Department of Psychiatry, State University of New York at Stony Brook, USA, 1 Ukrainian Psychiatric Association, Kyiv, Ukraine and 2 Department of Psychiatry, Free University of Amsterdam, Amsterdam, The Netherlands
* Author to whom correspondence should be addressed at: Charles P. M. Webb, 147 Putnam Hall, South Campus Department of Psychiatry and Behavioral Science, State University of New York, Stony Brook, N.Y. 117948790. Tel.: +1(631) 6327763; E-mail: cwebb{at}notes.cc.sunysb.edu
(Received 30 September 2004; first review notified 10 November 2004; in revised form 2 February 2005; accepted 8 March 2005)
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ABSTRACT |
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INTRODUCTION |
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Information about rates of heavy drinking in former Soviet Union and Eastern bloc countries is available from government data on per capita consumption and several national and municipal surveys (Table 1). The rates of monthly heavy alcohol use range from 12% in Krakow (Bobak et al., 2004) to 82% in Udmurtia (Pakriev et al., 1998
), and rates of daily heavy use range from 3% in Lithuania (McKee et al., 2000
) to 18% in Bulgaria (Balabanova and McKee 1999
), reflecting differences in the definitions of heavy consumption, the regions surveyed and the sampling methods employed.
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Our study is the first epidemiologic study of alcohol use in Ukraine to be based on a national probability sample. Consistent with the mandate of the World Health Organization (WHO) WMH Consortium, the main interview tool was the WMH-composite international diagnostic interview (WMH-CIDI). This paper focuses on heavy alcohol use determined from questions on frequency of drinking days and the amount typically consumed. We focused on heavy alcohol use, rather than alcoholism per se, for two reasons. First, our goal was to compare the rates of heavy alcohol use in Ukraine with rates reported for other countries in the former Soviet Union. Second, heavy use is widespread in the former Soviet countries and has been linked to illness and premature death. As such, its public health significance extends beyond that of alcohol disorders in the stricter sense. In this paper, the prevalence and correlates of heavy alcohol use are presented separately for men and women.
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SUBJECTS AND METHODS |
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The Ukraine-WMH survey is based on a nationally representative sample of residents aged 18 and older from the country's 24 oblasts (counties) and the autonomous republic of Crimea. The sampling design had four stages: In the first stage, 170 primary sampling units (PSUs) were selected from the cities, towns and villages with probability proportional to size. The PSUs were drawn such that each oblast (county), and the urban and rural populations in each oblast, were represented proportionally. Second, within the PSUs, postal districts were randomly selected. Third, within each postal district, streets were randomly selected; then buildings within streets; and then, apartments within buildings. Fourth, people 18 years and older were randomly selected within apartments. The response rate was 78.3%. Study participants, compared with those who were unlocated or refusers, tended to be female (61.2% vs 49.5%) and older (48.3 vs 42.9 years).
Face-to-face interviews were carried out with 4725 respondents by the professional interview field staff of the Kiev International Institute of Sociology (KIIS) in collaboration with the Ukrainian Psychiatric Association (UPA). The paper-pencil version of the WMH-CIDI, a fully structured, modularized mental health interview schedule designed for lay interviewers, was administered. The interviewers were trained by a certified CIDI trainer over a period of 1 week.
The recruitment, consent and field procedures were approved by the Human Subjects Committees of University at Stony Brook, KIIS and UPA. Standard forward and back translation procedures were used to translate the instrument into Russian and Ukrainian languages.
Definition of heavy alcohol use
Questions about alcohol consumption in the WMH-CIDI's substance use module addressed the frequency of drinking and the number of grams of liquor (including domestically produced bootleg), wine and beer consumed over the past year on a typical drinking day. Variability was not ascertained. Quantity data were converted to grams of ethanol using suggested equivalents: 0.4 x g of liquor; 0.12 x g of wine; and 0.033 x g of beer (Treml, 1975). For men, heavy alcohol use was defined as consuming
80 g of ethanol in a typical drinking day) or consuming either
60 g 34 days/week or
40 g nearly every day. In order to adjust for gender differences in metabolism and body weight (Wechsler and Nelson, 2001
), the dose criteria was reduced by 25% for women. Thus, for women, heavy alcohol use was defined as at least monthly consumption of
60 g of ethanol in a typical drinking day or consuming either
45 g 34 days/week or
30 g nearly every day. Non-heavy users included lifetime abstainers (Table 2).
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Data analysis
Comparison of the unweighted distribution of the sample with the 2001 population census of Ukraine showed that the sample over-represented women, people >55 years of age, and those living in semi-urban settings. These biases were corrected by weighting the sample to the approximate gender, age, urbanicity and regional distributions of the 2001 census. Analyses were conducted using SUDAAN (2003). All analyses were conducted separately for men and women. Logistic regression was used to explore the relationships of the risk factors to heavy alcohol use. Tests for trend (Wald F statistic with 1 degree of freedom for the numerator) were performed for age group, urbanicity, education and financial status. We first examined each risk factor separately, and then did a multivariate analysis, where age was kept in the model irrespective of significance, while other risk factors were eliminated in a stepwise fashion in order of least significance (modified backwards elimination). The explanatory power of the model was calculated as:
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RESULTS |
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The 12-month prevalence of heavy alcohol use was 38.7% for men and 8.5% for women (OR = 6.8: 95% CI = 5.78.2, p < 0.001). The overall rate was 22.0%. Figure 1 shows that the rates were the highest in men aged 2634 years (49.7%) and 3554 years (45.5%). In women, the highest rate occurred in the 1825 age group (16.2%).
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Risk factors
The associations of the socio-demographic variables with heavy alcohol use are presented in Tables 4 and 5. The univariate ORs for men (Table 4) showed that the odds of heavy alcohol use were significantly higher in those who were in the age group of 2634 years and 3554 years, lived in the Southeast (compared with the West), had a secondary education (i.e. high school), were employed or unemployed (vs out of the labor force), and were the parent of a child under the age of 18 living at home. The final multivariate model showed that heavy alcohol users were more likely to be in the age group of 2654 years, living in the Southeast, employed or unemployed (vs out of the labor force) and the father of a young child, but the explanatory power was 5.2%.
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Figure 2 shows the significant linear trends for the prevalence of heavy alcohol use with increasing number of risk factors.
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DISCUSSION |
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Our national rates of heavy alcohol use (38.7% for men; 8.5% for women) were comparable with the estimates of monthly binge drinking in Russia reported by Bobak et al. (1999). However, there were substantial regional variations within Ukraine, with the highest rate in the Southeast region, which is heavily populated by Russian migrants of the Soviet era. It is interesting to note that two of the three regional surveys in Russia also found particularly high rates (5182% for men; 511% for women) (Pakriev et al., 1998
; Malyutina et al., 2001
). Clearly, the issue of regional variations is important for targeted public health planning, and more focused research using comparable tools and sampling techniques is needed.
A comparison of our findings with surveys elsewhere suggests that there are differences in risk factors between countries on either side of the Atlantic; i.e. the positive association of male heavy alcohol use with middle age is consistent with surveys in Russia, the Baltics and Bulgaria (Balabanova and McKee, 1999; Bobak et al., 1999
; Cockerham, 2000
; McKee et al., 2000
), as well as Britain, Germany and Spain (Bloomfield, 1998
; Meyer et al., 2000
; Mateos et al., 2002
; Schroder et al., 2004
). However, the findings differ from North American surveys in which male heavy drinking declines after age 25 (Layne and Whitehead, 1985
; Bachman et al., 2002
; Naimi et al., 2003
). Our finding that marital status is not significantly related to heavy consumption in men is consistent with those of other surveys in the former Eastern bloc (Balabanova and McKee, 1999
; Bobak et al., 1999
; Cockerham, 2000
; Malyutina et al., 2004
), but not with findings from Western epidemiologic research. Most American and European surveys find adult family responsibilities (e.g. being or becoming married or a father) to be negatively correlated with heavy drinking in men (Power and Estaugh, 1990
; Miller-Tutzauer et al., 1991
; Temple et al., 1991
; Kunz and Graham, 1996
; Gotham et al., 1997
; Hajema and Knibber, 1998
; Vik et al., 2003
). Not only did our study find marriage unrelated to heavy use, but fatherhood was positively related.
Our study focuses on the prevalence and demographic correlates of heavy alcohol use. Future population-based casecontrol and longitudinal research is needed to evaluate other risk factors, such as genetic (Wang et al., 2004), environmental (Velleman, 1992
; Farrell et al. 1995
), alcohol-specific (e.g. drinking norms, peer drinking) (Choquette et al., 1985
; Chen et al., 1994
; Lintonen and Konu, 2004
), and factors associated with historical and concurrent political and economic upheavals in Ukraine. Research focused on economic risk factors is particularly important. To the best of our knowledge, the suggested link between economic stress and heavy drinking in the former Soviet Union (Pridemore, 2002
; Walberg et al., 1998
) has not been tested with individual-level data.
Further research is also needed to fully understand the public health significance of our findings. The high prevalence of heavy alcohol use, particularly by Ukrainian men, may mean that associated costs and problems are similarly prevalent. On the other hand, its ubiquity may be a sign that heavy drinking is largely normative, and thus, non-pathological. Indeed, despite high rates of alcoholism in Ukraine (Bromet et al., 2004, World Mental Health Consortium, 2004), only 23.1% of the male and 11.2% of the female heavy users met the diagnostic criteria for an alcohol disorder. Given Ukraine's declining population, a more pressing issue is the impact of heavy alcohol use on mortality. A recent longitudinal study by Malyutina et al. (2002)
found that middle-aged, Russian men who binged on an at least monthly basis were at a higher risk for death by injury and that more intense drinkers were at risk for cardiovascular-related death. Future prospectively designed epidemiologic research is needed, which incorporates direct measurement of cardiovascular functioning, and begins with a cohort of men before the age at risk for heavy drinking. The impact of heavy alcohol use on the economy is obviously important to Ukraine during its transitional period. We found that nearly one of two employed men and one of ten employed women are heavy users. Thus, future studies should examine the effect of heavy use on occupational functioning (e.g. productivity, days missed at work).
Past prevention efforts in the former Soviet Union have been criticized for being indiscriminate and overly inclusive (Korolenko et al., 1994). The results of our multivariate analyses indicated that heavy alcohol use is demographically widespread, but that groups with a higher concentration of heavy users can be identified when risk factors are clustered. Almost two-thirds of male heavy alcohol users in our study had three or more risk factors. One preliminary study in Russia (Lukomskaia, 1997
) suggests that primary care may serve as an appropriate venue for screening and intervening with patients who have high-risk profiles (e.g. unemployed father with a high school education). Moreover, since half of the heavy alcohol users in Ukraine are employed, work settings provide obvious places to locate intervention programs. Alcohol testing is fairly common in the public and private sectors (Rice and Repo, 2000
), but nearly half of Ukraine's oblasts (counties) are without state-funded outpatient programs for prevention or treatment of cases identified in the workplace (Ministry of Health of Ukraine, 2004
).
Our study has a number of strengths, including a large national probability sample that reflects the economic conditions of Ukraine (Rhodes et al., 1999; Barnett et al., 2000
), the structured assessment, and the use of a valid index for heavy alcohol use. Nevertheless, there are a number of limitations. First, the data are based on self-report, and past studies in former Soviet Union countries have shown that self-reported data underestimates drinking compared with biomedical and sales data (Laatikainen et al., 2002
; Nemtsov, 2003
). Second, 33 potential respondents could not be interviewed because they were never sober when the interviewer tried to approach them. Third, the diagnostic instrument only determined lifetime abstinence, and hence the non-heavy use group included both users and non-users of alcohol in the past year; unfortunately, it is not possible to estimate what effect this has had on the risk factors presented here. Lastly, the sample excluded people in the military or other institutional settings where heavy drinking is a well-known problem. Thus for men, our estimates may be conservative.
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CONCLUSIONS |
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ACKNOWLEDGEMENTS |
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