes a collection of papers that aim at estimating the relationship between per capita alcohol consumption and various forms of mortality, including mortality from liver cirrhosis, accidents, suicide, homicide, ischaemic heart disease, and total mortality. The papers apply a uniform methodological protocol, and they are all based on time series data covering the post‐war period in the present EU countries and Norway. In this paper we discuss various methodological and analytical issues that are common to these papers. We argue that analysis of time series data is the most feasible approach for assessing the aggregate health consequences of changes in population drinking. We further discuss how aggregate data may also be useful for judging the plausibility of individual‐level relationships, particularly those prone to be confounded by selection effects. The aggregation of linear and curvilinear risk curves is treated as well as various methods for dealing with the time‐lag problem. With regard to estimation techniques we find country specific analyses preferable to pooled cross‐sectional/time series models since the latter incorporate the dubious element of geographical co‐variation, and conceal potentially interesting variations in alcohol effects. The approach taken in the papers at hand is instead to pool the country specific results into three groups of countries that represent different drinking cultures; traditional wine countries of southern Europe, beer countries of central Europe and the British Isles and spirits countries of northern Europe. The findings of the papers reinforce the central tenet of the public health perspective that overall consumption is an important determinant of alcohol‐related harm rates. However, there is a variation across country groups in alcohol effects, particularly those on violent deaths, that indicates the potential importance of drinking patterns. There is no support for the notion that increases in per capita consumption have any cardioprotective effects at the population level.
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Citations
Cites
What To Do (and Not to Do) with Time-Series Cross-Section Data
Beck, N., & Katz, J. N. (1995) · American Political Science Review · doi:10.2307/2082979 · Cited by 6,840
Cited by
Popova, S., Giesbrecht, N., Bekmuradov, D., & Patra, J. (2009) · Alcohol and Alcoholism · doi:10.1093/alcalc/agp054 · Cited by 494
Chronic diseases and conditions related to alcohol use
Shield, K. (2013) · Alcohol Research: Current Reviews · doi:10.35946/arcr.v35.2.06 · Cited by 488
“…conditions, including even diseases such as cirrhosis, a large degree of the effects caused by changes in alcohol consumption can be seen immediately at the population level (Holmes et al. 2011; Leon et al. 1997; Zatonski et al. 2010; for a general discussion see Norström and Skog 2001; Skog 1988).”
BackgroundHolmes, J., Meier, P. S., Booth, A., Guo, Y., & Brennan, A. (2012) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2011.12.005 · Cited by 112
Alcohol and violence: use of possible confounders in a time‐series analysis
Bye, E. K. (2007) · Addiction · doi:10.1111/j.1360-0443.2006.01701.x · Cited by 72
Population drinking and liver cirrhosis mortality: is there a link in eastern Europe?
Ramstedt, M. (2007) · Addiction · doi:10.1111/j.1360-0443.2007.01872.x · Cited by 51
Metadata
- Authors
- Norström, T., & Skog, O.
- Venue
- Addiction
- Publisher
- Wiley
- Published
- 2001-02
- Volume
- 96
- Issue
- 1s1
- Pages
- 5-17
- ISSN
- 0965-2140 (ISSN-L)
- 1360-0443
- OpenAlex
- W2091351434
- Cited by
- 191
- References
- 1
- FWCI
- 4.57
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.