Effects of dairy products consumption on inflammatory biomarkers among adults: a systematic review and meta-analysis of randomized controlled trials

Journal Pre-proof Effects of dairy products consumption on inflammatory biomarkers among adults: a systematic review and meta-analysis of randomized controlled trials Seyedeh Parisa Moosavian, Mehran Rahimlou, Parvane Saneei, Ahmad Esmaillzadeh PII:

S0939-4753(20)30044-2

DOI:

https://doi.org/10.1016/j.numecd.2020.01.011

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NUMECD 2216

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Nutrition, Metabolism and Cardiovascular Diseases

Received Date: 23 October 2019 Revised Date:

31 January 2020

Accepted Date: 31 January 2020

Please cite this article as: Moosavian SP, Rahimlou M, Saneei P, Esmaillzadeh A, Effects of dairy products consumption on inflammatory biomarkers among adults: a systematic review and metaanalysis of randomized controlled trials, Nutrition, Metabolism and Cardiovascular Diseases, https:// doi.org/10.1016/j.numecd.2020.01.011. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.

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Effects of dairy products consumption on inflammatory biomarkers among adults: a systematic review and meta-analysis of randomized controlled trials Seyedeh Parisa Moosavian1,2,3, Mehran Rahimlou4, Parvane Saneei2,5 , Ahmad Esmaillzadeh6,7 1

Students’ Research Committee, Isfahan University of Medical Sciences, Isfahan, Iran Food Security Research Center, Isfahan University of Medical Sciences, Isfahan, Iran 3 Department of Clinical Nutrition, School of Nutrition and Food Science, Isfahan University of Medical Sciences, Isfahan, Iran 4 Department of Nutrition, School of Para-Medical Sciences, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran 5 Department of Community Nutrition, School of Nutrition and Food Science, Isfahan University of Medical Sciences, Isfahan, Iran 6 Obesity and Eating Habits Research Center, Endocrinology and Metabolism Molecular -Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran 7 Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran 2

Running Title: Dairy products and inflammatory biomarkers Word counts for abstract: 250 Word counts for text: 4460 Number of references: 74 Figures: 5 Tables: 3 Supplementary Figures: 3 Supplementary Tables: 1 Correspondence to: Parvane Saneei, PhD Department of Community Nutrition School of Nutrition and Food Science Isfahan University of Medical Sciences Isfahan Iran Tel:+98-31-37923151 Email: [email protected] Co-Correspondence to: Ahmad Esmaillzadeh, PhD Professor of Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, P.O. Box 14155-6117 1

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Iran Tel:+98-21-88955805 Fax:+98-21-88984861 Email: [email protected] Keywords: Dairy; Inflammation; CRP; Adipocytokines; Meta-analysis

Abbreviations ACEI: Angiotensin-converting enzyme inhibitory CRP: C-reactive protein ICAM-1: Intracellular adhesion molecule-1 IL-6: Interleukin 6 ISI: Institute for Scientific Information MetS: Metabolic syndrome MPC-1: Monocyte chemotactic protein-1 RCT: Randomized controlled trial SD: Standard deviations SE: Standard errors SIRT1: Sirtuin 1 TNF-α : Tumor necrosis factor α USDA: United States Department of Agriculture VCAMs : Vascular cellular adhesion molecules WMD: Weighed mean difference

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ABSTRACT

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Aims: This study aimed to summarize earlier studies on the effects of dairy consumption on

3

inflammatory biomarkers in adults and to quantify these effects through meta-analysis.

4

Data Synthesis: A comprehensive search of all relevant articles, published up to December 2019

5

indexed in PubMed, ISI (Institute for Scientific Information), EmBase, Scopus, and Google

6

Scholar was done using relevant keywords. Randomized controlled trials (RCTs) that examined

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the effect of dairy products consumption, compared with low or no dairy intake, on inflammatory

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biomarkers in adults were included.

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Results: Overall, 11 RCTs with 663 participants were included in this meta-analysis. We found

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that high consumption of dairy products, compared with low or no dairy intake,

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significantly reduce CRP [weighed mean difference (WMD): -0.24 mg/L; 95% CI, -0.35, -0.14],

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TNF-α (WMD:- 0.66 pg/mL; 95% CI, -1.23, -0.09), IL-6 (WMD: -0.74 pg/mL; 95% CI, -1.36, -

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0.12), and MCP concentrations (WMD: -25.58 pg/mL; 95% CI, -50.31, -0.86). However, when

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the analyses were confined to cross-over trials, no such beneficial effects of dairy intake on

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inflammation were observed. In addition, high dairy intake might result in increased adiponectin

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levels (WMD: 2.42µg/mL; 95% CI, 0.17, 4.66). No significant effect of dairy consumption on

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serum leptin (WMD: -0.32 ng/mL; 95% CI, -3.30, 2.65), ICAM-1 (WMD: -3.38 ng/ml; 95% CI,

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-15.57, 8.96) and VCAM-1 (WMD: 3.1 ng/mL; 95% CI, -21.38, 27.58) levels was observed.

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Conclusions: In summary, the current meta-analysis indicated that dairy intake might improve

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several inflammatory biomarkers in adults. In most subgroups without heterogeneity, effects

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tended to be null. Study design and participants’ age were the main sources of heterogeneity.

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More research, with a particular focus on fat content of dairy foods, is recommended.

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Keywords: Dairy; Inflammation; CRP; Adipocytokines; Meta-analysis

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might

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INTRODUCTION

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Low grade systematic inflammation is involved in the development and progression of several

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metabolic conditions. Elevated plasma concentrations of inflammatory markers, including C-

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reactive protein (CRP), tumor necrosis factor α (TNF-α) and interleukin 6 (IL-6) are associated

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with metabolic syndrome (MetS) (1), cardiovascular events (2), nonalcoholic fatty liver disease

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and even mortality (3, 4). Several factors including smoking (5), obesity (6), advanced age (7),

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alcohol consumption (8), and physical activity (9) are reported to contribute to elevated

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inflammation.

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Along with other dietary factors with their pro- or anti-inflammatory properties, findings from

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observational studies revealed a significant association between dairy consumption and

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inflammatory biomarkers (10-14). In addition, previous investigations have shown an inverse

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association between dairy intake and risk of chronic conditions including diabetes (15) and

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cardiovascular events (16); however, it remains unknown if these beneficial associations are

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mediated through their impacts on inflammation (15, 16).

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Several clinical trials have investigated the effects of dairy consumption on inflammation, but the

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findings were conflicting. Pei et al found that daily consumption of 339 g low-fat yogurt for 9

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weeks, compared with non-dairy control food, resulted in reduced concentrations of

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inflammatory biomarkers in premenopausal women (17). Consumption of 500 mL/d low-fat milk

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and 150 g/d low-fat yogurt, compared with carbohydrate-rich control products (600 mL fruit

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juice and three fruit biscuits), led to a marginal decrease in TNF-α concentrations without a

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significant effect on serum MCP-1, IL-6, and vascular cellular adhesion molecules (VCAMs),

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intracellular adhesion molecules (ICAMs), in overweight and obese individuals (18). Others

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reported no significant effect of milk consumption on markers of endothelial function and

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inflammatory response (TNF-α , IL-6, CRP, C3, and C4) (19). Findings of a meta-analysis on the

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effects of high and low fat dairy foods on cardio-metabolic risk factors indicated that high

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consumption of low- and whole-fat dairy products had no significant effect on serum CRP

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concentrations (20). In a systematic review of 8 trials that were published before the year of

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2012, it was concluded that high dairy intake in overweight or obese individuals did not

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adversely affect biomarkers of inflammation. In this investigation which was restricted to

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overweight or obese individuals, the authors considered several inflammatory biomarkers, but

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they did not conduct a meta-analysis (21). The aim of current study, conducted according to the

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Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement (22),

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was to summarize earlier studies on the effects of dairy consumption on inflammatory

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biomarkers (including CRP, IL-6, TNF-α, adiponectin, MPC-1, leptin, ICAM-1, VCAM-1) in

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adults and to quantify these effects through meta-analysis.

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METHODS

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Search strategy: This study was performed according to the Preferred Reporting Items for

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Systematic Reviews and Meta-analysis (PRISMA) statement (22) and was registered in Prospero

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database (CRD42018103180). Two investigators (SPM and PS) conducted a comprehensive

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systematic search in PubMed, database of Institute for Scientific Information (ISI), EmBase,

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Scopus, and Google Scholar for papers published up to the end of December 2019 to identify

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eligible studies. No limitation was applied in terms of language or time of publication. The

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following combination of search terms was used: (“Dairy” OR “Cheese” OR “Milk” OR

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“Yogurt”, OR “Yoghurt” OR “Yoghourt”) AND (“Inflammation” OR “Inflammatory biomarker”

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OR “Interleukin” OR “C- reactive protein” OR “CRP” OR “Cytokines” OR “TNF-α” OR “IL-6”

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OR “Tumor necrosis factor” OR “Transforming growth factor beta” OR “Inflammation

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mediator” OR “Adipokines” OR “Acute phase reactant” OR “Systemic inflammation” OR

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“Matrix metalloproteinase” OR “eselectin” OR “Neurogenic inflammation” OR “p-selectin”

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OR “Intercellular adhesion molecule-1” OR “Monocyte chemotactic protein 1” OR “Myokine”

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OR “Biological marker” OR “visfatin” OR “adiponectin” OR “leptin” OR “resistin”). In

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addition, reference lists of all relevant studies and review articles were also hand searched to

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avoid missing any publication. Duplicate citations were removed.

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Inclusion and exclusion criteria: PICOS (participants, interventions/exposures, comparators,

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outcomes and study design) criteria used to identify studies eligible for inclusion (Table 1). For a

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study to be included in the systematic review, it had to: 1) be a randomized controlled trial

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(RCT); 2) investigate the effect of dairy products (including yogurt, milk or cheese) consumption

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on inflammatory biomarkers as the main or secondary outcome; 3) report means and standard

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deviations (SD) or standard errors (SE) of inflammatory biomarkers; 4) be conducted on adult

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participants, irrespective of their health status. Reviews, editorials, commentaries, non-human

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studies, and letter-to-editors were not included. These studies were also not included: (1)

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investigated the outcome variables between the two groups with the same amount of dairy intake

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or dairy intake with calcium supplement; (2) studied participants who received dairy along with

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other foods or food supplements (such as omega-3 fatty acids) (23-26); (3) investigated

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participants who received enriched dairy products or probiotic dairy products; (4) investigated

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the effect of dairy products consumption on gene expression of inflammatory biomarkers; (5)

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studied effect of dairy after some hours of intake.

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Data extraction: Data extraction was performed independently by two investigators (SPM and

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PS) and the following information were extracted for each clinical trial: the first author’s name,

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year of publication, sample size, participants’ sex, number of participants in each group,

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7 93

participants’ mean age, design of the clinical trial (parallel or crossover), type of the intervention

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and control diets, duration of intervention, health and weight status of participants, means±SDs

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of inflammatory biomarkers at study baseline and after the intervention and adjustments done. In

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case of any disagreements, the third investigator (AE) was consulted. All reported SEs was

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converted to SDs using appropriate formula. When a cytokine concentration was reported in

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different units, we converted them to the most frequently used unit in the included studies.

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Appraisal of the quality of studies: The quality of included studies was assessed using the

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Downs and Black assessment tool (27). The Downs and Black Scale consists of 27 questions

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relating to quality of reporting (10 questions), external validity (3 questions), internal validity

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(bias and confounding) (13 questions), and statistical power (1 question) (27).

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Statistical analysis: Mean (±SDs) differences of inflammatory biomarker concentrations,

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comparing the two groups of dairy intake and control diet was used to compute the overall effect

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size. The pooled effect size was calculated using a random-effects model, which takes between-

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study heterogeneity into account. Subgroup analyses were performed to find the sources of

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heterogeneity. Subgroup analyses based on sex and quality of studies were pre-specified; while

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other subgroup analyses (including country, duration of follow up, age, treatment type, placebo

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type, and adjustments) were added afterwards. Between subgroup heterogeneity was evaluated

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using the fixed-effects model. Statistical heterogeneity between studies was evaluated by

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Cochran’s Q test. Heterogeneity was interpreted using Cochrane threshold: 0- 40% as important;

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30-60% as moderate; 50-90% as substantial and 75-100% as considerable heterogeneity.

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Sensitivity analysis was used to explore the influence of a single study on the overall estimate via

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eliminating one study and repeating analysis. Publication bias was assessed by visual inspection

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of funnel plots. Formal statistical assessment of funnel plot asymmetry was done using Begg’s

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8 116

test and Egger’s regression test. Statistical analyses were carried out by the use of Stata, version

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11.2 (STATA Corp., College Station, Texas). P values less than 0.05 were considered as

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statistically significant.

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RESULTS

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Systematic review: In our initial literature search, 230 potentially relevant studies were selected

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following the screening stage (Figure 1). The title and abstract of these articles was reviewed

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and then 219 papers were excluded based on the study inclusion criteria. After these exclusions,

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11 RCTs were included in this meta- analysis (17-19, 28-35). Characteristics of these RCTs are

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summarized in Table 2. Included trials were published between 2008 and 2017, with a sample

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size ranging from 20 to 113 participants. The studies were reported from USA (17, 28-32),

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Finland (19), Netherlands (18), Mexico (33), Australia (34), and Canada (35). Out of these 11

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RCTs, 6 studies were of parallel design (17, 19, 28, 30, 32, 33) and 5 remaining studies used a

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cross-over design (18, 29, 31, 34, 35). Nine studies were conducted on both genders (18, 19, 28-

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32, 34, 35), while two studies were conducted on women only (17, 33). Duration of intervention

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in these studies ranged from 4 weeks to 24 weeks. The average percent of fat from total calorie

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was 25% (33), 25-35% (34, 35), 28-33% (32), or ≈35% (19, 30, 31). However, 3 trials did not

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report the percentage of dietary fat (17, 18, 29). The intervention was consumption of 3

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servings/day yogurt (32), 3-5 servings/day dairy products (19), >3.5 servings/day dairy products

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(28), ≤4 servings/day dairy products (30), 3 servings/day dairy product (29, 35), 4-6 servings/day

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low fat dairy (34), 500 ml low fat milk and 150 gr low fat yogurt (18), 750 ml low fat milk (33),

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339 gr low fat yogurt (17), and dairy smoothies with nonfat dry milk (31). Control diets

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consisted of a diet with low dairy products (<0.5 or <1 dairy serving/day) (28, 30, 32), a habitual

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diet with low dairy products (19, 29), a carbohydrate-rich diet with low dairy products (18), a

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9 139

soy smoothie without dairy (31), an energy restricted diet without any dairy products (33), a soy

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pudding without any dairy products (17), an energy-matched control diet (including fruit juice,

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vegetable juice, cashews, and 1 cookie) without any dairy products (35), and a diet with 200 g of

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fish or chicken each day, with less than one serving/day of dairy intake (34). In addition, 5

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studies were conducted in healthy overweight and obese subjects (18, 30-33), 1 study in healthy

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individuals with various weight condition (over weight, obese, and normal weight) (34), one

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study in premenopausal women (BMI 18.5–27 and 30–40kg/m2) (17), two studies in overweigh

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and obese subject with metabolic syndrome (19, 28), one research in adults with metabolic

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syndrome (over weight, obese, and normal weight subjects) (29), and one other in over weight

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and obese adults with high values of hs-CRP (>1 mg/L) (35). In 7 of these investigations, no

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adjustments for potential confounders were done (17, 28-32, 34). One study had controlled for

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sex, and country (19), and one study had controlled for baseline values, sex, and weight (18),

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another investigation had considered age, and baseline values (33), and one trial had controlled

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for sex, study center and pre-diet inflammatory status (21). Compliance of study participants had

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been assessed using dietary records or checklists. These trials had mostly reported the effects of

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dairy consumption on levels CRP, TNF-α, IL-6, MCP, adiponectin, ICAM-1, VCAM-1, and

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leptin.

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Quality of included studies: Findings from assessing the quality of RCTs are shown in

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Supplementary Table 1. According to Downs and Black assessment tool, based on which five

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studies were of high quality (score >19) (19, 28, 33-35), while six studies were deemed as low

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quality, mostly due to lack of explanation of confounders and insufficient blinding (17, 18, 29-

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32).

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Findings from the meta-analysis of the effect of dairy consumption on CRP levels: In total,

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the effect of dairy intake on CRP levels was examined in 10 clinical trials (17, 19, 28-35), with a

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total 641 participants. Summarizing these effect sizes, we found that dairy consumption might

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lead to a 0.24 mg/L reduction in CRP levels compared to the control diet (weighed mean

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difference (WMD) = -0.24 mg/L; 95% CI, -0.35, -0.14 mg/L), with a significant between-study

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heterogeneity (I2=91.6, P<0.001). To find the source of heterogeneity, subgroup analysis was

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conducted based on study design, gender, country, quality of study, treatment type, control diet,

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age, duration of intervention and adjustments. There was no heterogeneity in RCTs with cross-

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over design (Figure 2, Table 3), high quality score RCTs (quality score>19), those with

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participants aged 40 years or older and those that administered total dairy rather than milk or/and

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yogurt (Table 3). Subgroup analysis according to study design (parallel or cross-over) revealed

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that in parallel studies, dairy consumption might lead to a significant decrease in CRP levels

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(WMD= -0.75 mg/L; 95% CI, -1.31, -0.19 mg/L), while in cross-over trials, dairy intake had no

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significant effect on CRP levels (WMD= -0.02 mg/L; 95% CI, - 0.05, 0.0 mg/L).

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Findings from the meta-analysis of the effect of dairy consumption on TNF-α levels: Eight

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RCTs had reported the effect of dairy intake on TNF-α levels (17-19, 28-31, 34). Overall, we

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found that consumption of dairy products might decrease serum TNF-α concentrations in

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comparison with the control group (WMD= -0.66 pg/mL; 95% CI, -1.23, -0.09 pg/mL). There

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was a significant heterogeneity between studies (I2 = 94.9, P<0.001). Potential sources of

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variation were evaluated by subgroup analysis; there was no heterogeneity in RCTs with cross-

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over design, those with a duration of intervention of >10 weeks, subjects’ age of 40 years or

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more and those that administered milk or yogurt (Table 3). We found a significant inverse

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association between dairy intake and serum TNF-α concentrations in parallel studies (WMD= -

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1.30 pg/mL; 95% CI, -2.38, -0.23 pg/mL); but the effect was not significant in cross-over RCTs

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(Figure 3).

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Findings from the meta-analysis of the effect of dairy consumption on IL-6 levels: This

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meta-analysis was done based on effect sizes from seven RCTs (17-19, 28, 30, 31, 35). We

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found that dairy intake could significantly reduce serum IL-6 levels compared to the control diet

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(WMD= -0.74 pg/mL; 95% CI, -1.36, -0.12 pg/mL). Subgroup analysis to find the source of

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between-study heterogeneity (I2 = 96.4 %, P < 0.001) revealed that participants' age and

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adjustments could explain this heterogeneity (Table 3). Dairy intake resulted in decreased IL-6

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concentrations in parallel studies (WMD= -2.45 pg/mL; 95% CI, -4.13, -0.77 pg/mL), not in

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cross-over RCTs (Figure 4, Table 3).

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Findings from the meta-analysis of the effect of dairy consumption on adiponectin levels:

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Seven RCTs had reported data for the effect of dairy intake on adiponectin levels (19, 28-32, 35).

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Overall, we observed that dairy intake could lead to a 2.42 µg/mL increment in adiponectin

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levels compared to the control group (WMD= 2.42 µg/mL; 95% CI, 0.17, 4.66 µg/mL).

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Heterogeneity between studies was significant (I2= 91.6 %, P<0.001). When sub-group analysis

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was done, there was no heterogeneity in non-US studies, those with participants aged 40 years

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and older, high quality RCTs and studies that made adjustments (Table 3). Heterogeneity was

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significant in both parallel studies and cross-over studies ((I2 = 95%, P<0.001), (I2 = 75.6%,

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P=0.006), respectively) (Figure 5, Table 3). Again, no significant effect was observed in cross-

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over studies.

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Findings from the meta-analysis of the effect of dairy consumption on serum leptin, MCP,

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ICAM-1 and VCAM-1 levels: Three RCTs had reported the effect of dairy intake on serum

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leptin levels (19, 29, 30). Summarizing these effect sizes, we failed to find any significant effect

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12 207

of dairy consumption on serum leptin concentrations (WMD= -1.56 ng/mL; 95% CI, -3.46,

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0.34). Between-study heterogeneity was not important (I2= 30%, P=0.23) (Supplementary

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Figure 1-A).

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In terms of the effect of dairy intake on MCP concentrations, 4 effect sizes were pooled from

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four studies (18, 28, 29, 31). Based on them, we found that consumption of dairy products might

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result in reduced MCP levels (WMD= -25.58 pg/mL; 95% CI, -50.31, -0.86; I2=87.2%, P<0.001)

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in comparison with the control group (Supplementary Figure 1-B). When subgroup analysis

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was conducted, there was no heterogeneity in non-US studies and those that recruited

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participants aged 40 years and older. When we removed the study of Stancliffe et al (28), there

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was no heterogeneity between studies (I2=0.0%, P=0.160); however, no difference between this

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study and other trials included in the analysis was found.

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Pooling 3 effect sizes from two studies (18, 29) revealed no significant effects of dairy

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consumption on ICAM-1 levels (WMD =-3.38 ng/mL; 95% CI, -15.57, 8.96; I2=0.0%, P=0.99)

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(Supplementary Figure 1-C). Pooling effect sizes from three RCTs on the effect of dairy intake

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on VCAM-1 concentrations (18, 19, 29), we failed to find any significant effect of dairy intake

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on serum VCAM-1 concentrations (WMD= 3.1 ng/mL; 95% CI, - 21.38, 27.58; I2=0.0%,

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P=0.47)(Supplementary Figure 1-D).

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Sensitivity analysis and Publication Bias:

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Sensitivity analysis indicated that no single study influenced the overall effect size for any

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inflammatory biomarkers (Supplementary Figure 2). Also, no evidence of publication bias was

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found, as shown in Supplementary Figure 3.

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DISCUSSION

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This meta-analysis on 11 RCTs with 663 adult participants showed that, compared to low or no

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dairy intake, high consumption of dairy products might result in decreased CRP, TNF-α, IL-6,

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and MCP concentrations and increased adiponectin levels. No significant effect of dairy

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consumption on serum leptin, ICAM and VCAM levels was found. Our findings highlight the

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probable anti-inflammatory properties of dairy products. However, it must be kept in mind that

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between-study heterogeneity was considerable for CRP, TNF-α, IL-6, adiponectin and moderate

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for leptin and substantial for MCP; such that the beneficial effects were not observed when the

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analyses were confined to cross-over studies. In addition, when we did subgroup analysis, the

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effects of dairy consumption on inflammatory biomarkers tended to be null in most cases when

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there was no heterogeneity in different subgroups. In addition, when we did subgroup analysis,

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the effects of dairy consumption on inflammatory biomarkers tended to be null in crossover

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RCTs and no heterogeneity was observed in these trials. Elevated concentrations of

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inflammatory biomarkers including CRP, TNF-α and IL-6 are involved in the pathogenesis of

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several chronic diseases, including CVD (36) and insulin resistance (37, 38). On the other hand,

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adipose tissue is an active endocrine organ that secretes several adipokines and proinflammatory

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cytokines (39, 40). Increased adiposity is generally associated with increased inflammation and

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reduced adiponectin production (41). Different mechanisms are proposed to explain the potential

246

anti-inflammatory effects of dairy products. Previous studies have shown that dairy’s calcium

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might lead to a reduction in body fat mass (42). In addition, earlier studies have shown

248

that1α,25-dihydroxy-cholecalciferol can increase the production of MCP-1 from adipocytes and

249

dietary calcium acts as an anti-inflammatory agent through suppression of 1α,25-dihydroxy

250

cholecalciferol (18, 32, 43).

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14 251

The role of dairy products in increasing adiponectin levels might be attributed to their effect on

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body fat mass (44). However, some studies have shown that dairy consumption reduces

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inflammatory factors without any significant changes in body weight. According to the findings

254

of the PREDIMED trial, the inverse association between dairy consumption and CRP or ICAM-1

255

concentrations were significant, even after adjustment for weight loss (14). Zemel et al. have also

256

reported the same findings (31). Prior investigations have shown that dairy products contains

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angiotensin-converting enzyme inhibitory (ACEI) peptides, whereas adipose tissue (45)

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contribute to the expression of all components of renin angiotensin system (30). This system

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induces inflammatory responses in the body (46, 47), and its suppression can result in the

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reduced inflammatory factors (48, 49). High concentrations of leucine in dairy products might

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also be another reason for their anti-inflammatory properties. According to the previous studies,

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leucine increases anti-inflammatory adiponectin expression and decreases proinflammatory

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cytokines (including TNF-α, MCP-1, and IL-6) expression (50, 51). Leucine reduces oxidative

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and inflammatory stress by several mechanisms including the stimulation of mitochondrial

265

biogenesis, increase in oxygen consumption and fatty acid oxidation in adipocytes and skeletal

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muscle cells and induction of protein synthesis and suppression of protein degradation (52-54).

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Leucine can also increase sirtuin 1 (SIRT1) expression. SIRT1 and adenosine monophosphate-

268

activated protein kinase can increase mitochondrial biogenesis and oxidative capacity which

269

prevent the oxidative and inflammatory stress (55). Also, SIRT1 inhibits NF-kB pathway activity

270

(56).

271

Soluble ICAM-1 and VCAM-1 concentrations increase in inflammatory stress and endothelial

272

dysfunction (57). These factors play an important role in the pathogenesis of atherosclerosis.

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Hlubocka et al. have reported that ACEI (such as ACEI peptides in dairy products) could lead to

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15 274

a significant drop of adhesion molecules in hypertensive patients (58). Similarly, Lee et al.

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reported a favorable effect for dairy products as a source of ACEI on endothelin-I and VCAM-1

276

concentrations in patients with hypertension or hypertriglyceridaemia (59). However, in the

277

present study, we did not find any significant effect of dairy products intake on ICAM-1,

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VCAM-1 or leptin levels. This could be attributed to the limited number of studies in this regard,

279

such that there were only three RCTs that reported the effects of dairy intake on ICAM-1,

280

VCAM-1 or leptin levels.

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Our findings on the favorable effect of dairy products on inflammation are consistent with some

282

previous studies. A review, conducted on the investigations that were done before the year 2013,

283

concluded the anti-inflammatory activity of dairy products in humans (60). Findings from a

284

meta-analysis demonstrated that high consumption of yogurt was associated with a lower

285

incidence of CVD (61). In a dose-response meta-analysis, total dairy intake was inversely

286

associated with risk of type 2 diabetes (62). High consumption of dairy products, due to their

287

high content of saturated fatty acids, may counteract with beneficial effects of minerals and

288

vitamins on cardiovascular health (39). Saturated fat content of dairy products might lead to

289

increased LDL-cholesterol concentrations However, in previous meta-analyses performed on

290

cohort studies, no significant relationship was found between dairy products consumption and

291

risk of cardiovascular disease; milk intake might even be inversely associated with overall CVD

292

risk (63-66). More consumption of total dairy products and low-fat dairy products has also

293

decreased the risk of T2D in a dose-response manner (66). In addition, an overview of previous

294

systematic reviews and meta-analyses showed that dairy product consumption is not significantly

295

associated with risk of all-cause mortality (67). In contrast, Qin et al have documented an inverse

296

association between low-fat dairy intake and incidence of stroke, while no significant association

15

16 297

between high fat dairy consumption and risk of stroke (68). Given the high mortality rate from

298

cardiovascular disease in many countries, an investigation in Finland has focused on changing

299

the lifestyle and dietary patterns (69). Lifestyle modification based on the type and amount of

300

saturated and unsaturated fats might reduce mortality rate. Reducing the consumption of

301

saturated fats, especially from dairy products (such as 85% reduction in butter consumption) in

302

the mentioned study and other investigations led to a 80% reduction in annual CVD mortality

303

rates among that population (69, 70) .Unfortunately, in the present meta-analysis we were not

304

able to conduct the analysis based on fat content of dairy products, due to the lack of sufficient

305

data in this regard in the published RCTs.

306

In the current analysis we have interestingly found that younger individuals had more

307

improvements in inflammatory markers after consumption of dairy products. Older age has been

308

long associated with altered inflammation and homeostasis regulation. Elderly, independently of

309

chronic disease status, is associated with chronically elevated circulating levels of inflammatory

310

markers such as interleukin IL-6, TNF-α, IL-1 and CRP (71, 72). Previous researches have also

311

shown that older people are less responsive to anti-inflammatory agents than young people (73).

312

Thus, various physiologic and confounding factors might make older people less respondent to

313

the anti-inflammatory effects of dairy products.

314

The present meta-analysis is the first one, to our knowledge, that assessed the effect of dairy

315

consumption on inflammatory cytokines, including CRP, IL-6, TNF-α, adiponectin, MCP,

316

ICAM-1, VCAM-1 and leptin. No evidence of substantial publication bias in this meta-analysis

317

was found. However, our study has several limitations. First, control or non-intervention groups

318

were different in the included trials in this meta-analysis; this might tend to bias the findings

319

toward null. Second, type of dairy products and the fat percentage of the dairy products were not

16

17 320

always specified in published RCTs; stratified analysis based on these variables might provide

321

more compelling results. Third, we were not able to do a subgroup analysis based on the fat

322

content of dairy products, while intake of saturated fats in high-fat dairy products could be

323

positively associated with inflammatory factors (74). Fourth, since dairy consumption was

324

reported as a range in the published studies, we were unable to conduct a dose-response or meta-

325

regression analysis. Fifth, it must be kept in mind that lack of blinding participants in RCTs on

326

dairy consumption is always a big problem and might overstate the findings. Sixth, all included

327

studies were conducted on healthy or over weight/obese adults; therefore, generalizing the

328

findings should be done cautiously.

329

In conclusion, this study demonstrated that consumption of dairy products might have beneficial

330

effects on serum concentrations of CRP, TNF-α, IL-6, MCP, and adiponectin among adults. No

331

significant effect of dairy intake on serum ICAM-1, VCAM-1 and leptin levels were found. In

332

most subgroups without heterogeneity, effects tended to be null. Study design and participants’

333

age were the main sources of heterogeneity. Additional precise investigations are needed in this

334

area, with a particular focus on fat content of dairy foods.

17

18 335

ACKNOWLEDGMENTS

336

Authors’ contributions: SPM and PS: conducted the research; SPM and PS: analyzed the data;

337

SPM, MR, PS and AE: wrote the manuscript; PS and AE: had primary responsibility for the final

338

content; and all authors: designed the research, and read and approved the final manuscript.

339

Funding/support: This study was financially supported by Students’ Research Committee,

340

Isfahan University of Medical Sciences, Isfahan, Iran, in collaboration with School of Nutritional

341

Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran. The funder had no

342

role in the undertaking, data analyses, or reporting of this systematic review.

343

Conflicts of interest: Authors declared no personal or financial conflicts of interest.

18

19

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23

24

Legend to Figures Figure 1: Flow diagram illustrating the study selection process for meta-analysis and systematic review. Figure 2: Forest plot for the effect of dairy intake on serum hs-CRP concentration, expressed as mean differences between the

intervention and the control diets, stratified by study design. Figure 3: Forest plot for the effect of dairy intake on serum TNF-α concentration, expressed as mean differences between the

intervention and the control diets, stratified by study design. Figure 4: Forest plot for the effect of dairy intake on serum IL-6 concentration, expressed as mean differences between the intervention

and the control diets, stratified by study design. Figure 5: Forest plot for the effect of dairy intake on serum adiponectin concentration, expressed as mean differences between the

intervention and the control diets, stratified by study design.

Supplementary Figure 1: Forest plot for the effect of dairy intake on serum leptin (A), MCP1 (B), ICAM-1 (C) and VCAM-1 (D)

concentration, expressed as mean differences between the intervention and the control diets. Supplementary Figure 2: Sensitivity analysis of included studies for hs-CRP (A), TNF-α (B), IL-6 (C) and adiponectin (D). (Influence of a single study on the overall estimate via eliminating one study and repeating analysis) Supplementary Figure 3: Funnel plot of included studies detailing publication bias for hs-CRP (A), TNF-α (B), IL-6 (C) and adiponectin (D).

24

25

Table 1. PICOS criteria for inclusion of studies Parameter Population

Study selection criteria Adult participants, irrespective of their health status.

Intervention

Dairy products (including yogurt, milk or cheese) consumption

Comparator

No dairy/ low dairy consumption

Outcomes

Change in inflammatory biomarkers

Study design

Randomized controlled clinical trials, published in any year or language

25

26 Table 2.

Characteristics of clinical trial studies which were included in the systematic review and meta-analysis.

Author

Subjects

Age

Desig

(Year) (Ref.)

and

range (y)

n

gender

Diet type

outcome

Du

Any

Notes

Adjustm

Total

Intervention

Control

rat

Intervention

Control

other

about

ent or

quality

Or

(name and

(name and

io

mean±SD or SE*

mean±SD or SE*

interve

subjects

matchin

score1

mean

composition)

compositio

n

and number

and number

ntion

n)

(w

age

g

(from)

k) Zemel et al. (2008)(32).

Wennersberg et al. (2009)(19).

F:27 M:7 Both:34 Interventi on (int) group:18 Control group:16

Interventi on group:39 ±10

F:23 M:11 Both:34 Interventi on group:17 Control group:17 F: 76 M: 37 Both: 113 Interventi on group: 56

18-50

RCT, Parall el

High dairy, yogurt , 3 serving/d, (eucaloric diet)

Low dairy, yogurt, ,<1 serving/d (eucaloric diet)

12

Control group: 42±6

F: 56.7 ±7.4 M: 51.2 ± 8.1 All:30-65

High dairy, yogurt (hypocaloric diet)

RCT, Parall el

Consume 3–5 portions of dairy products (milk, yogurt or cheese)

Low dairy,yogur t (hypocalori c diet)

Habitual diet. Clinical Investigatio ns were conducted

24

24

CRP (µg/l) Before int:8500±400* After int:7160±560* Adiponectin (µg/l) Before int:1000±8* After int:1126±16* CRP (µg/l) Before int:7400±440* After int: 5200±560* Adiponectin (µg/l) Before int:960±24* After int:1112±8* Adiponectin (mg/L) Before int:10.6±6.1 After int:11.2 ± 6.2 Changes:0.6 ± 2.6

26

CRP (µg/l) Before int:8824.5±421.05* After int:8480±500*

No

Healthy obese subjects

No

Middleaged overweigh t subjects (n = 121) with traits

No

19

Adiponectin (µg/l): Before int:1004±16* After int:962±6* CRP (µg/l) Before int:7000±620* After int:7280±440* Adiponectin (µg/l) Before int:964±44* After int:918±24* Adiponectin (mg/L) Before int: 8.7 ±6.2 After int: 8.8 ± 5.9 Changes: 0.7 ± 2.6

Sex, country

21

27 Control group: 57

Zemel et al. (2009)(31).

F: 6 M: 14 Both: 20 Over weight:10 Obes:10

daily.

31.0±10. 3

RCT, cross over

The dairy smoothies were milk based, with nonfat dry milk as the protein source, and contained 350 mg calcium per smoothie. Administered 3 times per day.

on admission and after 6 month.

The placebo smoothies were soy based and contained 50 mg calcium per smoothie. The soy protein isolate was used as the protein source in

4

Leptin (ng/mL) Before int: 28.8±20.3 After int: 30.5 ± 22.1 Changes: 1.7 ± 1.8

Leptin (ng/mL) Before int: 26.8 ±21.9 After int: 25.3 ± 18.7 Changes: -1.5 ± 11.8

CRP (mg/L) Before int: 3.5 ± 3.3 After int: 3.6 ± 3.2 Changes: 0.1± 2.3 IL-6 (pg/mL); Before int:2.9±1.4 After int: 3.1±1.3 Changes: 0.2 ±1.3

CRP (mg/L) Before int: 3.0 ± 3.0 After int: 3.0 ± 3.0 Changes: -0.1 ± 2.6

TNF-α (pg/mL) Before int:8.6±2.7 After int: 8.4 ±2.6 Changes: -0.2±1.9 VCAM-1(ng/mL) Before int:568±188 After int: 530 ± 177 Changes: -38 ± 70

TNF-α (pg/mL) Before int: 9.5±3.3 After int: 9.8 ± 3.6 Changes: 0.3 ± 0.3 VCAM-1 (ng/mL) Before int: 629 ± 249 After int: 609 ±248 Changes: -10 ± 61 TNF-α :(nmol/L) Changes: 80.70 ±130.27 MCP-1 (pg/mL) changes::14.16 ±22.28 IL-6 (pg/mL) Changes:11.81±34.1 3 CRP (ng/mL) Changes: 4.19 ± 12.49 Adiponectin (ng/mL) Changes:

TNF-α :(nmol/L) Changes:-61.20± 109.50 MCP-1 (pg/mL) Changes: -10.68 ±17.72 IL-6 (pg/mL) Changes: -12.07±9.60 CRP (ng/mL) Changes:-17.17 ± 52.50 Adiponectin (ng/mL) Changes:11.33±15.

27

of the metabolic syndrome

IL-6 (pg/mL); Before int: 3.4 ±3.5 After int: 3.8 ± 3.5 Changes: 0.4 ± 1.3

No

Twenty healthy subjects (10 obese, 10 overweigh t)

No

18

28 the placebo smoothies. Administed 3 times per day. van Meijl et al. (2010)(18).

Stancliffe et al. (2011)(28).

F:25 M: 10 Both: 35

F: 21 M:19 Both: 40 Interventi on group:20 Control group:20

49.5±13. 2

37.0 ± 9.9

RCT, cross over

RCT, Parall el

low-fat dairy products (500 ml low-fat milk and 150 g low-fat yogurt

adequatedairy (>3.5 daily servings) Two of the 3 dairy servings consumed daily were milk and/or yogurt.

carbohydra te-rich control products (600 ml fruit juice and three fruit biscuits)

low-dairy (<0.5 daily servings)

8

21

33

-4.73±13.57

TNF-α (pg/ml) After int:2.32±0.64 Change:-0.16±0.5 Il-6 (pg/ml)After int:3.01±3.47 Changes: -0.04±1.46 MCP-1 (pg/ml) After int: 291.1±68.5 Changes:1.45±29.4 ICAM-1 (ng/ml) After int:280.5±78.6 Changes: -6.43±27.7 VCAM-1 (ng/ml) After int:447.7±110 Changes: 11.6±76.4 TNF-α (nmol/L) Before int:17.03 ± 3.18 Changes from baseline:-5.99 ±2.07

TNF-α (pg/ml) After int:2.48±0.76

MCP-1 (pg/mL) Before int: 176.6 ± 59.8 Changes from baseline: -45.3 ±29.9

28

No

Thirty-five healthy subjects (BMI > 27 kg/m2). Age:18-70

Weight, sex, baseline differenc es, baseline values

19

No

Forty overweigh t and obese adults (19men and 21 women) with a diagnosis of metabolic

No

22

IL-6 (pg/ml) After int:3.05±3.24

MCP-1 (pg/ml) After int:289.7±66.5

ICAM-1 (ng/ml) After int:286.5±86.6

VCAM-1 (ng/ml) After int:436.1±103.1 TNF-α (nmol/L) Before int:14.22 ± 2.87 Changes from baseline :0.49 ± 1.40

MCP-1 (pg/mL) Before int: 165.9 ± 45.3 Changes from baseline: 25.4 ± 23.1

29

Rosado et al. (2011)(33).

F:64 Interventi on group:33 Control group:31

34±6

van Loan et al. (2011)(30).

Both:71 Interventi on group:35

32.5 ± 9.5

Control group:36

RCT, Parall el

RCT, Parall el

250 mL of low fat milk consumed three times per day in addition to an energy restricted diet ≤4 servings dairy/d (adequate dairy).

an energy restricted diet (−500 kcal/day) with no intake of milk

16

≤1 serving dairy/d (low dairy)

12

IL-6 (pg/mL) Before int: 37.4 ± 2.9 Changes from baseline: -13.7± 3.8 CRP (ng/mL) Before int:21.9 ±14.5 Changes from baseline -9.1±5.3

IL-6 (pg/mL) Before int: 31.8 ±1.6 Changes from baseline: 0.3 ± 3.8

Adiponectin (ng/mL) Before int:18.26 ± 6.32 Changes from baseline: 9.01±5.64 CRP (mg/l) Before int:5.5 ± 3 Changes: 0.2

Adiponectin (ng/mL) Before int:21.16 ± 7.65 Changes from baseline:-2.98± 1.59 CRP (mg/l) Before int: 6. ±3.9 Chenges: -1.1

Leptin (ng/mL) Before int:39.5± 23.7 After int:29.5±24.0

Leptin,(ng/mL) Before int: 28.7 ±21.0 After int:21.7 ±16.5

Adiponectin (µg/mL) Before int; 13.7± 7.2 After int: 13.8 ±6.7 IL-6 pg/mL Before int:3.38 ±2.86 After int:3.20±2.72

Adiponectin (µg/mL) Before int; 14.7± 7.6 After int:15.2 ± 7.1

29

syndrome

CRP (ng/mL) Before int: 24.8 ± 15.3 Changes from baseline:-1.1 ± 5.5

IL-6 pg/mL Before int:3.97± 4.97 After int:3.30 ± 3.96

No

No

Healthy Obese women (BMI ≥30), aged between 25 and 45 years Healthy overweigh t and obese adults

Age and initial value

22

No

19

30

Labonte et al. (2014)(35).

F: 74 M: 38 Both: 112

40.1 ±16.7

RCT, cross over

Consumed 3servings/d of dairy (375 mL low-fat milk,175g low-fat yogurt, and 30 g regularfat cheddar cheese)

energymatched control (fruit juice, vegetable juice, cashews, and 1 cookie) products

8

Dugan et al. (2016)(29).

M:13

-

RCT, cross over

low-fat dairy (LFD) products (10 oz 1% milk, 6 oz nonfat yogurt, and 2 oz 2% cheese, providing 3 dairy

control foods (CNT) (1.5 oz granola bar and 12 oz juice) into their usual diet

6

TNF-α (pg/mL) Before int:3.15± 1.65 After int; 3.07 ± 1.51 CRP ( mg/L) before int:3.4 ± 4.5 after int: 2.4 ± 2.4 CRP mg/L Before int: 3.08 ±3.07 After int: 2.85 ± 2.14 Changes: -0.23 Il-6 pg/mL Before int: 1.73 ±1.08 After int: 1.39 ± 0.68 Changes: -0.34 Adiponectin, µg/mL Before int: 8.91 ± 4.61 After int: 8.81 ±4.23 Changes: -0.09 CRP (mg/L) After int:1.53±1.84

TNF-α (pg/mL) Before int:3.07± 1.63 After int: 3.19 ± 1.46 CRP, (mg/L) before int:2.5 ± 3.3 after int: 2.1 ± 3.8 CRP mg/L Before int: 2.89 ± 2.29 After int: 2.55 ± 1.96 Changes: -0.34 Il-6 pg/mL Before int: 1.65 ± 1.10 After int: 1.36 ± 0.73 Changes: -0.29 Adiponectin, µg/mL Before int: 8.98 ±4.71 After int: 8.97 ± 4.36 Changes: 0.00

Leptin (ng/mL) After int:6.84±4.91 Adiponectin (µg/mL) After int:7.81±4.55

Leptin (ng/mL) After int:5.77±3.03 Adiponectin (µg/mL) After int:7.93±3.72

VCAM-1 (ng/mL) After int:793.13± 137.13

VCAM-1 (ng/mL) After int: 823.99± 142.52

30

CRP (mg/L) After int:1.82±1.57

No

112 over weight and obese adult men and women with highsensitivity C-reactive protein (hs-CRP) values >1 mg/L

sex, study center, and pre diet inflamma tory status .

20

No

Subjects with metabolic syndrome (over weight, obese, and normal weight)

No

19

31 servings/d)

F: 24

Pei et al. (2017)(17).

F: 112 M: 0 Both: 112 Yogurt non-obese (YN):30 Control non-obese (CN):30

CN:25·3 ±1.1 CO: 31.9 ±1.6 YN:24.8 ± 0.8 YO:36.7 ±2

RCT, Parall el

consume 339 g of low-fat yogurt daily

324 g of soya pudding daily

9

ICAM-1 (ng/mL) After int:193.85± 36.44 MCP-1 (pg/mL) After int:151.85± 60.19 TNFa(pg/mL) After int;5.28±2.18 CRP (mg/L) After int: 4.7± 0.74 Leptin (ng/mL) After int: 24.34±2.50 Adiponectin (µg/mL) After int:10.93 ±1.07 VCAM-1 (ng/mL) after int:719.42±38.36 ICAM-1 (ng/mL) after int: 191.93±10.42 MCP-1 (pg/mL) After int;147.66 ±8.69 TNFa (pg/mL) After int;4.36±0.36 IL-6 (pg/l) YN before int:0.88± 0.13 YN after int: 0.87± 0.1 YO before int:1.86± 0.22 YO after int:1.56± 0.19

31

ICAM-1 (ng/mL) After int:201.44± 39.41 MCP-1 (pg/mL) After int:141.61± 41.36 TNFa (pg/mL) After int;5.21±1.70 CRP (mg/L) After int:5.45±5.17 Leptin (ng/mL) After int: 27.37±14.00 Adiponectin (µg/mL) After int:11.21±5.36 VCAM-1 (ng/mL) after int:745.42 ±117.19 ICAM-1 (ng/mL) after int: 193.89±34.82 MCP-1 (pg/mL) After int; 174.62 ±39.89 TNFa (pg/mL) After int;4.72±1.87 IL-6 (pg/l) CN before int: 0·74± 0.08 CN after: 0.89± 0.11 CO before int:1.56± 0.13 CO after int: 1.47 ± 0.11

No

112 Premenop ausal women (BMI 18·5–27 and 30– 40kg/m2)

NO

18

32 Yogurt obese (YO):30 Control obese (CO):30

Turner et al. (2017)(34).

F:29 M:18 Both:47

49.5

RCT, cross over

low-fat dairy (from milk, yogurt, custard and cheese) consume 4–6 servings with chicken and fish but no red meat

at least 200 g of fish or chicken each day, with less than one serving/day of dairy

10

CRP (mg/l) YN before int:1.15± 0.21 YN after int:1.22 ±0.22 YO before int:2.63± 0.37 YO after int:2.42 ± 0.32

CRP (mg/l) CN before int:1.24 ±0.26 CN after int:1.33 ±0.23 CO before int:2.97± 0.31 CO after int: 2.98 ± 0.32

TNF-α (pg/ml) YN before int:1.14 ± 0.09 YN after int:1.05± 0.09 YO before int:1.52± 0.12 YO after int: 1.42 ± 0.10

TNF-α (pg/ml) CN before int:1.1± 0.07 CN after int:1.21 ± 0.09 CO before int:1.25 ± 0.1 CO after int:1.23± 0.08

CRP mg/L after int:5.03±8.10 TNF pg/mL After int:1.45±1.01

CRP mg/L after int:4.04 ±6.88 TNF pg/mL After int:1.45±1.02

1

No

Healthy subjects (over weight, obese, and normal weight)

No

22

According to Downs and Black Quality Assessment Scores. F: Female; M: Male; int: intervention; CRP: C- reactive protein; IL-6: Interleukin-6; TNF-α: Tumor necrosis factor; ICAM-1:Intercellular adhesion molecule-1; MCP: Monocyte chemotactic protein-1, f-1:Vascular cell adhesion molecule-1; BMI: Body mass index; YN: Yogurt non-obese; YO: Yogurt obese; CN: Control non-obese; CO: Control obese. *SE

32

33

33

34 Table 3. Results of subgroup-analysis for effect of dairy intake on CRP and TNF-α and IL-6 and adiponectin levels. No. of RR (95% CI) P within1 effect sizes Subgroup analyses for CRP and dairy products

I2 (%)

Gender

P between2

0.810 Male Female Both

1 2 9

-0.29 (-1.60, 1.02) -0.50 (-2.46, 1.46) -0.24 (-0.35, -0.14)

0.504 0.001

0.0 94.8

US Non US

6 6

-0.26 (-0.37, -0.14) -0.17 (-0.44, 0.10)

0.001 0.949

96.7 0.0

Scores≤median(19) Scores>median(19)

7 5

-0.84 (-1.42, -0.26) -0.01 (-0.01, -0.00)

0.001 0.752

95.1 0.0

Parallel Cross-over

7 5

-0.75(-1.31, -0.19) -0.02(-0.05, 0.00)

0.001 0.726

95.3 0.0

US vs. Non US

0.249

Quality score3

0.013

Study design

0.254

Duration of follow up Less than 10 weeks 6 -0.32 (-0.83, 0.18) 0.001 10 weeks and more 6 -0.74 (-1.51,0.02) 0.001 Age Less than 40 years old 7 -0.26 (-0.37, -0.14) 0.001 40 years and older 5 -0.17 (-0.44, 0.10) 0.914 Treatment type Milk or/and yogurt 5 -0.95 (-1.65, 0.24) 0.001 Total dairy 7 -0.01 (-0.01, -0.00) 0.618 Placebo type Low dairy 4 -0.97 (-2.08, 0.13) 0.001 Others 8 -0.28 (-0.71, 0.16) 0.001 Adjustment Adjusted 2 -0.25 (-0.37, -0.14) 0.345 Non adjusted 10 -0.16 (-0.44, 0.11) 0.001 Subgroup analyses for TNF-α and dairy products Gender Male 1 0.07 (-1.43, 1.57) 34

0.028 93 90.9 0.240 95.3 0.0 0.015 96.7 0.0 0.027 94.5 90.2 0.274 0 94.1 0.804 -

35 Female Both

1 7

-0.36 (-1.12, 0.40) -0.78 (-1.44, -0.12)

0.001

96.1

US Non US

4 5

-1.97 (-3.31, -0.62) -0.01 (-0.27, 0.28)

0.001 0.247

97.8 26.2

Scores≤median(19) Scores>median(19)

6 3

-0.17 (-0.51, 0.17) -1.93 (-4.71, 0.85)

0.001 0.001

77.2 98.5

Parallel Cross-over

4 5

-1.30 (-2.38,-0.23) -0.12(-0.36, 12)

0.001 0.896

98 0

3 6

-1.85 (-4.42, 0.72) -0.29 (-0.49, 0.09)

0.001 0.190

98.6 32.7

4 5

-1.97 (-3.31, -0.62) -0.01 (-0.27, 0.28)

0.001 0.247

97.8 26.2

3 6

-0.37 (-0.56, -0.18) -0.95 (-2.15, 0.28)

0.244 0.001

29.1 96.4

0.001

2 7

-3.12 ( -9.66, 3.43) -0.11 (-0.42, 0.20)

0.001 0.003

99.3 69.3

0.147

2 0.14 (-0.50, 0.78) 0.034 7 -1.03 (-1.82, -0.23) 0.001 Subgroup analyses for IL-6 and dairy products

77.8 95.7

US vs. Non US

0.001

Quality score3

0.562

Study design

0.013

Duration of follow up Less than 10 weeks 10 weeks and more Age Less than 40 years old 40 years and older Treatment type Milk or/and yogurt Total dairy Placebo type Low dairy Others Adjustment Adjusted Non adjusted

0.003

0.001

0.001

US vs. Non US

0.001 US Non US

4 3

-5.21 (-8.90, -1.51) 0.06 (-0.07, 0.20)

0.001 0.712

98 0.0

Scores≤median(19) Scores>median(19)

4 3

-0.21 (-1.31, 0.89) -3.51 (-5.73, -1.29)

0.002 0.001

79.7 99.5

Parallel Cross-over

4 3

-2.45 (-4.31, -0.77) -0.57 (-2.73, 1.60)

0.001 0.009

97.9 78.6

Quality score3

0.001

Study design

0.001

35

36 Duration of follow up Less than 10 weeks 4 0.17 (-0.2, 0.54) 0.001 10 weeks and more 3 -4.36 (-8.37, -0.35) 0.001 Age Less than 40 years old 4 -5.21 (-8.90, -1.51) 0.001 40 years and older 3 0.06 (-0.07, 0.20) 0.712 Treatment type Milk or/and yogurt 3 -0.43 (-2.69, 1.83) 0.006 Total dairy 4 -2.56 (-4.26, -0.86) 0.001 Placebo type Low dairy 2 -7.06 (-20.04, 5.91) 0.001 Others 5 0.18 (-0.12, 0.49) 0.001 Adjustment Adjusted `3 0.06 (-0.07, 0.20) 0.712 Non adjusted 4 -5.21 (-8.90, -1.51) 0.001 Subgroup analyses for adiponectin and dairy products Gender Male 1 -0.12 (-3.31, 3.07) Female 1 -0.28 (2.47,1.91) Both 7 3.59 (0.73, 6.45) 0.001 US vs. Non US US 5 7.98 (-1.13, 17.10) 0.001 Non US 4 -0.05 (-0.51, 0.41) 0.784 Quality score3 Scores≤median(19) 6 1.08 (-1.42, 3.58) 0.032 Scores>median(19) 3 3.54 (-0.45, -7.53) 0.001 Study design Parallel 5 3.65 (-1.51, 8.81) 0.001 Cross-over 4 0.95 (-1.53, 3.44) 0.006 Duration of follow up Less than 10 weeks 4 0.95 (-1.53, 3.44) 0.006 10 weeks and more 5 3.65 (-1.51, 8.81) 0.001 Age Less than 40 years old 5 7.98 (-1.13, 17.10) 0.001 40 years and older 4 -0.05 (-0.51, 0.41) 0.784 Treatment type 36

0.001 89 98.5 0.001 98 0.0 0.001 80.4 97.7 0.965 99.1 85.6 0.001 0.0 98 0.802 93.6 94.3 0.0

0.001 0.935

58.9 97.6 0.091 95 75.6 75.6 95

0.091 0.001

94.3 0.0

37 Milk or/and yogurt Total dairy

3 6

14.28 (5.81, 22.74) 1.75 (-0.45, 3.96)

0.502 0.001

0.0 94

Low dairy Others

4 5

5.31 (-5.05, 15.67) 0.14 (-1.19, 1.47)

0.001 0.009

95.2 70.2

Adjusted Non adjusted 1 P for heterogeneity, within subgroup 2 P for heterogeneity, between subgroups

2 7

0.04 (-0.53, 0.44) 4.54 (-0.40, 9.48)

0.311 0.001

2.6 92.4

Placebo type

0.001

Adjustment

3

0.001

0.001

Quality Scores were according to Downs and Black assessment tool

37

Identification

Records identified through PubMed, ISI, Scopus, and Google scholar searching (n =361)

Additional records identified through reference lists (n =1)

Screening

Articles excluded as duplicate (n = 132)

Records screened based on title and abstract (n = 230)

Not included studies (n = 214) 1. Irrelevant (196 studies) 2. On animal models (6 studies)

Eligibility

3. Observational (8 studies) Full-text articles assessed for eligibility (n = 16)

4. Review (4 studies)

Excluded studies:

Included

Studies included systematic review and meta-analysis (n =11)

Investigating outcome between groups which had the same dairy intake or participants received other food or food supplements along with dairy (5 studies)

12 effect sizes from 10 studies for effect of dairy products on CRP 9 effect sizes from 8 studies for effect of dairy products on TNF-α 7 effect sizes from 7 studies for effect of dairy products on IL-6 9 effect sizes from 7 studies for effect of dairy products on Adiponectin 5 effect sizes from 4 studies for effect of dairy products on MCP-1 4 effect sizes from 3 studies for effect of dairy products on Leptin 3 effect sizes from 2 for effect of dairy products on ICAM 4 effect sizes from 3 for effect of dairy products on VCAM

First Author (Year) (Ref.)

Mean Difference (95% CI) Weight (%)

Parallel studies Zemel (2008) (32) Zemel (2008) (32) Wennersberg (2009) (19) Stancliffe (2011) (28) Rosado (2011) (33) van Loan (2011) (30) Pei (2017) (17) Subtotal (I-squared = 95.3%, p < 0.001)

-0.98 (-1.65, -0.31) -2.40 (-3.10, -1.70) -0.10 (-0.62, 0.42) -0.01 (-0.01, -0.00) 1.30 (-4.33, 6.93) -0.60 (-1.41, 0.21) -0.82 (-1.01, -0.63) -0.75 (-1.31, -0.19)

2.22 2.06 3.62 33.16 0.03 1.59 16.08 58.75

Zemel (2009) (31) Labonte (2014) (35) Dugan (2016) (29) Dugan (2016) (29) Turner (2017) (34) Subtotal (I-squared = 0.0%, p = 0.726)

-0.02 (-0.04, 0.00) -0.19 (-0.52, 0.14) -0.29 (-1.60, 1.02) -0.75 (-2.84, 1.34) 0.99 (-2.05, 4.03) -0.02 (-0.05, 0.00)

32.62 7.64 0.62 0.25 0.12 41.25

Overall (I-squared = 91.6%, p < 0.001)

-0.24 (-0.35, -0.14) 100.00

Cross-over studies

-3

Intervention

0

3

Control

First Author (Year) (Ref.)

Mean Difference (95% CI) Weight (%)

Parallel Studies Wennersberg (2009) (19)

0.50 (-0.01, 1.01)

13.39

Stancliffe (2011) (28)

-6.48 (-7.58, -5.38)

9.68

van Loan (2011) (30)

0.20 (-0.08, 0.48)

14.47

Pei (2017) (17)

-0.43 (-0.46, -0.40)

15.00

Subtotal (I-squared = 98.0%, p < 0.001)

-1.30 (-2.38, -0.23)

52.54

van Meijl (2010) (18)

-0.16 (-0.49, 0.17)

14.29

Zemel (2009) (31)

-19.50 (-94.08, 55.08) 0.01

Dugan (2016) (29)

0.07 (-1.43, 1.57)

7.37

Dugan (2016) (29)

-0.36 (-1.12, 0.40)

11.85

Turner (2017) (34)

0.00 (-0.41, 0.41)

13.93

Subtotal (I-squared = 0.0%, p = 0.896)

-0.12 (-0.36, 0.12)

47.46

Overall (I-squared = 94.9%, p < 0.001)

-0.66 (-1.23, -0.09)

100.00

Cross-over Studies

-10

Intervention

0

10

Control

First Author (Year) (Ref.)

Mean Difference (95% CI) Weight (%)

Parallel Studies Wennersberg (2009) (19)

0.20 (-0.24, 0.64)

21.05

Stancliffe (2011) (28)

-13.73 (-16.09, -11.37) 5.30

van Loan (2011) (30)

-0.49 (-1.27, 0.29)

17.05

Pei (2017) (17)

0.37 (0.32, 0.42)

23.51

Subtotal (I-squared = 97.9%, p < 0.001)

-2.45 (-4.13, -0.77)

66.92

van Meijl (2010) (18)

-0.34 (-1.86, 1.18)

9.68

Zemel (2009) (31)

-23.88 (-39.42, -8.34)

0.16

Labonte (2014) (35)

0.05 (-0.09, 0.19)

23.25

Subtotal (I-squared = 78.6%, p = 0.009)

-0.57 (-2.73, 1.60)

33.08

Overall (I-squared = 96.4%, p < 0.001)

-0.74 (-1.36, -0.12)

100.00

Cross-over Studies

-15

Intervention

0

5

Control

First Author (Year) (Ref.)

Mean Difference (95% CI) Weight (%)

Parallel Studies Zemel (2008) (32)

-0.16 (-28.47, 28.15)

0.61

Zemel (2008) (32)

-0.19 (-59.51, 59.13)

0.14

Wennersberg (2009) (19)

-0.50 (-1.51, 0.51)

17.24

Stancliffe (2011) (28)

11.99 (9.42, 14.56)

14.47

van Loan (2011) (30)

0.40 (-0.91, 1.71)

16.84

Subtotal (I-squared = 95.0%, p< 0.001)

3.65 (-1.51, 8.81)

49.30

Zemel (2009) (31)

16.06 (7.09, 25.03)

4.63

Labonte (2014) (35)

0.09 (-0.44, 0.62)

17.69

Dugan (2016) (29)

-0.12 (-3.31, 3.07)

13.11

Dugan (2016) (29)

-0.28 (-2.47, 1.91)

15.27

Subtotal (I-squared = 75.6%, p = 0.006)

0.95 (-1.53, 3.44)

50.70

Overall (I-squared = 91.6%, p < 0.001)

2.42 (0.17, 4.66)

100.00

Cross-over Studies

-15

Intervention

0

15

Control

Highlights:

Dairy products intake could significantly reduce CRP levels. Dairy products intake could significantly decrease serum TNF-α and IL-6 concentrations. Dairy products intake could significantly increase serum adiponectin levels. Dairy products intake might result in reduced MCP levels. In cross-over trials, dairy intake had no effect on inflammation.