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      Consumption of Dairy Products in Relation to Changes in Anthropometric Variables in Adult Populations: A Systematic Review and Meta-Analysis of Cohort Studies

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          Abstract

          Background

          The current state of knowledge regarding the association of dairy products and weight gain, overweight, and obesity is based on studies reporting contradicting and inconclusive results. The aim of the present study was thus to clarify the link between dairy consumption in relation to changes in anthropometric measures/adiposity by a meta-analytical approach.

          Methods

          For the meta-analysis PubMed, EMBASE, Web of Sciences, and google scholar were searched by two independent authors up to May 2016 with no restriction to language or calendar date. Prospective cohort studies reporting about intake of dairy consumption (including milk, yogurt, cheese, butter) and changes in body weight or waist circumference, risk of overweight, obesity, or weight gain were eligible. Pooled effects were calculated using a random effects model, and also a fixed effect model for sensitivity analysis. Due to the heterogeneity of statistical analytical approaches of the studies the analysis were done separately for beta-coefficients of changes in body weight and/or waist circumference per serving of dairy, for differences in weight gain/gain in waist circumference when comparing extreme categories of dairy consumption, and for odds ratios in regard to weight gain, overweight/obesity, or abdominal obesity.

          Findings

          24 studies (27 reports) met the inclusion criteria for the systematic review, and 22 studies provided sufficient data for inclusion in the meta-analysis. The meta-analysis of the five studies on changes in body weight per serving of dairy no significant results could be found for whole fat dairy and low fat dairy. However, there was inverse association between changes in body weight for each serving’s increase of yogurt (beta: -40.99 gram/year, 95% CI, -48.09 to -33.88), whereas each serving’s increase of cheese was positively associated (beta: -10.97 gram/year, 95% CI, 2.86 to 19.07). Furthermore, the highest dairy intake category was associated with a reduced risk of abdominal obesity (OR: 0.85; 95% CI, 0.76 to 0.95), and risk of overweight (OR: 0.87; 95% CI, 0.76 to 1.00) compared to the lowest intake category. No significant association could be observed for risk of weight gain.

          Conclusion

          In summary the results of the meta-analysis still reflect that dairy consumption was not positively related to changes in body weight. Yogurt was the only dairy food that showed some evidence for a beneficial effect, where higher intakes were inversely associated a reduced risk of obesity, changes in body weight or waist circumference. Further research is needed, since the overall interpretation of the results is limited by heterogeneous risk estimates.

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          Most cited references40

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          Milk and dairy consumption and incidence of cardiovascular diseases and all-cause mortality: dose-response meta-analysis of prospective cohort studies.

          The consumption of dairy products may influence the risk of cardiovascular disease (CVD) and total mortality, but conflicting findings have been reported. The objective was to examine the associations of milk, total dairy products, and high- and low-fat dairy intakes with the risk of CVD [including coronary heart disease (CHD) and stroke] and total mortality. PubMed, EMBASE, and SCOPUS were searched for articles published up to February 2010. Of > 5000 titles evaluated, 17 met the inclusion criteria, all of which were original prospective cohort studies. Random-effects meta-analyses were performed with summarized dose-response data. Milk as the main dairy product was pooled in these analyses. In 17 prospective studies, there were 2283 CVD, 4391 CHD, 15,554 stroke, and 23,949 mortality cases. A modest inverse association was found between milk intake and risk of overall CVD [4 studies; relative risk (RR): 0.94 per 200 mL/d; 95% CI: 0.89, 0.99]. Milk intake was not associated with risk of CHD (6 studies; RR: 1.00; 95% CI: 0.96, 1.04), stroke (6 studies; RR: 0.87; 95% CI: 0.72, 1.05), or total mortality (8 studies; RR per 200 mL/d: 0.99; 95% CI: 0.95, 1.03). Limited studies of the association of total dairy products and of total high-fat and total low-fat dairy products (per 200 g/d) with CHD showed no significant associations. This dose-response meta-analysis of prospective studies indicates that milk intake is not associated with total mortality but may be inversely associated with overall CVD risk; however, these findings are based on limited numbers.
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            Dairy consumption, obesity, and the insulin resistance syndrome in young adults: the CARDIA Study.

            Components of the insulin resistance syndrome (IRS), including obesity, glucose intolerance, hypertension, and dyslipidemia, are major risk factors for type 2 diabetes and heart disease. Although diet has been postulated to influence IRS, the independent effects of dairy consumption on development of this syndrome have not been investigated. To examine associations between dairy intake and incidence of IRS, adjusting for confounding lifestyle and dietary factors. The Coronary Artery Risk Development in Young Adults (CARDIA) study, a population-based prospective study. General community sample from 4 US metropolitan areas of 3157 black and white adults aged 18 to 30 years who were followed up from 1985-1986 to 1995-1996. Ten-year cumulative incidence of IRS and its association with dairy consumption, measured by diet history interview. Dairy consumption was inversely associated with the incidence of all IRS components among individuals who were overweight (body mass index > or =25 kg/m(2)) at baseline but not among leaner individuals (body mass index or =35 times per week, 24/102 individuals) compared with the lowest (<10 times per week, 85/190 individuals) category of dairy consumption. Each daily occasion of dairy consumption was associated with a 21% lower odds of IRS (odds ratio, 0.79; 95% confidence interval, 0.70-0.88). These associations were similar for blacks and whites and for men and women. Other dietary factors, including macronutrients and micronutrients, did not explain the association between dairy intake and IRS. Dietary patterns characterized by increased dairy consumption have a strong inverse association with IRS among overweight adults and may reduce risk of type 2 diabetes and cardiovascular disease.
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              Protein-induced satiety: effects and mechanisms of different proteins.

              Relatively high protein diets, i.e. diets that maintain the absolute number of grams of protein ingested as compared to before dieting, are a popular strategy for weight loss and weight maintenance. Research into multiple mechanisms regulating body weight has focused on the effects of different quantities and types of dietary protein. Satiety and energy expenditure are important in protein-enhanced weight loss and weight maintenance. Protein-induced satiety has been shown acutely, with single meals, with contents of 25% to 81% of energy from protein in general or from specific proteins, while subsequent energy intake reduction was significant. Protein-induced satiety has been shown with high protein ad libitum diets, lasting from 1 to 6 days, up to 6 months. Also significantly greater weight loss has been observed in comparison with control. Mechanisms explaining protein-induced satiety are nutrient-specific, and consist mainly of synchronization with elevated amino acid concentrations. Different proteins cause different nutrient related responses of (an)orexigenic hormones. Protein-induced satiety coincides with a relatively high GLP-1 release, stimulated by the carbohydrate content of the diet, PYY release, while ghrelin does not seem to be especially affected, and little information is available on CCK. Protein-induced satiety is related to protein-induced energy expenditure. Finally, protein-induced satiety appears to be of vital importance for weight loss and weight maintenance. With respect to possible adverse events, chronic ingestion of large amounts of sulphur-containing amino acids may have an indirect effect on blood pressure by induction of renal subtle structural damage, ultimately leading to loss of nephron mass, and a secondary increase in blood pressure. The established synergy between obesity and low nephron number on induction of high blood pressure and further decline of renal function identifies subjects with obesity, metabolic syndrome and diabetes mellitus II as particularly susceptible groups.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                16 June 2016
                2016
                : 11
                : 6
                : e0157461
                Affiliations
                [1 ]Department of Epidemiology, German Institute of Human Nutrition, Nuthetal, Germany
                [2 ]Department of Nutritional Sciences, Faculty of Life Sciences, University of Vienna, Vienna, Austria
                University of Catanzaro Magna Graecia, ITALY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: LS TKU SK HB. Performed the experiments: LS TKU. Analyzed the data: LS TKU. Contributed reagents/materials/analysis tools: LS TKU. Wrote the paper: LS GH CS TKU BM SK HB.

                Article
                PONE-D-16-00739
                10.1371/journal.pone.0157461
                4911011
                27310919
                848076f3-cc13-49b5-b7c7-81597f70eb9a
                © 2016 Schwingshackl et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 11 January 2016
                : 30 May 2016
                Page count
                Figures: 2, Tables: 1, Pages: 15
                Funding
                The publication of this article was funded by the Open Access fund of the Leibniz Association
                Categories
                Research Article
                Biology and Life Sciences
                Biochemistry
                Lipids
                Fats
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Medicine and Health Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Meta-Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Meta-Analysis
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Obesity
                Medicine and Health Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Obesity
                Medicine and Health Sciences
                Public and Occupational Health
                Physical Activity
                Biology and Life Sciences
                Nutrition
                Diet
                Alcohol Consumption
                Medicine and Health Sciences
                Nutrition
                Diet
                Alcohol Consumption
                Biology and Life Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Weight Gain
                Medicine and Health Sciences
                Physiology
                Physiological Parameters
                Body Weight
                Weight Gain
                Research and Analysis Methods
                Research Assessment
                Systematic Reviews
                Custom metadata
                Data are available from Figshare { https://figshare.com/s/3464118303631c604de8}.

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