University of Greifswald, Medical Faculty, Institute of Epidemiology and Social Medicine, Ernst-Moritz-Arndt University, Walther-Rathenau-Strasse 48, D-17487 Greifswald, Germany
Received 23 January 2002; in revised form 19 April 2002; accepted 3 May 2002
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ABSTRACT |
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INTRODUCTION |
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The second approach provides longitudinal data based on population-survey studies including information about causes of death. They reveal that, with increasing alcohol consumption, the risk of death from alcohol-attributable disease is elevated (Fuchs et al., 1995; Thun et al., 1997
). Among individuals formerly detected as alcohol misusers or dependents, 26% were deceased 14 years thereafter (Neumark et al., 2000
). The third approach uses data from national mortality statistics and alcohol-related relative risks of death from long-term cohort studies. Evidence shows a U- or J-shaped relationship between the amount of drinking and mortality (Andreasson, 1998
; Rehm et al., 2001
). Mortality statistics have the advantage of not suffering from three main origins of selection bias inherent in the first two approaches in which: (1) the broad scope of alcohol-attributable disease is not sufficiently reflected; (2) the reduction of the mortality risk by treatment outcome is not estimated; (3) there is data attrition by cases lost to follow-up. The mortality statistics approach is particularly suitable when all death cases are needed, including rare ones.
AAM rates have been published based on a formula by Shultz et al. (1990) (cf. Stinson and DeBakey, 1992
; Stout et al., 1993
; Sutocky et al., 1993
; Landen, 1997
). It has been amplified in recent studies (Single et al., 1999
; World Health Organization, 2000
; Ridolfo and Stevenson, 2001
). According to this approach, alcohol-attributable aetiologic fractions (AF; the proportion of cases that may be attributed to the use of alcohol) are derived based on relative risk estimates for specific causes of death from large prospective population studies in which data on alcohol consumption and smoking were collected and data on causes of death were collected in the following time period (Boffetta and Garfinkel, 1990
; Corrao et al., 1999
; Ridolfo and Stevenson, 2001
). On this basis, for the USA, 4.5% of the total mortality was estimated to be alcohol-attributable (McGinnis and Foege, 1999
), and for Canada the estimate was 3% of the total mortality (Single et al., 1999
). Based on data from Europe, increases or decreases of 1 l of pure alcohol in the per capita consumption were estimated to be associated with increases or decreases of 1.3% in all-cause mortality rates (Her and Rehm, 1998
). In Italy, 4.6% among all male and 2.0% among all female death cases have been attributed to alcohol use. Restricted to middle adult age (3664 years), in France, the rates are 19.1% of all male and 13.0% of all female death cases (Zureik and Ducimetière, 1996
). Similar to France, Germany, which showed 10.8 l of pure alcohol per capita consumption in 1997, belongs to the five countries with the highest use according to alcohol beverage industries statistics (Produktschap Voor Gedistilleerde Dranken, 2000
). In 1991, 5.4% of females and 22.0% of males (age 1864 years) were risk drinkers (Meyer et al., 1998
) according to the criteria of the British Medical Association (1995)
.
One limitation of the estimates provided so far is that age groups, gender, as well as confounding caused by tobacco smoking, have not been considered to a satisfactory degree, although such knowledge might help to clarify whether female death cases occur at a younger age than male death cases. Therefore, the goal of this contribution was to estimate the AAM specified by the AF, gender and age at death, and at the same time, to estimate how large a part of this fraction is explained by tobacco smoking.
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SUBJECTS AND METHODS |
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For the calculation of the AF, we followed the recent literature (Single et al., 1999; World Health Organization, 2000
; Ridolfo and Stevenson, 2001
), derived using the following formula:
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where RRi,j,k = relative risk of mortality in exposed groups compared with the unexposed group (RR0), Pi,j,k = proportion of the population exposed in each group. From Corrao et al. (1999) the relative risks for 25/50/100 g of pure alcohol per day were used because they were provided based on a meta-analysis of 200 studies which included a large variety of diseases. We calculated the AF. If the cause of death was attributable to tobacco smoking as well as alcohol consumption, we used the higher AF, even when results showed lives were expected to be saved by alcohol consumption.
Alcohol-related mortality (AM)
Three main groups of AM were distinguished: (1) AAM with an AF of 1 (AAM1), i.e. diseases exclusively dependent on alcohol consumption (Shultz et al., 1991): alcohol psychosis (ICD-9 291), alcohol dependence (ICD-9 303), alcohol misuse (ICD-9 305.0), polyneuropathy from alcohol misuse (ICD-9 357.5), gastritis from alcoholism (ICD-9 535.3), alcoholic liver disease (ICD-9 571.0571.3), elevated blood alcohol concentration (ICD-9 790.3), alcoholic poisonings (ICD-9 E860.0, E860.1); (2) AAM with an AF < 1 (AAM<1), i.e. diseases which show an elevated relative mortality risk due to alcohol consumption, but not to smoking, which included unspecified liver cirrhosis, liver cancer and traffic accidents under the influence of alcohol (ICD-9 155, 174, 531, 532, 571.4571.9, 577.1, E810E825; Corrao et al., 1999
). Traffic accidents were calculated based on German relative risk data (16.9% alcohol-attributable; German Federal Statistics Office, 1999b
); (3) tobacco and alcohol-attributable mortality (TAAM), i.e. further diseases which are attributable to alcohol consumption as well as tobacco smoking include several cancers and diseases of the heart and circulation (ICD-9 153, 154 according to Chao et al., 2000
; ICD-9 140150, 161, 401, 410414, 425.5, 430438 according to Shultz et al., 1991
; John and Hanke, 2002). The three groups are specified for two reasons: First, the AF of 1 (AAM1) has the highest validity and may be seen as separate from death cases with an AF estimated from longitudinal data from population samples (AAM<1). Secondly, there is a considerable synergistic effect from tobacco smoking and alcohol risk drinking (John and Hanke, 2002). Therefore, a potential overlap has to be made obvious. In total, we used 187 single diseases and a further 162 single types of accidents or poisonings. Burn deaths were not counted as part of the tobacco-attributable mortality, because no adequate data were available for Germany. Age at death and AM rates in single age groups are presented.
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RESULTS |
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DISCUSSION |
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In males, the median age at death in all alcohol-attributable cases is 7 years, and in AAM1 cases it is 15 years, below that of the male general population. In females, the median age at death in all alcohol-attributable cases is 10 years, and in AAM1 it is 24 years, below that of the female general population. Thus, the alcohol-attributable reduction of life expectancy is more drastic in females. In order to give a complete picture of mortality, the large number of TAAM cases must be taken into account, although evidence is not clear as to how large a part is due to tobacco and how large a part is due to alcohol.
The results represent the AM in a high per capita consumption country, and, as such, they are equal to the rates shown for 3564-year-olds in France for females, but not for males. The German rates are slightly lower than those found for Italy and are similar to those of Canada and the USA. These two countries show a lower per capita consumption. Thus, there are some inconsistencies compared to the other countries. These inconsistencies may be due to the fact that, with recent developments in the estimation procedure, further causes of death detected as alcohol-related are included in our analysis, which in addition, makes transparent the confounding caused by tobacco-related causes of death.
There are several methodological limitations of this study (John and Hanke, 2002a). The time span between the collection of the alcohol risk drinking data and the mortality data is only 6 years. However, besides some short-term death cases of risk drinking, such as accidents, many diseases take more years to manifest themselves as alcohol-attributable causes of death. In Germany, alcohol consumption levels have been rather stable (Produktschap Voor Gedistilleerde Dranken, 2000
). Therefore, the drinking amounts estimated for this study seem to provide valid data. The smoking- and the alcohol risk drinking-attributable mortality is not adjusted according to confounders other than those analysed by Thun et al. (2000)
. The studies according to the relative mortality risks carried out in the USA would not show the same results in European countries. We changed the alcohol-attributable death rates by traffic accidents as there are data available for Germany. Estimation methods in the area of AAM are developing continuously and are becoming more and more differentiated, e.g. in more chronic and more short-term disturbances caused by alcohol risk drinking. Up to now, in most causes of death, the international data about relative risks are by far the best, mainly because of the large sample sizes which allow the inclusion of rare diseases, and because of the long time span included. There are no comparable data from Germany. It may be suspected that the inclusion of alcohol consumption from population surveys produces large under-estimates. We did not include years of potential life lost (John and Hanke, 2002b
) and life years with disability attributable to alcohol consumption. The data shown are from a high tobacco as well as a high alcohol consumption country. Taken together, several origins of potential bias exist. But, in spite of these limitations, the data reveal higher AAM1 rates below 65 years of age than the treatment follow-up data would suggest. This is probably due to the fact that somatic diseases are included in the mortality statistics data, which are neither in the foreground of treatment follow-up nor of survey-based data. Thus, the mortality statistics results give a more complete view. Therefore, it may be concluded that AM in both genders occurs at a young adult age to a substantial degree and that prevention and early intervention are strongly suggested by these data.
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ACKNOWLEDGEMENTS |
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FOOTNOTES |
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