Average Volume of Alcohol Consumption, Patterns of Drinking, and All-Cause Mortality: Results from the US National Alcohol Survey

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1 American Journal of Epidemiology Copyright 200 by The Johns Hopkins University School of Hygiene and Public Health All rights reserved Vol. 53, No. Printed in U.S.A. Average Volume, Patterns of Drinking, and Mortality Rehm et al. Average Volume of Alcohol Consumption, Patterns of Drinking, and All-Cause Mortality: Results from the US National Alcohol Survey Jürgen Rehm, 4 Thomas K. Greenfield, 5,6 and John D. Rogers 5 The objective of this study was to investigate the effects of an average volume of alcohol consumption and drinking patterns on all-cause mortality. The sample (n = 5,072) was drawn from the 984 National Alcohol Survey, representative of the US population living in households. Follow-up time was until the end of 995, with 532 people deceased during this period. The authors found a significant influence of drinking alcohol on mortality with a J-shaped association for males and an insignificant relation of the same shape for females. When the largest categories of equivalent average volume of consumption were divided into people with and without heavy drinking occasions, serving as an indicator of drinking pattern, this differentiation proved important in predicting mortality. Light to moderate drinkers had higher mortality risks when they reported heavy drinking occasions (defined by either eight drinks per occasion or getting drunk at least monthly). Similarly, when the category of exdrinkers was divided into people who did or did not report heavy drinking occasions in the past, people with heavy drinking occasions had a higher mortality risk. Finally, indicating alcohol problems in the past was related to higher mortality risk. Results emphasized the importance of routinely including measures of drinking patterns into future epidemiologic studies on alcohol-related mortality. Am J Epidemiol 200;53:64 7. alcohol drinking; data collection; drinking; drinking behavior; follow-up studies; mortality Starting with the classic study by Pearl (), epidemiologic evidence on alcohol and all-cause mortality in cohorts of individuals older than 40 years of age can be summarized in a J-shaped curve (2). This hypothesis states that light to moderate consumers have a lower mortality risk compared with abstainers, while the risk for heavy drinkers is higher than that for both moderate drinkers and abstainers. Although the level of minimal risk differs for both sexes (2, 3) and also seems to differ in different cultures (4), the basic J-shape of the curve has been confirmed in the vast majority of studies (5). The J-shape persisted after the major alternative explanations brought forward were empirically tested in more recent studies. The most prominent alternative explanation was the sick quitter hypothesis (6 8), which postulates that, in established market economies with high proportions of drinkers, drinkers often quit only after having experienced medical problems as a consequence of drinking. Thus, the J- shape would disappear if lifetime abstainers were chosen as Received for publication December 8, 999, and accepted for publication April 0, Public Health Sciences, University of Applied Sciences, Hamburg, Germany. 2 World Health Organization, Geneva, Switzerland. 3 Centre for Addiction and Mental Health, Toronto, Canada. 4 Public Health Sciences, University of Toronto, Toronto, Canada. 5 Alcohol Research Group, Public Health Institute, Berkeley, CA. 6 Department of Psychiatry, University of California, San Francisco, CA. Reprint requests to Dr. Jürgen Rehm, Addiction Research Institute, Konradstr. 32, CH 8003 Zurich, Switzerland ( jtrehm@isf.unizh.ch). the reference category instead of the mixed group of all abstainers. Other alternative explanations given concerned diet (9) or social isolation (0). Rehm and Sempos (, 2) provide just one example of persistence of the J-shape after controlling for former drinkers and, for body mass index and cholesterol level as indicators for diet, Murray et al. (3) provide an example for controlling for social isolation. However, almost all studies on alcohol and mortality are based on simple measures of alcohol consumption, often as part of a food frequency measure (4, 5). Even though such measures show sufficient test-retest reliability and concurrent validity (6 9), they tend to concentrate on overall average volume and disregard patterns of drinking (20, 2). Patterns here is defined in terms of intermittently drinking heavy quantities or to intoxication, which is related to the variability of drinking per drinking occasion (22, 23). For example, within the same average volume of two drinks per day, one could drink each day two drinks without any variation, or one could drink seven drinks each Friday and Saturday. It has been shown that alcohol-related mortality, especially accidents and injuries but also cardiovascular heart disease, is considerably related to patterns of drinking irrespective of volume (24, 25). In addition, pattern-related assessment measures of alcohol consumption have been shown to be more substantially associated with mortality and other forms of alcohol-related harm than pure volume measures (26). Thus, alcohol epidemiologists have repeatedly made a case for the inclusion of pattern in epidemiologic cohort studies involving alcohol as a risk factor (2, 27). 64

2 Average Volume, Patterns of Drinking, and Mortality 65 The 984 National Alcohol Survey offered a unique opportunity to examine the relation between alcohol consumption and all-cause mortality, including measures of patterns of consumption in addition to usual volume measures. The National Alcohol Survey was a specialized alcohol survey with a multistage probability sample of the adult US national household population. The survey included a whole variety of measures of present and past alcohol consumption (28). This survey was combined with a mortality study in order to determine how patterns of drinking would influence the J-shaped curve. MATERIALS AND METHODS Study design and sample The Institute for Survey Research of Temple University conducted fieldwork for the 984 National Alcohol Survey. The stratified national household probability sample consisted of 0 primary sampling units within the 48 contiguous US states. African-American and Hispanic respondents were oversampled. Adult respondents (aged 8 years and older) were interviewed face to face and were paid for their participation. The total number of interviews completed was 5,22, with a response rate of 74 percent. Consistent with the aims specified above, this article excludes persons of ethnicity other than White, Black, or Hispanic (n 44) and with missing information on age, sex, or volume of alcohol consumption (an additional n 05 or 2.0 percent of the eligible sample). The remaining sample for the main analysis was thus 5,072. All-cause mortality served as an endpoint in all analyses. Mortality information was obtained through a search of the National Death Index. Respondent information was submitted to the National Death Index by the fieldwork contractor and shielded from inappropriate linkage with survey data by a proxy identification system. After initial screening of likely matching records in the National Death Index search, death certificates were obtained from all but one state in the sample (New York State, 8 records; however, 20 records for New York City were obtained separately), and the information was used as a further check on the accuracy of each decedent. Precoded cause-of-death information was also obtained through the National Death Index, but the overall sample size did not allow for specific analyses. Some tentative analyses are presented in the Discussion below. The number of respondents identified as having died during the study period in our sample ( ) was 532 or 0.5 percent. The number of days from the original interview in the 984 National Alcohol Survey to either December 3, 995, or the date of death was retained for use in Cox proportional hazards regression analyses. The average follow-up time was.33 (standard deviation, 0.08) years for the nondeceased and 6.2 (standard deviation, 3.5) years for the deceased. Independent variables Alcohol consumption. The estimated frequency of drinking was determined from a self-administered booklet, administered during the interview, to increase confidentiality and encourage candor. This booklet presented four versions of the question, How often do you usually have (wine/beer/drinks containing whiskey or liquor/any alcoholic beverage)? Eleven answer categories were provided, ranging from three or more times a day, two times a day, and once a day, down to never for each beverage as well as for all alcoholic beverages. Respondents who reported drinking more often than less than once a year were coded as current drinkers. The average volume of alcohol consumed was estimated with successive questions about the proportion of drinking occasions on which five or six, three or four, and one or two drinks of wine, beer, and spirits were consumed. The estimated proportions were multiplied by the implied number of drinking days for each level, and the levels were summed for a measure of total volume (29). To give two examples: If a respondent indicated an intake of seven drinks of alcohol each Friday (i.e., once a week), his average would be one drink a day, the same as the average of a respondent who drinks one drink with dinner each day. A set of mutually exclusive categories for average volume was derived from this measure, including ) lifetime abstainers, 2) former drinkers, 3) >0 drink on average per day, 4) > 2 drinks on average per day, 5) >2 4 drinks on average per day, 6) >4 6 drinks on average per day, and 7) >6 drinks on average per day. For females for most analyses, the two highest categories had to be collapsed into one (>4 drinks) because of small sample size, especially for deaths (see table 2). For males the two lowest drinking categories were collapsed into one for most analyses (>0 2 drinks/day) to allow for pattern analysis within the same volume category. Different variables were used to measure patterns of drinking (e.g., a heavy drinking rate measures the indexing variability of present and past drinking). These variables were used to divide the large categories of light and moderate drinkers as well as the former drinker category. For males, the lowest drinking category (>0 2 drinks/day) was divided into two groups: ) drinkers who neither were drunk nor had 8 drinks on at least a monthly basis during the year preceding the baseline interview (n 984) and 2) drinkers who qualified according to at least one of those criteria (n 8). For females, the drinking volume category up to one drink per day was divided the same way. This resulted in,276 females without heavy occasional drinking and 43 females with such a pattern. In previous research, the consumption of 8 drinks on one occasion has been shown to be a good predictor of alcohol problems (30). Former drinkers of both sexes were similarly divided into persons ever having had 5 drinks (males: n 20; females: n 62) and persons who never exceeded this amount (males: n 63; females: n 469). The criterion of five drinks on one occasion has emerged as the most utilized single lifetime indicator of drinking patterns in the United States (3) that may betoken alcohol-related problems. We had to use a different measure for present and past drinking because of limitations in the available data set. Other volume categories could not be divided by pattern because their overall size and/or the number of deaths did Am J Epidemiol Vol. 53, No., 200

3 66 Rehm et al. not allow for further division (see table 2). In addition, although the average volume and the pattern indicators used here correlate only moderately (e.g., the overall correlation between the average volume and the 8 indicator is about 0.5), there is high overlap in the heavy drinking categories. For instance, in the category of having >6 drinks per day on average, the pattern of having at least eight drinks on one occasion monthly is quite common (73 percent). For separate analyses, past alcohol problems were operationalized by respondent reports of either having 5 drinks on a weekly basis or by having felt that their drinking was no longer under control in any year between 973 and 983, the year before the baseline assessment. Covariates. Based on the literature, the following variables were controlled, to avoid confounding: income as a proxy for social class (32, 33): dichotomized with referring to the upper third of the income distribution; marital status (34): dichotomized with referring to married individuals; and smoking status (2): dichotomized with referring to smokers. No data were available on the average dose of smoking. Other potential confounders such as diet (e.g., the healthy diet indicator (35)) or physical activity (34, 36) could not be included, as there were no suitable variables assessed in the National Alcohol Survey. Statistical analyses The Cox proportional hazard model was applied as the main tool of analysis (37). The assumption of proportional hazards was examined by visual inspection for the different sex, ethnicity, and volume categories (38). Because previous research strongly suggests a difference in risk curves for males and females (2, 3), analyses were conducted separately by sex. Ethnicity had a significant main effect only in females but was retained in all final models for both sexes. Interactions between alcohol consumption and ethnicity were not significant and thus dropped from the final models. All analyses were adjusted for age as a linear term in the regression equation. This adjustment was chosen after age, the exponential value of age, and age-squared were compared with regard to their influence on mortality, and for both sexes the linear age term had a better fit than a squared or exponential age term. The addition of squared age did not add significantly to models with age alone, as indicated by the maximum likelihood ratio test. Unweighted analyses were used based on the Groves (39) argument distinguishing between analytical and etiologic research, where no weights should be applied, and descriptive research, where weighting is appropriate. Following this distinction, the prevalence rates of risk factors and confounding factors are provided as weighted percentages. RESULTS Table provides an overview of the population distribution of the variables by sex. As expected, high volume drinking categories, past problems with alcohol, smoking, and also higher income were more prevalent in males than in females. Table 2 provides the numbers of males and females in different (average) volume categories, associated crude death rates, and age- and ethnicity-adjusted relative mortality risks. As indicated above, because of small numbers, high volume drinking categories could not be used separately for females for further analyses. The reference category for all relative risk and percentage comparisons in this article was lifetime abstainers. Table 3 shows the relative risks for different drinking categories for males adjusted either for age and ethnicity only or for all covariates. Overall, alcohol had a significant relation on allcause mortality in both models. As predicted, when considering the average volume alone, independent of pattern, the form of the relation between the volume of drinking and mortality resembled a J-shape, with the following relative risks: lifetime abstainer: ; >0 2 drinks:.0; >2 4 drinks: 0.73; >4 6 drinks: 0.93; >6 drinks: 2.29; in addition to the J-shape for volume: exdrinker:.50. The relative risks for exdrinker and >0 2 drinks were not shown in table 3, where data for these drinking categories were divided by pattern. Two drinking categories had smaller risks than that for lifetime abstainers, with heavy drinking constituting the highest mortality risk. However, the most striking feature of table 3, which includes the pattern indicators, was the influence of those patterns on mortality in the two relevant groups. Both for the group of former drinkers and for the light to moderate drinking category, there were substantial differences when respondent categories were divided by occasional heavy drinking status, for example, if they reported consuming alcohol regularly only in moderate quantities or if they had spikes of heavy drinking occasions. For males, in groups with occasional high quantity drinking, the risks were more than 70 percentage points above the risks for peers at the same volume but without this pattern of occasional high quantity drinking (all percentage points relative to lifetime abstainers). In the model adjusted for potential confounders (table 3), the picture did not change substantially. As expected, because of the correlation between heavy drinking and smoking, the relative risks for the heavy average volume and heavy occasional drinking categories decreased little compared with the model adjusted for age and ethnicity only. The potential confounding factors themselves showed the expected relations: higher income and being married were related to lower risks for mortality (data on marital status not shown; see below), whereas smoking was related to a higher mortality risk. In both sexes, the relation between marital status and mortality did not achieve significance, and this variable was therefore dropped for the final models. In females, we see approximately the same pattern of results as in males, but differences between drinking categories were much weaker, and neither the effect of overall consumption nor any comparisons with lifetime abstention approached significance (table 4). Besides the expected Am J Epidemiol Vol. 53, No., 200

4 Average Volume, Patterns of Drinking, and Mortality 67 TABLE. Descriptive statistics of exposures at baseline assessment, National Alcohol Survey, * No. Males % Weighted % Females No. % Weighted % Drinking categories at baseline Lifetime abstainer Current abstainer >0 drink/day on average > 2 drinks/day on average >2 4 drinks/day on average >4 6 drinks/day on average >6 drinks/day on average Eight drinks or more per occasion at least monthly Eight drinks or more at least once during last year Drunk at least once a month (past year) Past problematic drinking ( ) , Other exposures or control variables White Black Hispanic Married High income Smoking , * Based on sample with full information on ethnicity, age, gender, alcohol consumption, and mortality status (n = 3,035 for females and n = 2,037 for males) ,07,86 832, effect for age as an adjustment factor, only the difference between White females and Hispanic females was significant. With the known problems of correctly identifying Hispanic names in National Death Index searches and the fact that a substantial number of Hispanics move back to the countries of their origin after a period of working in the United States, this effect may well be due to methodological problems. The methods used for finding Hispanic deaths were restricted to US sources (40). Multivariate analyses showed small changes in the same direction as for males but did not change the picture. The only bigger difference was the fact that income was related to mortality to a lesser degree than in males. In separate analyses, past problems with drinking were also related significantly to higher mortality for both males and females (table 5). This relation remained stable after adjusting for the volume of drinking at baseline. For females, the relative risk associated with past problems with TABLE 2. Drinking categories and numbers of deaths, National Alcohol Survey, No. No. of deaths Males Crude death rate (%) Adjusted RR* No. No. of deaths Females Crude death rate (%) Adjusted RR* Lifetime abstainer Current abstainer >0 drink/day on average > 2 drinks/day on average >2 4 drinks/day on average >4 6 drinks/day on average >6 drinks/day on average , N/A* Total 2, , * RR, relative risk, adjusted for age and ethnicity; N/A, not applicable. RR differs significantly from lifetime abstainers. Am J Epidemiol Vol. 53, No., 200

5 68 Rehm et al. TABLE 3. Relative mortality risk (RR) for different drinking categories adjusted for other risk and protective factors, males, National Alcohol Survey, Lifetime abstainer Current abstainer without past Current abstainer with past occasional heavy drinking >0 2 drinks/day on average without >0 2 drinks/day on average with >2 4 drinks/day on average >4 6 drinks/day on average >6 drinks/day on average Alcohol consumption overall effect RR adjusted for age and ethnicity 95% CI* , , , , , , , 4.48 Wald 2.64; df = 7 p < 0.0 Full multivariate model RR 95% CI , , , , , , , 4.23 Wald 7.8; df = 7 p < 0.05 Covariates White Black Hispanic Income Smoking.9 0.9, ,.27 Not applicable Not applicable , , , ,.62 * CI, confidence interval. At least marginally significantly different from the reference group. The Wald test indicates if there are any significant differences between different categories of alcohol consumption with respect to mortality. TABLE 4. Relative mortality risk (RR) for different drinking categories adjusted for other risk and protective factors, females, National Alcohol Survey, Lifetime abstainer Current abstainer without past Current abstainer with past occasional heavy drinking >0 drink on average without >0 drink on average with > 2 drinks/day on average >2 4 drinks/day on average >4 drinks/day on average Alcohol consumption overall effect Covariates White Black Hispanic Income Smoking RR adjusted for age and ethnicity 95% CI* , , , , , , , 4.34 Wald 3.9; df = 7; n.s.* , , 0.88 Not applicable Not applicable Full multivariate model RR 95% CI , , , , , , , 3.86 Wald 3.8; df = 7; n.s , , , ,.86 * CI, confidence interval; n.s., not significant. The Wald test indicates if there are any significant differences between different categories of alcohol consumption with respect to mortality. At least marginally significantly different from the reference group. ` Am J Epidemiol Vol. 53, No., 200

6 Average Volume, Patterns of Drinking, and Mortality 69 TABLE 5. Relative risks (RRs)* for past problematic drinking by sex, adjusted for other protective and risk factors, National Alcohol Survey, Past problematic drinking alcohol was around 2.2 and larger than for males (relative risk.6). DISCUSSION RR Males Females 95% CI RR 95% CI 0.98, , * Relative risks are compared with lifetime abstention. Adjusted by age and ethnicity. CI, confidence interval. Model adjusted for volume of drinking..2, , 4.42 Results confirmed those in the existing literature but additionally point a way to go beyond current knowledge. The volume of drinking and mortality showed a curvilinear relation for both sexes even though this relation was not significant for females. Neither choosing lifetime abstainers as a reference category nor adjusting for social class, smoking, or marital status altered the basic J-shaped relation. Thus, the use of more sophisticated assessment methods for the volume of alcohol consumption alone did not yield different results from previous epidemiologic work based on simple food frequencies. Overall, the J-shaped curve seems to be remarkably stable and independent of assessment measures (4). However, including measures assessing patterns of drinking at baseline and for past drinking revealed new insights into the relations between alcohol and all-cause mortality. Even within the same category of volume of drinking, a division based on patterns yielded different results. Indications of monthly heavy drinking ( 8 drinks or intoxication) in light to moderate drinkers or of any heavy drinking in exdrinkers ( 5 drinks) were associated with about 70 percent higher relative risks compared with no heavy drinking at all in the same categories. For female former drinkers, the effect amounted to an 80 percent increase, and there was a difference of about 35 percent for female light drinkers (up to one drink a day on average). However, it must be noted that the overall effect of alcohol consumption on all-cause mortality was not significant for females. Looking into the causes of death by sex in our sample, there were no overall significant differences when the causes of death were divided into neoplastic, cardiovascular, cerebrovascular, accidental, and other categories. The largest difference in categories was for accidental causes of death (7 percent for males vs. 4 percent for females; odds ratio.8, 95 percent confidence interval: 0.85, 3.85). Together with the relatively small sample sizes for the heavy average and heavy drinking pattern categories in females, this difference may have contributed to the fact that, for this gender, no significant relation emerged. The effect of patterns within the low to moderate volume category of drinking found here cannot be explained by the correlation between volume and pattern as suggested by Mäkelä (42) in discussing the results of drinking patterns on social problems. First, the within-category correlation is not that high ( correlation between volume and pattern within the categories used), and second, the curve for allcause mortality is not linear as in many social problems; in this instance, a higher average volume does not automatically lead to higher risks of mortality. Consequently, the category with the lowest mortality risk for males here was drinking >2 4 drinks and for females, > 2 drinks. Thus, investigating pattern effects allows consideration of a new dimension of drinking that is, at least for the lower drinking categories, independent of volume and that appears to influence mortality independently of volume (43, 44). In this sense, including drinking patterns in assessments of alcohol consumption in mortality studies is necessary to capture this independent dimension. Based on the present results, the main contribution of pattern measures is not to improve volume estimates, which seems to be the main thrust of recent publications on the topic of improved alcohol measures (9, 45), but to contribute independently to explaining the outcome. In the data presented, for example, males drinking up to two drinks a day had a risk relative to that of lifetime abstainers of.07 without monthly heavy drinking occasions but a risk of.84 when they had such heavy drinking occasions (table 3). Thus, within the same range of average volume of consumption, the risks of allcause mortality associated with the pattern of obtaining that volume differed quite substantially. The reason for the relation of drinking patterns to overall mortality may be that certain patterns of drinking, especially frequent heavy drinking/intoxication, more closely relate to acute causes of death. Instances of of people who on average are drinking lightly to moderately on average are one aspect of the prevention paradox in alcohol epidemiology (46, 47). Risk function analyses among survivors have found that, at low volumes, risks of injuries (48), driving while drinking (49), and even alcohol dependence symptoms (50) are largely limited to those who at least occasionally drink heavy quantities. Therefore there are several plausible mechanisms for excess mortality with this pattern of consumption. Given our overall sample size, the cause of death data collected did not allow for detailed analysis of causes of death by sex and drinking pattern, controlling for such other variables as age. However, among the 3 people who died an accidental death, there was a more than 0 percent higher proportion of people with 5 drinks on any occasion during the last year and a 6 percent higher proportion of people with 8 drinks on any occasion during the last year compared with the general population. This can serve only as a preliminary indication because of the small sample involved. However, taken together with the emerging literature on patterns, it is recommended that all future epidemiologic studies involving alcohol should include patterns of drinking measures, such as the graduated frequency approach (26), and that these patterns should be analyzed as an additional dimension to volume (5). The results also indicate that past problem drinking was also related to higher mortality. This finding underlined Am J Epidemiol Vol. 53, No., 200

7 70 Rehm et al. again the importance of making the distinction between lifetime and current abstainers (exdrinkers), some of the latter group being past problem drinkers (6, 7). In many epidemiologic studies, even recent ones, this distinction was not made, leading to an overestimation of the protective effect of moderate drinking on mortality (52). It is also important to explore this effect further. How long does it persist? Under what conditions does the mortality risk of ex-problem drinkers reverse to normal, for example, to the risk level of lifetime abstainers or moderate drinkers? Such questions are important for planning public health remedies. They can be addressed only if future alcohol epidemiology is based on measures capturing drinking patterns, reliable and valid measures of past consumption or problems, and improved research designs incorporating repeated measures to track changes in drinking and to relate them to mortality (8). 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