Review articles

Dietary and lifestyle habits of drinkers with preference for alcoholic beverage: does it really matter for public health? A review of the evidence

Abstract

Although the detrimental effects of heavy drinking in terms of health are well-documented in the literature, there are inconsistent findings regarding the safety of light-to-moderate alcohol consumption. In particular, little is still known about the consumption of specific alcoholic beverages in combination with dietary habits and lifestyle, which in turn could influence health status. Thus, the aim of this review is to summarise and critically evaluate the evidence of a relationship between preference for alcoholic beverages and consumer dietary and lifestyle habits. A literature search retrieved 3,887 articles. By removing duplicates and articles which were not relevant, the final number of articles was 26. The adherence to a healthier diet and lifestyle was generally observed in light-to-moderate alcohol consumers, especially when wine was the preferred beverage. Considering the potentially strong impact of drinking patterns on health and the risk of developing chronic diseases, the data summarised in this review highlight that alcoholic beverage preferences, drinking patterns, dietary patterns and lifestyle should be studied together. Any future epidemiological studies should analyse the relationship between alcohol consumption and the abovementioned correlations with respect to impact on health.

Introduction

Although current epidemiological evidence is largely consistent as to the detrimental effects of heavy drinking in terms of health, the public in particular receives inconsistent and confusing message regarding the safety of light-to-moderate alcohol consumption (Kunzmann et al., 2018). In a SUN (Seguimiento Universidad de Navarra) prospective study, the authors concluded that the effect on mortality of the overall healthy alcohol-drinking pattern is more important than the total quantity of alcohol consumed (Gea et al., 2014), while other studies either suggested that “there were no clear risk thresholds below which lower alcohol consumption stopped being associated with lower disease risk” (Wood et al., 2018) or restricted the beneficial effects to people with no genetic predisposition (Au Yeung et al., 2013). Moreover, in a recent prospective population-based study, (Schutte et al. (2020) highlighted that only wine could be associated with a protective role with regards to ischemic heart disease, whereas the consumption of beer/cider and spirits, even in low levels, was associated with an increased risk for all health outcomes (Schutte et al., 2020). Furthermore, the findings from an ecological US study in a nationally representative cohort of households showed that, compared to non-drinkers, participants who purchased high levels of wine or beer, but not liquor, were less likely to be diagnosed with diabetes mellitus, while participants who purchased moderate levels of wine were 25 % less likely to be diagnosed with heart disease (Adjemian et al., 2015).

Thus surprisingly little is known about the risks or benefits of moderate consumption of specific alcoholic beverages in terms of the health status of adults. The interpretation of the conclusions of epidemiological studies which examine the effects of alcohol consumption on human health will be unclear, limited and unsustainable, if they are not evaluated from a wider and more holistic perspective. Any discrimination related to type of alcoholic beverage has to be based on more than differences in chemical composition (Osorio-Paz et al., 2019), mainly because choice of beverage type usually reflects a particular lifestyle, which can be defined as healthy, less healthy or even unhealthy.

Indeed, the combined impact of lifestyle-related factors on all-cause or cause-specific mortality has been the subject of much research, shedding light on the link between alcohol and health. In particular the “HALE” project, a longitudinal European study, concluded that the combined influence of four lifestyle habits, namely Mediterranean diet, moderate alcohol use, physical activity and absence of smoking, is associated with a more than 50 % lower rate of all-cause and cause-specific mortality (Knoops et al., 2004). Moreover, another recently conducted meta-analysis suggested that the management of multiple lifestyle risk factors should be the cornerstone for combating the global burden of disease (Zhang et al., 2021).

Thus, in line with the holistic approach (Hu, 2002), instead of asking “to drink or not to drink”?, a better question - which needs further investigation - might be “What is my lifestyle and “What do I usually eat with my favourite drink?” Therefore, when evaluating the relationship between alcohol and health outcomes, dietary pattern and other lifestyle habits should be studied in combination and not individually. The answer to the question will thereby elucidate many factors which may have been underestimated or misinterpreted in numerous epidemiological studies. Indeed, the authors from the most recently conducted systematic review on the same topic (Sluik et al., 2016a), concluded that alcohol consumption alone may not be related to health outcomes, but rather the underlying dietary habits.

In light of this, the aim of this study was to conduct an updated review and critical evaluation of studies found in the literature on the relationship between alcoholic beverage preference/choice and dietary and lifestyle patterns in adults.

Methods

1. Literature search

The most important scientific databases of references and abstracts on life sciences (PubMed, and ISI Web of Science and Core Collection) were systematically searched (from database inception up to 11 April 2021). In this updated review, we used wider selection of search criteria than that used in a previous systematic review conducted by Sluik et al. (2016a). Used search strings were: #1 "beverage" AND ("diet*" OR "food*" OR "lifestyle" ) AND ("wine" OR "beer" OR "spirits" OR "liquor") #2 "alcoholic beverages" AND ("preference" OR "choice") AND ("diet*" OR "nutr*"OR "food*" OR "lifestyle") # 3 "alcohol" AND ("preference" OR "beverage" OR "choice") AND ("diet*" OR "nutr*" OR "food*" OR "lifestyle") #4 ("wine" OR "beer" OR "spirits" OR "liquor") AND ("preference" OR "choice") AND ("diet*" OR "nutr*" OR "food*" OR "lifestyle"). The flow-chart of the selection process of the literature search is shown in Figure 1. Restricted to humans and the English language, 1.611 hits were obtained from the PubMed search. Moreover, 2.983 hits for the ISI Web of Science were retrieved using the same strings (restricted to the English language and document types (Article)), thus corresponding to a total of 3,887 unique hits after the removal of duplicates. By removing articles on alcohol as such, and articles not relevant (i.e., articles excluded upon screening the “title”, articles where no distinction between the type of alcoholic beverages was considered, reviews, and articles not meeting the inclusion criteria), the number of studies retained for this review was 23. Furthermore three more eligible articles (Forshee and Storey, 2006; Herbeth et al., 2012; Johansen et al., 2006) - which had been included in the previous systematic review (Sluik et al., 2016a) - were identified by manual screening, resulting in a total of 26 articles. Two reviewers (R.I.K. and C.D.L.) independently selected the articles, and any discrepancies between them were solved by consensus or by consulting with a third researcher (P.R.).

Figure 1. Flowchart of the selection process of the literature search for studies on relationship between alcoholic beverage preference/choice and diet/lifestyle, published up to 11 April 2021.

2. Eligibility criteria

In this review, only study designs published in peer-reviewed journals were included. Eligible studies had to meet the following inclusion criteria: i) to have been conducted on healthy adults, ii) to have clearly distinguished the different alcoholic beverage types (consumption or preference), iii) to have defined the exposure as being the consumption of a specific alcoholic beverage, and iv) to have assessed diet, either as food or nutrient intake, or diet quality index, alone or in combination with lifestyle. Given that there is no definition of preferred/chosen alcoholic beverage, the most chosen or consumed beverage among wine, beer, spirit or liquor was considered to be the preferred/chosen beverage in the reviewed studies. Restriction applied only to alcoholics and hospitalized patients with diseases or treatments associated with diet, in accordance with the restriction criteria set in a previous systematic review (Sluik et al., 2016a).

3. Data Extraction

From each study, the following relevant data were extracted: first author/year of publication, country of study population, subjects’ characteristics (number, sex and age), objectives of the study, method for assessing alcohol consumption, diet and lifestyle, and assessment employed, choice/types/preference of alcoholic beverages or drinking patterns, adjustments and main results.

Results

1. General Characteristics of the included studies

Table 1 shows the general characteristics of the 21 cross-sectional and five ecological studies included in this review. In the ecological studies, the observations had been made on supermarket transactions and shopping events/purchases, rather than on individuals (Berger et al., 2020; Gell and Meier, 2012; Hansel et al., 2015; Johansen et al., 2006; Uusitalo et al., 2019). In the cross-sectional studies, the size of the studied population varied between 423 (Herbeth et al., 2012) and 48,763 (Tjønneland et al., 1999), with an age range of > 18 years old (Ferreira-Pêgo et al., 2017) to 85 years old (González-Rubio et al., 2016), and they had been conducted in the following countries between 1997 and 2020: Spain (Alcácera et al., 2008; Carmona-Torre et al., 2008; Ferreira-Pêgo et al., 2017; González-Rubio et al., 2016; Sánchez-Villegas et al., 2009; Scholz et al., 2016; Valencia-Martín et al., 2011), Italy (Chatenoud et al., 2000), France (Hansel et al., 2015; Herbeth et al., 2012; Rouillier et al., 2004; Ruidavets et al., 2004), the Netherlands (Sluik et al., 2014; Sluik et al., 2016b; Sluik et al., 2016c), Denmark (Johansen et al., 2006; Tjønneland et al., 1999), Finland (Männistö et al., 1997; Uusitalo et al., 2019), Belgium (Mullie and Clarys, 2015), the United Kingdom (Berger et al., 2020; Gell and Meier, 2012), and the United States (Barefoot et al., 2002; Forshee and Storey, 2006; McCann et al., 2003; Paschall and Lipton, 2005).

Table 1. Characteristics of the 26 retained studies which assess the relationship between alcoholic beverage choice/preference and dietary patterns/diet quality/lifestyle.


Country

Study

(design, name)

Subject characteristics (n, sex, age)

Objectives of the study

Alcohol assessment

Methods used to assess dietary patterns/purchase of different food types

Types of/preference for alcoholic beverages or drinking patterns

Confounding factors (adjustment)

Main results

Ref.

UK

Ecological study

Data from the Expenditure and Food Survey for 2005–2006.

3146 UK adult-only households.

To identify the nature and strength of the association between alcohol and diet through the analysis of household expenditure on food and drink.

Questionnaire and a 2-week individual-level diary recording all purchases.

Expenditures relevant to healthy food (fruit and vegetables) and unhealthy foods and neutral foods through the use of Questionnaire and a 2-week individual-level diary recording all purchases.

Beer, wine and spirits. The preferred beverage was that on which the household spent the most combined off- and on-trade.

No adjustments made, controlled for income.

Adults who purchased wine were related to healthier expenditure patterns than those that preferred to buy beer or spirits.

(Gell and Meier, 2012)

FI

Ecological study

data consisted of 1,527,217 shopping events in grocery stores (2016).

13,274 customers with loyalty cards of supermarket groups (67 % women) and (33 % men). mean ± SD age: 46.2 ± 14.7 Age range: 16-90

To assess alcohol expenditure and associations with food and tobacco expenditures.

Registration of relevant information on the purchase (items and expenditure) of alcohol via the loyalty card.

Food and tobacco expenditures assessed through the customers’ loyalty card.

Beer, cider and non-alcoholic options. Preference beverage was not defined. The estimated approximate volumes were based on typical prices of alcoholic beverages in group supermarkets.

No adjustments made.

The expenditure on alcohol beverages (cider and beer) were associated with expenditure on tobacco and foods rich in saturated fat, salt and added sugar.

(Uusitalo et al., 2019)

FR

Ecological study

Retrospective analyses of the data collected on regular customers of a large supermarket chain (2010-2011)

196,604 loyal supermarket customers.

To describe the relationship between the consumption of alcoholic beverages and individual profiles of objective food purchases.

Registration of relevant information on the purchase of food and beverage items via the loyalty card

Purchased food items classified as: (1) healthy foods; (2) unhealthy foods; and (3) others. Food items purchase and total budget was obtained on each occasion when a customer passes the check out for payment through the use of the registrations of the loyalty customers’ card.

Anises, Grand wines /Champagne, Whisky PGII, Modern aperitifs, Table wine, Beer, Bordeaux, Non-alcohol buyers, Multi-wines.

No adjustments made.

The highest consumption of healthy foods was observed among wine consumers and the lowest consumption of healthy foods among beer and aniseed-based beverages consumers.

(Hansel et al., 2015)

DK

Ecological study/cross-sectional analysis

(September 2002 -February 2003).

3.5 million random transactions from two large Danish supermarkets.

To examine if people who buy wine buy healthier food items than those who buy beer.

Alcoholic beverage transactions.

Food items/transactions. 40 food categories.

Wine only, beer only, mixed, and non-alcohol buyers. Preferred beverage defined as the alcoholic beverage included in the transactions.

Number of items bought (stratification).

Wine buyers bought more olives, fruit and vegetables, poultry, cooking oil, and low-fat cheese, milk, and meat than beer buyers. Beer buyers bought more ready cooked dishes, sugar, cold cuts, chips, pork, butter or margarine, sausages, lamb, and soft drinks than wine buyers.

(Johansen et al., 2006)

UK

Ecological study/ cross-sectional latent class analysis (January 2016 - January 2017).

Data used from the 2016 GB Kantar Fast-Moving Consumer Goods (FMCG) panel, a large representative household purchase panel for food and beverages brought home - analyses restricted to consumers who purchase beverages regularly ( > 52 L per household member annually)

8,675 households with 14,007,226 product purchases

To determine a typology of regular beverage consumers on the basis of household purchasing behaviour.

Purchases of beverages assessed through scanned take-home purchases using hand-held barcode scanner.

Purchases of foods assessed through scanned take-home purchases using hand-held barcode scanner.

SSBs, diet beverages, fruit juices and milk-based beverages, beer and cider, wine, and bottled water.

No definition of preference was provided.

No adjustments made, but sensitivity analyses conducted to ensure that the exclusion criteria and the categorisation of the latent class indicators did not affect the results.

Wine dominant households had the lowest percentage of energy from less healthy foods, energy from saturated fats and sugar and the higher protein content of purchases.

(Berger et al., 2020)

ES

The SUN cohort study, cross sectional analyses.

(2000-2003)

10,526 male and female (recruited during the period 2000-2003) University graduates.
Age: M: (mean ± SD) 40.5 ± 12.3) and F: 34.1 ± 10.4).

To evaluate the association between alcohol beverage preference and dietary habits between wine drinkers, other alcoholic beverage drinkers and non-drinkers.

136-item validated FFQ. Total alcohol was calculated as the sum of all types of alcohol consumed (grams of alcohol/ day.

Nutrient score and MedDiet score excluding wine.

Wine, beer, spirits. The preferred beverage was defined when its intake was ≥50% of total alcohol intake.

Age and total energy intake.

No relevant differences were found in adherence to the Mediterranean food pattern according to alcoholic beverage preference.

(Alcácera et al., 2008)

FR

A cross-sectional survey on cardiovascular risk factors and nutrition by the French MONICA Centres (1995 – 1997)

1110 middle-aged men.
Age: 45–64

To investigate among others the associations between alcohol consumption, beverage type preference and diet.

With the use of a 3-consecutive day food intake diary and a quantitative questionnaire, total alcohol was calculated as the sum of all the types of alcohol consumed (grams of alcohol/ day.

Energy, selected nutrients, selected foods and Food group intake and Diet quality index through the use of a 3-consecutive day food intake diary.

Wine, beer, cider, aperitifs and spirits. The preferred beverage was defined as that representing > 70 % of total alcohol intake. When both beer and wine consumption varied between 20 % and 70 %, whatever the amount of other alcoholic beverages, the alcohol drinker pattern was considered as mixed preference.

Age, schooling, tobacco consumption, physical exercise, BMI, dieting, and alcohol consumption.

Healthy diet and behaviours were found in moderate alcohol drinkers or wine drinkers compared to other drinkers or abstainers.

(Ruidavets et al., 2004)

NL

Cross sectional study from the Dutch National Food Consumption Survey (2007–2010).

2100 men and women 1054 men and 1046 women
Age: > 19

To investigate associations between alcoholic beverage preference and dietary intake in the Netherlands.

A general questionnaire assessed alcoholic beverage preference, and two non-consecutive 24-hour dietary recalls assessed overall diet.

Mean nutrient intakes, food group intakes and adherence to the Dutch Healthy Diet Index (DHD-index) scores and its components through personal interviews (24-hour dietary recalls) twice with an interval of 2–6 weeks.

Beer, wine, spirits (including liqueurs and mixed drinks). Preference for a specific beverage was defined when the average number of reported glasses was ≥ 70 % of the total number of glasses

Age, sex, body mass index (BMI), education, smoking, physical activity, energy intake and frequency and absolute alcohol consumption.

A beer preference was associated with less healthy dietary behaviour, especially compared with wine preference.

(Sluik et al., 2014)

NL

Cross sectional study from The Dutch Longitudinal Nutrition Questionnaires and NQplus Study (2011-2013).

1653 men and women recruited between May 2011 and February 2013.
Age: 20–77

To investigate, among others, associations between alcoholic beverage preference and dietary patterns.

A 180-item semi-quantitative validated Food Frequency Questionnaire (FFQ).

Dietary patterns via a principal component analysis (PCA) on 32 energy-adjusted food groups, excluding alcoholic beverages with the use of a 180-item Semi-quantitative validated Food Frequency Questionnaire

Beer, wine and spirits (all liquors and distilled beverages such as gin, whiskey, rum and liqueur). Preference for a specific beverage was defined as the average number of reported glasses being ≥ 70 % of the total number of glasses.

Age, sex, education, birth country, employment status, and prevalent diseases.

Overall, wine consumers have a better health status than beer consumers with few differences in dietary patterns.

(Sluik et al., 2016b)

US

Cross-sectional study as part of the UNC Alumni Heart Study (UNCAHS) (1994).

4.435 of which 2864 men and 1571 women, 99 % European Americans.

Participants were students at the University of North Carolina in the years 1964-1966.

To evaluate the associations between alcoholic beverage preferences and indicators of a healthy diet and other health habits.

A 153-item food-frequency questionnaire (FFQ).

Food-group indexes, nutrient intakes, with the use of a 153-item food-frequency questionnaire (FFQ).

Beer, red wine, other wine, and liquor or mixed drinks. Preferred beverage defined as that representing > 50 % of their alcohol intake.

Controlled for education and income. No adjustment, only tested for sex and beverage preference interactions.

Wine drinkers had healthier diets than those who preferred beer or spirits or had no preference.

(Barefoot et al., 2002)

FI

Cross-sectional study of the 1992 Finmonica cardiovascular risk factor survey.

985 women and 863 men drawn from the population register in four monitoring areas. Mean age: 25 ± 64

To describe the associations between alcohol beverage drinking and macronutrients, antioxidants, and body mass index.

A 3-day food record and a self-administered questionnaire.

Mean nutrient intakes via a 3-day food record.

Beer, wine and spirits. Preferred beverage defined as that representing > 50 % of their alcohol intake.

Age, area, smoking, education, energy from food and alcohol intake.

Alcohol consumers were leaner than abstainers, and wine drinkers in particular had more antioxidants in their diet.

(Männistö et al., 1997)

US

Cross sectional analyses from the control group of a series of case-control studies on alcohol use, myocardial infarction, and lung, breast, and prostate cancer between 1996 and 2001.

1846 men and 1910 women.
Age: 35–79

To assess differences in dietary and lifestyle characteristics associated with alcoholic beverage preference.

Alcohol consumption was assessed with a detailed, computer-assisted interview querying intake during the 12 to 24 months prior to interview.

Daily intake of macro- and micronutrients, monthly frequency of selected food intake through a self-administered modified version of the Health Habits and History food frequency questionnaire developed by researchers at the National Cancer Institute.

Beer, wine, liquor, and mixed beverages. Preferred beverage was defined as that consumed on at least 75 % of all drinking occasions.

Age and total alcohol intake.

Wine drinkers had higher socioeconomic status and reduced smoking habit, along with higher intakes of nutrients and healthy dietary habits, than consumers of other beverages.

(McCann et al., 2003)

ES

Cross sectional analyses based on a Prospective cohort study (1999-2007).

15,073 free-living Mediterranean cohort of university graduates.

To evaluate the association between predefined dietary patterns with beverage consumption patterns.

A 136- items semi-quantitative FFQ.

Twenty-five predefined food categories were developed from the FFQ. Major dietary patterns were detected through Principal Components Analysis. A 136-food item semi-quantitative FFQ was used.

Spirits, total wine, red wine, beer. Preference for a specific beverage was not defined. Absolute intakes were assessed.

Age, gender, energy intake, BMI, physical activity during leisure time, smoking, marital status and several diseases.

Beer and spirits consumption showed an inverse linear trend with adherence to the MDP. Moderate red wine consumption (around 25 g/d) was found in all quintiles of MDP adherence.

(Sánchez-Villegas et al., 2009)

IT

Cross-sectional analysis based on the control group of a case-control study (1991-1996).

5642 subjects (3261 women and 2381 men)
age: 20 ± 74 (median age:58).

To identify the association between wine drinking and intake of selected indicator foods (in various populations).

A structured and validated questionnaire.

Food indicator considered (fruit, raw vegetables, cooked vegetables, salad and fish) with the use of a 78-item FFQ.

Wine only, mixed, beer and various spirits only. No definition of preference is defined.

Age, centre, education, body mass index and smoking habits, of reporting above the median intake of each food.

No association between wine drinkers or mixed drinkers with indicators of healthy diet, such as fruit, vegetables and fish.

(Chatenoud et al., 2000)

EU

Consortium on Health and Ageing: Cross-sectional analyses from the Network of Cohorts in Europe and the United States (CHANCES study).

29,423 adults >60 years old.

To compare dietary intake and diet quality according to alcoholic beverage preference in European older adults.

FFQ or dietary history.

FFQ or dietary history. Healthy Diet Indicator and dietary intake.

Wine, beer spirits, no preference, non-consumers. Preferred beverage defined as > 70 % of total alcohol intake.

Age, gender, education, employment status, smoking history, physical activity, history of coronary heart disease and cancer, alcohol consumption and energy intake.

Among alcohol drinkers wine consumers tend to have higher HEI score and the highest fruit and vegetable intake after non-consumers.

(Sluik et al., 2016c)

BE

Cross sectional study of military population.

5,000 men, of which 598 officers, 2103 non-commissioned officers and 2299 soldiers.

To evaluate the association between beer and wine consumption and dietary patterns.

A 150-item semi-quantitative FFQ.

Healthy Eating Index 2010, the Mediterranean Diet Score and a pattern obtained by principal component analysis.

Beer (all types) and wine (red, white and rosé).

Total beer and wine consumption was calculated in ml/day. Beer and wine drinkers were defined as participants for whom ≥ 60 % of their total alcohol consumption was beer or wine respectively.

Age, Military rank, BMI, Physical activity level and smoking-stratified analysis and total energy intake.

Wine drinkers characterised by higher dietary scores and overall better lifestyle compared to beer drinkers.

(Mullie and Clarys, 2015)

US

Cross-sectional analysis from the National Longitudinal Study of Adolescent Health

(1995 and 2002).

12,958 young adults.

Age: 21,8±1,9

To examine the relationships between wine preference and selected health determinants in a US national sample of young adults.

Alcohol specific questionnaire.

Questionnaire about 2 dietary habits: fast food consumption and being a vegetarian.

Beer, wine, wine coolers and liquor, hard cider, straight liquor and mixed drinks, and whatever was available. Lifetime abstainers, and ex-drinkers. Preference defined using a question about the most often consumed beverage.

Age, gender, race/ ethnicity, and marital status.

Wine drinkers were in a larger percentage light-moderate drinker and self-defined vegetarians, and reported lower frequency of fast-food consumption.

(Paschall and Lipton, 2005)

ES

A cross-sectional analysis on the baseline data of the DiSA-UMH study, an ongoing cohort study.

(2006-2012)

Spanish health science students (n = 1098, of which 791 women and 307 men)
Age: 17-35

To assess the relationship between beverage consumption and adherence to the Mediterranean diet.

A validated 84-item FFQ.

Mediterranean diet adherence assessed through a modified version of the Mediterranean Diet Score.

Red wine, other wines, beer, medium alcoholic drinks such as sherry, dry wines or vermouth and spirits such as brandy, gin, rum, whisky or vodka.

Subjects were grouped into: non-drinkers (alcohol intake = 0 g/day), exclusive beer and/or wine drinkers (only beer, only wine or only beer and wine consumption) and drinkers of all types of alcoholic beverages.

Preferred beverage was that whose consumption was ≥ 50 % of the total alcohol.

Sex, age, BMI, hours of TV viewing per day, smoking status, soft drink intake and total energy intake

Exclusive drinkers of beer and/or wine had a significantly higher Mediterranean Diet adherence than non-drinkers. No association was found for all types of alcoholic beverages’ drinkers.

(Scholz et al., 2016)

ES

Cross-sectional analysis with data from the Non-communicable Disease Risk Factor Surveillance System (2000-2005).

12,037 adults
Age: 18-64

To examine the association between alcohol consumption patterns and adherence to major food consumption guidelines in adults in Spain.

Alcohol specific structured questionnaire on alcohol consumption in the previous week.

Structured 24-hour recall questionnaire. Adherence to food guidelines.

Wine, beer, spirits, and no preference. Preferred beverage defined as > 80 % of total alcohol intake.

Age, gender, education, social class, body mass index,

physical activity

and tobacco consumption.

Spirit consumers had lower fruit and vegetable consumption, and more frequently skipped a meal. Beer consumers adhered less frequently to guidelines as compared with those with no beverage preference.

(Valencia-Martín et al., 2011)

DK

Cross-sectional analyses from the Diet, Cancer and Health Study

(1995-1997).

48,763 middle-aged adults (50-64) of which 23,284 men and 25,479 women.

To determine the relationship between the intake of different alcoholic beverages and the indicators of a healthy diet

192-item FFQ

Selected food groups as indicators of a healthy diet. Assessment was made through a

192-item FFQ.

Beer, wine, and spirits (schnapps, whiskey, or gin)

5 drinking categories: Wine, beer, spirits, mixed drinkers and abstainers. Preferred beverage defined as the intake of beverage ≥ 50 % of total alcohol intake.

Αge, gender, education, smoking habits, total alcohol

intake and BMI.

Wine drinkers as compared with other alcoholic drinkers showed a healthier dietary pattern (higher intake of fruit, fish, vegetables, and salad, and a stronger preference for olive oil for cooking).

(Tjønneland et al., 1999)

ES

Cross-sectional analysis of the baseline data of the PREDIMED study.

3825 participants, of which 1675 men aged 55 to 80 and 2150 women aged 60 to 80 - with no documented cardiovascular disease but at high risk of CVD.

To evaluate the association between alcoholic beverage preference and food habits in a Mediterranean population.

137-item validated FFQ.

Mediterranean Dietary Score (not including scoring from alcohol) and food groups’ consumption assessed through 137-item validated FFQ.

Wine, beer, spirits, no preference, non-consumers. Preferred beverage defined as > 50 % of total alcohol intake.

Age, BMI, blood cholesterol, and energy intake.

No significant differences found in adherence to the Mediterranean food between the main types of alcoholic beverage consumed.

(Carmona-Torre et al., 2008)

US

Cross-sectional analyses with data from the continuing Survey of Food Intake by Individuals

(1994-96, 1998).

11,898 adults (6,040 men and 5,858 women).

To examine the independent associations between consumption of food categories and beverages and the Healthy Eating Index (HEI).

Two 24-hour dietary recall instruments.

Health Eating Index (HEI)

Two 24-hour dietary recall instruments were applied on non-consecutive days.

Wine, and beer and ales. Preference was not determined.

Gender stratification.

Wine consumption was positively associated with the HEI for both males and females. Consumption of beer was positively associated with the HEI for males, but not for females.

(Forshee and Storey, 2006)

FR

Cross-sectional analysis with data from the STANISLAS study - a 10-year longitudinal study conducted since 1994.

423 fathers aged 30–60 (median age: 42).

To describe the association between drinking patterns of preferred alcoholic beverages and dietary patterns.

3-day dietary record completed on two weekdays and one weekend day.

Daily intake of specific food groups and 2 dietary patterns derived from principal component analysis.

Wine, beer, spirits Preferred beverage defined as that which represented pure alcohol intake ≥ 50 % of the total alcohol consumed.

Four drinking patterns (consuming 3–112 g/day).

Age, nonalcohol energy intake, alcohol intakes, cigarette smoking, body mass index, education and season.

Dietary patterns were not related to alcohol preference.

(Herbeth et al., 2012)

FR

Cross-sectional analysis in the context of SU.VI.MAX study - an 8-year randomized, double-blind, placebo-controlled trial

(1994-2002).

2126 men enrolled in 1994.
Age: 45–60

To describe associations between drinking patterns in relation with socio-economic and lifestyle characteristics.

Twelve 24-hour dietary recalls (completed on 8 weekdays and 4 weekend days per year).

The % of energy intake consumed at each meal (breakfast, lunch, dinner and snacks)

Beer and cider, table wines (red, rosé or white), local wines (red, rosé or white), high quality wines (red, rosé or white), champagne, low-alcohol aperitifs (fruit punch, sweet wine, sangria, kir/royal kir, amer picon/Americano, picon-beer, cocktails), high-alcohol aperitifs (aniseed aperitifs, Whisky – Bourbon, vodka, gin, tequila, rum, Marie-Brisard), and digestives (brandy, liquor).
Drinking patterns: Abstainers, low drinkers, high quality wine drinkers, beer and cider, digestives, local wines, table wines, abstainers. Cluster analysis.

Age.

The intake of high-quality wine had a higher contribution in energy at dinner, while beer and cider intake was associated with a higher contribution in energy when snacking.

(Rouillier et al., 2004)

ES

Cross-sectional study.

1262 men and women.
Age: 18-70

To assess the association between consumption of different types of beverages along with physical activity and MedDiet adherence.

A 24-hour fluid-specific diary over seven consecutive days.

Mediterranean diet adherence assessed through a 14-item validated screener.

Physical activity evaluated with a non-validated self-filled questionnaire.

Time, types and volumes of beverages using standard portion sizes were assessed. The alcoholic drinks (beer, alcohol-free beer, lemon beer, wine, wine with soda, alcoholic mixed drinks, other alcoholic drinks) were recorded. Preference was not determined.

Gender, age, population /region, socioeconomic characteristics, educational level.

Individuals with greater adherence to the MedDiet showed a higher intake of water and wine and a lower consumption of sweet regular beverages, and they engaged in more physical activity.

(Ferreira-Pêgo et al., 2017)

ES

Cross-sectional study

(April 2012-June 2013)

231 subjects

Age: 55–85

To evaluate the associations between moderate alcohol intake and the type of beverages consumed and health, behaviour and quality of life in elderly people.

Interviews were conducted by a trained nutritionist with an ad hoc frequency recall questionnaire specific for alcoholic drinks and dealcoholised beer.

A SF-36 questionnaire assessing physical activity, activities of daily living, Mediterranean diet-adherence score, tobacco consumption, quality of sleep, body composition, medication and perception of health.

Wine, beer, champagne, cider, liquors, spirits and all the mixtures. Drinkers were classified in three groups according to their alcohol intake: 1) abstainers and occasional consumers (ABS) (< 4 alcohol drinks per month); 2) beer consumers (≥ 80 % of alcohol intake was beer), and 3) mixed beverage consumers.

Age, gender, socioeconomic status and chronic disease prevalence, PA (physical activity), METs (metabolic equivalents) (minutes per week).

Moderate alcohol consumption, and in particular wine consumption, is associated with a more active lifestyle and better perception of own health in the Spanish elderly subjects studied.

(González-Rubio et al., 2016)

FFQ: ‘Subjective measure using a predefined, self- or interviewer administered format'(Shim et al., 2014)

24-hour dietary recalls: ‘Subjective measure using open-ended questionnaires administered by a trained interviewer'(Shim et al., 2014)

Diet Quality Scores: include variables that represent current nutrition guidelines or recommendations, such as the Diet Quality Index (DQI), the Healthy Eating Index (HEI), the Dietary Guidelines Index (DGI), the Meditarranean Diet Index (MDI) (Waijers et al., 2007)

Cross-sectional study : Observational study with individual-level variables, measuring exposure and disease at the same time to investigate relationships (Cataldo et al., 2019)

Ecological studies : Descriptive studies that examine populations or groups as the unit of observation (Cataldo et al., 2019).

For their assessment, seven studies measured nutrient intake across beverage preference categories (Alcácera et al., 2008; Barefoot et al., 2002; Männistö et al., 1997; McCann et al., 2003; Ruidavets et al., 2004; Sluik et al., 2014; Sluik et al., 2016c), eleven studies assessed intake according to food group (Alcácera et al., 2008; Barefoot et al., 2002; Carmona-Torre et al., 2008; Chatenoud et al., 2000; Herbeth et al., 2012; McCann et al., 2003; Ruidavets et al., 2004; Sluik et al., 2014; Sluik et al., 2016b; Sluik et al., 2016c; Tjønneland et al., 1999), and fourteen assessed diet via degree of adherence to food guidelines (Alcácera et al., 2008; Valencia-Martín et al., 2011), dietary patterns (Herbeth et al., 2012; Sánchez-Villegas et al., 2009; Sluik et al., 2016b), and diet quality indexes (Alcácera et al., 2008; Carmona-Torre et al., 2008; Ferreira-Pêgo et al., 2017; Forshee and Storey, 2006; Mullie and Clarys, 2015; Ruidavets et al., 2004; Scholz et al., 2016; Sluik et al., 2014; Sluik et al., 2016b). In one study, a cluster analysis was performed to determine how drinking patterns and socioeconomic and lifestyle variables are related, including mean caloric intake and distribution of energy intake throughout the day (Rouillier et al., 2004). Meanwhile, other studies were based on quality of life, using for their assessment the Mediterranean diet adherence score and physical activity habits (González-Rubio et al., 2016), or diet and lifestyle (Barefoot et al., 2002; Ferreira-Pêgo et al., 2017; McCann et al., 2003; Mullie and Clarys, 2015; Paschall and Lipton, 2005; Ruidavets et al., 2004). All five of the ecological studies used expenditures/purchases on food/beverage items (Berger et al., 2020; Gell and Meier, 2012; Hansel et al., 2015; Johansen et al., 2006) and food and tobacco expenditures (Uusitalo et al., 2019).

2. Preferred type of Alcoholic beverage and socio-demographic characteristics

In general, it is worth noting that there are substantial differences in socio-demographic characteristics, whether between drinkers and non–drinkers or between drinkers of different preferred alcoholic beverages. Most findings show that wine consumers have a higher income and are more likely to follow a diet, and that wine is more popular among women than men. Men consume alcoholic beverages in higher quantities and at a higher frequency than women do, with a preference for beer. Smoking is more prevalent among beer consumers, who tend to be younger. The educational level of wine, beer and spirit consumers varies between the studies. As a general observation, spirits were the least preferred alcoholic beverage in all studies and were associated with less healthy dietary and lifestyle habits.

2.1. Wine preference/choice

Wine as the preferred alcoholic beverage seems to be associated with an overall healthier diet and lifestyle, although the influence of bias should not be underestimated.

When summarising the results from the reviewed publications related to wine as the alcoholic beverage of choice, it seems that in the majority (nineteen out of twenty-six) of studies wine drinkers:

● had higher adherence to healthy dietary patterns (Paschall and Lipton, 2005; Ruidavets et al., 2004; Sánchez-Villegas et al., 2009; Tjønneland et al., 1999);

● exhibited healthier overall behaviours (González-Rubio et al., 2016; McCann et al., 2003; Mullie and Clarys, 2015; Rouillier et al., 2004; Ruidavets et al., 2004; Sluik et al., 2014),

● had better health status (Sluik et al., 2016b);

● had healthier diets/higher quality diet (Barefoot et al., 2002; Ferreira-Pêgo et al., 2017; Forshee and Storey, 2006; Hansel et al., 2015; Johansen et al., 2006; Sluik et al., 2016b);

● had better quality of life and physical activity habits (Ferreira-Pêgo et al., 2017; González-Rubio et al., 2016) with higher antioxidants content (Männistö et al., 1997).

In addition, people who mainly buy wine and consume it at home generally had a healthier food choice (Berger et al., 2020; Gell and Meier, 2012; Johansen et al., 2006).

More specifically, findings from cross-sectional studies showed that, as compared to the consumers/consumption of other alcoholic beverages, in terms of food groups, wine consumption was associated with a higher consumption of fruit, vegetables, fish, salads, olive oil, juices and grain (Barefoot et al., 2002; McCann et al., 2003; Tjønneland et al., 1999) and in general wine consumers were more likely to be vegetarian and have less unhealthy dietary habits (e.g., consumption of fast food) (Paschall and Lipton, 2005). As regards nutrients, wine consumers had higher intakes of protein, carbohydrates, fiber, potassium, folate, vitamin C and carotenoids (Männistö et al., 1997; McCann et al., 2003).

Regarding adherence to dietary guidelines and overall diet quality, results showed that moderate wine consumers exhibited healthier dietary behaviours (Barefoot et al., 2002; Ferreira-Pêgo et al., 2017; Forshee and Storey, 2006; McCann et al., 2003; Mullie and Clarys, 2015; Ruidavets et al., 2004; Sánchez-Villegas et al., 2009; Scholz et al., 2016; Sluik et al., 2014; Sluik et al., 2016b; Tjønneland et al., 1999).

Furthermore, wine consumers seem to be more engaged in higher physical activity (Ferreira-Pêgo et al., 2017; Ruidavets et al., 2004), have better health status and perception of health (González-Rubio et al., 2016; Sluik et al., 2016b), smoke less (McCann et al., 2003) and generally have better lifestyle habits (González-Rubio et al., 2016; Mullie and Clarys, 2015).

From the ecological studies conducted in Europe, findings showed statistically significant differences in spending on healthy foods between wine-preference households and those preferring beer/spirits (7.0 % and 5.5 % respectively), adjusted for income (Gell and Meier, 2012). Similar and even more pronounced trends were observed in a French supermarket cohort of 196,000 subjects (Hansel et al., 2015): the findings revealed that, in terms of healthy versus unhealthy food budget, purchasers of beer constituted the lowest level with a proportion of 48.9 % compared to 58.3 % for Bordeaux wine purchasers (Hansel et al., 2015). Another study showed that compared to wine buyers, beer buyers bought more ready-cooked dishes, sugar, cold cuts, chips, pork, sausages and soft drinks (Johansen et al., 2006).

In a Danish study, results showed that wine buyers preferred healthier foods, such as fruit and vegetables, poultry, oils and low-fat cheese, whereas beer buyers bought more sugar, chips, pork, lamb, sausages and soft drinks (Johansen et al., 2006). Moreover, the most recently conducted study in the U.K. showed that people consuming wine at home have a diet with a lower percentage of energy coming from unhealthy foods, saturated fats and sugar and the highest from protein (Berger et al., 2020).

It is worth mentioning that some studies in Mediterranean countries, including Italy and Spain, did not observe such strong relationships between wine preference and healthy dietary habits, in contrast to observations made in Northern-European and US populations. In particular, small differences or not significant associations between alcohol preference and dietary patterns/diet quality were observed in some studies. It should be noted that these findings were revealed in studies mainly conducted in the Mediterranean basin (Alcácera et al., 2008; Carmona-Torre et al., 2008; Chatenoud et al., 2000; Herbeth et al., 2012; Scholz et al., 2016). Specifically, Alcácera et al. (2008) did not observe any relevant differences in adherence to the Mediterranean diet according to alcoholic beverage preference. Meanwhile, Chatenoud et al. (2000) found no relationship between wine drinkers or mixed drinkers and the indicators of a healthy diet, such as fruit, vegetables and fish. Moreover, another study showed that no significant differences were found in adherence to the Mediterranean diet according to the different types of alcoholic beverage consumed (Carmona-Torre et al., 2008), similar to the findings of a French ecological study (Herbeth et al., 2012).

2.2. Beer preference

In general, no regional differences were found between consumers with a preference for beer, who generally had less healthy dietary and lifestyle habits. Research showed that beer drinkers were more likely to be smokers (Barefoot et al., 2002; Männistö et al., 1997; Mullie and Clarys, 2015; Paschall and Lipton, 2005; Ruidavets et al., 2004) and less physically active (Mullie and Clarys, 2015; Paschall and Lipton, 2005; Ruidavets et al., 2004), and they were less likely to be light-to-moderate drinkers (Paschall and Lipton, 2005) compared to wine and/or other drinkers. Ruidavets et al.(2004) showed that in beer drinkers, energy intake was about 9 % higher, energy supplied by protein was lower and energy from fat was higher than among wine drinkers. Consumption of vegetables, fruits, bread, soft cheese and eggs was significantly lower and potato consumption significantly higher among beer drinkers than among wine drinkers. Similar trends were displayed in diet quality: authors found lower diet quality among beer drinkers than among wine drinkers (Barefoot et al., 2002; Forshee and Storey, 2006; Mullie and Clarys, 2015; Ruidavets et al., 2004) and an inverse linear trend between beer and spirits consumption and adherence to the Mediterranean Dietary Pattern (Mullie and Clarys, 2015; Sánchez-Villegas et al., 2009). Another study conducted in the Netherlands showed that beer drinkers had a higher absolute intake of meat, soft drinks, margarine and snacks, and they consumed more energy and less vegetables and fruit juices than wine consumers; however, adherence to the Dutch dietary guidelines did not differ between preference categories (Sluik et al., 2014). Similar conclusions were reached in other studies, in which beer drinkers were found to have less healthy diets (Barefoot et al., 2002), significantly lower intake of vitamins C and E (McCann et al., 2003) and lower carotenoid intake of than wine drinkers (McCann et al., 2003) or wine/spirits drinkers (Männistö et al., 1997). Research has showed that beer drinkers have worse health status than wine drinkers (Sluik et al., 2016b). Beer consumption was associated with higher energy consumption and total and saturated fat intake, but less added sugar consumption (Mullie and Clarys, 2015). Beer drinkers had a higher frequency of fast food consumption (Paschall and Lipton, 2005) and greater odds of being smokers (Männistö et al., 1997).

No difference among exclusive beer or wine consumers was observed in the diet quality index (rMED), suggesting that beer and wine drinkers may have similar patterns of Mediterranean diet adherence (Scholz et al., 2016). Moreover, it is worth noting that the results of the cross-sectional analyses of a consortium of 29,423 elderly participants from 14 European countries showed that beer drinkers had lower intake of vegetables, PUFA and protein, compared to wine and spirits drinkers, even though no big differences were observed in dietary habits and diet quality according to alcoholic beverage preference (Sluik et al., 2016b). Beer consumers adhered less frequently to guidelines to compared to consumers with no beverage preference (Valencia-Martín et al., 2011). Beer and cider drinkers of often ate snacks and watched TV (Rouillier et al., 2004).

Other studies have also found that shopping baskets with beer as the dominant alcoholic beverage contained more fresh pork, beef, pastries and pickled cucumbers and beetroot than baskets containing cider (Uusitalo et al., 2019).

2.3. Spirit Preference

Findings showed that spirit consumers had the lowest diet quality and the highest intake of meat and spirits (Sluik et al., 2016b), which were mainly consumed in the evening (65 %), thus adhering the least to the Dutch guidelines for a healthy diet (Sluik et al., 2014). In Spain, it was shown that spirit preference was associated with smoking habits (Carmona-Torre et al., 2008), and inadequate consumption of fruit and vegetables, as well as with skipping breakfast (Valencia-Martín et al., 2011) ; it was also associated with a higher energy intake from food and lipids compared to the wine- and beer- preference consumers or non-drinkers (Alcácera et al., 2008). Consumption of poultry was significantly higher in the spirit drinkers group (Herbeth et al., 2012). In a US study, authors demonstrated that spirit preference was significantly associated with the highest intake of cholesterol and the lowest intake of fiber, and the highest proportion of smokers and the lowest proportion of physically active persons were found in the spirit preference group (Barefoot et al., 2002). Spirit preference was significantly associated with the highest intake of energy from fats, saturated fats and protein, especially among women, and spirit consumers displayed the highest physical activity index and the highest proportion of smokers (Männistö et al., 1997). Moreover, research showed that both men and women liquor consumers had lower intakes of fruit and vegetables, but gender differences in other food groups were detected (McCann et al., 2003). A lower adherence to the Mediterranean diet (Ferreira-Pêgo et al., 2017; Sánchez-Villegas et al., 2009), poor adherence to major food consumption guidelines (Valencia-Martín et al., 2011) and the lowest physical activity frequency (Ferreira-Pêgo et al., 2017) were recorded in drinkers with a preference for spirits. The ecological studies showed that the highest expenditure on unhealthy food occurred in the spirit-preferring households (Gell and Meier, 2012).

Discussion

From this review, it seems that alcoholic beverage preference is correlated with specific dietary and lifestyle habits. Individuals with a wine preference generally had healthier dietary and lifestyle habits than individuals with other preferences, which was mainly observed in Northern European and US studies, as well as to a lesser extent in Mediterranean countries; the latter discrepancy could be explained by the fact that the Mediterranean diet is a cultural heritage in South Europe and is not limited to certain consumer groups, and therefore differences between alcoholic beverages can be expected to be less marked. Those who preferred beer and spirits displayed less healthy dietary habits, without any regional discrepancies arising from the country where the studies were carried out.

The observed relationships between wine preference and a healthier dietary and lifestyle profile could be attributed to cultural, personal (beliefs, concerns, perceptions and attitudes), behavioural and socio-demographic determinants, and their latent interrelations.

From historical perspective, in Mediterranean countries the use of wine without social aspects is meaningless. Wine is considered to be the cornerstone of the traditional Mediterranean dietary patterns in social context, always being consumed at mealtimes with a strong “essence of sharing and conviviality” (Fara, 2015). The worldwide popularity of the Mediterranean diet for its healthiness and sustainability (Fara, 2015) is undeniable, being similar in philosophy to diets in Blue Zones, areas of the world where people live exceptionally long lives (Buettner and Skemp, 2016).

Moreover, the health benefits of wine consumption - in particular regarding red wine and cardiovascular disease prevention - have been extensively studied in literature, mainly due to its high antioxidant content (Das et al., 2011), thus exposing consumers to a vast array of marketing claims for the role of resveratrol in health and wellness (Higgins and Llanos, 2015). Red wine contains polyphenolic compounds that are associated with the reduction of the inflammatory process, oxidative stress (OS), oxidation of LDL-cholesterol and platelet aggregation, and as a consequence it has a protective role against cardiovascular diseases. Resveratrol is among the most interesting polyphenols in red wine since it is believed to aid in a wide range of medical problems by reducing oxidative stress (Koushki et al., 2020). However, it has been suggested that beyond polyphenols newly detected molecules, such as melatonin and hydroxytyrosol (Marhuenda et al., 2016; Marhuenda et al., 2017), produce anti-oxidative effects in synergy. Consumers with few health issues or concerns about their health are more likely to follow a healthy diet, and the knowledge of the beneficial role of wine on health could influence their willingness to consume wine as part of their diet, suggesting that they value the relationship between food/beverage intake and their health status (Higgins and Llanos, 2015). This speculation is also justified by the following findings: a higher proportion of participants who followed a specific diet for hypertension, hypercholesterolemia or diabetes was found among wine drinkers (Ruidavets et al., 2004), wine drinkers were more likely to have dyslipidemia or to be overweight (Carmona-Torre et al., 2008), a higher percentage of wine drinkers considered themselves to be vegetarians (Paschall and Lipton, 2005), and had better health status (Sluik et al., 2016b) and the ratio of budget for healthy food over budget for unhealthy food was higher for wine drinkers, particularly Bordeaux wine (58.3 %) purchasers (Hansel et al., 2015).

In a study carried out by Sluik et al. (2014) in the Netherlands, about half of the wine consumed was found to be red (46 %), followed by white wine (32 %), and it was mostly consumed in the evening (56 %), but also often during dinner (27 %), which is in agreement with the recommended Mediterranean drinking pattern.

As regards the behavioural characteristics of wine drinkers, the literature suggests that healthy diets on their own are not sufficient for improving health, if they are not combined with daily physical exercise (Fara, 2015). Moreover, regular physical activity is considered to be related to stress reduction and better mood, partly explaining the mediating associations between depression, stress and health outcomes (Hamer et al., 2012). Research has shown the co-occurrence of anxiety disorders and alcohol-use disorders (Smith and Randall, 2012). A recently conducted study demonstrated the positive mood modulation of resveratrol (Zhu et al., 2019). Beyond that, epidemiological research showed that adherence to healthy or Mediterranean dietary patterns is associated with a reduced risk of depression (Lassale et al., 2019). In the present review, it was revealed that among wine drinkers the prevalence of physical activity was higher (Ferreira-Pêgo et al., 2017; González-Rubio et al., 2016; Ruidavets et al., 2004), the perception of their own health was better (González-Rubio et al., 2016), the prevalence of depressive symptoms and of alcohol-related problems were lower (Paschall and Lipton, 2005), a healthier drinking pattern was exhibited (Ferreira-Pêgo et al., 2017). Moreover, a recent review demonstrated that binge drinking and binge eating are different sides of the same coin (Escrivá-Martínez et al., 2020) and thus a healthy drinking pattern goes “hand in hand” with a healthy diet. A cross-sectional study conducted on Danish adults concluded that wine drinking was associated with optimal social, intellectual and personality capacities, compared to beer drinking (Mortensen et al., 2001). This is also illustrated by the results of the study by Valencia-Martin et al., which showed that binge drinking is associated with less adherence to dietary guidelines and less physical activity (Valencia-Martín et al., 2011). Other studies also reported that heavy drinking was related to a lower intake of dietary fibre, fruit and vegetables (Ruidavets et al., 2004; Tjønneland et al., 1999; Valencia-Martín et al., 2011). The trend for a healthier lifestyle among wine drinkers is also justified in the present review by a lower prevalence of smoking habits (Carmona-Torre et al., 2008; Rouillier et al., 2004). Another probable underlying explanation of the observed correlations between wine drinking and healthier dietary and lifestyle habits is the socio-demographic factors among wine drinkers, such as the female gender, older age bracket and generally higher-income, which are considered as strong determinants of health behaviours, although with contradictory effects. For instance, in our review wine preference was observed in higher-income (Barefoot et al., 2002; McCann et al., 2003) and higher education participants (Paschall and Lipton, 2005), whereas another study found no significant difference in education and employment status between the groups with different alcoholic beverage preferences (González-Rubio et al., 2016). Moreover, in the study by Rouillier et al. (2004), differences in terms of education and employment status of wine drinkers were observed depending on the type of wine they drank. The literature suggests that there is interplay between age, gender, chemosensory responsiveness and alcohol consumption (Cravero et al., 2020). It seems that regional differences in socio-demographic factors could influence the preference for a specific alcoholic beverage. In countries dominating global wine production and trade, where wine is more accessible in price and linked to gastronomy, a dominant preference for wine can be expected, as is the case in Mediterranean countries. On the other hand, in Northern-European countries and in the US, it seems that income could play a role in the preference for wine. In particular, higher income households purchase healthier foods (French et al., 2019) and can afford to purchase more expensive wine. Hence, it seems that through diverse mechanisms, socio-economic factors may influence dietary behaviour. Indeed, in the cross-sectional Dutch study on 12965 subjects conducted by Hulshof et al. (2003), the consumption of wine, especially with meals, was associated with a healthier dietary behaviour. On the other hand, beer was consumed mostly outside meals and formed part of a less healthy dietary pattern. It is worth noting that these findings were correlated with socio-economic factors; in particular, wine consumption was more frequent among subjects with higher educational and economic status, while beer consumption was found among classes with a lower income. Authors speculated that subjects with a higher educational level tended to be more aware of the characteristics of a healthy diet. Conversely, accessibility to healthy foods might be limited by low income. Similar conclusions were previously drawn in studies by Kesse et al. (2001) and Marques-Vidal et al. (2000), in which a light-to-moderate alcohol drinking pattern (especially for wine) and healthy dietary behaviour were positively correlated to socioeconomic factors in 72904 middle-aged French women and 1367 Irish men.

The aforementioned conclusions are confirmed by the results of the most recently conducted prospective cohort study on 309,123 participants with a median follow-up period of 9 years, and which studied beverage type, consumption with food and consumption frequency as exposures. This study found that the consumption of red wine within the context of a healthy drinking pattern and when consumed at meals was associated with lower risk of mortality and vascular events among regular alcohol drinkers, after adjusting for the effects of average amount consumed (Jani et al., 2021).

The following general conclusions can be drawn from the data collected in this review: i) socio-economic status and demographic characteristics are correlated with alcoholic beverage preferences: wine drinkers are generally middle aged, with higher incomes and level of education than beer or spirit consumers; wine is preferred by women and beer by men in the majority of the studies, ii) wine consumers, especially in Northern European countries and the US, generally adhere to a healthier dietary pattern and lifestyle and follow the national dietary guidelines, iii) beer is the second alcoholic beverage that is consumed, especially among young people, and it is generally associated with a less healthy dietary pattern, a higher energy intake and consumption of food with relatively poor nutritional quality, and iv) spirits are the least preferred alcoholic beverage in all the studies and are associated with less healthy dietary and lifestyle habits (including smoking), low adherence to dietary guidelines and the lowest physical activity status.

Limitations

Due to the cross-sectional and ecological nature of the included studies no temporal relationship and, hence, causal inferences can be made. However, this limitation does not weaken the importance of the findings, given that the aim of the present review was to evaluate whether alcoholic beverages preference is associated with certain dietary and lifestyle habits, and not to assess causality. Furthermore, recall bias could be an issue among wine drinkers with higher health literacy. According to Grønbaek (2001), reporting bias relevant to the type of alcoholic beverage does not appear to be a problem in the majority of the population studies (GrØnbaek, 2001). Moreover, the lack of a formal definition of “preference”, the absence of conducted studies in many regions around the world, the high heterogeneity between the studies, the wide spectrum of possible outcomes relevant to diet and lifestyle and the lack of quality assessment of the reviewed studies could influence the generalisability of the findings. The risk of bias assessment of cross-sectional studies is heterogeneous with less applicability (Migliavaca et al., 2020) than other observational study designs, for which standard, valid and widely used tools are available.

Conclusions

This review has demonstrated that alcoholic beverage preference is associated with diet and lifestyle habits, including drinking patterns and absolute alcohol consumption. Age, gender and socio-economic status are shown to be confounding factors in the association between alcoholic beverage consumption and health outcomes. Given that alcoholic beverage preference is linked to specific dietary and lifestyle patterns, it may be arbitrary and risky to attribute the risk of developing chronic diseases to alcoholic beverages without an in-depth investigation of the underlying inter-correlations with statistical adjustment for ‘dietary pattern’ as a confounding factor. Therefore, from a public health perspective it seems that drinking pattern, dietary pattern and lifestyle should be studied in combination and as such be evaluated in any future epidemiological studies analysing the relationship between alcohol consumption and underlying correlations in terms of health outcomes.

Acknowledgements

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Most authors are government delegates and/or experts to the International Organization of Vine and Wine’s (OIV) Commission IV Safety and Health. Although this work was initiated under the auspices of the OIV and its Consumption, Nutrition and Health expert group, the statements herein are the sole responsibility of the undersigned authors. The authors would like to acknowledge Ionas Papasotiriou for his support in the initial step of data curation.

References

  • Adjemian, M. K., Volpe, R. J., & Adjemian, J. (2015). Relationships between diet, alcohol preference, and heart disease and type 2 diabetes among Americans. PLoS ONE, 10(5), 1–12. doi:10.1371/journal.pone.0124351
  • Alcácera, M. A., Marques-Lopes, I., Fajó-Pascual, M., Foncillas, J. P., Carmona-Torre, F., & Martínez-González, M. A. (2008). Alcoholic beverage preference and dietary pattern in Spanish university graduates: The SUN cohort study. European Journal of Clinical Nutrition, 62(10), 1178–1186. doi:10.1038/sj.ejcn.1602833
  • Au Yeung, S. L., Jiang, C., Cheng, K. K., Cowling, B. J., Liu, B., Zhang, W., Lam, T. H., Leung, G. M., & Schooling, C. M. (2013). Moderate Alcohol Use and Cardiovascular Disease from Mendelian Randomization. PLoS ONE, 8(7), 1-9. doi:10.1371/journal.pone.0068054
  • Barefoot, J. C., Grønbæk, M., Feaganes, J. R., McPherson, R. S., Williams, R. B., & Siegler, I. C. (2002). Alcoholic beverage preference, diet, and health habits in the UNC Alumni Heart Study. American Journal of Clinical Nutrition, 76(2), 466–472. doi:10.1093/ajcn/76.2.466
  • Berger, N., Cummins, S., Allen, A., Smith, R. D., & Cornelsen, L. (2020). Patterns of beverage purchases amongst British households: A latent class analysis. PLoS Medicine, 17(9), 1–20. doi:10.1371/JOURNAL.PMED.1003245
  • Buettner, D., & Skemp, S. (2016). Blue Zones: Lessons From the World’s Longest Lived. American Journal of Lifestyle Medicine, 10(5), 318–321. doi:10.1177/1559827616637066
  • Carmona-Torre, F. D. A., Garcia-Arellano, A., Marques-Lopes, I., Basora, J., Corella, D., Gómez-Gracia, E., Fiol, M., Covas, M. I., Aros, F., Conde, M., Lapetra, J., Estruch, R., & Martinez-Gonzalez, M. A. (2008). Relationship of alcoholic beverage consumption to food habits in a mediterranean population. American Journal of Health Promotion, 23(1), 27–30. doi:10.4278/ajhp.07050143
  • Cataldo, R., Arancibia, M., Stojanova, J., & Papuzinski, C. (2019). General concepts in biostatistics and clinical epidemiology: Observational studies with cross-sectional and ecological designs. Conceptos generales en bioestadística y epidemiología clínica: estudios observacionales con diseños transversal y ecológico. Medwave, 19(8), e7698. doi:10.5867/medwave.2019.08.7698
  • Chatenoud, L., Negri, E., La Vecchia, C., Volpato, O., & Franceschi, S. (2000). Short communication wine drinking and diet in Italy. European Journal of Clinical Nutrition, 54(2), 177–179. doi:10.1038/sj.ejcn.1600913
  • Cravero, M. C., Laureati, M., Spinelli, S., Bonello, F., Monteleone, E., Proserpio, C., Lottero, M. R., Pagliarini, E., & Dinnella, C. (2020). Profiling Individual Differences in Alcoholic Beverage Preference and Consumption: New Insights from a Large-Scale Study. Foods, 9(8), 1-17. doi:10.3390/foods9081131
  • Das, D. K., Mukherjee, S., & Ray, D. (2011). Erratum to: Resveratrol and red wine, healthy heart and longevity (Heart Failure Reviews (2011) 16 (425-435)). Heart Failure Reviews, 16(4), 425–435. doi:10.1007/s10741-011-9234-6
  • Escrivá-Martínez, T., Herrero, R., Molinari, G., Rodríguez-Arias, M., Verdejo-García, A., & Baños, R. M. (2020). Binge Eating and Binge Drinking: A Two-Way Road? An Integrative Review. Current Pharmaceutical Design, 26(20), 2402–2415. doi:10.2174/1381612826666200316153317
  • Fara, G. M. (2015). Nutrition between sustainability and quality. Annali Di Igiene : Medicina Preventiva e Di Comunità, 27(5), 693–704. doi:10.7416/ai.2015.2061
  • Ferreira-Pêgo, C., Babio, N., & Salas-Salvadó, J. (2017). A higher Mediterranean diet adherence and exercise practice are associated with a healthier drinking profile in a healthy Spanish adult population. European Journal of Nutrition, 56(2), 739–748. doi:10.1007/s00394-015-1117-5
  • Forshee, R. A., & Storey, M. L. (2006). Demographics, not beverage consumption, is associated with diet quality. International Journal of Food Sciences and Nutrition, 57(7–8), 494–511. doi:10.1080/09637480600991240
  • French, S. A., Tangney, C. C., Crane, M. M., Wang, Y., & Appelhans, B. M. (2019). Nutrition quality of food purchases varies by household income: The SHoPPER study. BMC Public Health, 19(1), 1–7. doi:10.1186/s12889-019-6546-2
  • Gea, A., Bes-Rastrollo, M., Toledo, E., Garcia-Lopez, M., Beunza, J. J., Estruch, R., & Martinez-Gonzalez, M. A. (2014). Mediterranean alcohol-drinking pattern and mortality in the SUN (Seguimiento Universidad de Navarra) Project: A prospective cohort study. British Journal of Nutrition, 111(10), 1871–1880. doi:10.1017/S0007114513004376
  • Gell, L., & Meier, P. (2012). The nature and strength of the relationship between expenditure on alcohol and food: An analysis of adult-only households in the UK. Drug and Alcohol Review, 31(4), 422–430. doi:10.1111/j.1465-3362.2011.00330.x
  • González-Rubio, E., San Mauro, I., López-Ruíz, C., Díaz-Prieto, L. E., Marcos, A., & Nova, E. (2016). Relationship of moderate alcohol intake and type of beverage with health behaviors and quality of life in elderly subjects. Quality of Life Research, 25(8), 1931–1942. doi:10.1007/s11136-016-1229-2
  • GrØnbaek, M. (2001). Factors influencing the relation between alcohol and mortality - With focus on wine. Journal of Internal Medicine, 250(4), 291–308. doi:10.1046/j.1365-2796.2001.00885.x
  • Hamer, M., Endrighi, R., & Poole, L. (2012). Physical activity, stress reduction, and mood: Insight into immunological mechanisms. Methods in Molecular Biology (Clifton, N.J.), 934, 89–102. doi:10.1007/978-1-62703-071-7_5
  • Hansel, B., Roussel, R., Diguet, V., Deplaude, A., Chapman, M. J., & Bruckert, E. (2015). Relationships between consumption of alcoholic beverages and healthy foods: The French supermarket cohort of 196,000 subjects. European Journal of Preventive Cardiology, 22(2), 215–222. doi:10.1177/2047487313506829
  • Herbeth, B., Samara, A., Stathopoulou, M., Siest, G., & Visvikis-Siest, S. (2012). Alcohol consumption, beverage preference, and diet in middle-aged men from the Stanislas study. Journal of Nutrition and Metabolism, 987243, 1–7. doi:10.1155/2012/987243
  • Higgins, L. M., & Llanos, E. (2015). A healthy indulgence? Wine consumers and the health benefits of wine. Wine Economics and Policy, 4(1), 3–11. doi:10.1016/j.wep.2015.01.001
  • Hu, F. B. (2002). Dietary pattern analysis: A new direction in nutritional epidemiology. Current Opinion in Lipidology, 13(1), 3–9. doi:10.1097/00041433-200202000-00002
  • Hulshof, K. F. A. M., Brussaard, J. H., Kruizinga, A. G., Telman, J., & Löwik, M. R. H. (2003). Socio-economic status, dietary intake and 10 y trends: The Dutch National Food Consumption Survey. European Journal of Clinical Nutrition, 57(1), 128–137. doi:10.1038/sj.ejcn.1601503
  • Jani, B. D., McQueenie, R., Nicholl, B. I., Field, R., Hanlon, P., Gallacher, K. I., Mair, F. S., & Lewsey, J. (2021). Association between patterns of alcohol consumption (beverage type, frequency and consumption with food) and risk of adverse health outcomes : a prospective cohort study. BMC Medicine, 19(1), 1–14. doi:10.1186/s12916-020-01878-2
  • Johansen, D., Friis, K., Skovenborg, E., & Grønbæk, M. (2006). Food buying habits of people who buy wine or beer: Cross sectional study. British Medical Journal, 332(7540), 519–521. doi:10.1136/bmj.38694.568981.80
  • Kesse, E., Clavel-Chapelon, F., Slimani, N., & Van Liere, M. (2001). Do eating habits differ according to alcohol consumption? Results of a study of the French cohort of the European Prospective Investigation into Cancer and Nutrition (E3N-EPIC). American Journal of Clinical Nutrition, 74(3), 322–327. doi:10.1093/ajcn/74.3.322
  • Knoops, K. T. B., De Groot, L. C. P. G. M., Kromhout, D., Perrin, A. E., Moreiras-Varela, O., Menotti, A., & Van Staveren, W. A. (2004). Mediterranean diet, lifestyle factors, and 10-year mortality in elderly European men and women: The HALE project. Journal of the American Medical Association, 292(12), 1433–1439. doi:10.1001/jama.292.12.1433
  • Koushki, M., Lakzaei, M., Khodabandehloo, H., Hosseini, H., Meshkani, R., & Panahi, G. (2020). Therapeutic effect of resveratrol supplementation on oxidative stress: A systematic review and meta-analysis of randomised controlled trials. Postgraduate Medical Journal, 96(1134), 197–205. doi:10.1136/postgradmedj-2019-136415
  • Kunzmann, A. T., Coleman, H. G., Huang, W. Y., & Berndt, S. I. (2018). The association of lifetime alcohol use with mortality and cancer risk in older adults: A cohort study. PLoS Medicine, 15(6), 1–18. doi:10.1371/journal.pmed.1002585
  • Lassale, C., Batty, G. D., Baghdadli, A., Jacka, F., Sánchez-Villegas, A., Kivimäki, M., & Akbaraly, T. (2019). Healthy dietary indices and risk of depressive outcomes: a systematic review and meta-analysis of observational studies. Molecular Psychiatry, 24(7), 965–986. doi:10.1038/s41380-018-0237-8
  • Männistö, S., Uusitalo, K., Roos, E., Fogelholm, M., & Pietinen, P. (1997). Alcohol beverage drinking, diet and body mass index in a cross-sectional survey. European Journal of Clinical Nutrition, 51(5), 326–332. doi:10.1038/sj.ejcn.1600406
  • Marhuenda, J., Medina, S., Martínez-Hernández, P., Arina, S., Zafrilla, P., Mulero, J., Genieser, H.G, Ferreres, F., & Gil-Izquierdo, Á. (2016). Melatonin and hydroxytyrosol-rich wines influence the generation of DNA oxidation catabolites linked to mutagenesis after the ingestion of three types of wine by healthy volunteers. Food & Function, 7(12), 4781-4796. doi: 10.1039/c6fo01246a.
  • Marhuenda, J., Medina, S., Martínez-Hernández, P., Arina, S., Zafrilla, P., Mulero, J., Oger, C., Galano, J.M, Durand, T., Ferreres, F., & Gil-Izquierdo, A. (2017). Melatonin and hydroxytyrosol protect against oxidative stress related to the central nervous system after the ingestion of three types of wine by healthy volunteers. Food & Function, 8(1), 64-74. doi: 10.1039/c6fo01328g.
  • Marques-Vidal, P., Arveiler, D., Evans, A., Montaye, M., Bingham, A., Ruidavets, J. B., McMaster, D., Haas, B., Amouyel, P., & Ducimetière, P. (2000). Patterns of alcohol consumption in middle-aged men from France and Northern Ireland. The PRIME study. European Journal of Clinical Nutrition, 54(4), 321–328. doi:10.1038/sj.ejcn.1600954
  • McCann, S. E., Sempos, C., Freudenheim, J. L., Muti, P., Russell, M., Nochajski, T. H., Ram, M., Hovey, K., & Trevisan, M. (2003). Alcoholic beverage preference and characteristics of drinkers and nondrinkers in western New York (United States). Nutrition, Metabolism and Cardiovascular Diseases, 13(1), 2–11. doi:10.1016/S0939-4753(03)80162-X
  • Migliavaca, C. B., Stein, C., Colpani, V., Munn, Z., & Falavigna, M. (2020). Quality assessment of prevalence studies: a systematic review. Journal of Clinical Epidemiology, 127, 59–68. doi:10.1016/j.jclinepi.2020.06.039
  • Mortensen, E. L., Jensen, H. H., Sanders, S. A., & Reinisch, J. M. (2001). Better Psychological Functioning and Higher Social Status May Largely Explain the Apparent Health Benefits of Wine:. Archives of Internal Medicine, 161(15), 1844–1848. doi:10.1001/archinte.161.15.1844
  • Mullie, P., & Clarys, P. (2015). Beer, wine and lifestyle: A cross-sectional study of the Belgian military population. Military Medical Research, 2(1), 1–7. doi:10.1186/s40779-015-0066-x
  • Osorio-Paz, I., Brunauer, R., & Alavez, S. (2019). Beer and its non-alcoholic compounds in health and disease. Critical Reviews in Food Science and Nutrition, 60(20), 3492–3505. doi:10.1080/10408398.2019.1696278
  • Paschall, M., & Lipton, R. I. (2005). Wine preference and related health determinants in a U.S. national sample of young adults. Drug and Alcohol Dependence, 78(3), 339–344. doi:10.1016/j.drugalcdep.2004.12.004
  • Rouillier, P., Boutron-Ruault, M. C., Bertrais, S., Arnault, N., Daudin, J. J., Bacro, J. N., & Hercberg, S. (2004). Drinking patterns in French adult men: A cluster analysis of alcoholic beverages and relationship with lifestyle. European Journal of Nutrition, 43(2), 69–76. doi:10.1007/s00394-004-0442-x
  • Ruidavets, J. B., Bataille, V., Dallongeville, J., Simon, C., Bingham, A., Amouyel, P., Arveiler, D., Ducimetière, P., & Ferrières, J. (2004). Alcohol intake and diet in France, the prominent role of lifestyle. European Heart Journal, 25(13), 1153–1162. doi:10.1016/j.ehj.2003.12.022
  • Sánchez-Villegas, A., Toledo, E., Bes-Rastrollo, M., Martín-Moreno, J. M., Tortosa, A., & Martínez-González, M. A. (2009). Association between dietary and beverage consumption patterns in the SUN (Seguimiento Universidad de Navarra) cohort study. Public Health Nutrition, 12(3), 351–358. doi:10.1017/S1368980008002127
  • Scholz, A., Navarrete-Muñoz, E. M., Garcia de la Hera, M., Gimenez-Monzo, D., Gonzalez-Palacios, S., Valera-Gran, D., Torres-Collado, L., & Vioque, J. (2016). Alcohol consumption and Mediterranean Diet adherence among health science students in Spain: The DiSA-UMH Study. Gaceta Sanitaria, 30(2), 126–132. doi:10.1016/j.gaceta.2015.10.011
  • Schutte, R., Papageorgiou, M., Najlah, M., Huisman, H. W., Ricci, C., Zhang, J., Milner, N., & Schutte, A. E. (2020). Drink types unmask the health risks associated with alcohol intake – Prospective evidence from the general population. Clinical Nutrition, 39(10), 3168–3174. doi:10.1016/j.clnu.2020.02.009
  • Shim, J. S., Oh, K., & Kim, H. C. (2014). Dietary assessment methods in epidemiologic studies. Epidemiology and Health, 36, e2014009, 1-8. doi:10.4178/epih/e2014009
  • Sluik, D., Van Lee, L., Geelen, A., & Feskens, E. J. (2014). Alcoholic beverage preference and diet in a representative Dutch population: The Dutch national food consumption survey 2007-2010. European Journal of Clinical Nutrition, 68(3), 287–294. doi:10.1038/ejcn.2013.279
  • Sluik, D., Bezemer, R., Sierksma, A., & Feskens, E. (2016a). Alcoholic Beverage Preference and Dietary Habits: A Systematic Literature Review. Critical Reviews in Food Science and Nutrition, 56(14), 2370–2382. doi:10.1080/10408398.2013.841118
  • Sluik, D., Brolsma, E. M. B., Vries, J. H. M. D., Geelen, A., & Feskens, E. J. M. (2016b). Associations of alcoholic beverage preference with cardiometabolic and lifestyle factors: The NQplus study. BMJ Open, 6(6), 1–9. doi:10.1136/bmjopen-2015-010437
  • Sluik, D., Jankovic, N., O’Doherty, M. G., Geelen, A., Schöttker, B., Rolandsson, O., Kiefte-De Jong, J. C., Ferrieres, J., Bamia, C., Fransen, H. P., Boer, J. M. A., Eriksson, S., Martínez, B., Huerta, J. M., Kromhout, D., de Groot, L. C., Franco, O. H., Trichopoulou, A., Boffetta, P., Kee, F. ,… Feskens, E. J. (2016c). Alcoholic beverage preference and dietary habits in elderly across Europe: Analyses within the Consortium on Health and Ageing: Network of Cohorts in Europe and the United States (CHANCES) project. PLoS ONE, 11(8), e0161603, 1-19. doi:10.1371/journal.pone.0161603
  • Smith, J. P., & Randall, C. L. (2012). Anxiety and alcohol use disorders: Comorbidity and treatment considerations. Alcohol Research: Current Reviews, 34(4), 414–431.
  • Tjønneland, A., Grønbœk, M., Stripp, C., & Overvad, K. (1999). Wine intake and diet in a random sample of 48763 danish men and women. American Journal of Clinical Nutrition, 69(1), 49–54. doi:10.1093/ajcn/69.1.49
  • Uusitalo, L., Erkkola, M., Lintonen, T., Rahkonen, O., & Nevalainen, J. (2019). Alcohol expenditure in grocery stores and their associations with tobacco and food expenditures. BMC Public Health, 19(1), 1–8. doi:10.1186/s12889-019-7096-3
  • Valencia-Martín, J. L., Galán, I., & Rodríguez-Artalejo, F. (2011). The association between alcohol consumption patterns and adherence to food consumption guidelines. Alcoholism: Clinical and Experimental Research, 35(11), 2075–2081. doi:10.1111/j.1530-0277.2011.01559.x
  • Waijers, P. M., Feskens, E. J., & Ocké, M. C. (2007). A critical review of predefined diet quality scores. The British journal of nutrition, 97(2), 219–231. doi:10.1017/S0007114507250421
  • Wood, A. M., Kaptoge, S., Butterworth, A., Nietert, P. J., Warnakula, S., Bolton, T., Paige, E., Paul, D. S., Sweeting, M., Burgess, S., Bell, S., Astle, W., Stevens, D., Koulman, A., Selmer, R. M., Verschuren, M., Sato, S., Njølstad, I., Woodward, M., … Thompson, S. (2018). Risk thresholds for alcohol consumption: combined analysis of individual-participant data for 599 912 current drinkers in 83 prospective studies. The Lancet, 391(10129), 1513–1523. doi:10.1016/S0140-6736(18)30134-X
  • Zhang, Y. B., Pan, X. F., Chen, J., Cao, A., Xia, L., Zhang, Y., Wang, J., Li, H., Liu, G., & Pan, A. (2021). Combined lifestyle factors, all-cause mortality and cardiovascular disease: A systematic review and meta-analysis of prospective cohort studies. Journal of Epidemiology and Community Health, 75(1), 92–99. doi:10.1136/jech-2020-214050
  • Zhu, X., Li, W., Li, Y., Xu, W., Yuan, Y., Zheng, V., Zhang, H., O’Donnell, J. M., Xu, Y., & Yin, X. (2019). The antidepressant- and anxiolytic-like effects of resveratrol: Involvement of phosphodiesterase-4D inhibition. Neuropharmacology, 153, 20–31. doi:10.1016/j.neuropharm.2019.04.022

Authors


Rena I. Kosti

renakosti@uth.gr

ORCID iD

Affiliation : Department of Nutrition and Dietetics, School of Physical Education, Sport Science & Dietetics, University of Thessaly, 42132 Trikala

Country : Greece


Chiara Di Lorenzo

ORCID iD

Affiliation : Department of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, 20133 Milan

Country : Italy


Demosthenes B. Panagiotakos

ORCID iD

Affiliation : Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, 17671 Athens

Country : Greece


George Sandeman

ORCID iD

Affiliation : Wine in Moderation, 1040 Bruxelles

Country : Belgium


Nadia Frittella

Affiliation : Wine in Moderation, 1040 Bruxelles

Country : Belgium


Barbara Iasiello

Affiliation : Safety & Health Unit - Organisation Internationale de la Vigne et du Vin, 75008 Paris, France

Country : France


Pierre-Louis Teissedre

ORCID iD

Affiliation : Université de Bordeaux, Unité de recherche Œnologie, EA 4577, USC 1366 INRA, ISVV, 33882 Villenave d’Ornon cedex - Inrae, ISVV, USC 1366 Œnologie, F-33140 Villenave d’Ornon

Country : France


Patrizia Restani

ORCID iD

Affiliation : Department of Pharmacological and Biomolecular Sciences, Università degli Studi di Milano, 20133 Milan - CRC “Innovation for Well-Being and environment”

Country : Italy

Attachments

No supporting information for this article

Article statistics

Views: 242

Downloads

XML: 20

Citations

PlumX