INFLUENCE OF DIFFERENT TYPES OF ALCOHOLIC BEVERAGES ON SELF-REPORTED HEALTH STATUS

Holger Theobald1,*, Sven-Erik Johansson1 and Peter Engfeldt1,2

1 Family Medicine Stockholm, Karolinska Institute, Huddinge and 2 Department of Clinical Medicine, Family Medicine Research Centre, Örebro University, Örebro, Sweden

(Received 5 October 2002; first review notified 3 January 2003; in revised form 23 June 2003; accepted 9 July 2003)

* Author to whom correspondence should be addressed at: Family Medicine Stockholm, Karolinska Institutet, Alfred Nobels alle 12, S-141 83 Huddinge, Sweden. E-mail: holger.theobald{at}klinvet.ki.se


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Aims: This study investigated the effect of the consumption of wine, beer and spirits on self-reported health status. Methods: A sample of 14 950 individuals was randomly selected from the total population register in Sweden in 1996–97. Their self-reported health status and consumption of wine, beer and spirits were assessed at face-to-face interviews. Results: Of 11 606 individuals in the age range 16–84 years, 2659 reported a poor health status. Consumption of wine was associated with a decreased odds ratio (OR) (0.56; 95% confidence interval (CI) 0.50–0.63) for poor, self-reported health status, as compared with non-users. Consumers of fortified wine, beer, strong beer and hard liquor had a similar, self-reported health status to that of non-consumers. The results were adjusted for age, sex and total alcohol consumption. Adjustments for body-mass index, smoking, educational level and physical activity did not change the results. The relationship between poor self-reported health status and intake of wine had a form similar to a ‘U’ with the lowest OR among individuals consuming small to moderate amounts of wine. Conclusions: The study shows that a moderate consumption of wine was associated with a positive effect on the self-reported health status. Factors related to lifestyle may be underlying causes.


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The beneficial effects of a moderate intake of alcohol on mortality have been demonstrated in several studies (for review, see Poikolainen, 1995Go). This effect is due largely to a reduced risk of fatal, coronary heart disease. The question whether any of the three types of alcoholic beverages—wine, beer and spirits—is more protective than the others is yet undecided. In a review, it was concluded that wine was not superior to the other beverages in its cardioprotective effect (Rimm et al., 1991Go). We have recently found that a moderate intake of wine reduces mortality from cardiovascular diseases (Theobald et al., 2000Go). The advantageous effect of wine was evident, despite the fact that the results were controlled for possible lifestyle factors such as smoking, social class, number of siblings and body-mass index. However, we were not able to correct for such potentially important, lifestyle factors as physical activity and diet.

Self-reported, subjective health has been shown to be a strong predictor of both coronary heart disease and all-cause mortality (Mossey and Shapiro, 1982Go; Kaplan and Camacho, 1983Go; Idler and Angel, 1990Go). It has recently been shown that there is a J-shaped association between self-reported health status and alcohol consumption (Poikolainen et al., 1996Go). That is, individuals with the best self-reported health status were moderate consumers; abstainers had a self-reported health status between those of moderate and high consumers; and high consumers had the lowest health status. In two recent studies (Grønbaek et al., 1999Go; Poikolainen and Vartiainen, 1999Go), it was found that, after controlling for different confounders, a moderate intake of wine was related to a good, self-perceived health. For beer and spirits, no such association was found. In both studies, the variables were obtained from self-administered questionnaires.

The aim of the present study was to investigate the influences of different types of alcoholic beverages on the self-reported health status in a representative sample of the Swedish population. In contrast to the above-mentioned studies, the data were collected at face-to-face interviews; the response rate was higher and the effect of non-response was also considered.


    SUBJECTS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The Swedish Annual Level of Living Survey (SALLS) started in 1974 and included questions about health, social relations, work and physical environment (Statistics Sweden, 1996Go). The samples are drawn each year from the total population register; the size of the samples varies between 6000 and 9000 individuals. The quality of the variables has been studied in re-interviews and is mostly high (Wärneryd, 1990Go). However, a potential ‘response bias’ is that some individuals may give answers that they believe to be desirable, for example that health is good when wine is consumed. Thus bias could not be ruled out, but we do not think that this is common and the high reliability of the data also speaks against this type of bias. In 1996–97, a random sample of 14 950 adults (7575 women; 7375 men) aged 16–84 years was included in the SALLS; it is these individuals that constitute the population of our study. The individuals were interviewed in their homes and the response rate was about 80%. The causes of non-participation were as follows: 15.2% refused to participate, 1.9% were unable to participate because of disease and 3.6% could not be found. In another part of the SALLS, conducted in 1987–91, with a similar design and response rate to those in our study and concerning 40 078 individuals from the same population, the following relative death rates (diseases related to excessive alcohol consumption, that is, somatic and psychiatric diseases and accidents caused by alcohol) were observed at a follow-up after 5 years: participants 1.00 (reference), decliners 1.41 (95% confidence interval (CI) 0.87–2.28), individuals with disease 3.78 (CI 1.80–7.93) and individuals who could not be found 5.34 (CI 3.10–9.21). As this last group was a group with high alcohol consumption it could be stated that we probably underestimated the prevalence of high-consumption individuals in our study. However, this underestimation is small and has only a minor influence on the OR.

Outcome variable
Information about the dependent variable, the self-reported health status, was given by the individuals in answer to the question ‘How would you describe your general health?’ There were five possible responses: very good, good, moderate, bad or very bad. Those who answered that their health status was very good or good were considered to have good, self-reported health status; the others were considered to have poor, self-reported health status.

Independent variables
Age was analysed according to the age groups 16–24, 25–34, 35–44, 45–54, 55–64, 65–74 and 75–84 years. The questionnaire consisted of several items, some of which were used in the different statistical analyses. The educational attainment was classified in three groups: elementary school (<=9 years), completed up to 2 years of high school (10–11 years) and completed more than 2 years of high school or university studies (>11 years). Body mass index (BMI) was classified into four groups: underweight (BMI <=18.5), normal weight (>18.5 but <=25), overweight (>25 but <=30) and obesity (>30). Marital status comprised two groups: single and married/cohabiting. The smoking habits were categorized into three groups: current smokers, former smokers and never a smoker. The level of leisure-time, physical activity was dichotomized in the analysis into being physically inactive or occasionally active versus regular physical activity at least once a week.

Alcohol consumption was assessed by questions about the extent of use: the amount and frequency of intake of ordinary beer, strong beer, red or white wine, fortified wine and hard liquor during the last month. Thus, for each of the alcoholic beverages mentioned in our study, the individuals were asked to tell the quantity they consumed each day of the week in the form of glasses, bottles, cans or, if they could, specify the volume of the beverage consumed (for example, the phrasing could be as follows: ‘How much fortified wine did you drink last Friday, how many glasses? How many bottles?’). They were also asked to specify the quantity they consumed each time they consumed alcoholic beverages. The individuals who claimed that their intake of alcohol during the last month differed from their regular intake were asked about that and the answers were used for the calculations. A few individuals (less than 100) refused to answer questions concerning alcohol intake and the questions about general health. Thus, the small differences in the number of individuals in some of the calculations reflect missing data. By multiplying the frequency of intake by the amount of alcohol in grams for each beverage, the alcohol consumption in g/week for each beverage could be calculated. We also analysed the frequency of drinking different beverages, that is for each alcoholic beverage we analysed the number of individuals who consumed the specified beverage during different specified time periods. We decided to categorize the individuals into four groups according to alcohol intake and the influence of that intake on self-reported health status. Individuals who consumed less than 150 g/week constituted the reference group. The cut-off limit for high alcohol consumption, 150 g/week, was chosen in accordance with the recommendations made by the Swedish National Food Administration (Sandström et al., 1996Go) as 150 g alcohol per week (or 21 g/day) is considered to be the upper level for consumption which has no harmful effects on the individuals health. We do not think that it is meaningful to have a lower or more narrow reference category than 1–149 g as negative effects on health can probably only be expected with higher consumption. Further, we also found that a narrower reference category did not change the results. As most participants consumed several types of beverage, an analysis of an eventual interaction between the different alcoholic beverages was performed. This was done through inclusion of a new variable in the logistic regression model. This variable was the product of the two alcoholic beverage type variables which we tested. We did not find any significant interactions of combined drinking (data not shown). Thus, we believe it correct to use our statistical model to correct for the use of multiple beverage types in order to estimate the effect of one single type of beverage.

The study was approved by the local Ethics Committee at Huddinge University Hospital.

Statistical analysis
Using logistic regression, crude and adjusted OR with 95% CI were estimated for the relationship between exposure (intake of wine, beer and spirits) and poor, self-reported health status. The analyses were performed by the SAS data package, PROC LOGISTIC (SAS Institute, Cary, NC, USA).


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Of the 11 606 individuals in this study, 20% were non-consumers, 71% consumed less than 150 g alcohol per week, 7% consumed 150–289 g/week and 2% consumed 290 g/week or more. Poor, self-reported health status was reported by 23% of the individuals. In Table 1, some of the demographic data, some of the potential confounders and further data concerning alcohol consumption are shown and related to poor, self-reported health status. A total alcohol consumption of over 290 g/week was associated with an increased risk of poor, self-reported health status (OR 1.79; CI 1.24–2.58; Table 2) in relation to individuals who consumed 1–149 g/week. Non-consumers also had an increased risk of poor, self-reported health status (OR 1.39; CI 1.20–1.60; Table 2).


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Table 1. Prevalence of poor, self-reported health status for 11 606 subjects in a study on the influence of different types of alcoholic beverages on self-reported health status

 

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Table 2. Odds ratios for poor, self-reported health status in 11 606 individuals, according to intakes of wine, fortified wine, beer, strong beer or hard liquor, and average weekly alcohol consumption in a study on the influence of different types of alcoholic beverages on self-reported health status.

 
The OR for poor, self-reported health status for individuals consuming wine—in relation to those not consuming wine—was 0.56 (CI 0.50–0.63; Table 2). Consumption of the other beverages did not influence the self-reported health status (Table 2). The odds ratios were adjusted for sex, age and total alcohol consumption. Controlling for confounders such as smoking, physical activity, BMI and education did not change the risks (Table 3).


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Table 3. Full model with odds ratios for poor, self-reported health status in 11 324 individuals, according to intakes of wine, fortified wine, beer, strong beer or hard liquor, and average weekly alcohol consumption in a study on the influence of different types of alcoholic beverages on self-reported health status.

 
When we performed a sensitivity analysis and included only those with self-reported bad and very bad health status (5% of the population), there were no significant changes in the OR.

Wine and beer were consumed more often than were the other beverages, as shown by the weekly consumption (Table 4). The relationship between intake of wine and poor self-reported health status showed the following OR (adjusted for age, sex and total alcohol consumption): 1.74 (CI 1.55–1.96) for those consuming 0 g/week, 1.00 (reference) for those consuming 1–149 g/week, 1.37 (CI 0.74–2.54) for those consuming 150–289 g/week and 0.61 (CI 0.06–6.01) for those consuming >=290 g/week.


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Table 4. Frequency of drinking different beverages in a study on the influence of different types of alcoholic beverages on self-reported health status. For each alcoholic beverage the percentage of individuals consuming the specified beverage during the indicated period is given

 
Table 5 shows the proportions of smokers, ex-smokers and those devoted to physical activity among the different beverage consumers.


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Table 5. The proportions of smokers, ex-smokers and individuals engaging in regular physical activity for each alcoholic beverage in a study on the influence of different types of alcoholic beverages on self-reported health status. Multiple beverage consumption was not taken into account

 
There was no significant difference between men and women with regard to any of the results presented (data not shown).


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The main finding in our cross-sectional study was that a moderate consumption of wine was associated with a lower odds ratio (OR) for poor self-reported health status, compared with that of non-users of wine. There are only a few studies dealing with the effects of alcohol and different alcoholic beverages on self-reported health status (Poikolainen et al., 1996Go; Grønbaek et al., 1999Go; Poikolainen and Vartiainen, 1999Go). Our study confirms the results of those studies and also adds new information.

It could be argued that some objective measure of physical health instead of self-reported health status could have strengthened the results. In the SALLS there are no such objective measures of physical health. However, as self-reported health status has been shown to be a strong predictor of both coronary heart disease and all-cause mortality (Mossey and Shapiro, 1982Go; Kaplan and Camacho, 1983Go; Idler and Angel, 1990Go, Sundquist and Johansson, 1997Go), we believe it appropriate to use it in our study.

In our study the response rate was high (80%). A drop-out analysis, in another part of the SALLS, has shown that the majority of the non-participating individuals have similar, relative, death rates as do the participants and thus should have similar, self-reported health status, as this parameter mirrors mortality. Therefore it is possible that our results could be generalized to the whole population. We also found that poor, self-reported health status was associated with increased age, low educational level, high BMI, smoking and low physical activity. These results are in accordance with the results of other studies (Grønbaek et al., 1999Go; Johansson and Sundquist, 1999Go), which suggests that our results are reliable. Furthermore, it has been shown in some studies that more reliable results concerning the alcohol intake are obtained if individuals are asked about their intakes over longer periods of time (O'Hare, 1991Go; Duffy and Alanko, 1992Go). In our study the alcohol intake was assessed by asking about the intake in the last month, and individuals who claimed that their intake of alcohol during the last month differed from their regular intake were asked about their usual intake. This may give better estimates of alcohol intake than did the study by Grønbaeck et al. (1999)Go, in which the intake was based on the last, non-weekend day.

Our results were adjusted for total alcohol consumption, age and sex. Adjusting the results for other confounders, such as smoking, educational level, BMI or level of physical, activity did not change the results. This is in accordance with results from other studies (Grønbaek et al., 1999Go; Poikolainen and Vartiainen, 1999Go). However, in those studies the results were also adjusted for confounders such as chronic disease, presence of social networks and marital status. Those confounders, also, did not change the results. One important lifestyle factor which we, as well as others, could not adjust for was dietary habits; we have no data on this. It has been shown that drinkers of alcoholic beverages who have increasing alcohol consumption tend to consume diets higher in fat and lower in dietary fibre. Adjusting for those variables did not change the effect of alcohol on total, coronary artery disease (Stampfer et al.,1988Go; Rimm et al., 1991Go). It has also been shown that wine consumers have more healthy dietary habits than do consumers of other beverages (Tjønneland et al., 1999Go). However, there are no data on the consequences of that for cardiovascular diseases or self-reported health status.

Many individuals in our study consumed several types of beverage; which is the usual drinking pattern. To analyse the effects of a single type of beverage, we used a statistical model for the adjustment of multiple beverage drinking. There were no interactions of combined drinking, but the use of a statistical model for correction of multiple beverage drinking obviously does not give as reliable data as that obtained from individuals drinking only one type of alcoholic beverage. However, the latter situation is very uncommon in normal everyday life.

In contrast to the two other studies dealing with self-reported health status and the effects of different alcoholic beverages (Grønbaek et al., 1999Go; Poikolainen and Vartiainen, 1999Go), we found a beneficial effect of wine but not of fortified wine. In the other studies, the different types of alcoholic beverage were not subgrouped, as in our study, and it is possible that fortified wine could also have been without effect in those studies, if it had been analysed. The mechanisms behind the positive effects of wine on self-reported health status have not been identified. It has been suggested that the contents of anti-oxidants such as flavonoids and phenolic compounds in wine may have cardioprotective effects (Das et al., 1999Go). However, it is not known whether these substances also have positive effects on the self-reported health status, but theoretically it is possible. If there is an effect, it is unlikely that a common substance in wine and fortified wine has favourable effects. However, it has been shown that the content of polyphenols differs in different types of wines, and that the bio-availability varies (Scalbert and Williamson, 2000Go), so it is still possible that some substance in wine may have positive effects.

The U-shaped association between self-reported health status and amount of wine consumed does not support a clear-cut, pharmacological effect of some substance in wine. If a pharmacological effect is to be expected from a substance, an optimal dosage and a regular intake of the substance should produce the effect. In our study only a few individuals consumed alcoholic beverages regularly, and beer, which had no effect, was consumed more often than the other beverages. This also argues against the ‘pharmacological’ action of wine.

There is some evidence that moderate wine drinkers have a healthier lifestyle than those who prefer other alcoholic beverages (Klatsky et al., 1990Go; Klatsky and Armstrong, 1993Go). It is likely that lifestyle factors are important constituents of the favourable effects of wine on self-reported health status. The factors reflecting lifestyle that we examined were not found to be confounders of the positive effect of wine on self-reported health status. Dietary habits are probably of importance, but they could not be analysed as we lacked the data. When we examined the occurrence of smoking and physical activity (important lifestyle and risk factors for ill-health), it was found that only non-users of alcoholic beverages and users of fortified wine differed from the other beverage users, with regard to the percentage of individuals who were smokers and engaged in physical activity. Our study was not designed to evaluate the importance of lifestyle factors in connection with the consumption of different beverages for self-reported health status. Thus it is possible that some of the lifestyle factors that we analysed and other, less important ones, may have synergistic effects on self-reported health status; this may explain the positive effects of wine. Studies designed to resolve these issues are needed.

In conclusion, we found that the moderate consumption of wine is associated with positive effects on self-reported health status. Constituents of the beverage that have favourable effects and/or lifestyle factors are potential, underlying causes.


    Acknowledgements
 
This study was supported by grants from the Swedish Council for Social Research (9003/1999) and the ‘Förenade Liv’ Mutual Group Life Insurance Company, Stockholm, Sweden.


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