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. Author manuscript; available in PMC: 2015 Nov 1.
Published in final edited form as: Diabet Med. 2014 Nov;31(11):1301–1309. doi: 10.1111/dme.12537

Dietary magnesium intake and risk of metabolic syndrome: a meta-analysis

D T Dibaba 1, P Xun 1, A D Fly 1, K Yokota 2, K He 1
PMCID: PMC4198467  NIHMSID: NIHMS609190  PMID: 24975384

Abstract

Aims

To estimate quantitatively the association between dietary magnesium intake and risk of metabolic syndrome by combining the relevant published articles using meta-analysis.

Methods

We reviewed the relevant literature in PubMed and EMBASE published up until August 2013 and obtained additional information through Google or a hand search of the references in relevant articles. A random-effects or fixed-effects model, as appropriate, was used to pool the effect sizes on metabolic syndrome comparing individuals with the highest dietary magnesium intake with those having the lowest intake. The dose–response relationship was assessed for every 100-mg/day increment in magnesium intake and risk of metabolic syndrome.

Result

Six cross-sectional studies, including a total of 24 473 individuals and 6311 cases of metabolic syndrome, were identified as eligible for the meta-analysis. A weighted inverse association was found between dietary magnesium intake and the risk of metabolic syndrome (odds ratio 0.69, 95% CI 0.59, 0.81) comparing the highest with the lowest group. For every 100-mg/day increment in magnesium intake, the overall risk of having metabolic syndrome was lowered by 17% (odds ratio 0.83, 95% CI 0. 77, 0.89).

Conclusion

Findings from the present meta-analysis suggest that dietary magnesium intake is inversely associated with the prevalence of metabolic syndrome. Further studies, in particular well-designed longitudinal cohort studies and randomized placebo-controlled clinical trials, are warranted to provide solid evidence and to establish causal inference.

Introduction

Metabolic syndrome is the name given to a cluster of risk factors for cardiovascular diseases, including coronary heart disease and stroke [1,2]. Reducing the prevalence of metabolic syndrome is of great significance to cardiovascular disease prevention. Proper identification of the risk factors would improve public awareness and inform risk-reducing prevention programmes for metabolic syndrome and the management of its health consequences. Several risk factors, including vitamin D deficiency [3], an unhealthy diet (e.g. diets high in carbohydrates and high total fat) [4–14], an inactive lifestyle [15], obesity, excess triglycerides, insulin resistance, family history of metabolic syndrome, genetics [16] and aging, have been thought to be determinants of metabolic syndrome.

Magnesium is required for hundreds of physiological processes, including glucose and insulin metabolism [17], but dietary magnesium intake has been inadequate in the general population in both the USA and worldwide [18]. There is evidence to suggest there are potential benefits of dietary magnesium intake in preventing metabolic syndrome and its components [19,20] as well as Type 2 diabetes [21], although the literature is not consistent.

In two double-blind placebo-controlled randomized trials, oral magnesium supplementation at various doses reduced insulin resistance, a central feature of metabolic syndrome [19,22]. Another randomized control trial showed that magnesium supplementation reduced blood pressure and increased HDL cholesterol significantly in the intervention group compared with the placebo group in patients with diabetes, hypertension and hypomagnesaemia at baseline [23]; however, one case–control study has documented a higher prevalence of metabolic syndrome in participants with high serum magnesium levels [24]. In addition, a prospective cohort study has found that there was no significant association between dietary magnesium and the prevalence of metabolic syndrome [14]. Studies directly relating dietary magnesium intake to risk of metabolic syndrome using study designs other than cross-sectional studies are sparse. Only one randomized controlled clinical trial [22], two cohort studies (one in the general population [20] and the other in patients undergoing renal transplant [14]), and three case–control studies [24–26] with either different exposure (dietary magnesium or hypomagnesaemia) or different effect measures (Pearson’s correlation coefficients or odds ratios) that directly related magnesium intake to metabolic syndrome were identified, which meant that we did not have enough studies to pool evidence from these study designs. The aim of the present study, therefore, was to aggregate the existing knowledge on the association of dietary magnesium intake and metabolic syndrome in the general population, by conducting a meta-analysis of cross-sectional studies.

Methods

Data sources and study selection

We searched the PubMed, EMBASE and Google Scholar databases for articles published up to August 2013 using the terms ‘magnesium’, ‘Mg’, ‘dietary magnesium intake’ and ‘dietary micronutrient’, combined with ‘metabolic syndrome’, ‘MetS’, ‘insulin resistance syndrome’, ‘syndrome X’, ‘Reaven’s syndrome’ and ‘metabolic cardiovascular syndrome’. Additional information was found through a hand search of the references of relevant articles. We followed the PRISMA guidelines for this process; the PRISMA checklist is shown in Table S1.

Studies were included in the meta-analysis if they were published in English before August 2013 and met all the following criteria: 1) a cross-sectional design; 2) dietary magnesium intake was the exposure of interest; 3) metabolic syndrome was the outcome of interest ; 4) data were available on odds ratios or relative risk with 95% CIs, or the relevant data could be derived from the reported results; and 5) the study was conducted among the general population.

Data extraction

Data were carefully extracted from the original study independently by two authors (D.D. and P.X.). Discrepancies were resolved through group discussion. The collected data included the first author’s name, year of publication, number of participants, age, percentage of male participants, exposure assessment and category, outcome definition, adjusted covariates, adjusted odds of having metabolic syndrome and 95% CIs for the corresponding categories.

We re-computed the odds ratio with 95% CI, taking the lowest magnesium intake category as the reference for one study [27] that reported the odds ratio using the highest magnesium intake group as the reference. We also extracted the odds ratios (and 95% CIs) of metabolic syndrome for every 100-mg/day increment in dietary magnesium intake. If a study did not provide the linear association of magnesium intake with risk of metabolic syndrome, we estimated it using the method described by Greenland and Longnecker [28], or calculated it under a linear assumption if appropriate.

Data synthesis and analyses

The included studies were cross-sectional studies that reported odds ratios and relative risk as measures of effect size. We extracted the odds ratios and 95% CIs of having metabolic syndrome across categories of dietary magnesium intake, with the highest or the lowest group as the reference, or for a dose–response relationship. In all included studies, data from fully adjusted models were used.

Odds ratios and 95% CIs were transformed to their natural logarithms for computing the corresponding standard errors and inverse variance. A random-effects or fixed-effects model, as appropriate, was used to assess the pooled association between dietary magnesium intake and the prevalence of metabolic syndrome by comparing participants in the highest with those in the lowest magnesium intake group. We also pooled the odds ratios (95% CIs) for linear trend (per 100-mg/day increment in magnesium intake). Cochran’s chi-squared test was used to examine heterogeneity among the included studies and I2 was computed to determine the degree of inconsistency across studies. Publication bias was assessed using Egger’s asymmetry test. All analyses were conducted using STATA statistical software (version 13, STATA Corp., College Station, TX, USA). All statistical tests were two sided and a P value ≤0.05 was considered to indicate statistical significance.

Results

Literature search

The study selection process for the meta-analysis is shown in Fig. 1. A total of 78 articles were identified by searching the databases. Of those, 66 articles were excluded because they either did not report results on the association of dietary magnesium intake and metabolic syndrome or they were not original studies. Of the remaining 12 studies, we further excluded one cross-sectional study because it reported the risk of metabolic syndrome on Z-score [29]. Two cohort studies were excluded because the samples were too low to be combined [14,20]. Three case–control studies were identified, but one of these reported only correlation coefficients [24] and another one only presented the association between hypomagnesaemia and metabolic syndrome [26], which meant that the three case–control studies could not be pooled. A final total of six identified eligible cross-sectional studies were included in the present meta-analysis.

FIGURE 1.

FIGURE 1

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Study selection process. Mg, magnesium; MetS, metabolic syndrome; OR, odds ratio.

Study characteristics

The information extracted from the six included cross-sectional studies is shown in Table 1 [27–34]. The six studies included a total of 24 473 participants with 6311 prevalent cases of metabolic syndrome. Four out of six studies, including 19 744 participants with 4989 cases of metabolic syndrome, compared the risk of metabolic syndrome between the highest and the lowest magnesium intake groups, and reported linear association (per 100-mg/day increment in magnesium intake)[27,30] or such information could be derived from two of the studies [31,32]. One study that included 4519 participants and 1166 cases reported only the linear association [33]. Another study reported the results of linear association across quartiles of magnesium intake but in magnesium/day/kg, hence relevant information could not be derived from it for analysing the dose–response relationship and it was therefore excluded from the dose–response meta-analysis [34].

Table 1.

Characteristics of the cross-sectional studies included in the meta-analysis

Source No. of participants/cases Age Proportion of male participants, % Assessment of exposure Exposure category Variables adjusted for Assessment of outcome Measure of association
Huang et al., 2012, Taiwan [34] 210/156 ≥65 years 46.7 Dietary magnesium intake was derived from 24-h dietary intake recall using the Taiwan Nutritional Database and E-Kitchen nutritional analyses software Quartiles, mg/day/kg: <2.3; 2.3–3.2; 3.3–4.4; ≥4.5. Gender, age, physical activity, total energy intake, carbohydrate intake (%energy), protein intake (%energy), total fat intake (%energy), smoking status and alcohol intake. Diagnosis of metabolic syndrome was made using either NCEP-ATPIII or IDF criteria. Odds ratios (95% CIs) across quartiles: 1.00 (reference); 2.10(0.73, 6.06); 1.68(0.60, 4.70); 0.49(0.17, 1.43).
P for linear trend=0.153.
Beydoun MA et al.2008, USA [33] 4519/1166 ≥18 years Exact figure unavailable One 24-h dietary intake recall for each of the 1999–2000 and 2001–2002 periods, and two for 2003–2004 were obtained from NHANES Continuous, per 100 mg/day magnesium intake. Gender, ethnicity, dietary groups, e.g. calcium, phosphorus, dairy products, fats, NCEP-ATP III criteria. Odds ratio (95% CI) per 100 mg/day increment in magnesium intake: 0.83 (0.72, 0.96).
McKeown et al. 2008, USA [32] 535/213 ≥60 years 33.0 3-day food records were obtained from participants. Foods were coded for magnesium using US Department of Agriculture Food and Nutrient Database for Dietary Studies (Version 1.0). Quartiles, median, mg/day: 188.4; 240.0; 297.5; 384.0. Age, gender, race, education, marital status, smoking status, alcohol intake, exercise, BMI, total energy intake, percentage of energy from saturated fatty acid intake, lipid-lowering medication use and blood pressure medication use. NCEP/ATP III criteria except for replacing abdominal adiposity with: BMI≥31kg/m2 for male and ≥27kg/m2for female participants. Odds ratios (95% CIs) across quartiles: 1.00 (reference); 0.74(0.45, 1.24); 0.55(0.32, 0.97); 0.36(0.19, 0.69).
P for linear trend=0.002
Ford et al., 2007, USA [31] 7669/1982 ≥20 years 50.5 A single 24-h dietary intake recall recorded by NHANES III Dietary Data Collection from 1988 to 1994 was used. Quintiles, mg/day:
Male:
≤221; 222–292; 293–376; 377–465; ≥466.
Female:
≤164; 165–213; 214–263; 264–336; ≥337.		 Gender, race or ethnicity, education, smoking, concentration of C-reactive protein, alcohol use, physical activity, family history of early coronary heart disease, use of vitamin or supplement, history of diabetes (except model for hyperglycemia), percent calories from fat, percent calories from carbohydrate, fibre intake, and total energy intake. NCEP/ATP III criteria. Odds ratios (95% CIs) across quintiles: 1.00 (reference); 0.84 (0.58, 1.23); 0.76 (0.54, 1.07); 0.62 (0.40, 0.98); 0.56 (0.34, 0.92).
P for linear trend = 0.029
Bo et al., 2006, Italy [27] 1653/381 45–64 47.2 Semi-quantitative food frequency questionnaire assessed average frequency of and portion intake of 148 foods consumed during 12months before examination Tertiles, mg/day: Male:
<269.1; 269.1–337.4; >337.4.
Female:
<278.1; 278.1–338.6; >338.6.		 Age, gender, BMI, smoking status, alcohol intake, level of physical activity, dietary intake of total calories, total % of fat and dietary intake of fibre. NCEP/ATP III criteria. Computed odds ratio* (95% CI) for tertile 3 as compared with tertile 1: 0.97 (0.59, 1.61).
P for trend = 0.07
Song et al., 2005, USA[30] 9,887 / 2,413 ≥45 0 Semi-quantitative food frequency questionnaire was used to assess the amount of magnesium intake by asking participants how often on average they had of a commonly used portion size during previous year Quintiles, mg/day: <277; 277–309; 309–341; 341–383; >383. Age, smoking, total calories, alcohol, multivitamin use, parental history of myocardial infarction before age 60 years, total fat intake, cholesterol, folate and glycaemic load. NCEP/ATP III criteria. Odds ratios (95% CIs) across quintiles: 1.00 (reference); 0.91 (0.78,1.06); 0.84 (0.72, 0.99); 0.81 (0.68, 0.96); 0.73 (0.60, 0.88).
P for linear trend = 0.0008
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IDF, International Diabetes Federation; NCEP/ATP, National Cholesterol Education Program/Adult Treatment Panel; NHANES, National Health and Nutrition Examination Survey; SFA: saturated fatty acid.

*

In Bo et al. (2006), the reference was changed to the lowest magnesium intake group and odds ratio was re-calculated for the highest magnesium intake group.

In five of the six studies included in the meta-analysis, both men and women were included, while in one study only women were included. The age of the participants in these studies was ≥ 18 years. Two studies used a semi-quantitative food frequency questionnaire, three studies used 24-h diet recalls and one used 3-day food records. One study used interview and the US Department of Agriculture Food and Nutrition Database to code food for magnesium intake, and another study used interview and the Taiwan Nutritional Database and E-Kitchen nutritional analysis software (Nutritional Chamberlain Line, Professional Edition, version 2001/ 2003, E-Kitchen Inc, Taichung, Taiwan) to analyse magnesium intake. In the original studies, participants were categorized into tertiles, quartiles or quintiles based on the distributions of dietary magnesium intake.

In the six cross-sectional studies included in the meta-analysis, the average (median or mean) dietary magnesium intake ranged from 117 to 423 mg/day. In all six studies, metabolic syndrome was defined using the National Cholesterol Education Program/Adult Treatment Panel III criteria. Metabolic syndrome was diagnosed if a participant met the diagnostic criteria for at least three of the five components of metabolic syndrome [35]. In almost all studies, age, gender, physical activity, total energy intake, carbohydrate intake, smoking status, alcohol intake and dietary fibre intake were adjusted for in the final model as potential confounders, because those variables are associated with both magnesium intake and risk of metabolic syndrome. Some of the studies adjusted for additional covariates including race/ethnicity, education and family history of diabetes.

Magnesium intake and risk of metabolic syndrome: highest vs lowest

As shown in Fig. 2, for the five cross-sectional studies [31,32,34] that reported risk of having metabolic syndrome according to magnesium intake categories, the pooled estimate from the meta-analysis indicated an inverse association between dietary magnesium intake and the prevalence of metabolic syndrome. The odds ratio (95% CI) was 0.69 (0.59, 0.81) comparing the highest with the lowest groups of dietary magnesium intake. There was no significant heterogeneity among the studies (I2=43.5%; P=0.13) and there was no evidence of publication bias (Egger’s test; P =0.38).

FIGURE 2.

FIGURE 2

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Multivariable adjusted odds ratios (95% CI) of having prevalent metabolic syndrome in participants with the highest level of dietary magnesium intake compared with those with the lowest. The overall estimate is from fixed-effects models. The dots indicate the adjusted odds ratios. The size of the shaded square is proportional to the weight of each study. Horizontal lines represent 95% CIs. The diamond markers indicate the pooled odds ratios. OR, odds ratio.

Magnesium intake and risk of metabolic syndrome: dose–response relationship analysis

Five studies [27,30–33], comprising 24 263 participants, reported the odds ratios (95% CI) of having metabolic syndrome for every 100-mg/day increment in dietary magnesium intake or such information could be derived from the published data. The pooled odds ratio (95% CI) was 0.83 (0.77, 0.89). No significant heterogeneity among the studies was found (I2=0.0%, P =0.45). No evidence indicated publication bias (Egger’s test; P =0.65).

Discussion

The cumulative evidence from the present meta-analysis indicates that dietary magnesium intake and the prevalence of metabolic syndrome are inversely associated. Metabolic syndrome is less prevalent in participants with a higher level of dietary magnesium intake. Results from this study support the hypothesis that a low level of dietary magnesium intake is a risk factor for metabolic syndrome.

The inverse association found in the present study is supported by the findings from a randomized controlled trial [22], a prospective cohort study [20] and a case–control study [26]. One cross-sectional study [29], which was not eligible for the present meta-analysis, also reported an inverse association between dietary magnesium and risk of metabolic syndrome on Z-score. The present findings are not consistent, however, with results from another case–control study [24], which reported metabolic syndrome was more prevalent in participants with high dietary magnesium intake, and a prospective cohort study, which found no significant difference in the risk of having prevalent metabolic syndrome between the highest and the lowest dietary magnesium intake groups [14].

A possible explanation for the inconsistent results is that metabolic syndrome has multiple dietary and non-dietary risk factors, including high fructose diets, high carbohydrate diets [15,36], high saturated fat intake [37] or a high percentage of total dietary fat intake [38], and physical inactivity [36]. Although the primary studies adjusted for some potential confounding variables, the covariates varied across studies; thus, residual confounding or confounding from unknown or unmeasured factors cannot be completely excluded. Also, the inconsistent results may be explained by the different sample sizes of the original studies. For example, Huang et al. [34] reported a nonsignificant inverse association, which may reflect the fact that the sample size in that study was relatively small. In addition, the variability in the characteristics of the study population might partially explain the inconsistent findings of the original studies, although the test for heterogeneity was not significant. For example, the study by Huang et al. [34] was conducted among elderly patients with Type 2 diabetes who were likely to have higher prevalence of metabolic syndrome. Nevertheless, in the sensitivity analysis, excluding one study each time did not substantially change the overall association, the pooled odds ratios (95% CIs) varied from 0.61 (0.45,0.82) by excluding the study by Song et al. [30] to 0.72 (0.61, 0.86) by excluding the study by Mckeown et al. [32].

One of the strengths of the present study is that the included studies were found to have insignificant heterogeneity, showing that the evidence of a pooled association between dietary magnesium and metabolic syndrome is robust. In addition, the relatively large sample size obtained from the various study populations included in the meta-analysis strengthens the evidence generated from it. The present meta-analysis is based on cross-sectional studies, and therefore does not warrant a causal inference, but the data included in it were the first of their kind and highlight a need for future studies to establish the causal link and to further understand the dose–response relationship between dietary magnesium intake and risk of metabolic syndrome. The study also shares the strength of the original studies in that potential confounding variables were adjusted for, and in that the present study used the fully adjusted model of the original studies.

The main limitation of the present study is that the meta-analysis is only based on cross-sectional studies. As dietary intake that relied on participant recall was used in the assessment of dietary magnesium intake during the original data collection, recall bias in the original studies, although not high, could not be excluded. Another limitation is that dietary measurement errors may have ocurred, although errors are likely to be non-differential and might somewhat attenuate the observed association.

Dietary magnesium acts through several mechanisms to prevent the cluster of health disorders that arises as a consequence of metabolic syndrome. There are a number of suggested mechanisms. The first is magnesium effects on glucose metabolism. Intracellular magnesium is reported to be functionally related to glucose metabolism by promoting the autophosphorylation of the β-subunit of insulin receptor by tyrosine-kinase switching on the receptor, which is important for insulin sensitivity and Type 2 diabetes [39]. Intracellular magnesium can also promote the translocation of glucose transporter protein (GLUT4) to the cell membrane for glucose uptake in the cell. Extracellular magnesium is also reported to increase the affinity of insulin binding to its receptor [40]. Animal studies support this explanation and have shown that magnesium deficiency has a deleterious effect on glucose metabolism as a result of impairment of both insulin secretion and action, thus predisposing to Type 2 diabetes [40–42]. Deficiency of intracellular and extracellular magnesium therefore impairs intracellular signalling and may induce insulin resistance. A second possible mechanism is magnesium effects on fat metabolism. Magnesium is a known cofactor of lipoprotein lipase, which promotes chylomicron clearance: both lipolysis and hepatic uptake of lipids. One study has reported that magnesium supplementation reduced and delayed postprandial increase in serum and chylomicron triacylglycerol [43,44]. Reduced activity of lipoprotein lipase attributable to magnesium deficiency causes hyperlipidaemia, which predisposes to diabetes and cardiovascular disease [45,46]. A third mechanism is magnesium effects on inflammatory mediators and proatherogenic changes. Studies have documented that magnesium prevents chronic low-grade inflammation, a well-established intermediate pathogenic state for metabolic syndrome and its consequences (cardiac disease, hypertension and Type 2 diabetes), by preventing the activation of inflammatory mediators and proatherogenic changes [18]. A fourth mechanism is magnesium effects as a cofactor in adenosine triphosphate (ATP)-transfer reactions and regulating enzymes of glycolysis. Several studies have documented magnesium as an important cofactor in all ATP-transfer reactions and as a regulator of the rate-limiting enzymes of glycolysis. A fifth possible mechanism is magnesium effects on smooth muscle activity through regulation of Ca2+ion transport. This also modulates the activity of many membrane and intracellular ion transport pump mechanisms, which maintain critical intracellular levels of cytosolic free calcium and sodium. The role of calcium in the contraction and relaxation of smooth muscles depends on intracellular magnesium steady activity. Magnesium ions actively promote muscle relaxation, offset calcium-related excitation–contraction coupling, and decrease cellular responsiveness to depolarizing stimuli by stimulating Ca2+-dependent K+ channels, which serve to offset the potential depolarizing influence of cellular calcium accumulation; therefore, calcium-induced contraction of vascular smooth muscles is sensitive to changes in magnesium concentration [47–49]. This mechanism may explain the hypertension in metabolic syndrome observed in populations with magnesium deficiency. Further studies are warranted to better understand the mechanisms, for example, if calcium levels modify the association between magnesium and metabolic syndrome.

In conclusion, the findings from the present meta-analysis provide evidence that dietary magnesium intake is inversely associated with the prevalence of metabolic syndrome. Further studies, especially well-designed longitudinal cohort studies and randomized placebo-controlled trials, are warranted to provide stronger evidence and establish causal inference.

Supplementary Material

supplemental table

FIGURE 3.

FIGURE 3

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Multivariable adjusted odds ratios (95% CI) of having metabolic syndrome for every 100-mg/day dietary magnesium intake increment. The overall estimate is from a fixed-effects model. Dots indicate the adjusted odds ratios. The size of the shaded square is proportional to the weight of each study. Horizontal lines represent 95% CIs. Diamond markers indicate the pooled odds ratios. OR, odds ratio.

What’s new?

  • This is a meta-analysis of original studies on the association of dietary magnesium intake and risk of metabolic syndrome.

  • The results of the meta-analysis could inform programmes focusing on the prevention of metabolic syndrome and its complications, including cardiovascular diseases.

Acknowledgments

Funding sources

This study was partially supported by National Institutes of Health grants (R01HL081572 and R01ES021735).

Footnotes

Competing interests

None declared.

Supporting information

Additional Supporting Information may be found in the online version of this article:

References

  • 1.Ninomiya JK, L’Italien G, Criqui MH, Whyte JL, Gamst A, Chen RS. Association of the metabolic syndrome with history of myocardial infarction and stroke in the Third National Health and Nutrition Examination Survey. Circulation. 2004;109:42–46. doi: 10.1161/01.CIR.0000108926.04022.0C. [DOI] [PubMed] [Google Scholar]
  • 2.Chien KL, Hsu HC, Sung FC, Su TC, Chen MF, Lee YT. Metabolic syndrome as a risk factor for coronary heart disease and stroke: An 11-year prospective cohort in Taiwan community. Atherosclerosis. 2007;194:214–221. doi: 10.1016/j.atherosclerosis.2006.07.033. [DOI] [PubMed] [Google Scholar]
  • 3.Boucher BJ. Is vitamin D status relevant to metabolic syndrome? Dermato-Endocrinology. 2012;4:212–224. doi: 10.4161/derm.20012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Andersen CJ, Fernandez ML. Dietary strategies to reduce metabolic syndrome. Rev Endocr Metab Disord. 2013;14:241–254. doi: 10.1007/s11154-013-9251-y. [DOI] [PubMed] [Google Scholar]
  • 5.Volek JS, Feinman RD. Carbohydrate restriction improves the features of Metabolic Syndrome. Metabolic Syndrome may be defined by the response to carbohydrate restriction. Nutr Metab. 2005;2:31. doi: 10.1186/1743-7075-2-31. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Volek JS, Phinney SD, Forsythe CE, Quann EE, Wood RJ, Puglisi MJ, et al. Carbohydrate restriction has a more favorable impact on the metabolic syndrome than a low fat diet. Lipids. 2009;44:297–309. doi: 10.1007/s11745-008-3274-2. [DOI] [PubMed] [Google Scholar]
  • 7.Feldeisen SE, Tucker KL. Nutritional strategies in the prevention and treatment of metabolic syndrome. Appl Physiol Nutr Metab. 2007;32:46–60. doi: 10.1139/h06-101. [DOI] [PubMed] [Google Scholar]
  • 8.Joung H, Hong S, Song Y, Ahn BC, Park MJ. Dietary patterns and metabolic syndrome risk factors among adolescents. Kor J Pediatr. 2012;55:128–135. doi: 10.3345/kjp.2012.55.4.128. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.de Oliveira EP, McLellan KC, Vaz de Arruda Silveira L, Burini RC. Dietary factors associated with metabolic syndrome in Brazilian adults. Nutr J. 2012;11:13. doi: 10.1186/1475-2891-11-13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Gillingham LG, Harris-Janz S, Jones PJ. Dietary monounsaturated fatty acids are protective against metabolic syndrome and cardiovascular disease risk factors. Lipids. 2011;46:209–228. doi: 10.1007/s11745-010-3524-y. [DOI] [PubMed] [Google Scholar]
  • 11.Deshmukh-Taskar PR, O’Neil CE, Nicklas TA, Yang SJ, Liu Y, Gustat J, et al. Dietary patterns associated with metabolic syndrome, sociodemographic and lifestyle factors in young adults: the Bogalusa Heart Study. Pub Health Nutr. 2009;12:2493–2503. doi: 10.1017/S1368980009991261. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Leite ML, Nicolosi A. Dietary patterns and metabolic syndrome factors in a non-diabetic Italian population. Pub Health Nutr. 2009;12:1494–503. doi: 10.1017/S1368980008004539. [DOI] [PubMed] [Google Scholar]
  • 13.Steemburgo T, Dall’Alba V, Gross JL, Azevedo MJ. Fatores dieteticos e sindrome metabolica [Dietary factors and metabolic syndrome] Arq Bras Endocrinol Metabol. 2007;51 :1425–1433. doi: 10.1590/s0004-27302007000900004. [DOI] [PubMed] [Google Scholar]
  • 14.Noori N, Nafar M, Poorrezagholi F, Ahmadpoor P, Samadian F, Firouzan A, et al. Dietary intakes of fiber and magnesium and incidence of metabolic syndrome in first year after renal transplantation. J Ren Nutr. 2010;20:101–111. doi: 10.1053/j.jrn.2009.06.001. [DOI] [PubMed] [Google Scholar]
  • 15.Wannamethee SG, Shaper AG, Whincup PH. Modifiable lifestyle factors and the metabolic syndrome in older men: Effects of lifestyle changes. J Am Geriatr Soc. 2006;54:1909–1914. doi: 10.1111/j.1532-5415.2006.00974.x. [DOI] [PubMed] [Google Scholar]
  • 16.Li XT, Wei DY, He HJ, Zhang JH, Wang CX, Ma MJ, et al. Association of the adiponectin gene (ADIPOQ) +45 T > G polymorphism with the metabolic syndrome among Han Chinese in Sichuan province of China. Asia Pac J Clin Nutr. 2012;21:296–301. [PubMed] [Google Scholar]
  • 17.Paolisso G, Sgambato S, Gambardella A, Pizza G, Tesauro P, Varricchio M, et al. Daily magnesium supplements improve glucose handling in elderly subjects. Am J Clin Nutr. 1992;55:1161–1167. doi: 10.1093/ajcn/55.6.1161. [DOI] [PubMed] [Google Scholar]
  • 18.Liu S, Chacko S. Dietary Mg Intake and Biomarkers of Inflammation and Endothelial Dysfunction. In: Watson RR, Preedy VR, Zibadi S, editors. Magnesium in Human Health and Disease. New York: Humana Press; 2013. pp. 35–50. [Google Scholar]
  • 19.Guerrero-Romero F, Tamez-Perez HE, Gonzalez-Gonzalez G, Salinas-Martinez AM, Montes-Villarreal J, Trevino-Ortiz JH, et al. Oral magnesium supplementation improves insulin sensitivity in non-diabetic subjects with insulin resistance. A double-blind placebo-controlled randomized trial. Diabetes Metab. 2004;30:253–258. doi: 10.1016/s1262-3636(07)70116-7. [DOI] [PubMed] [Google Scholar]
  • 20.He K, Liu K, Daviglus ML, Morris SJ, Loria CM, Van Horn L, et al. Magnesium Intake and Incidence of Metabolic Syndrome Among Young Adults. Circulation. 2006;113:1675–1682. doi: 10.1161/CIRCULATIONAHA.105.588327. [DOI] [PubMed] [Google Scholar]
  • 21.Hata A, Doi Y, Ninomiya T, Mukai N, Hirakawa Y, Hata J, et al. Magnesium intake decreases Type 2 diabetes risk through the improvement of insulin resistance and inflammation: the Hisayama Study. Diabet Med. 2013;30:1487–1494. doi: 10.1111/dme.12250. [DOI] [PubMed] [Google Scholar]
  • 22.Mooren FC, Kruger K, Volker K, Golf SW, Wadepuhl M, Kraus A. Oral magnesium supplementation reduces insulin resistance in non-diabetic subjects - a double-blind, placebo-controlled, randomized trial. Diabetes Obes Metab. 2011;13:281–284. doi: 10.1111/j.1463-1326.2010.01332.x. [DOI] [PubMed] [Google Scholar]
  • 23.Guerrero-Romero F, Rodriguez-Moran M. The effect of lowering blood pressure by magnesium supplementation in diabetic hypertensive adults with low serum magnesium levels: a randomized, double-blind, placebo-controlled clinical trial. J Hum Hypertens. 2009;23:245–251. doi: 10.1038/jhh.2008.129. [DOI] [PubMed] [Google Scholar]
  • 24.Yu Y, Cai Z, Zheng J, Chen J, Zhang X, Huang XF, et al. Serum levels of polyunsaturated fatty acids are low in Chinese men with metabolic syndrome, whereas serum levels of saturated fatty acids, zinc, and magnesium are high. Nutr Res. 2012;32:71–77. doi: 10.1016/j.nutres.2011.12.004. [DOI] [PubMed] [Google Scholar]
  • 25.Guerrero-Romero F, Rodriguez-Moran M. Low serum magnesium levels and metabolic syndrome. Acta Diabetol. 2002;39:209–213. doi: 10.1007/s005920200036. [DOI] [PubMed] [Google Scholar]
  • 26.Guerrero-Romero F, Rodriguez-Moran M. Hypomagnesemia, oxidative stress, inflammation, and metabolic syndrome. Diabetes Metabol Res Rev. 2006;22:471–476. doi: 10.1002/dmrr.644. [DOI] [PubMed] [Google Scholar]
  • 27.Bo S, Durazzo M, Guidi S, Carello M, Sacerdote C, Silli B, et al. Dietary magnesium and fiber intakes and inflammatory and metabolic indicators in middle-aged subjects from a population-based cohort. Am J Clin Nutr. 2006;84:1062–1069. doi: 10.1093/ajcn/84.5.1062. [DOI] [PubMed] [Google Scholar]
  • 28.Greenland S, Longnecker MP. Methods for Trend Estimation from Summarized Dose-Response Data, with Applications to Meta-Analysis. Am J Epidemiol. 1992;135:1301–1309. doi: 10.1093/oxfordjournals.aje.a116237. [DOI] [PubMed] [Google Scholar]
  • 29.Mirmiran P, Shab-Bidar S, Hosseini-Esfahani F, Asghari G, Hosseinpour-Niazi S, Azizi F. Magnesium intake and prevalence of metabolic syndrome in adults: Tehran Lipid and Glucose Study. Pub Health Nutr. 2012;15:693–701. doi: 10.1017/S1368980011002941. [DOI] [PubMed] [Google Scholar]
  • 30.Song Y, Ridker PM, Manson JE, Cook NR, Buring JE, Liu S. Magnesium Intake, C-Reactive Protein, and the Prevalence of Metabolic Syndrome in Middle-Aged and Older U.S. Women. Diabetes Care. 2005;28:1438–1444. doi: 10.2337/diacare.28.6.1438. [DOI] [PubMed] [Google Scholar]
  • 31.Ford ES, Li C, McGuire LC, Mokdad AH, Liu S. Intake of dietary magnesium and the prevalence of the metabolic syndrome among U.S. adults. Obesity. 2007;15:1139–1146. doi: 10.1038/oby.2007.628. [DOI] [PubMed] [Google Scholar]
  • 32.McKeown NM, Jacques PF, Zhang XL, Juan W, Sahyoun NR. Dietary magnesium intake is related to metabolic syndrome in older Americans. Eur J Nutr. 2008;47:210–216. doi: 10.1007/s00394-008-0715-x. [DOI] [PubMed] [Google Scholar]
  • 33.Beydoun MA, Gary TL, Caballero BH, Lawrence RS, Cheskin LJ, Wang Y. Ethnic differences in dairy and related nutrient consumption among US adults and their association with obesity, central obesity, and the metabolic syndrome. Am J Clin Nutr. 2008;87:1914–1925. doi: 10.1093/ajcn/87.6.1914. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Huang JH, Lu YF, Cheng FC, Lee JN, Tsai LC. Correlation of magnesium intake with metabolic parameters, depression and physical activity in elderly type 2 diabetes patients: a cross-sectional study. Nutr J. 2012;11:41. doi: 10.1186/1475-2891-11-41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Expert Panel on Detection E, Treatment of High Blood Cholesterol in A. Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III) JAMA. 2001;285:2486–2497. doi: 10.1001/jama.285.19.2486. [DOI] [PubMed] [Google Scholar]
  • 36.Zhu S, St-Onge MP, Heshka S, Heymsfield SB. Lifestyle behaviors associated with lower risk of having the metabolic syndrome. Metabolism. 2004;53:1503–1511. doi: 10.1016/j.metabol.2004.04.017. [DOI] [PubMed] [Google Scholar]
  • 37.Riccardi G, Giacco R, Rivellese AA. Dietary fat, insulin sensitivity and the metabolic syndrome. Clin Nutr. 2004;23:447–456. doi: 10.1016/j.clnu.2004.02.006. [DOI] [PubMed] [Google Scholar]
  • 38.Riccardi G, Rivellese AA. Dietary treatment of the metabolic syndrome–the optimal diet. Br J Nutr. 2000;83 (Suppl 1):S143–148. doi: 10.1017/s0007114500001082. [DOI] [PubMed] [Google Scholar]
  • 39.Cahill F, Shahidi M, Shea J, Wadden D, Gulliver W, Randell E, et al. High dietary magnesium intake is associated with low insulin resistance in the Newfoundland population. PloS One. 2013;8:e58278. doi: 10.1371/journal.pone.0058278. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Eckel J, Reinauer H. Effect of EDTA on insulin binding and insulin action in isolated cardiocytes from adult rat. Evidence for a functional role of low-affinity insulin receptors. Diabetes. 1984;33:214–218. doi: 10.2337/diab.33.3.214. [DOI] [PubMed] [Google Scholar]
  • 41.Suárez A, Pulido N, Casla A, Casanova B, Arrieta FJ, Rovira A. Impaired tyrosine-kinase activity of muscle insulin receptors from hypomagnesaemic rats. Diabetologia. 1995;38:1262–1270. doi: 10.1007/BF00401757. [DOI] [PubMed] [Google Scholar]
  • 42.Kandeel FR, Balon E, Scott S, Nadler JL. Magnesium deficiency and glucose metabolism in rat adipocytes. Metabolism. 1996;45:838–843. doi: 10.1016/s0026-0495(96)90156-0. [DOI] [PubMed] [Google Scholar]
  • 43.Montague C, Farooqi I, Whitehead J, Soos M, Rau H, Wareham N, et al. Congenital leptin deficiency is associated with severe early-onset obesity in humans. Nature. 1997;387:903–908. doi: 10.1038/43185. [DOI] [PubMed] [Google Scholar]
  • 44.Kishimoto Y, Tani M, Uto-Kondo H, Saita E, Iizuka M, Sone H, et al. Effects of magnesium on postprandial serum lipid responses in healthy human subjects. Br J Nutr. 2010;103:469–472. doi: 10.1017/S0007114509992716. [DOI] [PubMed] [Google Scholar]
  • 45.Syvanne M, Taskinen MR. Lipids and lipoproteins as coronary risk factors in non-insulin-dependent diabetes mellitus. Lancet. 1997;350(Suppl 1):SI20–3. doi: 10.1016/s0140-6736(97)90024-6. [DOI] [PubMed] [Google Scholar]
  • 46.Laakso M. Lipids and lipoproteins as risk factors for coronary heart disease in non-insulin-dependent diabetes mellitus. Ann Med. 1996;28:341–345. doi: 10.3109/07853899608999091. [DOI] [PubMed] [Google Scholar]
  • 47.Altura BM, Altura BT, Carella A, Turlapaty PD. Ca2+ coupling in vascular smooth muscle: Mg2+ and buffer effects on contractility and membrane Ca2+ movements. Can J Physiol Pharmacol. 1982;60:459–482. doi: 10.1139/y82-066. [DOI] [PubMed] [Google Scholar]
  • 48.Noguera MA, D’Ocon MP. Modulatory role of magnesium on the contractile response of rat aorta to several agonists in normal and calcium-free medium. J Pharm Pharmacol. 1993;45:697–700. doi: 10.1111/j.2042-7158.1993.tb07091.x. [DOI] [PubMed] [Google Scholar]
  • 49.D’Angelo EK, Singer HA, Rembold CM. Magnesium relaxes arterial smooth muscle by decreasing intracellular Ca2+ without changing intracellular Mg2+ J Clin Invest. 1992;89:1988–1994. doi: 10.1172/JCI115807. [DOI] [PMC free article] [PubMed] [Google Scholar]

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supplemental table
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