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ORIGINAL RESEARCH COMMUNICATION |
1 From the Endocrine Research Center, Shaheed Beheshti University of Medical Sciences, Tehran, Iran
2 Supported by grant no. 121 from the National Research Council of the Islamic Republic of Iran and by the collaborative support of the National Research Council of the Islamic Republic of Iran and the Endocrine Research Center of Shaheed Beheshti University of Medical Sciences. 3 Address reprint requests to F Azizi, Endocrine Research Center, Shaheed Beheshti University of Medical Sciences, PO Box 19395-4763, Tehran, Iran. E-mail: azizi{at}erc.ac.ir.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Objective: The objective was to evaluate the relation between dairy consumption and metabolic syndrome in Tehranian adults.
Design: Dairy consumption and features of metabolic syndrome were assessed in a population-based cross-sectional study of 827 subjects (357 men and 470 women) aged 18–74 y. Metabolic syndrome was defined according to guidelines of the Adult Treatment Panel III. Multivariate logistic regression adjusted for lifestyle and nutritional confounders was used in 4 models.
Results: Mean (±SD) consumption of milk, yogurt, and cheese was 0.7 ± 0.2, 1.06 ± 0.6, and 0.9 ± 0.3 servings/d, respectively. Subjects in the highest quartile of dairy consumption had lower odds of having enlarged waist circumference [odds ratio (OR) by quartile: 1, 0.89, 0.74, 0.63; P for trend < 0.001], hypertension (OR by quartile: 1, 0.88, 0.79, 0.71; P for trend < 0.02), and metabolic syndrome (OR by quartile: 1, 0.83, 0.74, 0.69; P for trend < 0.02). The values of ORs became weaker after further adjustment for calcium intake.
Conclusion: Dairy consumption is inversely associated with the risk of having metabolic syndrome. It seems that this relation is somewhat attributed to calcium.
Key Words: Dairy intake • metabolic syndrome • abnormal glucose homeostasis • cardiovascular risk factors • enlarged waist circumference
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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The cause of this syndrome is largely unknown, and variations worldwide have prompted researchers to present hypotheses for the natural development of the syndrome. It is thought that genetic, metabolic, and environmental factors, including diet, play an important role in its development (8). Although a whole array of dietary factors, such as high intakes of saturated fatty acids (9) and low intakes of n–3 fatty acids (10), are reported to contribute to the development of components of metabolic syndrome, the role of diet in the development of this syndrome is poorly understood and limited to a few observational studies (11, 12).
Several studies reported the role of nutrients in chronic diseases (13-16), but comparatively little emphasis has been placed on the specific contribution of foods, especially dairy products. Dairy products are a rich source of calcium, a nutrient that has been reported to reduce blood pressure (17, 18) and to be associated with adiposity (19, 20). In addition, dairy or calcium or both may decrease the risk of coronary artery disease (21) and stroke (22). We showed in our previous investigations that dairy consumption and calcium intake are inversely related to body mass index [BMI; in kg/m2 (23)] and blood pressure (24).
Although the relation of dairy intake and some chronic diseases has been investigated previously, there are few reports about the association between dairy consumption and metabolic syndrome (11, 12). The purpose of this study was to ascertain the relation between dairy consumption and metabolic syndrome in a representative sample of Tehranian adults.
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SUBJECTS AND METHODS |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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3 y were selected by a multistage cluster, random sampling method. A representative sample of 1476 persons was randomly selected for dietary assessment, including 861 subjects aged 18–74 y. In the current population-based cross-sectional study, subjects with a history of CVD, diabetes, or stroke were excluded because of possible changes in diet. We also excluded subjects whose reported daily energy intakes outside the range of 800–4200 kcal/d (3347–17 573 kJ/d) (26). Therefore, 827 subjects (357 men and 470 women) aged 18–74 y remained for the current analysis. Each subject provided written informed consent. The protocol of this study was approved by the research council of the Endocrine Research Center of Shaheed Beheshti University of Medical Sciences.
Assessment of dietary intake
Usual dietary intake was assessed with the use of a 168-item semiquantitative food-frequency questionnaire (FFQ). All the questionnaires were administered by trained dietitians who had 5 y experience in the Nationwide Food Consumption Survey project (27, 28). The FFQ consisted of a list of foods with a standard serving size (Willett format). Participants were asked to report their frequency of consumption of each food item during the previous year on a daily (eg, bread), weekly (eg, rice or meat), or monthly (eg, fish) basis. Portion sizes of consumed foods were converted from household measures to grams (29). Each food and beverage was then coded according to the prescribed protocol and analyzed for content of energy and the other nutrients by using NUTRITIONIST III software (version 7.0; N-Squared Computing, Salem, OR), which was designed for Iranian foods.
Dairy products were defined according to the US Food Guide Pyramid (30). The amounts of yogurt, milk, and cheese that count as a serving were 8 ounces (240 g), 1 cup (240 cc), and 1.5 ounces (45 g), respectively (31).
The reliability of the FFQ in this cohort was evaluated in a randomly chosen subgroup of 132 subjects by comparing nutrient consumption ascertained by FFQ responses on 2 occasions. The correlation coefficients for the repeatability of cheese, milk, and yogurt were 0.73, 0.69, and 0.79, respectively. The FFQ also had high reliability for nutrients. For example, the correlation coefficients were 0.78 for dietary protein, 0.70 for riboflavin, and 0.75 for dietary calcium. Comparative validity was determined by comparison with intake estimated from the average of twelve 24-h dietary recalls (one for each month of the year). Preliminary analysis of the validation study showed that nutrients commonly found in dairy products were moderately correlated (all correlation coefficients were >0.5) between these 2 methods after control for total energy intake. The performance of the FFQ in assessing the individual dairy products also was high. For example, between FFQ and detailed dietary recalls, correlation coefficients were 0.66 for cheese, 0.61 for yogurt, and 0.70 for milk. Overall, these data indicate that the FFQ provides reasonably valid measures of the average long-term dietary intake.
Assessment of other variables
While the subjects were minimally clothed and not wearing shoes, weight was measured with the use of digital scales and recorded to the nearest 100 g. Height was measured with a tape measure while the subjects were in a standing position and not wearing shoes and while the shoulders were in a normal position. BMI was calculated. Waist circumference was measured at the narrowest level between the lowest rib and the iliac crest and hip circumference was measured at the maximum level over light clothing, with the use of an unstretched tape measure without any pressure to body surface. Measurements were recorded to the nearest 0.1 cm, as reported earlier (32), and the waist-to-hip ratio was calculated.
Blood pressure was measured twice after the participants sat for 15 min (33). Additional covariate information about age, smoking habits (34), physical activity (35), medical history, and current use of medications (34) was obtained with the use of validated questionnaires, as reported earlier.
Fasting blood samples for the measurement of glucose and lipid concentrations were drawn after an overnight fast of 12 h (36). Blood glucose was measured on the day of blood collection by using the enzymatic colorimetric method with glucose oxidase. Serum concentrations of total cholesterol and triacylglycerols were measured by using commercially available enzymatic reagents (Pars Azmoon, Tehran, Iran) adapted to the Selectra autoanalyzer (Vital Scientific, Spankeren, Netherlands). HDL cholesterol was measured after precipitation of the apolipoprotein B–containing lipoproteins with phosphotungstic acid. LDL cholesterol was calculated according to the method of Friedewald et al (37). It was not calculated when the serum concentration of triacylglycerol was >400 mg/dL. All samples were analyzed when internal quality control met the acceptable criteria. Interassay and intraassay CVs were 2% and 0.5% for total cholesterol and 1.6% and 0.6% for triacylglycerol, respectively.
Definition of terms
Metabolic syndrome was defined as the presence of 3 of the following 5 components as recommended by the Adult Treatment Panel III (38): 1) enlarged waist circumference (waist circumference 102 cm in men and 88 cm in women); 2) low serum HDL cholesterol (<40 mg/dL in men and <50 mg/dL in women); 3) high serum triacylglycerol concentrations (150 mg/dL); 4) elevated blood pressure (130/85 mm Hg); and 5) abnormal glucose homeostasis (fasting plasma glucose concentration 110 mg/dL).
Statistical analysis
We used SPSS software (version 9.05; SPSS Inc, Chicago IL) for all statistical analyses. In separate models, first-order interactions between sex and dairy intakes were entered to ascertain whether associations were similar between men and women. No significant interactions by sex were observed for the association of dairy intakes and metabolic risk factors. Cutoffs for quartiles of dairy intake were calculated, and subjects were categorized according to the quartiles. The cutoffs were the same for men and women: <1.0, 1.0 to <1.8, 1.8 to <2.7, and 2.7 servings/d for quartiles 1–4, respectively.
Significant differences in general characteristics across quartiles of dairy intake were searched by using one-way analysis of variance. If there was a significant main effect, Tukey test was used to detect pairwise differences. Chi-square test was used to detect any significant differences in the distribution of subjects across quartiles of dairy intake with regard to qualitative variables. We determined multivariate-adjusted means (ie, age; sex; physical activity; smoking; BMI; waist-to-hip ratio; total energy intake; consumption of fruit, vegetables, and meats and fish; percentage of energy from fat; and current use of antihypertensive medication and estrogen replacement therapy) for metabolic risk factors and determined age-, sex-, and energy-adjusted means for dietary variables across quartiles of dairy intake by using a general linear model analysis of covariance with the Tukey test to compare these means. All correlation coefficients reported were calculated as Pearson’s correlation coefficients. To ascertain the association of dairy intakes with metabolic risks, we used multivariable logistic regression models controlled for age (in y), energy intake (in kcal/d), percentage of energy from fat, use of blood pressure medication (yes or no), cigarette smoking (categorical), physical activity level (light, moderate, or severe), and current estrogen replacement therapy among women (yes or no). When a significant association with dairy intake was observed, we repeated the analysis after adjustment for intakes of whole grains, refined grains, fruit, vegetables, and meats and fish. In all multivariate models, the first quartile of dairy intake was considered as a reference. The Mantel-Haenszel extension chi-square test was performed to assess the overall trend of an increasing quartile of dairy intake associated with an increasing or decreasing likelihood of being classified as high risk.
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RESULTS |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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. No significant differences were observed between the age of participants in quartile 1 (the lowest quartile) and that of those in quartile 4 of dairy intake. Those in the fourth quartile of dairy intake had a lower BMI than did those in the 3 lower quartiles. Most subjects had light activity in all quartiles of dairy intake. The proportion of obese persons was different between different quartiles. The percentage of daily smokers in the quartiles of dairy intake was not similar.
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. The frequency of metabolic syndrome and its components was the highest in quartile 1 of dairy consumption.
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. Subjects in quartile 4 of dairy intake had significantly lower mean waist circumference than did subjects in quartile 1. Subjects in quartile 4 of dairy intake had significantly lower mean systolic and diastolic blood pressures than did subjects in quartiles 1 and 2.
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. Subjects in quartile 4 of dairy intake consumed more fiber than did subjects in the other quartiles. A higher intake of dairy was associated with a healthier diet, and subjects in quartile 4 also consumed more fruit and vegetables and less meat than did subjects in quartile 1. Dairy intake was positively associated with total intakes of dietary protein (r = 0.51), riboflavin (r = 0.49), and calcium (r = 0.52), which are important constituents of dairy products.
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. In model 1, we adjusted for the effect of age, total energy intake, percentage of energy from fat, BMI, use of blood pressure and estrogen medication, smoking, and physical activity. In model 2, we further adjusted for the effect of food group intake, and we found that the ORs became weaker in model 2. After adjustment for the effect of calcium in model 3, the probability of metabolic syndrome became weaker than it was in models 1 and 2. In model 4, when we further adjusted for the effect of protein intake, no significant change was observed in the ORs. A significant trend was observed in all models toward the incidence of metabolic syndrome, enlarged waist circumference, high serum concentrations of triacylglycerol, and elevated blood pressure.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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An inverse favorable association between dairy consumption and the metabolic syndrome may be attributed to the healthy lifestyle associated with higher intakes of dairy. People who consumed higher amounts of dairy also consumed higher amounts of fiber, fruit, vegetables, and whole grains. However, the apparently protective effect of dairy consumption persisted in multivariate models that accounted for metabolic risks. Of course, some disorders, eg, dyslipidemia or hypertension, could have led to changes in diet and therefore could confound the association between dairy intake and metabolic risks. Changing dietary patterns may have played an important role in the epidemic of metabolic syndrome in Iran in recent years (39). Patterns in dietary intake during the past few years have shifted to a decreasing consumption of dairy products and an increasing consumption of soft drinks, especially in children and adolescents (40).
The relation between dairy consumption and metabolic syndrome became weaker after adjustment for calcium intake. Therefore, the relation of dairy intake and the metabolic syndrome was mediated by calcium intake to some extent. This result was seen for the probability of the incidence of a component of metabolic syndrome. Calcium and dairy are highly correlated, and it is difficult to interpret dairy intake after adjustment for calcium, but we adjusted for the effect of calcium to find the mechanism by which dairy affects the metabolic syndrome. Therefore, our purpose for adjustment of the calcium intake in a separate model in logistic regression was to identify one of the possible mechanisms. Most published studies cited calcium as a factor that was responsible for reducing the incidence of adiposity, hypertension, and CVD risks (41-44). Calcium intake could affect body fat mass in various ways. Its simplest effect is the inhibition of fat and fatty acid absorption (45). It seems that the main effect of calcium is mediated by its effect on the control of intracellular calcium. Evidence has shown that the product of the agouti gene, which is expressed in human adipocytes, stimulates calcium current into the cells and, by its concurrent effect on lipolysis and lipogenesis, causes the deposition of fat on adipocytes. This product increases the activity of fatty acid synthetase and inhibits lipolysis by a calcium-dependent mechanism (46, 47). The entrance of calcium into the cells is reduced by calcitriol, which inhibits lipolysis. Higher intake of calcium reduces calcium’s entrance into the cells by decreasing concentrations of 1,25-dihydroxyvitamin D, and, therefore, it inhibits fatty acid synthesis and stimulates lipolytic activity. The beneficiary effect of calcium in preventing fat accumulation also may be attributed to the expression of uncoupling protein 2 in white adipose tissue and, hence, to thermogenesis (48). A decrease in the plasma concentration of insulin by dietary calcium was suggested as another reason.
Although previous studies focused mostly on the relation between general obesity and dairy consumption, the current study showed an inverse relation between dairy consumption and enlarged waist circumference. Calcium has an important role through the mentioned mechanisms, but other substances also play a role in this context. Lin et al (49) reported that nondairy calcium failed to lower weight. However, dairy-rich diets lowered weight more than did calcium-rich diets. Therefore, factors in addition to calcium may play a role in the prevention of fat accumulation. For example, conjugated linolenic acid has an important role in fat accumulation in adipocytes (50, 51). The protein content of milk also may be responsible for its antiobesity effect (52). Milk proteins have an angiotensin-converting enzyme–inhibitory effect (53, 54). The inhibition of the rennin-angiotensin system in adipocytes has the potential to reduce obesity and hypertension. In the current study, after adjustment for the effect of protein intake, no significant changes were observed in the values of ORs, and further adjustment for protein intake did not affect the weakness of the OR values, but the significance remained in most of the models. Therefore, the current study showed that, although calcium played a greater role in the mechanism of the association between dairy intake and metabolic syndrome, we could not ignore the effect of protein.
In the current study, dairy consumption has an inverse association with hypertension. Calcium and magnesium may lower the risk of hypertension and may be responsible for lowering the risk of metabolic syndrome. Resnick (55) hypothesized from his analysis that hypertension and its associated disorders in metabolic syndrome, obesity, hyperlipidemia, and insulin resistance are all related to elevated intracellular calcium and depressed intracellular magnesium. These cellular ionic disturbances have been related to vasoconstriction, increased platelet aggregation and thrombosis, insulin resistance, and salt sensitivity. Young et al (56) showed that increased plasma potassium inhibits free radical formation and the proliferation of vascular smooth muscle cells as well as arterial thrombosis. It is difficult to associate any one mineral in dairy products with hypertension because an appropriate metabolic balance of all 3 is important and because there are strong correlations between the intakes of calcium, magnesium, and potassium when dairy products are consumed. In fact, dairy products are important sources of all 3 of these minerals. In addition, milk is a low-sodium food, which provides further benefit in blood pressure reduction.
Studies showed that magnesium was inversely associated with insulin resistance, fasting serum insulin, and glucose (57, 58). Dairy food contributes a significant amount of the daily intake of magnesium in the food supply. New results indicate that a short-term high intake of milk increases insulin secretion and resistance. The intake of high animal protein from milk, which results in higher serum branched-chain amino acid concentrations, may be responsible for this result; the long-term consequences are unknown, and more research is needed (59).
Findings from our data imply an inverse relation between dairy consumption and metabolic syndrome, elevated blood pressure, high serum concentrations of triacylglycerols, and enlarged waist circumference. This does not mean that greater dairy consumption ameliorates enlarged waist circumference, elevated blood pressure, or high triacylglycerol concentrations in a causal manner. However, it should be noted that, in the current study, although we did not separate high- and low-fat dairy products, we did control for the effect of fat intake on our data. Although low-fat dairy products are available today in Iran, only 2.5%-fat dairy products were available when the data for the current study were gathered (1999–2000). We adjusted for the effect of fat intake in all analyses. Because butter is categorized in the fat group and not in the dairy group (60), we did not include butter in our analysis as a dairy product. The amount of fat in Iranian ice cream is high. Many kinds of ice cream in Iran are not produced from milk but, rather, are fruit-based ice creams. Because in our data the kind of ice cream was not separated, we did not include ice cream in our analysis as a dairy product. In addition, the amount of ice cream consumption was low, which is another reason for its exclusion as a dairy food.
Two previous studies were conducted in this field, one cross-sectional and one prospective. In the cross-sectional study, the effects of confounders such as physical activity and the intake of other food groups, such as vegetables and fruit, were not considered (11). However, in the current study, we adjusted for the effect of different lifestyle factors, and we observed the association in separated models that were further adjusted for the intakes of other food groups, calcium, and protein. In the prospective study, the longitudinal design compared the 10-y cumulative incidence of insulin resistance syndrome across dairy categories (12). However, we were unable to conclude in the current study that a higher dairy intake reduces the incidence of metabolic syndrome in a causal manner and in a longitudinal design.
Several limitations should be considered when examining the results of the current study. We used cross-sectional data to identify the association of dairy consumption with the metabolic syndrome, whereas future studies that use longitudinal data will provide stronger evidence on this association. It must be kept in mind, however, that appropriate analysis of cross-sectional data represents a valuable initial step in identifying relations between diet and disease. Moreover, prospective cohort studies and clinical trials have their own weaknesses. High consumption of dairy products appears to reflect an overall healthier lifestyle that may not have been accurately captured and controlled for in our analysis, and this omission would result in residual confounding. Subjects with known CVD, diabetes, or stroke were excluded from the study. These exclusions may have reduced the likelihood of finding significant trends in the odds of metabolic risks across quartiles of dairy consumption. In addition, chronic diseases such as metabolic syndrome are heterogeneous, and, along with dietary patterns, factors such as heredity may need to be considered. In addition, most of the risk factors are interrelated and could confound the relation between dairy consumption and metabolic risk factors.
The current study has several strengths, including the use of a population sample that is representative of Tehran, the use of logistic regression models and simultaneous adjustment of confounding variables in the association of dairy consumption with metabolic syndrome, and the finding of a cross-sectional relation between dairy intake and metabolic syndrome and some of its features, such as hypertension and enlarged waist circumference. In conclusion, we found evidence indicative of an inverse relation between dairy consumption and metabolic syndrome. It is recommended that future studies assess this issue further by addressing the components of dairy products and related mechanisms of action that are responsible for this effect (11).
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ACKNOWLEDGMENTS |
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LA, PM, and AE designed the study, collected and analyzed the data, and wrote the manuscript. FA supervised the research. None of the authors had any personal or financial conflicts of interest.
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REFERENCES |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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