or dependence

Journal of Substance Abuse, 6, 381-392 (1994)

A Study of the Gender Differences in Morbidity Among Individuals Diagnosed With Alcohol Abuse and/or Dependence S. Patricia Chou Deborah A. Dawson National Institute on Alcohol Abuse and Alcoholism

The majority of studies on medical consequences of excessive alcohol consumption have been carried out with male subjects, mostly from clinical or hospitalized sa,nples. The purpose of this report was to study differences in morbidity outcomes of men and women anaong respondents diagnosed with alcohol abuse and/or dependence. Utilizing data from the 1988 National Health Interview Survey, this study compared several indicators of physical morbidity among male and female respondents meeting the criteria for Diagnosttc and Stattsttcal Manual of Mental Disorders (DSM-III-R; American Psycluatric Association, 1987) alcohol abuse and/or dependence. The resuhs revealed complex gender differences, not all of which can be explained by differences in sociodemographic characteristics or drinking practices. Moreover, the results indicated that it is inadequate to generalize results based on morbidity data of men with alcohol abuse and/or dependence to their female counterparts or female drinkers, hnplications of these findings are discussed.

T h e r e is a large literature d o c u m e n t i n g the i n c r e a s e d risks o f m o r b i d i t y a n d m o r t a l i t y associated with heavy alcohol use. I n a r e c e n t review o f the m e d i c a l c o n s e q u e n c e s o f alcohol c o n s u m p t i o n , the U.S. D e p a r t m e n t o f H e a l t h a n d H u m a n Services ( U S D H H S , 1990) cited effects o f alcohol o n a l m o s t every h u m a n o r g a n system, with the m o s t p r o n o u n c e d rates o f excess m o r b i d i t y a n d m o r t a l i t y d u e to liver disease, diseases o f the circulatory a n d r e s p i r a t o r y systems, a n d s o m e types o f c a n c e r (Wilkinson, 1980). T h e elevated levels o f m o r t a l i t y a n d hospitalization a m o n g alcoholics a n d heavy d r i n k e r s also reflect the c o n t r i b u t i o n o f accid e n t a l a n d i n t e n d e d injury, which a r e s t r o n g l y associated with alcohol use ( U S D H H S , 1990). Most o f the early studies o f the health effects o f alcohol c o n s u m p t i o n w e r e c a r r i e d o u t with clinical s a m p l e s o f alcoholics, largely o r totally c o m p o s e d o f m e n . For lack o f c o n t r a d i c t o r y evidence, it was a s s u m e d t h a t t h e effects o f alcohol o n m o r b i d i t y a n d mortality were essentially the s a m e f o r m e n as f o r w o m e n . H o w e v e r , m o r e r e c e n t r e s e a r c h based o n e i t h e r g e n e r a l p o p u l a t i o n s a m p l e s o r s a m p l e s o f b o t h male a n d f e m a l e alcoholics a n d / o r hospital p a t i e n t s suggests Correspondence and requests for reprints should be sent to S. Patricia Chou, Division of Biometry and Epidemiology, National Institute on Alcohol Abuse and Alcoholism, Suite 514, 6000 Executive Boulevard, Bethesda, MD 20892-7003. 381

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that the effects of alcohol consumption on health may in fact differ between men and women. In her review of gender differentials in morbidity among alcoholics, Wilkinson (1980) cited a number of areas in which male and female alcoholics have been shown to differ. Women have greater adverse effects on liver function, a higher incidence of dementia, and more frequent problems with folate deficiency. Similarly, Glenn, Parsons, and Stevens (1989), who compared small samples of alcoholic and nonalcoholic men and women in terms of medical history, alcohol-related disorders, and trauma history, controlling for family history, found more adverse effects of alcoholism among women. Worner and Lechtenberg (1991) studied men and women admitted for alcohol detoxification and found more electroencephalogram (EEG) abnormalities among women, but no difference in focal neurological deficits or history of seizures. In their study of men and women with alcoholic liver disease, Rabinovitz, Van Thiel, Dindzans, and Gavaler (1989) found a greater prevalence of gastric ulcers among women, but no gender difference in the prevalence of other gastrointestinal complications. In summary, evidence suggests that excessive alcohol consumption may have different effects on health outcomes in men and women, but these differentials are neither consistent nor fully understood in terms of their etiology. In studying gender differences in health outcomes among alcoholics, differences in the drinking styles of male and female alcoholics must be considered. It is well documented that female alcoholics begin drinking at a later age and have a shorter interval from first drink to onset of alcohol-related problems (Beckman, 1976; Blume, 1986). Ross (1989), who studied a sample of male and female treated alcoholics, found that men were significantly more likely than women to have been drunk more than once prior to age 15, to have drunk the equivalent of a fifth of liquor in a day, and to have drunk the equivalent of seven drinks per day for 2 weeks. Olenick and Chalmers (1991) studied a group of treated alcoholics and a control group drawn from the nearby community and found that within both groups, men had higher scores for sustained drinking style and daily quantity of alcohol, as measured by the Alcohol Use Inventory (AUI) scales. Because factors such as drinking patterns and the level of alcohol consumption are likely to affect health outcomes, gender differences in these aspects of drinking must be accounted for when comparing the morbidity of male and female alcoholics. This study compares four indicators of physical morbidity among respondents classified with alcohol abuse and/or dependence, using data from the 1988 National Health Interview Survey (NHIS). The morbidity indicators are restriction of activity due to illness, doctor consultations, hospitalizations excluding delivery, and days spent in bed due to illness. The sample consists of 3,731 men and women who met the Diagnostic and Statistical Manual of Mental Disorders (DSM-III-R; American Psychiatric Association, 1987) criteria for past-year alcohol abuse and/or dependence. Multivariate analyses were adjusted for the confounding effects of sociodemographic factors, drinking practices, and smoking history. The results for these individuals with alcohol abuse and/or dependence were compared with those from a more general population, all men and women

Gender Differences in Morbidity Among Heavy Alcohol Users

383

who drank at least 12 drinks in the year preceding the NHIS interview. Selection of this population was guided by the desire to adjust for the same factors, including drinking practices, as in the analysis of the sample of respondents with an alcohol use disorder.

METHOD Sample Design This report was based on the merged file of the Core questionnaire, the Alcohol supplement, and the Occupational Health supplement of the 1988 National Health Interview Survey (NHIS). This survey is a nationwide household interview survey conducted by the National Center for Health Statistics (1989). Basic health and demographic information were collected for all individuals within each sample household. The NHIS featured a complex multistage sample design (Massey, Moore, Parsons, & Tadros, 1989). The sampling was both stratified and clustered. Blacks were oversampled to provide adequate numbers for data analysis. Health and demographic data on the Core questionnaire were collected for all 122,310 individuals in the sample households. Questions on smoking habits appeared on the Occupational Health supplement, whereas the Alcohol supplement contained information about drinking practices and related problems. For both supplements, one sample adult 18 years old or older was randomly selected from each household. After merging, a total of 43,763 individuals remained on the file. Among them, 22,084 were current drinkers (classified as having at least 12 drinks in the preceding 12 months). Also, 3,731 met the D S M - I I I - R criteria for past-year alcohol abuse and/or dependence. DSM-III-R

Diagnoses

The 1988 N H IS Alcohol supplement contained a series of questions that were used to assess the presence of symptoms of alcohol abuse or dependence during the year preceding the NHIS interview. To derive a D S M - I I I - R diagnosis, symptom items or questions appearing on the NHIS questionnaire were matched with each of the abuse and dependence criteria. A diagnosis of alcohol abuse required that the respondent demonstrate either a pathological drinking pattern characterized by continued drinking despite a persistent or recurrent social, occupational, psychological, or physical problem that was caused or exacerbated by drinking, or recurrent drinking in situations where alcohol use was hazardous. A diagnosis of alcohol dependence required fulfillment of at least three of the nine diagnostic criteria for dependence. In order to satisfy the D S M - I I I - R duration criterion for alcohol abuse, at least one symptom of abuse must have occurred two or more times during the preceding year. Likewise, to satisfy the D S M - I I I - R duration criterion for alcohol dependence, one or more symptoms for at least two of the positive diagnostic criteria must have occurred twice or more in the last year. The correspondence of the NHIS symptom item

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questions with the diagnostic criteria has been presented elsewhere (Grant et al., 1991).

Study Variables Sociodemographic Variables In studying gender differences in physical morbidity among those with alcohol use disorders, gender differences in sociodemographic characteristics must also be considered. The following sociodemographic variables, implicated in the literature as potential confounders or modifiers of the gender differences in morbidity, were included in the analysis: age in years, race (1 = Black, 0 = nonBlack), marital status (1 -- currently married, 0 = all others), poverty status (1 = below poverty threshold, 0 = otherwise), and education (1 = below high school education, 0 = otherwise). Poverty status was determined based on family size, number of children under 18 years of age, and family income using the 1986 poverty levels derived from the 1987 Current Population Survey conducted by the Bureau of Census (National Center for Health Statistics, 1989). An additional variable also was included that indicates whether the health information collected on the respondent was self-reported (1), or reported through a proxy (0). In addition, the adverse effect of cigarette smoking on health was accounted for by dichotomizing the smoking status into ever smokers (1) versus never smokers (0).

Alcohol Variables To account for the fact that there are substantial sex differences in drinking practices, several alcohol consumption variables were considered in this study: logarithm transformation of average daily ethanol consumption in ounces, age of first drink in years, daily drinker (1 = yes, 0 = no), ever drank 5 + (ever drank five or more drinks on at least one occasion in the past year; 1 = yes, 0 = no), and most recent drink occurred prior to the 2 weeks immediately preceding the interview (1 = yes, 0 = no). The model also included a term representing total body water, measured in liters according to Moore et al. (1963). Including a measure of total body water was necessitated by the fact that gender differences in body composition affect ethanol absorption. Also, the logarithm transformation of average daily ethanol intake was implemented to linearize the relationship between this variable and the morbidity outcomes.

Morbidity Measures According to Last (1988), morbidity is "any departure, subjective or objective, from a state of physiological or psychological well-being. In this sense, sickness, illness, and morbid conditions are similarly defined and synonymous" (p. 83). Clarke (1983) argued that illness is a multifaceted and complex phenomenon with large variability in definitions and measurements. For the purposes of this report, four dichotomous measures of morbidity were defined: (1) whether the respondent had any restricted activity days during the 2 weeks immediately preceding the interview, (2) whether the respondent consulted with a physician during the

Gender Differences in Morbidity Among Heavy Alcohol Users

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2 weeks prior to the interview, (3) whether the respondent had been hospitalized for reasons other than delivery during the 12 months preceding the interview, and (4) whether the respondent had stayed in bed for more than 2 weeks during the last 12 months.

Statistical Analysis Multiple logistic regression was performed to account for the potential confounding and modifying effects of the sociodemographic and alcohol variables. Sex (1 = female, 0 = male) was the exposure variable of interest. The various indicators of physical morbidity just mentioned were the outcome measures. In addition, all first-order interaction terms involving the sex variable and the model covariates were included in the analysis to identify important modifiers. A twostep approach was taken. At the first step, only smoking and sociodemographic variables were included in the logistic model. Next, variables on consumption level and drinking pattern were added, to study the extent to which the gender differences in drinking behavior would modify the observed gender difference in morbidity when only sociodemographic variables were taken into account. Within each step, the logistic regression analysis was performed in stages to (a) eliminate any nonsignificant cross-product or interaction terms (p > .05), and (b) eliminate any nonconfounders, that is, nonsignificant main effect terms not involved in any significant interactions and whose removal did not affect the parameter estimates. Standard errors of the estimated logistic regression parameters were calculated by the SUDAAN software (Research Triangle Institute, 1992). Statistical procedures of this software utilize the first-order Taylor series approximation to take into account the stratified and clustered sampling characteristics of the NHIS. The standardized regression coefficients also were calculated, which make direct comparisons of the relative importance of the explanatory variables possible.

RESULTS Table 1 presents the characteristics of the respondents classified with alcohol abuse and/or dependence by sex. The majority of those diagnosed were younger adults in the 18- to 29- or 30- to 44-year-old age groups, currently married or ever married, non-Black, and with incomes at or above the poverty threshold. No substantial gender differences were noted in terms of the sociodemographic characteristics. With respect to the pattern and level of alcohol consumption, however, Table 1 indicates that men were more likely than women to be daily drinkers, and to be classified as heavy drinkers (average daily ethanol consumption -> 1.0 ounce [29.57 ml]). Figure 1 shows the overall prevalence rates and the gender-specific rates for all four measures of morbidity. Each of these morbid conditions was more prevalent among women than among men. Figure 1 also indicates that the morbidity indicators based on a 2-week reference period--restricted activity days and con-

S.P. Chou and D.A. Dawson

386

Table 1. Characteristics of Respondents Classified With D S M - I I I - R Alcohol Abuse and/or Dependence Men

Age 18-29 30-44 45-64 ->65 Marital Status Married Widowed/separated/divorced Single Race Black Non-Black Poverty Status Below poverty level At/above poverty level Type of Drinker Light Moderate Heavy Daily Drinker Ever Drank 5+ c Total

Women

~a

lib

~a

nb

48.0 35.0 14.0 2.9

1142 942 371 87

59.6 28.7 10.2 1.5

683 372 114 20

49.0 12.4 38.6

1040 459 1043

44.5 18.2 37.3

403 304 482

6.9 93.1

197 2345

6.7 93.3

117 1072

10.8 89.2

330 2212

16. I 83.9

263 926

16.1 43.3 40.6 24.3 77.0

400 1080 1062 643 1952 2542

30.7 46.1 23.2 12.2 68.6

349 559 281 152 805 1189

aBased on weighted data. Components may not sum to 100% due to rounding. bBased on unweighted data. ~Everdrank five or more drinks on at least one occasion during the past year.

sultation with p h y s i c i a n s - - w e r e m o r e prevalent than those indicators associated with a 12-month reference period (i.e., hospitalization and bed days l o n g e r than 2 weeks). T h e morbidity indicator o f consultation with a physician had the largest g e n d e r difference, whereas the morbidity indicator o f hospitalization showed the least g e n d e r difference. Table 2 presents results o f the logistic regression analysis, which adjusted for differences in smoking and d e m o g r a p h i c characteristics. T h e results shown are for the three morbidity measures for which g e n d e r retained a statistically significant effect. T h e g e n d e r difference in the omitted morbidity m e a s u r e o f staying in bed for at least 2 weeks was not significant, once the differences in s m o k i n g and s o c i o d e m o g r a p h i c characteristics were taken into account. As the m o d e l regression coefficients indicate, a m o n g persons whose family incomes were not below the poverty level, the odds o f having e x p e r i e n c e d any restricted activity days d u r i n g the 2-week reference period were 65% h i g h e r for w o m e n than for m e n (odds ratio [OR] = e-5°s = 1.65). A m o n g those who did fall below the poverty threshold, the odds o f having restricted activity days were slightly lower for w o m e n than for m e n (OR = e-5°s--625 = 0.89). With respect to d o c t o r consul-

18-

16-

14-

12-

Restncted Act=vJty Days

Figure 1.

Doctor's Consultabons

Hospitahzotlon Excluding Dehvenes

•

Mole

[]

Female

[]

Total

Bed Days > 2 Weeks

Prevalence of measures of morbidity by sex.

Table 2. Regression Coefficients of Logistic Regression Analyses of Morbidity Measures, A d j u s t i n g for Smoking a n d Sociodemographic Characteristics Morbility Measure Variable

Intercept (p) Female (p) Age (p) Black (p) Less than high school (p) In poverty (p) Self-respondent (p) Ever smoking (p) Female x Poverty (p) Female x Age (p)

Restricted Activity Days ~

Doctor Consultation b

-3.017 (.0000) 0.503 (.0007) 0.010 (.0272)

-3.350 (.0000) 1.698 (.0000) 0.030 (.0000) -0.710 (.0037)

Hospitalization c

-4.077 (.0000) 0.439 (.0129) 0.028 (.0000)

0.506 (.0094) 0.687 (.0020) 0.328 (.0394)

0.267 (.0490) 0.416 (.0286)

-0.625 (.0488) -0.032 (.OOO6)

"Wald F(5, 72) = 5.70, p = .0002. bWald F(5, 72) = 14.62, p = .0000. cWaldF(4, 72) = 16.09, p = .0000.

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S.P. Chou and D.A. Dawson

Table 3. Fitted Logistic Regression Model of Morbidity Measure of Doctor Consultations in 2 Weeks, Controlling for Differences in Sociodemographic Characteristics, Smoking, and Drinking Practices Variable

Intercept Female Age Black Self-respondent Last drink before 2 weeks Female x Age Female x Last Drink

Parameter Estimate

SE

p

Standardized Coefficient

3.403 1.518 0.030 -0.703 0.278 0.350 -0.031 0.584

0.227 0.325 0.005 0.237 0.132 0.201 0.009 0.290

.0000 .0000 .0000 .0041 .0392 .0869 .0010 .0477

.6748 .3790 -.1786 .1334 .1164 -.4631 .1195

Note. Model Wald F statistic: F(7, 72) = 14.56, p = .0000. tations, the excess o d d s a m o n g w o m e n d e c r e a s e d with age, with o d d s ratios r a n g ing f r o m 3.07 (¢1.698-18(.032)) at age 18 to 0.68 (¢ 1.698-65(.032)) at age 65. For hospitalizations, the o d d s were 55% h i g h e r f o r w o m e n t h a n f o r m e n (OR = e -439 = 1.55). F u r t h e r analysis was c o n d u c t e d to adjust f o r the p a t t e r n a n d level o f alcohol c o n s u m p t i o n in the logistic r e g r e s s i o n analysis. Interestingly, the p r e v i o u s l y observed g e n d e r d i f f e r e n c e s b e c a m e n o n s i g n i f i c a n t a f t e r a d j u s t i n g f o r g e n d e r diff e r e n c e s in d r i n k i n g , e x c e p t f o r the m o r b i d i t y m e a s u r e o f d o c t o r c o n s u l t a t i o n s . T h e final fitted r e g r e s s i o n m o d e l f o r the latter m o r b i d i t y m e a s u r e s (see Table 3) indicates t h a t the g e n d e r d i f f e r e n c e was m o d i f i e d by the r e s p o n d e n t ' s age a n d w h e t h e r h e o r she h a d his o r h e r last d r i n k in the 2 weeks p r i o r to the interview. B e c a u s e the sign o f the Sex x A g e i n t e r a c t i o n t e r m was negative, the g e n d e r

Table 4. Estimated Adjusted Female/Male Odds Ratios for Morbidity Measure of Doctor Consultations in 2 Weeks, Adjusting for Sociodemographic Characteristics, Smoking and Drinking Practices Odds Ratio a Age

20 30 40 50 60

Last Drink Before 2 Weeks

4.37 (2.54, 3.20 (1.92, 2.33 (1.37, 1.71 (0.92, 1.25 (0.60,

7.54) 5.32) 3.99) 3.15) 2.58)

Last Drink in 2 Weeks

2.44 (1.73, 1.78 (1.37, 1.30 (0.97, 0.95 (0.64, 0.69 (0.40,

3.43) 2.31) 1.74) 1.42) 1.21)

aFigures in parentheses are 95% confidence intervals.

Gender Differences in Morbidity Among Heavy Alcohol Users

389

difference decreased with increasing age. In addition, if the respondent had his or her last drink earlier than 2 weeks prior to the interview, the gender difference was greater than otherwise. A separate table (Table 4) was constructed to show the odds ratios at various age/last-drink combinations. Table 4 shows that at older ages (->50) there was no gender difference, especially for respondents whose last drink was within the past 2 weeks. Also, among adults under 31 years old who abstained in the 2 weeks preceding the interview, women had three to four times greater odds of" experiencing this morbid condition when compared to men. DISCUSSION

In this study of morbidity among male and female alcohol abusers and/or dependent persons, four indicators of morbidity were examined: restricted activity days and doctor consultations in the 2 weeks preceding the NHIS interview, hospitalizations excluding delivery, and excessive bed days during the year preceding interview. Unadjusted for differences in sociodemographic characteristics and drinking practices, all of these morbidity indicators were reported more frequently by women than by men. However, after adjusting for sociodemographic differences, the gender difference in the proportion of individuals spending more than 14 days in bed in the preceding year was not statistically significant. Controlling for differences in both sociodemographic characteristics and drinking practices rendered the gender differences in hospitalizations and restricted activity days statistically nonsignificant. One morbidity indicator remained different for men and women even after taking into account these other potential confounders. Women continued to have a greater risk of doctor consultations in the 2 weeks preceding interview, and their excess risk declined with age and among those women who consumed their most recent drink in the 2-week period immediately preceding interview. The age differential may result in large part from medical consultations related to pregnancy, obtaining medically prescribed contraceptives, and routine gynecological examinations. Such an explanation is consistent with the greater degree of excess risk among younger women and the fact that the excess odds were almost twice as high among women who did not drink in the 2 weeks preceding the interview (assuming that women would abstain or at least would not admit to drinking during pregnancy). Another plausible explanation for why timing of last drink modified the effect of female gender could be that individuals who abstained during the 2 weeks prior to the interview might include sick quitters who gave up drinking entirely due to medical conditions related to alcohol, and that women were more compliant than men in this respect. Alternatively, this group of abstainers might include a disproportionate number of women whose medical consultations were related to treatment for alcoholism. To test this, we excluded individuals who abstained during the 2 weeks preceding the interview and reported that they had stopped drinking permanently. After refitting the logistic model, the interaction term of gender by recency of latest drink was no longer statistically significant, that is, after excluding the sick quitters, female excess morbidity was no longer modified by timing of the latest drink. However,

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S.P. Chou and D.A. Dawson

timing of last drink remained as a confounder with a positive regression coefficient, indicating that individuals who abstained in the 2 weeks prior to the interview generally had a tendency of seeking medical advice more frequently. In general, the morbidity patterns observed for male and female alcohol abusers and/or dependent persons were the same as those that were observed when the analysis was repeated for all drinkers (data not shown). One disparate finding for all current drinkers concerns restricted activity days in the 2 weeks preceding the NHIS interview. Among respondents diagnosed with alcohol use disorders, no gender differences were observed after adjusting for the model covariates. Among all current drinkers, the odds of this outcome were greater for women than for men, and varied according to age, race, poverty status, and marital status. There is no obvious explanation for this disparity, but it may reflect gender-related health differences between respondents receiving diagnoses of alcohol use disorders and all drinkers. When comparing the gender differences in morbidity among respondents receiving diagnoses of alcohol abuse and/or dependence with those observed in the general population, the results were similar. Many studies have noted that, whereas men have higher mortality rates than women of the same age, women have higher rates of self-reported morbidity and health care utilization. This paradox is often attributed to women's greater symptom sensitivity: a greater willingness to acknowledge signs of illness and to seek medical care at an earlier stage of illness than men (Gijsbers van Wijk, van Vliet, Kolk, & Everaerd, 1991). Unadjusted for differences in consumption level and patterns, previous findings (Chou, 1994) indicate that alcoholism inflates the gender differences in morbidity observed in the general population. Even though this study was not able to describe precisely the extent to which excess female morbidity was attributed to alcoholism or the way that alcoholism affects the gender differences, it renders several significant implications. First, given the fact that women generally score higher on morbidity indices such as physical symptoms, restriction of activity due to illness, and health care utilization, treatment services and health care providers for alcoholic women need to address a broader range of comorbid symptoms. Also, their excess use of medical consultations and services by women provides more opportunities for diagnosis and intervention of alcohol use and related disorders among women. Moreover, data from clinical samples suggest that women present equally or more severe physical symptoms than men upon entering into treatment for alcohol problems (Corrigan, 1974; Hasin, Grant, & Weinflash, 1988; Piazza, Vrbka, & Yeager, 1989), with particular vulnerability in physiological effects such as liver disease and pancreatitis (Grant, Dufour, & Harford, 1988; Mezey, Kolman, Diehl, Mitchell, & Herlong, 1988; Morgan & Sherlock, 1977). This presents a challenge to health care administrators for patient management, and to treatment professionals for developing and implementing treatment programs to address the special needs of women in treatment. One other important implication pertains to family prevention and public education. This deals with the effects of maternal problem drinking on the well-being and subsequent drinking of young and adult children. These children are raised not only by an alcoholic mother but also a sick-

Gender Differences in Morbidity Among Heavy Alcohol Users

391

er one. T h u s , women may be an i m p o r t a n t target for p r e v e n t i o n and intervention strategies. W h e n dealing with self-reported data similar to that collected in the N H I S survey, reliability has been a major issue. Previous research (Grant, 1991) showed that the self-reported alcohol and smoking c o n s u m p t i o n data and o t h e r variables a p p e a r i n g on the 1988 N H I S were m o d e r a t e l y to highly reliable. With respect to validity, studies o f the self-reported data on alcohol and smoking are limited d u e to methodological limitations. However, evidence indicates that selfr e p o r t e d data are highly correlated with actual c o n s u m p t i o n levels, or at a minim u m , provide an accurate description o f relative c o n s u m p t i o n levels (Midanik, 1982). Nevertheless, there are limitations i n h e r e n t in this study. All the morbidity indicators e x a m i n e d in this analysis were, to some extent, subjective, that is, they reflected men's and women's d i f f e r e n t responses to illness as well as differences in actual prevalence o f illness. It also does not lend itself to address the intriguing possibilities that physiological differences between m e n and w o m e n in the body's response to alcohol might account for the observed g e n d e r differences, n o r does it address the issue o f g e n d e r differences d u e to differences in lifestyle a m o n g alcoholic m e n and women. T a k e n as a whole, this analysis revealed c o m p l e x differences in morbidity a m o n g male and female alcohol abusers a n d / o r d e p e n d e n t persons, not all o f which can be explained by differences in their alcohol c o n s u m p t i o n patterns or s o c i o d e m o g r a p h i c characteristics. T h e y suggest that it may be i n a p p r o p r i a t e to use data f r o m samples o f male alcoholics to estimate the excess risk o f disease a m o n g their female c o u n t e r p a r t s or female drinkers. We r e c o m m e n d that furt h e r research identify w h e t h e r specific types o f morbidity, for example, h e a r t disease and cirrhosis, vary by g e n d e r a m o n g r e s p o n d e n t s classified with alcohol abuse a n d / o r d e p e n d e n c e after accounting for c o n s u m p t i o n patterns. For diseases that may be aggravated by a specific type o f alcoholic beverage, for example, by the acidity o f wine, studies o f g e n d e r differences must account for the d i f f e r e n t beverage mix c o n s u m e d by m e n and women. We also look f o r w a r d to studies that include a full r a n g e o f measures o f d r i n k i n g behaviors, including quantity, frequency, duration, d r i n k i n g styles, and f r e q u e n c y o f heavier alcohol c o n s u m p t i o n in studying g e n d e r differences. REFERENCES

American Psychiatric Association. (1987). Diagnostic and statistical manual of mental disorders (3rd ed., rev.). Washington, DC: Author. Beckman, L.J. (1976). Alcoholism problems and women: An overview.In M. Greenblatt & M. Shuckit (Eds.), Alcoholism problems in women and children. New York: Grune & Stratton. Blume, S.B. (1986). Women and alcohol: A review.Journal of the American Medical Association, 256, 1467-1470. Chou, S.P. (1994). Sex differences in morbidity among respondents classified as alcohol abusers and/or dependent: Results of a national survey. Addiction, 89, 87-93. Clarke, J.N. (1983). Sexism, feminism and medicalism: A decade review of literature on gender and illness. Sociology of Health and Illness, 5, 62-82. Corrigan, E.M. (1974). Notes on beliefs and facts. Addictive Diseases: International Journal, 2, 215.

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