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Journal of the American College of Nutrition, Vol. 25, No. 6, 486-492 (2006)
Published by the American College of Nutrition

Magnesium Intake Is Related to Improved Insulin Homeostasis in the Framingham Offspring Cohort

Marcella E. Rumawas, MD, MS, Nicola M. McKeown, PhD, Gail Rogers, MA, James B. Meigs, MD, MPH, Peter W.F. Wilson, MD, BS and Paul F. Jacques, ScD

Nutritional Epidemiology Program, Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University
General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts
General Clinical Research Center, Medical University of South Carolina, Charleston, South Carolina

Address correspondence to: Nicola M. McKeown, PhD, Nutritional Epidemiology Program, JM USDA HNRC at Tufts University, 711 Washington Street, Boston, MA, 02111-1524. E-mail: nicola.mckeown{at}tufts.edu


   ABSTRACT
TOP
 FOOTNOTES
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 CONCLUSION
 REFERENCES
 
Objective: Higher dietary intake of magnesium may protect against development of type 2 diabetes. The aim of this study was to examine the association between dietary magnesium intake and metabolic risk factors for diabetes.

Methods: We examined cross-sectional associations between magnesium intake and fasting glucose and insulin, 2-hour post-challenge plasma glucose and insulin, and insulin resistance assessed by the homeostasis model (HOMA-IR) in 1223 men and 1485 women without diabetes from the Framingham Offspring cohort. Magnesium intake was assessed by a food frequency questionnaire and magnesium intake was categorized into quintile categories. Geometric mean insulin, glucose, 2-hour post challenge plasma glucose and insulin concentrations and HOMA-IR were estimated across quintile categories of magnesium intake using Generalized Linear Models.

Results: After adjustment for potential confounding factors, magnesium intake was inversely associated with fasting insulin (mean: 29.9 vs 26.7 µU/mL in the lowest vs highest quintiles of magnesium intake; P trend <0.001), post-glucose challenge plasma insulin (86.4 vs 72 µU/mL; P trend <0.001), and HOMA-IR (7.0 vs 6.2; P trend <0.001). No significant association was found between magnesium intake and fasting glucose or 2-hour post challenge glucose.

Conclusions: Improved insulin sensitivity may be one mechanism by which higher dietary magnesium intake may reduce the risk of developing type 2 DM.

Key words: observational, diet, magnesium, insulin, glucose, diabetes


   INTRODUCTION
TOP
 FOOTNOTES
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 CONCLUSION
 REFERENCES
 
The number of Americans with type 2 Diabetes Mellitus (DM) is rapidly increasing [1]. In the year 2000, approximately 17 million Americans had diabetes and the prevalence of this disease is predicted to affect 30 million by the year 2030 [1,2]. Impaired insulin sensitivity is a key risk factor in the etiology of type 2 DM. Low magnesium status has been linked to reduced insulin sensitivity and increased risk of type 2 DM risk [3]. Magnesium, an intracellular metal cation that acts as a cofactor in several enzymatic reactions including glucose and insulin metabolism [4], may reduce tissue glucose uptake by interfering with insulin signaling pathways and by promoting peripheral insulin resistance by decreasing cellular glucose utilization [5].

Observational studies have demonstrated that low plasma magnesium concentrations are a common feature in individuals with metabolic syndrome [6] and type 2 DM [7,8], and experimental studies have shown improvements in insulin sensitivity and glucose control among type 2 diabetic patients receiving magnesium supplements [9,10]. Furthermore, dietary magnesium intake has been inversely associated with fasting insulin levels [11,12]. Magnesium is found in a wide range of foods including whole grains, green leafy vegetables, nuts, legumes, coffee and reduced-fat dairy products, which have been linked to type 2 DM in observational and intervention studies [13–16]. Yet magnesium intake appears to be inadequate in American men and women [17].

Although several observational studies have found that magnesium status is related to diabetes risk, few have examined the relationships between magnesium intake, insulin resistance and hyperglycemia. Therefore, we examined cross-sectional relationships between dietary magnesium intake and measures of glucose and insulin metabolism in middle-aged men and women from the Framingham Offspring Cohort.


   MATERIALS AND METHODS
TOP
 FOOTNOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 CONCLUSION
 REFERENCES
 
Study Population
The Framingham Offspring Study is a longitudinal community-based study of cardiovascular disease among the offspring of the original participants of the Framingham Heart Study Cohort and their spouses [18]. In 1971, 5135 participants were enrolled into the study and since then, the cohort has been examined every 3 to 4 years. Between 1991 and 1995 during the fifth examination cycle of the Framingham Offspring Study, 3799 participants underwent a standardized medical history and physical examination. Of these participants, 3418 participants had valid food frequency questionnaire (FFQ) data based on reported energy intakes >2.51 MJ/d (600 kcal) for men and women or <16.74 MJ/d (4000 kcal/d) for women and <17.57 (4200 kcal/d) for men, respectively, or fewer than 13 blank food items. Additional participants were excluded from these analyses if they had previously diagnosed diabetes based on use of insulin or oral hypoglycemic medication (n = 122), or if they were taking cholesterol-lowering medication (n = 229). Furthermore, we excluded participants with undiagnosed diabetes (n = 128) based on either a fasting blood glucose level (≥126 mg/dL) or an oral glucose tolerance test (2-hr post-challenge plasma glucose level ≥200 mg/dL) and those with missing information on fasting glucose or 2-hour post challenge glucose (n = 117). We also excluded participants with missing covariate information (n = 114), reducing the final sample to 2708 (1223 men and 1485 women). The Institutional Review Board for Human Research at Boston University and the Institutional Review Board at Tufts/New England Medical Center approved the protocol.

Dietary Intake
A 126-item food frequency questionnaire (FFQ) administered at the fifth examination cycle of the Framingham Offspring Study was used to estimate usual dietary intake during the previous year [19]. The FFQ was mailed to the participants before the examination, and the participants were asked to bring the completed questionnaire with them to their appointment. The FFQ consisted of a list of foods together with a standard serving size and a selection of 9 frequency categories ranging from never or less than 1 serving per month to more than six serving per day. Nutrient intakes were calculated by multiplying the frequency of consumption of each unit of food from the FFQ by the nutrient content of the specified portion. Although questions about vitamin and mineral use were also included in the FFQ, we did not separate the contribution of magnesium from supplements. Total magnesium intake represents the intake from diet and multivitamin/mineral and magnesium supplements. Magnesium from supplements contributed only 2.7% to total magnesium intake. The relative validity of the FFQ for both nutrients and foods was examined previously in several populations [19–21]. Correlation coefficients between FFQ and multiple diet records for magnesium intake have been reported to be 0.67–0.71 [19].

Outcome Measurements
As part of the 5th offspring cohort examination, blood samples were obtained from subjects who had fasted for at least 10 h and stored at –70°C. Fasting plasma glucose was measured in fresh specimens with a hexokinase reagent kit while fasting plasma insulin was determined using the Coat-A-Count 125I-radioimmunoassay (Diagnostic Products, Los Angeles, CA). Among patients without diagnosed diabetes, a 75-g oral glucose tolerance test (OGTT) was administered according to the World Health Organization (WHO) standards [22] and 2-hour post challenge glucose and insulin concentrations were measured. The homeostasis model assessment for insulin resistance [HOMA-IR = fasting plasma insulin (µU/ml) x fasting plasma glucose (mmol/L)/22.5] was used to estimate insulin sensitivity [23].

Covariates
Height and weight were measured with the subject standing. Body mass index (BMI) was calculated as weight (kg)/height (m)2. Smoking was categorized based on the number of cigarettes smoked per day (none, 1–15, 16–25, >25). Diagnosis of hypertension was based on the two measures of of blood pressure (elevated systolic blood pressure ≥160 or dystolic blood pressure ≥95) or taking blood pressure-lowering treatment. Other covariates included age (yrs), sex, total energy intake (kcal/day), physical activity score [24] alcohol intake (g/day), dietary glycemic index, dietary fiber (g/day), total fat (g/day) and cholesterol (mg/day) intakes, whole grain (servings/week) and coffee intake (servings/week).

Statistical Methods
Statistical analyses were conducted using SAS statistical software (version 8; SAS Institute, Cary, NC). Dependent variables were fasting glucose and insulin, 2-hour post challenge glucose and insulin and HOMA-IR. Because all of these dependent variables were positively skewed, analyses were performed on the natural logarithmic transformed data. To express these variables on their original scale, geometric means and their 95% confidence intervals (CI) were calculated by taking the exponent of adjusted least-squares means and their corresponding confidence intervals.

Characteristics of the participants, adjusted for age and sex, are presented across quintile categories of magnesium intake. Nutrient intake variables were also adjusted for total energy intake. We examined the relationship between magnesium intake and fasting glucose, fasting plasma insulin, 2-h glucose, 2-h plasma insulin and HOMA-IR levels using SAS PROC GLM. Multivariate models included magnesium intake as quintile categories and age, BMI, sex, hypertension, smoking dose, alcohol intake, physical activity score and total energy intake as covariates. Additional models also adjusted for dietary glycemic index, dietary fiber, total fat, cholesterol, coffee and whole grain intake. Tests for trend across categories of magnesium intake were based on linear regression by assigning the median magnesium intake for each quintile category to each individual in that category and then treating it as a continuous variable.


   RESULTS
TOP
 FOOTNOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
CONCLUSION
 REFERENCES
 
The median intake of magnesium from both foods and supplements was 298 mg/d for men and 281 mg/d for women. The contribution of magnesium from multivitamin supplements to total magnesium intake was only 2.7%. In this sample, the main food sources that contributed to dietary magnesium intake were coffee (7.7%), skim milk (6.7%), cold cereal (4.1%), dark bread (3.4%), banana (3.2%), chicken (without skin) (2.9%), beer (2.9%) and orange juice (2.7%).

Participants in the highest quintile category of magnesium were more likely to exercise and take multivitamin or magnesium supplements, less likely to smoke cigarettes, and had higher total energy, alcohol, carbohydrate, protein, dietary fiber and whole grain intake and lower intakes of fat, cholesterol and dietary glycemic index than those in the lowest magnesium intake quintile category (Table 1).


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  		Table 1. Characteristics of Subjects in Framingham Offspring Cohort across Quintile Categories of Magnesium Intake*

 
After adjustment for potential confounding factors, magnesium intake was significantly inversely associated with fasting plasma insulin concentrations (mean: 29.9 vs 26.7 µU/mL in the lowest vs highest quintile categories of magnesium intake; P trend <0.001), post-glucose challenge plasma insulin values (86.4 vs 72 µU/mL; P trend <0.001) and HOMA-IR (7.0 vs 6.2; P trend <0.001) (Table 2). Additional individual and simultaneous adjustment for dietary glycemic index, dietary fiber, whole grain intake, coffee, total fat, and cholesterol did not alter these associations. Magnesium intake was inversely associated with 2-hour post challenge glucose (104.4 vs 100.7 mg/dL; P trend <0.04), although this association did not remain significant after adjustment for other dietary factors including dietary glycemic index (102.9 vs 102 mg/dL; P trend 0.41), total fat (104.2 vs 101 mg/dL; P trend 0.07), dietary fiber (104.5 vs 100.7 mg/dL; P trend 0.06) and coffee intake (103.3 vs 101.3 mg/dL; P trend 0.17). No significant relationship was found between magnesium intake and fasting glucose concentrations.


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  		Table 2. Indicators of Glucose and Insulin Homeostasis by Quintile Categories of Magnesium Intake

 
We found that the associations between magnesium intake and insulin and glucose measures were unaffected by excluding participants who reported that they took either a magnesium supplement (n = 13), a multivitamin/mineral supplements (n = 763) or both magnesium supplement and multivitamin/mineral supplements (n = 38) (data not shown). We also examined the potential effect modification with sex, BMI (< or ≥25 kg/m2), calcium intake (continuous) or hypertension status, but none of these interactions were statistically significant.


   DISCUSSION
 
Our cross sectional findings suggest that magnesium intake is associated with measures of glucose and insulin homeostasis. In particular, a higher magnesium intake was significantly associated with lower fasting insulin and post-glucose challenge plasma insulin, and better insulin sensitivity as assessed by HOMA-IR, after adjustment for many potential risk factors for insulin resistance and type 2 DM.

Fasting plasma insulin reflects both target tissue insulin resistance and diminished insulin production and is a valid measure of insulin resistance [25] in both healthy [26] and type 2 diabetic subjects [27]. In a situation of normal glucose status, elevated fasting insulin levels are indicative of a worsening degree of insulin resistance and are predictive of diabetes risk [28]. Our findings that higher magnesium intake is associated with lower fasting plasma insulin concentrations in healthy individuals confirms findings from other observational studies [11,12,29]. The difference in fasting plasma insulin level between the highest and lowest quintiles of magnesium intake was approximately 3 µU/mL in our population, greater than that reported in the Nurses Health Study (1.7 µU/mL) [11] and Women Health Study (0.5 µU/mL) [12].

Based on a meta-analysis of 17 studies on insulin and CVD risk, the difference of 3.2 µU/mL in insulin concentrations would translate into a 6% greater risk of developing CVD [30]. A greater impact may be found with type 2 diabetes risk, based on one study [31], this difference in fasting insulin would translate into a 17% greater risk of developing type 2 DM. Song et al [12] reported that the association between magnesium intake and fasting insulin levels was significant in overweight women, but not in normal weight women. However, similar to the Nurses Health Study [11], we did not find a significant interaction between BMI and magnesium intake on insulin levels.

We also reported a cross sectional association between magnesium intake and post-glucose challenge plasma insulin, implying that less insulin is needed to dispose of glucose in those with higher magnesium intake. Clinical studies have suggested that post-glucose challenge plasma insulin is a more sensitive indicator of peripheral insulin resistance than fasting insulin [32, 33]. Humpries et al. [34] observed that post-glucose challenge plasma insulin was inversely related to magnesium intake (R = –0.25, p <0.02) in a small sample of non-diabetic men, but not in women. Our study is the first to our knowledge to observe an inverse association between magnesium intake and post-glucose challenge plasma insulin in a large population-based study.

Furthermore, we observed that magnesium intake was significantly associated with HOMA-IR, another predictor of insulin resistance used in population-based studies [35–37]. This finding is not unexpected given the high correlation between fasting insulin and HOMA-IR (R = 0.94, p <0.0001) in our non-diabetic sample. Taken together our data support the hypothesis that in the community higher levels of magnesium intake are associated with improved insulin sensitivity.

Fasting hyperglycemia arises as a consequence of hepatic insulin resistance, insufficient insulin secretion or increased hepatic production [38]. Some [9, 39], but not all studies [10, 40], have found that oral magnesium supplements appears to improve glycemic control and lower risk of type 2 DM [41]. However, consistent with a previous report from the Atherosclerosis Risk in Communities Study (ARIC) [42], our study did not find a significant relationship between magnesium intake and fasting glucose concentration. This is not unexpected given that our sample is a healthy group whose blood glucose levels are under tight homeostatic control. We did however find a significant inverse association between magnesium intake and 2-hour post challenge glucose, although the association was attenuated after adjustment for other aspects of diet including, total fat, dietary fiber, coffee and dietary glycemic index. Elevated post challenge glucose concentration is one of the earliest abnormalities of glucose homeostasis associated with type 2 diabetes [43] and is a more predictive of type 2 DM risk [44] and mortality [45] than fasting glucose. Further studies relating aspects of diet to fasting and post-challenge glucose concentrations, in different populations, is clearly needed.

Magnesium is a rich component of whole grains [46]. Observational studies have found that fasting and post-challenge insulin concentrations, as well as HOMA-IR, are lower among individuals reporting higher dietary fiber or whole grain intakes [47–49]. Furthermore, based on epidemiological evidence, it appears that magnesium, either alone or in combination with dietary fiber, may be the mediating nutrient in the relationships between whole grain intake, insulin sensitivity and diabetes risk [48–51]. We found that after controlling for dietary fiber, associations between magnesium intake and insulin were slightly attenuated but remained significant. Furthermore, the association between magnesium intake and insulin was independent of both dietary glycemic index and whole grains intakes. These results imply that the association between magnesium intake and insulin sensitivity was not a function of correlated higher complex carbohydrate intakes.

Although the underlying mechanisms in the relationship between magnesium and insulin sensitivity is not well understood, one proposed mechanism is that low intracellular Mg concentrations reduce the activity of tyrosine kinase at the insulin receptor level [5]. Consequently, this reduced activity impacts the insulin signaling cascade and ultimately reduces glucose uptake and utilization. Low magnesium status may not arise solely because of low magnesium intake but may be a consequence of imparied absorption of magnesium due to adverse effects of high-calcium diets [52]. However, it has been suggested that the ratio of dietary calcium to magnesium intake (Ca:Mg) would need to be greater than 5 to induce magnesium deficiency [53]. The percentage of the population with Ca:Mg ratio >5 in our sample was small (3%), therefore we would not expect, and did not observe, a significant interaction between calcium and magnesium intake on insulin homeostasis.

Interpretation of the findings from the present study is subject to some caveats. Although magnesium intake estimated from the FFQ is highly correlated with diet records (r = 0.67 –0.71) [19], this dietary assessment method is subject to reporting errors that may cause misclassification of subjects with respect to magnesium intake. However, such misclassification of intake would underestimate the associations between magnesium intake and insulin resistance. Furthermore, although the apparent protective association with total magnesium intake persisted after adjustment for lifestyle and dietary factors associated with a healthier lifestyle, we cannot rule out residual confounding. At the population level, HOMA-IR can be used as surrogate measure of insulin resistance to identify those individuals who are most insulin resistant. However, comparison between studies is limited because of a lack of standardization of insulin assays. Finally, the cross-sectional nature of this study prohibits establishing a causal relationship. Nonetheless, results from this study support the hypothesis that magnesium intake may be an important determinant of insulin resistance. Diets characterized by higher levels of magnesium intake may be our means to help prevent the development of type 2 diabetes. Further studies are required to examine the relationship between magnesium intake on measures of insulin sensitivity, particularly longitudinal studies and ideally, dietary intervention studies.


   CONCLUSION
TOP
 FOOTNOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 CONCLUSION
REFERENCES
 
We found that higher magnesium intake is associated with lower fasting insulin, 2-hour post-glucose challenge plasma insulin and HOMA-IR. This study supports the hypothesis that diets rich in magnesium intake may improve glucose and insulin homeostasis and therefore reduce the risk of type 2 DM.


   FOOTNOTES
TOP
 FOOTNOTES
ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 CONCLUSION
 REFERENCES
 
Supported in part by the USDA Agreement 58-1950-4-401, NIH/NHLBI Contract N01-HC-25195, ADA Career Development Award (J.B.M.) & AHA Scientist Development Award (N.M.M.).

The results were presented in the Experimental Biology and the XXXV International Congress of Physiological Science in San Diego CA, on April 5, 2005.

Received June 17, 2005. Accepted December 21, 2005.


   REFERENCES
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 FOOTNOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 CONCLUSION
 REFERENCES
 

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