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The Association between Magnesium Intake and Fasting Insulin Concentration in Healthy Middle-Aged Women

Department of Nutrition, Simmons College (T.T.F.), Harvard School of Public Health; Channing Laboratory
Department of Nutrition (T.T.F., W.W., F.H.), Harvard School of Public Health; Channing Laboratory
Department of Epidemiology (J.A.M., S.L., W.W.), Harvard School of Public Health; Channing Laboratory (J.A.M., W.W., F.H.)
Division of General Medicine (C.S.), Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
Division of Preventive Medicine (J.A.M., S.L.), Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts

Address reprint requests to: Teresa Fung, Sc.D., Department of Nutrition, Simmons College, 300 The Fenway, Boston, MA 02115. Email: fung{at}simmons.edu

	ABSTRACT

TOP FOOTNOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS CONCLUSION REFERENCES

 
Objective: We assessed the association between magnesium intake and fasting insulin levels in a large cohort of women.

Methods: Female nurses free of diabetes, cardiovascular diseases and cancer from the Nurses Health Study provided blood samples between 1989–1990. We selected a sub-sample of 219 women for this analysis. Magnesium intake was assessed by a food frequency questionnaire in 1990 and categorized into quartiles. Cross-sectional geometric means of fasting insulin concentrations by quartiles of magnesium intake were obtained with Generalized Linear Model and adjusted for several risk factors and lifestyle characteristics.

Results: After adjustment for age, body mass index (BMI), total energy, physical activity, hours per week spent sitting outside work, alcohol intake, smoking, and family history of diabetes, magnesium intake was inversely associated with fasting insulin concentration. The multivariate adjusted geometric mean for women in the lowest quartile of magnesium intake was 11.0 µU/mL and 9.3 µU/mL among those in the highest quartile of magnesium intake (p for trend = 0.04). The inverse association remained when we considered magnesium from only food sources.

Conclusion: Higher magnesium intake is associated with lower fasting insulin concentrations among women without diabetes. Because lower fasting insulin concentrations generally reflect greater insulin sensitivity, these findings provide a mechanism through which higher dietary magnesium intake may reduce the risk of developing type 2 diabetes mellitus.

Key words: insulin, magnesium, diet, women, epidemiology

	INTRODUCTION

TOP FOOTNOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS CONCLUSION REFERENCES

 
Individuals with diabetes tend to have lower plasma magnesium concentrations than those without diabetes [1–3]. Although this has been partly attributed to increased urinary loss [4] and reduced intake [5], lower magnesium concentrations may predispose individuals to type 2 diabetes due to its role in insulin action [6,7]. Studies on magnesium depletion in animals have shown a reduction of post insulin receptor action [8]. In addition, magnesium is a cofactor in several enzymes related to carbohydrate metabolism [9]. Prospective studies have shown an inverse association between serum or dietary magnesium and risk of type 2 diabetes [10,11]. Magnesium may influence diabetes development through effects on insulin sensitivity, which are reflected in fasting insulin concentrations, a marker of insulin resistance. An inverse association between plasma or erythrocyte magnesium concentrations and fasting insulin has been observed in both diabetic and non-diabetic middle-aged individuals in the Atherosclerosis Risk in Communities Study [3]. Physiological studies suggest that low magnesium intake may impair insulin sensitivity [12] and dietary magnesium supplementation may improve glucose utilization [13]. Few observational studies have investigated the association between magnesium intake and fasting insulin concentration exclusively in individuals without diabetes [14,15]; therefore, we conducted a cross-sectional analysis of magnesium intake and fasting insulin in a sample of healthy middle-aged women.

	MATERIALS AND METHODS

TOP FOOTNOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS CONCLUSION REFERENCES

 
Subjects
The women included in this analysis were a sub-sample of participants in the Nurses’ Health Study (NHS) of which details have been documented elsewhere [16]. Briefly, the NHS is a prospective cohort study of 121,700 women, 30–55 years of age at study inception in 1976, from 11 U.S. states, who responded to a mailed questionnaire about health and lifestyle. Since its inception, biennial questionnaires have been sent to update health and lifestyle characteristics. Dietary intake was assessed every two to four years. Follow-up rates were 95% of the potential person-years through 1994. Between 1989 and 1990, 32,826 women provided fasting blood samples.

The sub-sample in this analysis consisted of age-matched controls selected for a nested case-control study of fasting insulin concentrations and type 2 diabetes risk. These controls were free of diabetes, cardiovascular disease, stroke, and cancer prior to blood collection in 1989–1990 (N = 235). We excluded outliers of fasting insulin concentration, <3 µU/mL (N = 3) and >35 µU/mL (N = 2), as well as those without food intake information in 1990 (N = 11). The outliers were at least three standard deviations away from the geometric mean value. Because hemolysis may artificially elevate insulin concentrations through the release of an insulinase on red cell membrane [17], we excluded samples with more than mild hemolysis (N = 7). We included 212 samples for this analysis.

Assessment of Insulin Concentrations
Blood samples were collected between 1989 and 1990. Each willing participant was sent a blood collection kit containing instructions and needed supplies (blood tubes, tourniquet, gauze, band-aid, needles). The participants made arrangements for the blood to be drawn, placed in a cool pack, and then sent the sample back by overnight courier. The vast majority of samples arrived in our laboratory within 26 hours of being drawn. A frozen water bottle was used as the coolant during transport of the blood to the laboratory for processing. Upon arrival in the laboratory, the whole blood samples were centrifuged and aliquotted and stored at temperatures no higher than -130°C. Participants who returned a blood sample in the NHS were generally similar in lifestyle and dietary characteristics to those who did not return a blood sample. Insulin concentrations were measured by LINCO kit with an average intra-assay CV of 4.6%. Cross-reactivity with proinsulin was less than 0.2% for this assay.

Assessment of Magnesium Intake
Magnesium intake for this analysis was calculated from self-reported intake of 138 items, including water, in a semi-quantitative food frequency questionnaire (FFQ) administered in 1990. The questionnaire was developed for the Nurses’ Health Study and included foods most commonly consumed in the cohort. In addition, the questionnaire allowed for participants to write down foods that they consumed significantly but were omitted on the FFQ. Participants were to recall average food intake over the previous year. Standard portion sizes were given for each food item. Women were asked to choose from nine possible frequency responses, ranging from "never" to "more than six times a day" for each food. Macro- and micronutrient intakes were computed for the frequency and portion size of each food, and contributions from all foods were summed. Magnesium contents were obtained from the USDA, other published data, and food manufacturers [18]. Magnesium intake values were adjusted for total energy by the residual method [19]. Validation studies have shown acceptable correlation between dietary minerals assessed by FFQ and diet records [20]. A validation study of a similar FFQ in a cohort of male health professionals yielded a correlation coefficient of 0.66 for magnesium intake when compared with two weeks of food records [21]. Although this level of correlation is considered modest, it represented reasonable validity due to the differences in methodology in FFQ and food records. Validity of magnesium in NHS is not available, but we do not expect substantial difference from the male health professional.

Statistical Analysis
Magnesium intake was categorized into quartiles. We examined the association between magnesium intake and fasting insulin concentrations by calculating geometric means of insulin concentration for each quartile of magnesium intake. Insulin concentrations were log_e-transformed to improve normality, and adjusted geometric means were obtained with general linear models. We used Generalized Linear Model for multivariate analysis to adjust for age (5 categories), BMI (continuous), total energy intake (quintiles), physical activity (quintiles), weekly hours of sitting down outside of work (5 categories), alcohol intake (0g, 0.1–15g, 15.1–30g, >30g/day), smoking (never, past smoker, 1–14 cigarettes, 15+ cigarettes a day), and family history of diabetes. Physical activity information was obtained by self-report of 10 leisure-time physical activities. We calculated total weekly energy expenditure for each individual and expressed as Metabolic Equivalents (METs) [22]. The p-values for trend tests were obtained using the median intake of each quartile and model intake as a continuous variable. We also examined the association with magnesium from food sources only. In addition, we assessed the association between major food contributors of magnesium in the Nurses’ Health Study and fasting insulin concentrations. In a separate analysis, we excluded those with supplemental magnesium intake (including multi-vitamin preparation), leaving 123 women for analysis. Since overweight and obesity is a strong predictor of insulin resistance, we analyzed the data stratified by weight status, using BMI = 25 as a cut point to explore possible differential associations according to weight. Statistical analysis was conducted using SAS [23] and all p-values are two sided.

	RESULTS

TOP FOOTNOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS CONCLUSION REFERENCES

 
Characteristics of the 212 women in this sample in 1990 are shown in Table 1. Women with higher magnesium intake were less likely to be current smokers, but more likely to use multivitamin supplements. They tended to consume less fat, sugar, and alcohol, and to consume more carbohydrates, cereal fiber, and low-fat milk. Average intake of total magnesium unadjusted for energy intake was 347 mg/day (sd = 151mg), and average magnesium intake from foods was 332 mg/day (sd = 145mg). Lifestyle characteristics of this sub-sample of women were similar to the entire NHS cohort. In particular, this sub-sample had a similar mean level of energy intake (1784 kcal vs. 1744 kcal in main cohort), alcohol (approximately 5 grams/day), and magnesium intake (347 mg vs. 309 mg), compared with the entire cohort. They had similar levels of physical activity (16 Metabolic-Equivalent hours a week vs. 15 a week in the main cohort), and similar proportions of the women had a family (parents and siblings), and history of diabetes (20% vs. 22% in the main cohort). However, the sub-sample appeared to spend somewhat more time outside work sitting down than the main cohort (20.5 hours/week vs. 15.7 hours/week).

Among our sample, 138 women had BMI less than 25, and 81 had BMI above or equal to 25. As expected, overweight individuals had higher fasting insulin concentrations (Fig. 1). When the analysis was stratified by BMI, the inverse association between magnesium intake and fasting insulin concentrations remained regardless of body weight, and there was no significant interaction with BMI (p for interaction = 0.51).

View larger version (21K): [in this window] [in a new window]   Fig. 1. Geometric means of fasting insulin concentrations (µU/mL) by quartiles of magnesium intake according to BMI levels. Adjusted for age (5 categories), total energy (quintiles), physical activity (quintiles), alcohol intake (0g, 0.1–15g, 15.1–30g, >30g/day), smoking (never, past smoker, up to 14 cigarettes, 15+ cigarettes a day), family history of diabetes, and weekly hours of sitting down (5 categories). Q1 to Q4 = Quartiles of magnesium intake. BMI >25, p for trend = 0.02; BMI 25, p for trend = 0.2.

	DISCUSSION

Magnesium is a co-factor in the signal transduction pathway of insulin action and affects enzymes in carbohydrate metabolism [9,24]. Several epidemiological studies suggest that higher magnesium intake or serum magnesium concentrations are predictive of reduced risk of type 2 diabetes [10,11]. An earlier study in the NHS cohort showed that women in the top quintile of magnesium intake had an RR of 0.73 (95% CI = 0.53–1.02, p for trend across all quintiles = 0.008) for type 2 diabetes compared with those in the lowest quintile [11]. Among white (but not black) participants of the Atherosclerosis Risk in Communities Study, individuals in the lowest (0.5–0.7 mmol/L) serum magnesium group had approximately double the risk of type 2 diabetes as those in the highest (0.95+ mmol/L) group [10]. Insulin resistance is also known to predispose to type 2 diabetes, and low magnesium concentrations have been shown to impair glucose tolerance [12]. Insulin sensitivity, as measured by an intravenous glucose tolerance test, was reduced after four weeks of low magnesium intake. Also, euglycemic clamp studies in middle-aged non-diabetic subjects showed plasma magnesium concentration to be inversely correlated with insulin resistance among healthy middle-aged individuals [25,26]. In healthy young adults, an inverse association was seen between dietary magnesium and fasting insulin concentrations [14,15]. However, previous data were limited by small numbers of subjects and failure to take into account confounding variables, such as BMI [27]. The present study was conducted among a larger group of healthy women, and well controlled for potential confounders. Analyses that considered food source magnesium and total magnesium intake (including supplements) showed similar results, suggesting that the association was due to magnesium intake rather than health behaviors correlated with supplement use.

Although 43% of the women used multivitamin supplements regularly, the magnesium content of many of these formulations (100 mg) is only a fraction of the current Recommended Dietary Allowances of 320 mg for adult women [28]. Food sources were the major contributors to magnesium intake in our sample. This would explain why our results were similar regardless of whether we assessed total magnesium intake or food source magnesium only. The level of intake in our sample is somewhat higher than that of U.S., middle-aged, white women in the mid-1990s, according to data from the Continuing Survey of Food Intake in Individuals [29]. The observation that none of the major food contributors of magnesium showed a strongly inverse association with magnesium is not unexpected, as magnesium is present in many food, and even the "major" contributors provide only modest amounts.

BMI and physical activity are two major independent determinants of fasting insulin concentrations, although existing data on the impact of these two factors on fasting insulin concentrations have varied substantially. In a group of non-diabetic premenopausal women, a 1 unit increase in BMI was associated with a 0.51 µU/mL increase in fasting insulin concentration after adjusting for other risk factors for diabetes [30]. Among middle-aged men, each unit increase in BMI was associated with insulin increase of 0.15 µU/mL to 1.06 µU/mL after adjusting for risk factors for diabetes [31,32]. In a randomized trial among men and women, endurance exercise three times a week for one year resulted in a 1.01 µU/mL reduction of fasting insulin concentrations in the intervention group while the control group had a slight increase in concentration [33]. We observed a difference of approximately 3 µU/mL insulin between the top and bottom quartiles of magnesium intake, which suggests the potential impact of magnesium intake on insulin sensitivity may be clinically relevant.

The strengths of this study include the use of a validated food frequency questionnaire to assess magnesium intake. Also, we used energy-adjusted magnesium intake level and adjusted in detail for other predictors of diabetes. Members of the NHS are a relatively homogenous group in terms of educational attainment and ethnicity. This may limit the generalizability of the results, but this also reduces the likelihood that our results are confounded by extraneous factors. Although some misclassification of covariates is possible, in previous validation studies, members of the NHS cohort have demonstrated accurate self-report of health characteristics [16, 34]. Misclassification of magnesium intake is likely to be random, which would attenuate the true association. A single measurement of insulin may be only a crude measure of insulin sensitivity. In a previous study in male health professionals from our group, two fasting insulin measurements two to three years apart among 82 individual was modestly correlated (Spearman r = 0.37, p = 0.007). Given the cross-sectional nature of our analysis, the inverse association observed does not necessarily represent causal relationship. However, the results do support a role of dietary magnesium in influencing insulin sensitivity.

	CONCLUSION

TOP FOOTNOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS CONCLUSION REFERENCES

 
We found that higher magnesium intake was associated with lower fasting insulin concentrations among women without diabetes. This suggests greater insulin sensitivity among those with a higher magnesium intake, and this may mediate an inverse association between higher magnesium intake and reduced risk of type 2 diabetes observed in other studies.

	FOOTNOTES

TOP FOOTNOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS CONCLUSION REFERENCES

 
Supported by grant number CA87969, DK36798 from the National Institute of Health. Dr. Hu’s work is partially supported by a Research Award from the American Diabetes Association.

The results were presented in part at the 62nd Scientific Session of the American Diabetes Association in San Francisco, CA, on June 19, 2002.

Received November 12, 2002. Accepted February 24, 2003.

	REFERENCES

TOP FOOTNOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS CONCLUSION REFERENCES

 

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