AJCN Tufts Nutrition Symposium, Boston & Online Sept 2009
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American Journal of Clinical Nutrition, Vol. 87, No. 4, 957-963, April 2008
© 2008 American Society for Nutrition

ORIGINAL RESEARCH COMMUNICATION

Alcohol drinking frequency in relation to subsequent changes in waist circumference1,2,3

Janne S Tolstrup, Jytte Halkjær, Berit L Heitmann, Anne M Tjønneland, Kim Overvad, Thorkild IA Sørensen and Morten N Grønbæk

1 From the Center for Alcohol Research, National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark (JST and MNG); Research Unit for Dietary Studies (BLH), Institute of Preventive Medicine (TIAS), Centre for Health and Society, Copenhagen, Denmark; The Danish Cancer Society, Institute of Cancer Epidemiology, Copenhagen, Denmark (AMT and JH); and the Department of Clinical Epidemiology, Aarhus University Hospital, Aalborg, Denmark (KO)

2 Supported by grants from the Health Insurance Foundation, the Ministry of the Interior and Health, the Danish Cancer Society, and the Danish National Board of Health.

3 Reprints not available. Address correspondence to J Tolstrup, National Institute of Public Health, Oster Farimagsgade 5a, Dk-1399 Copenhagen K, Denmark. E-mail: jst{at}niph.dk.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: Cross-sectional studies have reported a lower prevalence of abdominal obese persons among frequent drinkers than among nonfrequent drinkers.

Objective: We tested the hypothesis that drinking frequency is associated with subsequent changes in waist circumference.

Design: Data come from a prospective cohort study conducted in 1993–1997 (baseline) and 1999–2002 (follow-up) and included 43 543 men and women. Baseline information on alcohol drinking frequency was related to 1) change in waist circumference by linear regression and 2) major gain and major loss in waist circumference (defined as waist change in the lowest or highest quintile of waist changes) by polytomous logistic regression, also taking into account amount of alcohol intake.

Results: Drinking frequency was inversely associated with changes in waist circumference in women and was unassociated with changes in waist circumference in men. Drinking frequency was unassociated with major waist loss but was inversely associated with major waist gain: odds ratios among men were 0.97 (95% CI: 0.73, 1.28), 0.95 (95% CI: 0.81, 1.12), 0.88 (95% CI: 0.77, 0.99), 0.82 (95% CI: 0.71, –0.95), and 0.79 (95% CI: 0.69, 0.9) for never drinking, drinking on 1, 2–4, 5–6, and 7 d/wk, respectively, compared with men who drank alcohol on <1 d/wk (P for trend < 0.0001). Results for women were similar. Adjustment for the amount of alcohol intake or total energy intake did not affect results considerably.

Conclusions: Drinking pattern may be associated with development of abdominal obesity; in this prospective study, drinking frequency was inversely associated with major waist gain and was unassociated with major waist loss.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Abdominal obesity is an independent risk factor for the development of type 2 diabetes, stroke, coronary heart disease, and total mortality (1–5). Alcohol drinking pattern was associated with abdominal obesity in cross-sectional studies: frequent drinkers are leaner than nonfrequent drinkers, which seems to apply for different amounts of alcohol intake (6, 7). This means that the association between the alcohol drinking pattern and abdominal obesity may resemble the association between the alcohol drinking pattern and coronary heart disease: steady drinking is more healthy than drinking in binges (8–12). Plausible biological mechanisms supporting a causal nature of the association between drinking pattern and heart disease have been suggested, including effects of drinking pattern on blood pressure and lipids. A binge-like drinking pattern may be associated with a higher blood pressure and a less favorable ratio of total cholesterol to HDL cholesterol than with more regular drinking, factors highly associated with risk of heart disease (13–17). In contrast, no obvious mechanisms support a causal link between drinking pattern and obesity. Furthermore, previous results are obtained from cross-sectional studies, and it is hence not possible to observe the temporal sequence of the associations. It cannot be excluded that being obese may cause a different alcohol-drinking behavior than being lean.

In this study, we test the hypothesis that drinking frequency is associated with development of abdominal obesity. We use data from a prospective cohort study consisting of middle-aged men and women with baseline data on alcohol drinking frequency and with baseline and follow-up data on waist circumference.


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Study population
Baseline
From December 1993 to May 1997, 160 725 Danish men and women aged 50–64 y were invited by mail to participate in the population-based study Diet, Cancer, and Health (18). Eligible subjects were born in Denmark and had no previous cancers at the time of inclusion; 57 053 persons agreed to participate (35% response proportion). The protocol was approved by the Ethical Committee (KF 01-116/96). A 192-item food-frequency questionnaire, including questions about usual amount of alcohol intake, was enclosed with the invitation (19, 20). This questionnaire was scanned and interviewer checked during a clinic visit, when another questionnaire about lifestyle factors, including information on alcohol drinking frequency, was filled in (18). Among the participants, 547 persons were excluded from the cohort because they had a cancer diagnosis before recruitment, which, because of processing delays, was not registered in the Danish Cancer Registry at the time of the invitation.

Follow-up
The follow-up survey took place from September 1999 to October 2002 and included self-administered questionnaires about diet, lifestyle, and anthropometry. Between baseline and the time of invitation to follow-up, 1692 participants had died and 435 had emigrated, leaving 54 379 eligible for invitation. Of those, 89 (0.02%) had died after the invitation was sent out (information was given by the spouses), 25 (0.05%) had disappeared or had errors in the address, 2860 (5.3%) did not want to participate, and 5869 (10.8%) did not respond. Finally, 632 (1.1%) persons had returned questionnaires with too many errors, leaving 44 904 persons in the follow-up study sample.

Measurement of waist circumference
Waist circumference was measured by technicians at the baseline examination at the smallest horizontal circumference between the ribs and the iliac crest (the natural waist), or, in case of an indeterminable waist narrowing, halfway between the lower rib and the iliac crest. All participants were measured in light underwear.

At follow-up, waist circumference was measured at home by the participants themselves and reported in the questionnaires. A measuring tape was provided, and, to ease the identification of site of measurement, participants were instructed to measure the circumference at the level of the umbilicus.

A validation study was performed on 408 participants to compare measures of waist circumference obtained by technicians and by self-report. The 2 measures were found to be highly correlated (Spearman's correlation coefficients were 0.87 in men and 0.88 in women) (21). The 2 different measurement sites also showed a high correlation (Spearman's correlation coefficients were 0.98 in men and 0.93 in women).

Variables
Drinking frequency
Participants were asked to report their usual frequency of alcohol intake in 7 possible response categories: never drink alcohol, <1 time/mo, 1–3 times/mo, 1 time/wk, 2–4 times/wk, 5–6 times/wk, and daily.

Total alcohol intake
Participants were asked to state their average amount of alcohol consumption as the intake of specific amounts of each beverage type: light, normal, and fortified beer (in number of bottles); red, white, and fortified wine (in number of glasses); and spirits (in number of drinks). On the basis of ethanol content in the different beverage types, these categories were converted into number of standard drinks (12 g alcohol) and added to yield a measure of average drinks per week.

Total energy intake
Total energy intake, excluding energy from alcohol, was calculated from the information from the diet questionnaire with the use of the software program FOODCALC (J Lauritsen, University of Copenhagen; 22) with the use of population-specific standardized recipes and sex-specific portion sizes.

Other covariates
Information about physical activity was registered in hours of sport per week; smoking habits were reported as never, past, and amount of smoking for current smokers; and school education (in categories of ≤7 y, 8–10 y, and ≥11 y, corresponding to lower primary school, higher primary school, and secondary school, respectively).

Final study population
Participants with missing baseline values on waist circumference (n = 29), implausibly large waist circumference (>155 cm) (n = 2), or small waist circumference [<55 cm for women (n = 1) and <60 cm for men (n = 1)] were excluded. Follow-up waist circumference was missing for 635 persons, and 61 and 45 were excluded because of implausibly large and small waist circumferences. Participants with incomplete information on the alcohol variables (n = 74), and participants reporting the following impossible or unlikely combinations of frequency and average amount were further excluded: 1) drinking on average ≥7 drinks/wk at a frequency of less than monthly (n = 104) and 2) drinking on average ≥21 drinks/wk at a frequency of thrice monthly or less frequent (n = 23). In addition, subjects with incomplete information on any of the potential confounders (n = 386) were excluded. In all, the final study population for analysis consisted of 43 543 persons.

Statistical analyses
Five-year waist change was calculated as the difference between follow-up and baseline waist circumference divided by follow-up time (in y) and multiplied by 5. Associations between the alcohol variables and average 5-y waist change were estimated in multiple linear regression analyses (PROC GENMOD in SAS release 9.1; SAS Institute, Cary, NC). Major waist loss was defined as 5-y waist change below the lowest quintile of the sex-specific distribution of 5-y waist changes for all participants (0.94 cm for women and –1.94 cm for men). Correspondingly, major waist gain was defined as 5-y waist change above the highest quintile of the sex-specific distribution of 5-y waist changes (12.6 cm for women and 6.9 cm for men). Multiple polytomous logistic regression was applied to estimate odds ratios of major waist loss and major waist gain (PROC LOGISTIC in SAS release 9.1; SAS Institute).

All models included baseline waist circumference, age, physical activity, smoking, total energy intake (without energy from alcohol), and school education. Age and amount of alcohol intake were entered as linear variables; physical activity was entered as a categorical variable (nonactive, active) and a linear variable (number of hours per week); smoking status was entered in categories of never smoking, past smoking, current smoking of 1–14, 15–24, and 25 g tobacco/d; and school education in categories of lower primary school (≤7 y), higher primary school (8–10 y), and secondary school (≥11 y).

For linear variables, the linearity assumption was evaluated by linear splines with knots placed at sex-specific quintiles of the distribution (23). No systematic departure from linearity was found except for the total energy intake, and, as a result, total energy intake was modeled with linear splines set at the quintiles.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Baseline characteristics of the study population
The median time between the baseline and the follow-up examination was 5.3 y (range: 3.0–8.7 y). During that time, the average 5-y change in waist circumference was 6.7 cm for women and 2.5 cm for men. The median amount of alcohol intake was 5.5 drinks/wk (10th, 90th percentile: 0.7, 20 drinks/wk) among women and 11 drinks/wk (10th, 90th percentile: 2.3, 35 drinks/wk) for men (Table 1Go). Drinking frequency was positively correlated with the amount of alcohol intake; Spearman's correlation coefficient was 0.86 among women and 0.78 among men. Generally, the most rare drinkers (never drinkers and <1 d/mo) had shorter education than more frequent drinking participants (Table 2Go). In addition, the most rare drinkers (never drinkers and <1 d/mo) and the most frequent drinkers (7 d/wk) were more often smokers than were participants in the in-between categories of drinking frequency. These tendencies were observed among both women and men (Table 2Go).


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  		TABLE 1. Selected baseline characteristics by percentiles of the Diet, Cancer, and Health Study (1993–1997)

 

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  		TABLE 2. Selected baseline characteristics by sex and drinking frequency of 43 543 women and men in the Diet, Cancer, and Health Study (1993–1997)

 
Drinking frequency and 5-y change in waist circumference
For women, an inverse association was observed between alcohol drinking frequency and 5-y waist change (P for linear trend < 0.0001; Figure 1Go). For men, drinking frequency was not statistically associated with waist change (P for linear trend = 0.15; Figure 1Go). Further adjustment for the amount of alcohol intake had only minor influence on size and precision of the estimates (Figure 1Go, black dots).


Figure 1
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  		FIGURE 1.. Average change in waist circumference (estimated in multiple linear regression analyses) over 5 y according to drinking frequency among men and women. Estimates were adjusted for baseline waist circumference, age, physical activity, smoking, total energy intake (without energy from alcohol), and school education, and black dots were further adjusted for the amount of alcohol intake. P values for linear trend are for the analysis not adjusted for the amount of alcohol intake.

 
Drinking frequency and major changes in waist circumference
Drinking frequency was not associated with major waist loss (Figure 2Go) but was inversely associated with major waist gain among both men and women (Figure 2Go). The lowest odds ratios (ORs) for major waist gain according to drinking frequency was observed among daily drinking women (OR: 0.74; 95% CI: 0.66, 0.84) and daily drinking men (OR: 0.79; 95% CI: 0.69, 0.90), compared with drinking on <1 d/wk. P values for linear trend was < 0.0001 for women and < 0.0001 for men. Further adjustment by the amount of alcohol intake did not affect the size and precision of the ORs considerably (black dots).


Figure 2
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  		FIGURE 2.. Odds ratios for major waist loss and major waist gain (estimated in multiple logistic regression analyses) by drinking frequency. Major waist loss was defined as change in waist circumference below the lowest quintile of the distribution, and major waist gain was defined as change in waist circumference above the highest quintile of the distribution. All estimates were adjusted for baseline waist circumference, age, physical activity, smoking, total energy intake (without energy from alcohol), and school education, and black dots were further adjusted for the amount of alcohol intake. P values for linear trend are for the analysis not adjusted for the amount of alcohol intake.

 
To examine the possibility that the association between drinking frequency and major waist changes depends on the baseline waist circumference, a stratified analysis was produced, in which the association between drinking frequency and major waist change were analyzed within categories of the baseline waist circumference. Categories were defined by the 33rd and 66th percentiles of baseline waist circumferences (76.0 cm and 84.5 cm for women and 91.0 cm and 99.0 cm for men). Inverse associations between drinking frequency and major waist gain and no associations between drinking frequency and major waist loss were consistently observed in all 3 strata and for both men and women (data not shown).

Additional analyses were performed, defining major changes in waist circumference as having a 5-y waist change in the lowest or highest 10% of the distribution. The resulting ORs showed similar trends for major waist loss and major waist gain as when using the 20th percentile as cutoff (data not shown).

Analyses were also repeated for smokers and nonsmokers separately. Within both smokers and nonsmokers, the resulting ORs showed the same trends for major waist loss and major waist gain as the main analysis: drinking frequency did not seem to be associated with major waist loss and was inversely associated with major waist gain (data not shown).

To address the possibility that some participants may have changed their drinking patterns during the 5-y follow-up and that this may have partially caused the observed associations, sensitivity analyses were performed, including only participants who reported the same drinking frequency at baseline and at follow-up (n = 23 682; 54%). Results were similar to results obtained from the unrestricted sample (data not shown).

Amount of alcohol intake and major changes in waist circumference
The amount of alcohol intake was not associated with major waist loss among men and women (data not shown). For major waist gain, a slight suggestion was observed of a U-shaped relation, with odds for major waist gain being highest in the light or nondrinkers, dropping to a minimum in participants drinking 14–20 drinks for women (OR: 0.81; 95% CI: 0.72, 0.92) and 21–28 drinks for men (OR: 0.83; 95% CI: 0.73, 0.93), then rising a little in the heaviest drinkers (>28 drinks/wk) (Table 3Go). However, the odds for major waist gain in this category was not significantly different from drinking <1 drink/wk. Further adjustment by the drinking frequency affected results toward the null, and all statistical significance was lost (data not shown).


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  		TABLE 3. Odds ratios for major waist gain by amount of alcohol intake1

 
Drinking frequency within the amount of alcohol intake and major waist gain
The association between drinking frequency and major waist gain was reanalyzed, stratified on categories of the amount of alcohol intake (data not shown). Never drinkers were excluded from this particular analysis (2.3% of the total study population). No clear tendencies for drinking frequency within categories of the amount of alcohol intake were observed, but 95% CIs were quite broad because of the large number of data cells. When the same analysis stratifying on the median alcohol intake (5.5 drinks/wk for women and 11 drinks/wk for men) was repeated, the inverse association between drinking frequency and major waist gain was observed in both strata (data not shown).

Drinking frequency and major waist gain according to beverage preference
We categorized participants according to their beverage preference, defining preference for beer if at least two-thirds of the total alcohol intake consisted of beer. Similarly, wine preference was defined if at least two-thirds of the total alcohol intake consisted of wine. Seven percent of women and 27% of men preferred beer, 53% of women and 23% of men preferred wine, and 40% of women and 50% of men did not fulfill either criteria ("no preference") (Table 4Go). Never drinkers were excluded from this analysis (2.3% of the total study population). Within strata of beer preference, wine preference, and no preference, inverse associations between drinking frequency and major waist gain were consistently observed among both men and women in accordance with the main analysis (Table 4Go). Furthermore, no associations were observed between drinking frequency and major waist loss within strata of beverage preference (data not shown).


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  		TABLE 4. Odds ratios for major waist gain by drinking frequency according to beverage preference1

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
In this prospective study, we observed that drinking frequency was inversely associated with major gain in waist circumference, meaning that nondrinkers and the most rare drinker had the highest odds for major gain in waist circumference during the follow-up time of {approx}5 y. This finding was consistently observed in women and men and was independent of baseline waist circumference, smoking status, and preferred type of alcoholic beverage. Results from subanalyses on stable drinkers (participants who reported the same drinking frequency at baseline and at follow-up) were consistent with results from the entire cohort, indicating that the observed associations are not caused by changed drinking habits during follow-up. Adjustment by the amount of alcohol intake had only little effect on results, indicating that drinking frequency may be more strongly associated with abdominal obesity than the amount of alcohol intake. Drinking frequency was unassociated with major waist loss.

Other studies
Alcohol is suspected to be associated with the development of obesity for a number of reasons. Alcoholic beverages are energy dense and may not be substituting food but rather added to the total daily energy intake (24). In addition, inhibition of fat oxidation might occur as a consequence of the antilipolytic properties of metabolites from alcohol degradation (25). These features could potentially promote fat storage and hence an increased risk of developing obesity. Nevertheless, results from most prospective studies of the association between alcohol intake and obesity do not point toward a significant role of alcohol consumption in obesity development. A study of 7230 American adults found that drinkers had more stable weights during a 10-y period than nondrinkers (26), a result that agrees with findings from a study that included 336 American women in which alcohol intake was unassociated with subsequent weight gain (27). However, 2 studies, a Finnish study of >12 000 adults and a British study of 7608 men (28, 29), have found that heavy alcohol drinking is associated with increased risk of obesity. However, alcohol was not associated with increasing waist circumference among 16 587 men participating in the Health Professionals Follow-up Study (30). The association between alcohol drinking pattern and obesity has not been examined prospectively, but 3 cross-sectional studies have suggested that, for the same total intake of alcohol, frequent drinkers are leaner than nonfrequent drinkers (6, 7, 31). In the present study, we found that drinking frequency seemed to be more strongly associated with waist gain than the amount of alcohol intake. If this finding represents a causal association, the discrepancy in results from previous studies may be due to drinking pattern.

Limitations
This study has some limitations. The self-measuring of waist circumference at the level of the umbilicus at follow-up compared with technician-measured waist circumference at the natural waist at baseline could have introduced bias. However, even though absolute differences were present, the 2 measures were highly correlated (21), which is the important aspect when the significances of associations between alcohol drinking frequency and waist changes are evaluated.

Another limitation is that we did not have the ability to identify participants with a binge-like drinking pattern, ie, participants drinking more than a certain number of drinks per drinking occasion. In our study, 2 types of participants, the first of whom drinks 2 drinks each day and the second who drinks 1 drink each day plus 7 additional drinks on Saturday nights, report the same weekly amount and drinking frequency, but they represent 2 different drinking patterns that may be associated with different risks of abdominal obesity.

The participation rate was 35% in the Diet, Cancer, and Health Study. Such low participation rate could cause selection bias if both drinking frequency and the probability of change in waist circumference were associated with participation. We do not consider this to be likely.

Strengths
Strengths of the present study include the large study population, the prospective design, and the detailed information on drinking frequency and amount of alcohol intake. Furthermore, participants were almost evenly distributed over the whole range of drinking frequencies, conveying sufficient statistical power to produce reliable estimates.

Mechanism
If the observed associations between drinking frequency and obesity actually represent causal associations, a possible biological mechanism is differential induction of the microsomal ethanol-oxidizing system (MEOS) by drinking frequency. Alcohol dehydrogenase is the most important alcohol-degrading enzyme, but heavy, regular intake of alcohol is known to induce the action of MEOS (32). It was suggested that alcohol dehydrogenase and MEOS in conjunction constitute a futile cycle, so that energy from alcohol is resulting mostly in increased thermogenesis. If such a cycle is of any physiologic significance, drinking frequency may be important for the degree of MEOS activation and hence for the fraction of energy from alcohol that is lost as heat (33). Another mechanism could be that low doses of alcohol stimulate energy expenditure because alcohol has an acute thermogenic effect (34). It is possible that, for the same weekly alcohol intake, a frequent drinking pattern results in relatively more energy being converted to heat, compared with a less frequent intake. Another potential mechanistic pathway is through insulin resistance. Insulin resistance is reduced in moderate drinkers compared with abstainers and heavy drinkers, and insulin resistance may protect against weight gain (35, 36). The role of drinking pattern in the relation between alcohol and insulin resistance is unknown, but this mechanism does not seem to be the explanation for our results, because we observed that regular alcohol intake was associated with a reduced risk of a positive increase in waist circumference. It remains to be seen whether any of the above putative mechanisms can explain an association between drinking frequency and obesity. We found that drinking frequency was associated with subsequent gain and not with subsequent loss in waist circumference. This could represent that different mechanisms underlie gain and loss, and, if so, associations between exposure and changes in waist circumference should be modeled separately in future studies.

In conclusion, results from this prospective study do not imply that regular alcohol intake is involved in development of abdominal obesity. Rather, we observed that drinking frequency was inversely associated with waist gain, suggesting that the most frequent drinkers had the lowest odds for a positive change in waist circumference during the follow-up period of {approx}5 y. This finding was independent of smoking status, absolute value of waist circumference at baseline, preferred beverage type, and amount of alcohol intake.


   ACKNOWLEDGMENTS
 
We thank the participants of the Diet, Cancer, and Health Study.

The authors' responsibilities were as follows—JST: contributed to the conception and design of the study, the analysis and interpretation of data, and wrote the manuscript; JH, BLH, TIAS, and MNG: contributed to the conception and design of the study, interpretation of data, and to critically revising the paper; AMT and KO: contributed to the design of the study, the acquisition and interpretation of data, and critically revising the paper. All authors approved the final version of the article. None of the authors had personal or financial conflict of interest.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

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Received for publication August 21, 2007. Accepted for publication November 11, 2007.





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