Alcohol consumption has become a widely prevalent life style in a multitude of societies and cultures, with approximately 40% of the world’s population drinking regularly [
Although the relationships between chronic alcohol consumption and disorders such as cancer and liver disease have been thoroughly studied [
The prevalence of MS varies largely across demographics [
This report is part of the Maracaibo City Metabolic Syndrome Prevalence Study (MMSPS), a cross-sectional study whose purpose is to identify Metabolic Syndrome and cardiovascular risk factors in the adult population of the Maracaibo, the second largest city of Venezuela. The sample (1,986 individuals) was calculated based on estimations of the city’s population by our National Institute of Statistics (1,428,043 inhabitants for the year 2007). A total of 244 subjects (12%) were added for oversampling, in order to increase accuracy of the estimates obtained from smaller subgroups from the overall sample, amounting to a total of 2,230 individuals. Maracaibo City is divided in parishes, each of which was proportionally sampled with a multistage cluster method: In the first stage, clusters were represented by sectors from each of the 18 parishes, selecting 4 from each parish by simple randomized sampling. In the second phase, clusters were represented by city blocks within each sector, which were selected by simple randomized sampling using a random number generation tool. From the overall population, 2,026 individuals were selected on the basis of availability of insulin determination. Further details of the sampling process have been previously published elsewhere [
All individuals enrolled in the study signed a written informed consent before undergoing physical examination and blood sample collection. All procedures were approved by the Ethics Committee of the Endocrine and Metabolic Diseases Research Center of The University of Zulia, Maracaibo, Venezuela.
Data were collected through completion of a full clinical record carried out by trained personnel, which included interrogation regarding personal and family medical history, with an emphasis on current or past acute or chronic liver disease. Likewise, ethnic origin, educational status, occupational status, tobacco use, and socioeconomic status, according to the Graffar scale modified by Méndez Castellano and de Méndez [
For the assessment of alcohol intake, subjects were asked to estimate the amount of alcoholic drinks they consumed within a month, with the approximate quantity and frequency of daily intake for each type of drink: beer, spirits, and wine and its derivatives. Accounting for the standard content of alcohol grams in each kind of beverage [ Gender-specific quartiles of alcohol grams consumed daily (25th percentile, 50th percentile, and 75th percentile). Three gender-specific conglomerate categories obtained from two-staged cluster analysis, which allows separation of patterns into clusters, sets, or groups, according to distance criteria (Figure
Diagram showing the processing of the sample applying two-staged cluster analysis for categorizing subjects according to gender, type of beverage, and daily alcohol intake. Maracaibo, 2015.
Blood pressure (BP) was taken with subjects sitting down with their feet on the floor following 15 minutes of rest, determined through the auscultatory method with a calibrated mercury sphygmomanometer, identifying Korotkoff’s phases I and V as systolic and diastolic BP, respectively. BP was determined 3 times, with 15 minutes in between each take, on two different days.
Waist circumference (WC) was measured using calibrated measuring tapes in accordance with the anatomical landmarks proposed by the USA National Institutes of Health protocol [
Overnight fasting determination of glucose, total cholesterol, triacylglycerides (TAG), and HDL-C was done with an automated analyzer (Human Gesellschaft für Biochemica und Diagnostica mbH, Germany); the intra-assay variation coefficients for total cholesterol, TAG, and HDL-C were 3%, 5%, and 5%, respectively. LDL-C and VLDL-C levels were calculated applying Friedewald’s formula [
MS was diagnosed using the criteria from the IDF/AHA/NHLBI-2009 consensus [
Qualitative variables were expressed as absolute and relative frequencies and were assessed for associations with Pearson’s Chi-squared (
A total of 2,230 subjects were studied (52.6% females,
Characteristics of general population by gender. Maracaibo, 2015.
Females | Males | Total | ||||
---|---|---|---|---|---|---|
|
|
|
||||
|
% |
|
% |
|
% | |
Age groups (years) | ||||||
18–29 | 349 | 29.8 | 413 | 39.0 | 762 | 34.2 |
30–44 | 325 | 27.7 | 297 | 28.1 | 622 | 27.9 |
45–59 | 346 | 29.5 | 259 | 24.5 | 605 | 27.1 |
≥60 | 152 | 13.0 | 89 | 8.4 | 241 | 10.8 |
Ethnic groups | ||||||
Mixed | 876 | 74.7 | 816 | 77.1 | 1692 | 75.9 |
Hispanic white | 191 | 16.3 | 161 | 15.2 | 352 | 15.8 |
Afro-Venezuelan | 30 | 2.6 | 36 | 3.4 | 66 | 3.0 |
Amerindian | 62 | 5.3 | 44 | 4.2 | 106 | 4.8 |
Others | 13 | 1.1 | 1 | 0.1 | 14 | 0.6 |
Alcohol intake quartiles | ||||||
Nondrinkers | 976 | 83.3 | 582 | 55.0 | ||
Quartile 1 | 53 | 4.5 | 119 | 11.2 | — | — |
Quartile 2 | 45 | 3.8 | 145 | 13.7 | — | — |
Quartile 3 | 58 | 4.9 | 89 | 8.4 | — | — |
Quartile 4 | 40 | 3.4 | 123 | 11.6 | — | — |
Alcohol intake pattern (conglomerates) | ||||||
Nondrinkers | 976 | 83.3 | 580 | 54.8 | — | — |
Low intake | 160 | 13.7 | 328 | 31.0 | — | — |
Moderate intake | 27 | 2.3 | 124 | 11.7 | — | — |
High intake | 9 | 0.8 | 26 | 2.5 | — | — |
Metabolic Syndrome |
474 | 40.4 | 472 | 44.6 | 946 | 42.4 |
High blood pressure |
410 | 35.0 | 456 | 43.1 | 866 | 38.8 |
Hyperglycemia |
301 | 25.7 | 322 | 30.4 | 623 | 27.9 |
Low HDL-C |
752 | 64.2 | 536 | 50.7 | 1288 | 57.8 |
High triacylglycerides |
269 | 23.0 | 347 | 32.8 | 616 | 27.6 |
Abdominal obesity |
926 | 79.0 | 749 | 70.8 | 1675 | 75.1 |
Body Mass Index classification (kg/m2) | ||||||
<24.9 | 420 | 35,8 | 275 | 26,0 | 695 | 31,2 |
25.0–29.9 | 371 | 31,7 | 415 | 39,2 | 786 | 35,2 |
≥30.0 | 381 | 32,5 | 368 | 34,8 | 749 | 33,6 |
Prevalence of Metabolic Syndrome by gender and daily alcohol intake quartiles. Maracaibo, 2015.
With Metabolic Syndrome |
|
||
---|---|---|---|
|
% | ||
Females |
|
||
Nondrinkers | 407 | 41.7 | |
<3.80 g/day | 12 | 22.6 | |
3.80–10.41 g/day | 14 | 31.1 | |
10.42–28.40 g/day | 24 | 41.4 | |
≥28.41 g/day | 17 | 42.5 | |
Males |
|
||
Nondrinkers | 247 | 42.4 | |
<9.54 g/day | 49 | 41.2 | |
9.54–28.40 g/day | 71 | 49.0 | |
28.41–47.33 g/day | 49 | 55.1 | |
≥47.34 g/day | 56 | 45.5 |
On the other hand, Table
Prevalence of Metabolic Syndrome by gender and drinking pattern conglomerates. Maracaibo, 2015.
With Metabolic Syndrome |
|
||
---|---|---|---|
|
% | ||
Females (gr/day) |
|
||
Nondrinkers | 407 | 41.7 | |
Low intake (1.28–39.76) | 51 | 31.9 | |
Moderate intake (6.40–92.77) | 11 | 40.7 | |
High intake (16.13–136.32) | 5 | 55.6 | |
Males (gr/day) |
|
||
Nondrinkers | 246 | 42.4 | |
Low intake (1.00–42.60) | 151 | 46.0 | |
Moderate intake (5.76–102.24) | 62 | 50.0 | |
High intake (106.03–408.96) | 13 | 50.0 |
When assessing the association between separate MS components and quartiles of daily alcohol intake (Table
Prevalence of Metabolic Syndrome components by gender and daily alcohol intake quartiles. Maracaibo, 2015.
Hyperglycemia | Low HDL-C | Elevated waist circumference | High blood pressure | High TAG | ||||||
---|---|---|---|---|---|---|---|---|---|---|
|
% |
|
% |
|
% |
|
% |
|
% | |
Females | ||||||||||
Nondrinkers | 253 | 25.9 | 635 | 65.1 | 769 | 78.8 | 354 | 36.3 | 236 | 24.2 |
<3.80 g/day | 11 | 20.8 | 28 | 52.8 | 37 | 69.8 | 14 | 26.4 | 4 | 7.5 |
3.80–10.41 g/day | 13 | 28.9 | 29 | 64.4 | 37 | 82.2 | 8 | 17.8 | 7 | 15.6 |
10.42–28.40 g/day | 14 | 24.1 | 35 | 60.3 | 50 | 86.2 | 20 | 34.5 | 12 | 20.7 |
≥28.41 g/day | 10 | 25.0 | 25 | 62.5 | 33 | 82.5 | 14 | 35.0 | 10 | 25.0 |
Males | ||||||||||
Nondrinkers | 165 | 28.4 | 305 | 52.4 | 402 | 69.1 | 244 | 41.9 | 176 | 30.2 |
<9.54 g/day | 38 | 31.9 | 58 | 48.7 | 87 | 73.1 | 49 | 41.2 | 33 | 27.7 |
9.54–28.40 g/day | 41 | 28.3 | 76 | 52.4 | 108 | 74.5 | 64 | 44.1 | 56 | 38.6 |
28.41–47.33 g/day | 37 | 41.6 | 46 | 51.7 | 70 | 78.7 | 46 | 51.7 | 38 | 42.7 |
>47.33 g/day | 41 | 33.3 | 51 | 41.5 | 82 | 66.7 | 53 | 43.1 | 44 | 35.8 |
HDL-C: High-Density Lipoprotein-Cholesterol. TAG: triacylglycerides.
Pearson’s Chi-squared test (
In consonance, evaluation of the association between the conglomerate classification and MS components revealed hypertriacylglyceridemia to show the greatest degree of association, progressively increasing in prevalence across groups (low intake: 13.8%,
Prevalence of Metabolic Syndrome components by gender and drinking pattern conglomerates. Maracaibo, 2015.
Hyperglycemia | Low HDL-C | Elevated waist circumference | High blood pressure | High TAG | ||||||
---|---|---|---|---|---|---|---|---|---|---|
|
% |
|
% |
|
% |
|
% |
|
% | |
Females (gr/day) | ||||||||||
Nondrinkers | 253 | 25.9 | 635 | 65.1 | 769 | 78.8 | 354 | 36.3 | 236 | 24.2 |
Low intake (1.28–39.76) | 40 | 25.0 | 93 | 58.1 | 125 | 78.1 | 44 | 27.5 | 22 | 13.8 |
Moderate intake (6.40–92.77) | 7 | 25.9 | 19 | 70.4 | 24 | 88.9 | 9 | 33.3 | 7 | 25.9 |
High intake (16.13–136.32) | 1 | 11.1 | 5 | 55.6 | 8 | 88.9 | 3 | 33.3 | 4 | 44.4 |
Males (gr/day) | ||||||||||
Nondrinkers | 165 | 28.4 | 304 | 52.4 | 401 | 69.1 | 242 | 41.7 | 176 | 30.3 |
Low intake (1.00–42.60) | 102 | 31.1 | 165 | 50.3 | 243 | 74.1 | 143 | 43.6 | 113 | 34.5 |
Moderate intake (5.76–102.24) | 42 | 33.9 | 56 | 45.2 | 84 | 67.7 | 60 | 48.4 | 46 | 37.1 |
High intake (106.03–408.96) | 13 | 50.0 | 11 | 42.3 | 21 | 80.8 | 11 | 42.3 | 12 | 46.2 |
HDL-C: High-Density Lipoprotein-Cholesterol. TAG: triacylglycerides.
Pearson’s Chi-squared test (
Figure
Serum triacylglyceride concentration by gender and daily alcohol intake quartiles. Maracaibo, 2015.
Females
Males
On the other hand, Figure
Serum triacylglyceride concentration by gender and drinking patter conglomerates. Maracaibo, 2015. One-way ANOVA. Post hoc Tukey:
Females
Males
Multivariate analysis of the relationship between drinking and MS and its components indicated hypertriacylglyceridemia to be the most tightly associated with this life style in females. Indeed, in this gender, analysis by daily alcohol intake quartiles (Table
Adjusted odds ratios for Metabolic Syndrome and its components by daily alcohol intake quartiles in females. Maracaibo, 2015.
Metabolic Syndrome | High fasting glucose | Low HDL-C | High waist circumference | High blood pressure | High triacylglycerides | |
---|---|---|---|---|---|---|
OR (95% CI); |
OR (95% CI); |
OR (95% CI); |
OR (95% CI); |
OR (95% CI); |
OR (95% CI); |
|
Nondrinkers | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
<3.80 g/day | 0.53 (0.25–1.12); 0.09 | 1.01 (0.48–2.14); 0.98 | 0.73 (0.41–1.32); 0.30 | 0.76 (0.36–1.61); 0.47 | 1.12 (0.54–2.34); 0.76 |
|
3.80–10.41 g/day | 1.08 (0.51–2.28); 0.83 | 1.67 (0.79–3.50); 0.18 | 1.08 (0.57–2.07); 0.81 | 1.82 (0.75–4.39); 0.19 | 0.61 (0.25–1.50); 0.28 | 0.79 (0.32–1.93); 0.60 |
10.42–28.40 g/day | 0.86 (0.45–1.63); 0.64 | 0.94 (0.48–1.86); 0.86 | 0.69 (0.39–1.24); 0.22 | 1.05 (0.45–2.46); 0.92 | 1.08 (0.55–2.09); 0.83 | 0.65 (0.31–1.38); 0.26 |
≥28.41 g/day | 1.33 (0.59–2.94); 0.49 | 1.06 (0.47–2.36); 0.89 | 0.83 (0.41–1.67); 0.60 | 1.25 (0.49–3.23); 0.64 | 1.53 (0.64–3.63); 0.34 | 1.12 (0.48–2.58); 0.79 |
HDL-C: High-Density Lipoprotein-Cholesterol.
Models adjusted for age groups, ethnic groups, occupational status, educational status, socioeconomic status, family history of hypertension and diabetes, tobacco use, four domains of physical activity, and daily alcohol intake quartiles.
Adjusted odds ratios for Metabolic Syndrome and its components by drinking pattern conglomerates in females. Maracaibo, 2015.
(gr/day) | Metabolic Syndrome | High fasting glucose | Low HDL-C | High waist circumference | High blood pressure | High triacylglycerides |
---|---|---|---|---|---|---|
OR (95% CI); |
OR (95% CI); |
OR (95% CI); |
OR (95% CI); |
OR (95% CI); |
OR (95% CI); |
|
Nondrinkers | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
Low intake (1.28–39.76) | 0.77 (0.50–1.18); 0.23 | 1.17 (0.76–1.80); 0.48 | 0.76 (0.53–1.09); 0.14 | 1.00 (0.61–1.61); 0.98 | 1.00 (0.64–1.57); 0.99 |
|
Moderate intake (6.40–92.77) | 0.97 (0.39–2.42); 0.94 | 1.08 (0.42–2.78); 0.87 | 1.40 (0.58–3.35); 0.45 | 1.69 (0.45–6.32); 0.44 | 1.07 (0.40–2.86); 0.89 | 1.03 (0.39–2.75); 0.95 |
High intake (16.13–136.32) |
|
0.49 (0.05–4.43); 0.52 | 0.59 (0.15–2.36); 0.46 | 4.24 (0.47–38.14); 0.19 | 1.85 (0.33–10.47); 0.49 |
|
HDL-C: High-Density Lipoprotein-Cholesterol.
Models adjusted for age groups, ethnic groups, occupational status, educational status, socioeconomic status, family history of hypertension and diabetes, tobacco use, four domains of physical activity, and drinking pattern conglomerates.
Meanwhile, in males, multivariate analysis by daily alcohol intake quartiles (Table
Adjusted odds ratios for Metabolic Syndrome and its components by daily alcohol intake quartiles in males. Maracaibo, 2015.
Metabolic Syndrome | High fasting glucose | Low HDL-C | High waist circumference | High blood pressure | High triacylglycerides | |
---|---|---|---|---|---|---|
OR (95% CI); |
OR (95% CI); |
OR (95% CI); |
OR (95% CI); |
OR (95% CI); |
OR (95% CI); |
|
Nondrinkers | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
<9.54 g/day | 0.94 (0.59–1.50); 0.79 | 1.35 (0.84–2.18); 0.21 | 0.83 (0.55–1.26); 0.39 | 1.28 (0.76–2.16); 0.35 | 1.08 (0.58–1.72); 0.76 | 0.79 (0.49–1.28); 0.34 |
9.54–28.40 g/day | 1.26 (0.81–1.95); 0.31 | 0.91 (0.58–1.43); 0.68 | 0.88 (0.59–1.31); 0.53 | 1.32 (0.81–2.16); 0.27 | 1.15 (0.74–1.79); 0.53 | 1.32 (0.86–2.01); 0.20 |
28.41–47.33 g/day |
|
|
0.89 (0.56–1.43); 0.64 |
|
|
|
≥47.34 g/day | 1.23 (0.77–1.97); 0.39 | 1.45 (0.90–2.34); 0.13 |
|
1.05 (0.63–1.76); 0.84 | 1.42 (0.88–2.28); 0.15 | 1.15 (0.72–1.83); 0.56 |
HDL-C: High-Density Lipoprotein-Cholesterol.
Models adjusted for age groups, ethnic groups, occupational status, educational status, socioeconomic status, family history of hypertension and diabetes, tobacco use, four domains of physical activity, and daily alcohol intake quartiles.
Adjusted odds ratios for Metabolic Syndrome and its components by drinking pattern conglomerates in males. Maracaibo, 2015.
gr/day | Metabolic Syndrome | High fasting glucose | Low HDL-C | High waist circumference | High blood pressure | High triacylglycerides |
---|---|---|---|---|---|---|
OR (95% CI); |
OR (95% CI); |
OR (95% CI); |
OR (95% CI); |
OR (95% CI); |
OR (95% CI); |
|
Nondrinkers | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
Low intake (1.00–42.60) | 1.18 (0.85–1.63); 0.32 | 1.19 (0.85–1.66); 0.30 | 0.85 (0.64–1.14); 0.29 | 1.42 (0.99–2.03); 0.06 | 1.23 (0.89–1.71); 0.21 | 1.11 (0.81–1.53); 0.52 |
Moderate intake (5.76–102.24) | 1.46 (0.92–2.32); 0.11 | 1.41 (0.88–2.25); 0.15 |
|
0.97 (0.58–1.61); 0.90 |
|
1.15 (0.73–1.81); 0.55 |
High intake (106.03–408.96) | 1.33 (0.51–3.44); 0.56 |
|
0.58 (0.25–1.38); 0.22 | 3.33 (0.92–12.06); 0.07 | 1.02 (0.39–2.68); 0.97 | 1.98 (0.79–4.89); 0.14 |
HDL-C: High-Density Lipoprotein-Cholesterol.
Models adjusted for age groups, ethnic groups, occupational status, educational status, socioeconomic status, family history of hypertension and diabetes, tobacco use, four domains of physical activity, and drinking pattern conglomerates.
Psychobiologic life styles play an indisputable role in global well-being and are particularly prominent in the development of cardiometabolic alterations, with diet, physical activity, smoking, and alcohol consumption attracting vast scientific attention in recent decades [
Initially, alcohol consumption was evaluated in quartiles according to sex but not taking into account the beverage consumed by the subjects. Later, a cluster analysis according to sex was calculated adding the daily quantity of alcohol consumption per beverage [
We have ascertained a lower prevalence of MS in female subjects with low alcohol intake, in concordance with the findings of Lee et al. [
When individually studying clinical-metabolic alterations, we found hypertriacylglyceridemia to behave similarly to MS, again in the female gender. This trend echoes the results of the ATTICA study, where, after a 10-year follow-up, moderate alcohol consumption (1-2 drinks/day) was associated with decreased incidence of high TAG [
Multivariate analysis further supports this finding in women, with the impact of drinking confined to serum TAG concentration. Indeed, low alcohol consumption appeared to act as a protective factor when studied through daily intake quartiles, similar to the results of Clerc et al. [
In contrast, in men, univariate analysis revealed a weak or absent degree of statistical association between drinking and MS or its components. Nonetheless, multivariate assessment yielded significant results concerning the group consuming 28.41–47.33 g/day (third quartile of daily intake), who displayed increased risk of MS. This concurs with observations in 19,000 Chinese subjects, although these were exclusive wine consumers [
Our finding of ≥47.34 gr/day intake or moderate intake by conglomerates acting as a protective factor for low HDL-C is consistent with reports from studies with differing methodology and drinking patterns: The Cooper Center Longitudinal Study, realized in 3,000 healthy American subjects, showed men with high consumption to have the highest HDL-C values (
The limitations of this study include its cross-sectional design which hinders the possibility of determining causality relationships and the lack of nutritional data which might add another measure of influence over alcohol consumption frequency and quantity. Currently, this branch of research is being conducted as part of the MMSPS, which will render the necessary data to answer this important inquiry, especially in light of MS risk.
Finally, it is important to highlight that in our population the protective effect of alcohol against high TAG in women appears to occur with daily intake quantities equal to less than half the standard measures of the main alcoholic beverages in our locality. On the other hand, in men, the effects of alcohol on MS and its components are apparent with daily quantities equal to 4–6 beers, 3–5 spirit drinks, or 4–7 glasses of wine. These values should be utilized by clinicians as reference for educational efforts regarding the role of this substance in cardiometabolic health in our community. We also support evaluation by daily intake quartiles as the most easily applicable and reproducible method for quantitative assessment of this practice in our region, never forgetting to take into account those subjects with high alcohol intake.
The authors have no conflict of interests to disclose.
This work was supported by Research Grant no. CC-0437-10-21-09-10 from CONDES, University of Zulia, and Research Grant no. FZ-0058-2007 from Fundacite Zulia.