Abstract
Background: Diet plays a key role in the development of type 2 diabetes (T2D), but little is known about the contributions of specific nutrients in populations in which dietary patterns differ from Western populations.
Objective: We examined associations between calcium and magnesium intakes and the risk of T2D in a Chinese population.
Design: We used data from a population-based, prospective study of 64,191 women who were free of T2D or other chronic diseases at study recruitment and were living in urban Shanghai, China. Dietary intake, physical activity, and anthropometric measurements were assessed through in-person interviews. A Cox regression model was used to evaluate the association of the exposures under study with the risk of T2D.
Results: An inverse association between calcium and magnesium intakes and T2D risk was observed. The relative risks for the lowest to the highest quintiles of calcium intake were 1.00, 0.82, 0.73, 0.67, and 0.74 (P for trend < 0.001), and for magnesium they were 1.00, 0.84, 0.84, 0.79, and 0.86 (P for trend < 0.001). Milk intake was also inversely associated with the risk of T2D.
Conclusion: Our data suggest that calcium and magnesium intakes may protect against the development of T2D in this population.
INTRODUCTION
Diet plays an important role in the development of type 2 diabetes (T2D). Data from dietary pattern analyses indicate that high intake of fruit, vegetables, and whole-grain foods may be protective against T2D (1, 2). A diet with a low glycemic index is also associated with a lower risk of T2D (3). However, it is not clear which particular nutrients or food constituents may be responsible for this effect.
Previous studies have found inverse associations between calcium and magnesium intakes and the risk of T2D (4–12). Intake of dairy foods, good sources of both calcium and magnesium, have also been associated with lower risk of T2D, although the effect was only found for low-fat dairy products in 2 studies (4, 5). Intake of food sources of magnesium, such as whole-grain foods, have been associated with lower risk of T2D (13). The data available on the association between calcium and magnesium intakes and T2D come from Western populations. In Western populations, low-fat dairy and whole-grain foods are part of a prudent diet that has been associated with lower risk of T2D (2), whereas a more typical Western dietary pattern is more likely to be low in magnesium-containing foods and high in refined starches and high-fat dairy products (mainly saturated fatty acids) that could increase the risk of T2D. No data are available from populations that exhibit different dietary patterns.
We evaluated the association of calcium and magnesium intakes with the incidence of T2D in a large, population-based, prospective study of middle-aged women conducted in Shanghai, China, where consumption of dairy products is low and sources of calcium and magnesium differ from those in Western populations. Thus, this population provides an excellent opportunity to investigate associations between these 2 nutrients and the incidence of T2D in a different context and with minimum confounding from Western dietary patterns.
SUBJECTS AND METHODS
Study population
The Shanghai Women's Health Study (SWHS) is a population-based, prospective cohort study of middle-aged women (40–70 y old) conducted in 7 urban communities in Shanghai, China. Details of the SWHS survey have been reported elsewhere (14). From a total of 81,170 women who were invited to participate, 75,221 enrolled in the study (92.7% participation rate). Reasons for nonparticipation were refusal (3.0%), absence during the enrollment period (2.6%), and other reasons (health, hearing, or speaking problems; 1.6%). After exclusion of women <40 y or >70 y at the time of the interview (n = 278), 74,942 women remained for the study. Participants completed a detailed survey, including an in-person interview for assessment of dietary intake, physical activity, and measurement of anthropometrics and other lifestyle factors. Protocols for the SWHS were approved by the institutional review boards of all institutes involved in the study, and all participants provided written, informed consent before the interview. Three biennial in-person follow-ups for all living cohort members were conducted by in-home visit between 2000 and 2002, 2002 and 2004, and 2004–2006 with response rates of 99.8%, 98.7%, and 94.9%, respectively.
Outcome ascertainment
Incident T2D was identified through outcome follow-up surveys. A total of 2273 study participants reported having a T2D diagnosis because the baseline survey and of those participants 2270 subjects had valid dietary data. We considered a case of T2D to be confirmed if the participants reported having T2D diagnosed and met one or more of the following criteria as recommended by the American Diabetes Association (15): fasting glucose concentration ≥7 mmol/L on ≥2 separate occasions or an oral-glucose-tolerance test (OGTT) ≥11.1 mmol/L and/or use of hypoglycemic medication (ie, insulin or oral hypoglycemic drugs). Of the self-reported cases, a total of 1514 participants met the study outcome criteria and are referred to as confirmed cases of T2D in the present study. Participants from whom information on fasting glucose and OGTT was available only at the second and third follow-up surveys are referred to as probable diabetes cases. Because information on the number of abnormal fasting glucose tests and OGTT was not collected in the first follow-up survey, nearly one-third of self-reported cases did not meet our confirmation criteria. Therefore, cases identified during the first follow-up survey could not be confirmed. We performed analyses for all T2D cases and confirmed cases only.
Calcium and magnesium intakes
Dietary intake was assessed twice—during the baseline survey and at the first follow-up survey—via in-person interviews by using a food-frequency questionnaire (FFQ) that was designed for and validated in this population (16). The SWHS FFQ includes 77 food items and food groups that cover 90% of foods commonly consumed in urban Shanghai during the study period. The correlations between the FFQ and 24-h recalls were 0.54 for calcium and 0.55 for magnesium. If women had a history of T2D, cancer, or cardiovascular disease reported between the baseline and follow-up surveys, we only used dietary data from the baseline FFQ in the analyses. For other participants, we used the average of baseline and follow-up FFQ data. The Chinese Food Composition Tables (17) were used to estimate intake of energy (in kcal/d), calcium (in mg/d), and magnesium (in mg/d). We also derived variables for the amount of calcium and magnesium intakes originating from animal, vegetable, or milk sources (in mg/d). In this population, dairy intake primarily comes from the consumption of milk. We also investigated the association between milk intake and T2D. We excluded participants who had extreme values for total energy intake (<500 or >3500 kcal/d; n = 36) (18), leaving 64,191 participants for the final analysis.
Other factors as potential confounders
All anthropometric measurements, including weight, height, and circumferences of the waist and hips, were taken at baseline recruitment according to a standard protocol by trained interviewers who were retired medical professionals (19). From these measurements, the following variables were created: body mass index (BMI; in kg/m2) and waist-hip ratio (WHR; waist circumference divided by hip circumference).
Details about physical activity were collected with the use of a validated questionnaire (20). The questionnaire evaluated regular exercise and sports participation during the 5 y before interview, daily physical activity, and physical activity related to the daily commuting journey to and from work. We calculated the metabolic equivalent tasks (METs) for each activity, using a compendium of physical activity values (21). One MET-h/d is roughly equivalent to 1 kcal/kg · d or about 15 min of participation in moderate-intensity (4 METs) activity for an average adult (21). We combined each of the exercise and lifestyle activity indexes to derive a quantitative estimate of overall nonoccupational physical activity (MET-h/d).
Information on sociodemographic factors and potential confounders was collected by using a structured questionnaire. This information included age, level of education (none, elementary school, middle or high school, or college), family income (<10,000, 10,000–19,999, 20,000–29,999, or >30,000 yuan/y), occupation (professional, clerical, manual laborers, housewife, or retired), smoking (ever smoked ≥1 cigarette/d for >6 mo continuously), alcohol intake (ever drank beer, wine, or spirits ≥3 times/wk), and presence of hypertension at baseline.
Statistical analysis
Person-years of follow-up for each participant were calculated as the interval between the baseline recruitment to the diagnosis of T2D, censored at death or completion of the third follow-up survey. The Cox proportional hazards model was used to assess the effect of calcium and magnesium intakes on the incidence of T2D. Total calcium intake, total magnesium intake, and calcium and magnesium intakes combined from animal, plant, and milk sources (in mg/d) were categorized by quintile distribution with the lowest quintile serving as the reference. Tests for trend were performed by entering the categorical variables as continuous parameters in the models. Sociodemographic factors and T2D risk factors were adjusted for in the analyses as potential confounders. To reduce measurement error and to adjust for extraneous variation because of total energy intake, we adjusted total calcium and magnesium intake by total energy intake by the residual method described by Willett and Stampfer (22). We conducted analyses stratified by categories of BMI, WHR, physical activity, and vitamin supplement use. The log-likelihood ratio test was used to evaluate multiplicative interactions between total calcium and magnesium intake and BMI, WHR, and exercise participation categories. All analyses were performed with the use of SAS (version 9.1; SAS Institute, Cary, NC), and all tests of statistical significance were based on 2-sided probability.
RESULTS
In this cohort of 64,191 middle-aged women, we documented 2270 incident cases of T2D after 6.9 y of follow-up. The median intakes for calcium and magnesium were 466.27 mg/d and 267.0 mg/d, respectively. The content of calcium and magnesium in foods included in the SWHS FFQ are presented in Appendix A. The main contributors to calcium in this population were tofu (20.76%), milk (15.11%), Chinese greens (14.65%), fish (8.15%), rice (8.74%), and legumes (6.53%). For magnesium intake, the main contributors were rice (33.3%), tofu (8.25%), seafood (6.92%), legumes (6.35%), and Chinese greens (4.35%).
APPENDIX A.
Calcium and magnesium content of items in the Shanghai Women's Health Study food-frequency questionnaire
| Calcium | Total calcium | Magnesium | Total magnesium | |
| mg/100 g | % | mg/100 g | % | |
| Staple food | ||||
| Rice | 13.0 | 8.74 | 34.0 | 33.32 |
| Noodles, steamed bread, and other wheat foodstuffs | 31.0 | 2.55 | 50.0 | 6.20 |
| Meat, eggs, fish | ||||
| Pork chops | 5.4 | 0.12 | 11.6 | 0.39 |
| Pork ribs | 10.1 | 0.25 | 10.1 | 0.38 |
| Pig's feet | 19.8 | 0.09 | 3.0 | 0.02 |
| Fresh pork (fat) | 3.0 | 0.004 | 2.0 | 0.004 |
| Fresh pork (lean) | 6.0 | 0.28 | 25.0 | 1.79 |
| Fresh pork (mixture) | 6.0 | 0.16 | 16.0 | 0.63 |
| Pig liver, cow liver, sheep liver | 5.9 | 0.01 | 23.8 | 0.08 |
| Animal parts | 11.1 | 0.02 | 12.3 | 0.03 |
| Beef, lamb | 7.2 | 0.05 | 19.5 | 0.23 |
| Eggs, duck eggs | 43.0 | 3.09 | 11.0 | 1.26 |
| Chicken | 5.9 | 0.23 | 12.5 | 0.76 |
| Duck, goose | 3.8 | 0.05 | 9.9 | 0.20 |
| Saltwater fish | 26.8 | 1.63 | 29.7 | 2.83 |
| Freshwater fish | 29.1 | 1.87 | 18.6 | 1.92 |
| Rice field eel or river eel | 29.6 | 0.24 | 15.4 | 0.205 |
| Shrimp, crab, etc | 130.3 | 4.16 | 27.6 | 1.46 |
| Conch, etc | 43.2 | 0.25 | 58.8 | 0.51 |
| Fresh milk | 104.0 | 12.56 | 11.0 | 2.69 |
| Powdered milk | 676.0 | 2.55 | 79.0 | 0.57 |
| Desserts, beans, and other | ||||
| All kinds of desserts | 40.0 | 1.33 | 25.7 | 1.36 |
| Bread | 49.0 | 1.19 | 31.0 | 1.25 |
| Candy and preserved fruit | 55.0 | 0.32 | 22.2 | 0.20 |
| Soy milk, powdered soy milk | 10.0 | 1.69 | 9.0 | 2.27 |
| Bean curd | 140.0 | 10.56 | 31.5 | 3.93 |
| Fried bean curd, vegetarian chicken, bean curd cake | 271.7 | 10.20 | 69.2 | 4.32 |
| Dried soybeans | 191.0 | 0.32 | 199.0 | 0.52 |
| Mung beans, red beans, and other dried beans | 126.3 | 1.94 | 168.7 | 1.49 |
| Soybean sprouts | 21.0 | 0.20 | 21.0 | 0.31 |
| Mung bean sprouts | 9.0 | 0.10 | 18.0 | 0.32 |
| Peanuts | 4.2 | 0.03 | 58.3 | 0.61 |
| Black and white edible tree fungi | 140.8 | 0.25 | 101.9 | 0.29 |
| Dried xianggu mushrooms | 78.8 | 0.15 | 139.6 | 0.41 |
| Vegetables | ||||
| Greens, Chinese greens | 73.0 | 14.65 | 14.6 | 4.76 |
| Spinach | 58.7 | 0.70 | 51.6 | 0.95 |
| Green cabbage | 42.1 | 0.66 | 10.3 | 0.26 |
| Chinese cabbage, bok choi cabbage | 43.5 | 0.77 | 9.6 | 0.26 |
| Cauliflower | 18.9 | 0.20 | 14.8 | 0.25 |
| Celery | 38.2 | 0.15 | 10.8 | 0.52 |
| Eggplant | 37.6 | 0.65 | 13.2 | 0.36 |
| Wild rice stems | 3.0 | 0.03 | 5.9 | 0.11 |
| Asparagus lettuce | 14.3 | 0.09 | 11.8 | 0.12 |
| Potatoes | 7.5 | 0.21 | 21.6 | 0.94 |
| Wax gourd | 15.2 | 0.15 | 6.4 | 0.77 |
| Cucumber, luffa | 16.8 | 0.89 | 11.5 | 0.98 |
| Fresh mushrooms, fresh xianggu mushrooms | 4.0 | 0.06 | 10.9 | 0.25 |
| Fresh red and green peppers | 17.9 | 0.205 | 11.7 | 0.21 |
| Tomatoes | 9.7 | 0.87 | 8.3 | 1.23 |
| Bamboo shoots | 7.2 | 0.20 | 3.7 | 0.17 |
| Lotus root | 34.3 | 0.13 | 16.7 | 0.09 |
| Garlic and garlic shoots | 23.5 | 0.09 | 15.1 | 0.09 |
| Head of garlic | 33.1 | 0.07 | 17.8 | 0.06 |
| Onions | 21.6 | 0.03 | 13.5 | 0.03 |
| Chinese chives | 37.8 | 0.18 | 22.5 | 0.17 |
| Green onions | 52.6 | 0.58 | 13.1 | 0.22 |
| Carrots | 30.9 | 0.23 | 10.1 | 0.13 |
| White turnips | 36.1 | 0.35 | 13.3 | 0.21 |
| Sweet potatoes | 20.7 | 0.12 | 12.7 | 0.12 |
| Baby soybeans, fresh peas, fresh broad beans | 44.8 | 2.76 | 26.9 | 2.61 |
| Yard-long beans | 26.2 | 0.38 | 30.1 | 0.68 |
| Green beans (4-season beans) | 45.1 | 0.95 | 26.7 | 0.88 |
| Hyacinth beans or snow peas (Dutch peas) | 39.7 | 0.18 | 22.5 | 0.16 |
| Fruit | ||||
| Apples | 3.0 | 0.40 | 3.0 | 0.63 |
| Pears | 7.4 | 0.57 | 6.5 | 0.79 |
| Tangerines, oranges, grapefruits | 18.7 | 1.27 | 10.3 | 1.09 |
| Bananas | 4.1 | 0.25 | 25.4 | 2.34 |
| Grapes | 4.3 | 0.09 | 6.9 | 0.23 |
| Watermelon | 4.5 | 2.13 | 4.5 | 3.28 |
| Peaches | 5.2 | 0.10 | 6.0 | 0.18 |
| Other fruits (eg, strawberries, cantaloupe) | 9.5 | 0.62 | 10.2 | 1.03 |
Characteristics of the study population stratified by calcium and magnesium intakes are shown in Table 1. Higher intakes of calcium and magnesium were associated with higher educational status, having a professional job, and higher household income. Participants with higher intakes of calcium and magnesium were less likely to have ever smoked and were more likely to exercise and consume alcohol. The correlation between calcium and magnesium intake was 0.81.
TABLE 1.
Characteristics of the population by quintile (Q) of calcium and magnesium intakes1
| Calcium |
Magnesium |
|||||||||||
| Q1 | Q2 | Q3 | Q4 | Q5 | P2 | Q1 | Q2 | Q3 | Q4 | Q5 | P2 | |
| Median intake (mg/d) | 277.5 | 383.1 | 462.9 | 538.3 | 649.6 | 213.8 | 242.9 | 262.5 | 282.7 | 318.1 | ||
| Age (y) | 51.0 ± 9.43 | 50.4 ± 8.8 | 50.2 ± 8.4 | 50.2 ± 8.3 | 50.2 ± 8.2 | <0.001 | 52.7 ± 9.4 | 51.0 ± 8.8 | 50.6 ± 8.4 | 50.4 ± 8.3 | 50.1 ± 8.2 | <0.001 |
| Energy intake (kcal/d) | 1627.9 ± 411 | 1667.3 ± 360 | 1682.2 ± 336 | 1688.0 ± 307 | 1618.9 ± 304 | 0.07 | 1644.9 ± 45 | 1650.0 ± 342 | 1658.6 ± 314 | 1660.1 ± 299 | 1650.8 ± 291 | 0.02 |
| BMI (kg/m2) | 24.4 ± 3.6 | 23.9 ± 3.4 | 23.6 ± 3.2 | 23.5 ± 3.2 | 23.5 ± 3.1 | <0.001 | 23.9 ± 3.5 | 23.7 ± 3.3 | 23.7 ± 3.3 | 23.7 ± 3.2 | 23.9 ± 3.2 | 0.03 |
| WHR | 0.82 ± 0.05 | 0.81 ± 0.05 | 0.80 ± 0.05 | 0.80 ± 0.05 | 0.80 ± 0.05 | <0.001 | 0.81 ± 0.05 | 0.81 ± 0.05 | 0.80 ± 0.05 | 0.80 ± 0.05 | 0.80 ± 0.05 | <0.001 |
| Regular smoker (%) | 3.8 | 2.5 | 1.8 | 1.4 | 1.6 | <0.001 | 3.88 | 2.06 | 1.74 | 1.71 | 1.68 | <0.001 |
| Regular alcohol consumption (%) | 2.3 | 1.9 | 2.1 | 2.1 | 3.0 | <0.001 | 2.15 | 2.00 | 1.99 | 2.17 | 3.11 | <0.001 |
| Regular exercise (%) | 25.7 | 29.7 | 32.8 | 35.5 | 41.1 | <0.001 | 26.5 | 30.2 | 32.7 | 35.5 | 39.7 | <0.001 |
| Educational level (%) | ||||||||||||
| None | 34.4 | 20.6 | 15.3 | 12.2 | 9.3 | <0.001 | 31.9 | 19.5 | 15.7 | 12.9 | 11.3 | <0.001 |
| Elementary | 40.7 | 43.2 | 40.2 | 36.7 | 32.9 | 38.6 | 40.6 | 39.2 | 38.6 | 36.7 | ||
| Up to high school | 18.6 | 26.1 | 30.7 | 33.9 | 35.8 | 21.0 | 27.4 | 30.4 | 32.5 | 34.0 | ||
| College | 6.0 | 9.9 | 13.7 | 17.1 | 21.9 | 8.0 | 12.4 | 14.6 | 15.9 | 17.9 | ||
| Income level (%) | ||||||||||||
| <10,000 yuan/y | 21.0 | 16.9 | 14.3 | 12.7 | 11.6 | <0.001 | 20.4 | 15.3 | 13.9 | 13.1 | 13.4 | <0.001 |
| 10,000–19,999 yuan/y | 41.9 | 40.7 | 38.3 | 35.6 | 33.4 | 40.9 | 38.9 | 37.0 | 37.2 | 35.6 | ||
| 20,000–29,999 yuan/y | 25.0 | 27.7 | 29.3 | 31.1 | 30.5 | 25.9 | 28.9 | 30.4 | 29.5 | 29.0 | ||
| ≥30,000 yuan/y | 12.1 | 14.7 | 18.1 | 20.6 | 24.4 | 8.0 | 12.4 | 14.6 | 15.9 | 17.9 | ||
| Occupation (%) | ||||||||||||
| Professional | 10.6 | 16.2 | 210 | 24.5 | 26.9 | <0.001 | 13.0 | 18.8 | 21.3 | 22.7 | 23.7 | <0.001 |
| Clerical | 11.6 | 12.9 | 13.1 | 13.3 | 14.0 | 11.9 | 12.4 | 13.1 | 13.3 | 14.3 | ||
| Manual laborers | 23.8 | 25.3 | 23.9 | 22.4 | 19.5 | 22.8 | 24.6 | 23.6 | 23.1 | 20.6 | ||
| Housewife or retired | 54.0 | 45.6 | 41.9 | 39.8 | 39.5 | 52.2 | 44.1 | 42.0 | 40.9 | 41.4 | ||
| Hypertension | 20.9 | 18.7 | 18.3 | 18.1 | 18.2 | <0.001 | 18.8 | 17.8 | 18.4 | 18.7 | 20.6 | <0.001 |
WHR, waist-hip ratio.
Calculated by using a chi-square test for the prevalence of population characteristics; with an ANOVA for energy intake (in kcal/d), BMI, and WHR; and with a Kruskal-Wallis test for age.
Mean ± SD (all such values).
Calcium and magnesium intakes were both associated with a decrease in risk of T2D (Table 2). As compared with the lowest quintile of intake, the multivariate-adjusted relative risks (RRs) of T2D across quintiles for calcium were 1.00, 0.82, 0.73, 0.67, and 0.74 (P for trend < 0.001), and for magnesium they were 1.00, 0.84, 0.84, 0.79, and 0.86 (P for trend < 0.001). Although the trend tests were significant, the association of calcium and magnesium with T2D did not appear to follow a log-linear pattern. We repeated the analysis with data from only confirmed cases of diabetes and found similar trends (Table 2). We conducted additional analyses excluding participants with T2D diagnosed during the first 2 y of follow-up. The adjusted RRs for T2D across quintiles relative to the lowest quintile of intake for calcium were 1.00, 0.83, 0.74, 0.68, and 0.75 (P < 0.001), and for magnesium they were 1.00, 0.83, 0.85, 0.79, and 0.86 (P = 0.01; data not shown in tables).
TABLE 2.
Associations between the intakes of calcium and magnesium and risk of type 2 diabetes1
| Median intake | Cases | Person-years | All participants | Confirmed diabetes | |
| mg/d | n | n | |||
| Calcium2 | |||||
| Quintile 1 | 277.5 | 708 | 58,971.9 | 1.00 (reference) | 1.00 (reference) |
| Quintile 2 | 383.1 | 488 | 59,709.3 | 0.82 (0.73, 0.92)3 | 0.81 (0.70, 0.93) |
| Quintile 3 | 462.9 | 386 | 59,798.1 | 0.73 (0.65, 0.83) | 0.72 (0.62, 0.84) |
| Quintile 4 | 538.3 | 341 | 59,749.5 | 0.67 (0.59, 0.76) | 0.64 (0.54, 0.75) |
| Quintile 5 | 649.6 | 347 | 59,515.5 | 0.74 (0.65, 0.85) | 0.73 (0.62, 0.86) |
| P for trend | <0.001 | <0.0001 | |||
| Magnesium2 | |||||
| Quintile 1 | 213.8 | 608 | 60,133.2 | 1.00 (reference) | 1.00 (reference) |
| Quintile 2 | 242.9 | 455 | 63,118.5 | 0.84 (0.74, 0.95) | 0.80 (0.69, 0.93) |
| Quintile 3 | 262.5 | 399 | 54,231.9 | 0.84 (0.74, 0.96) | 0.85 (0.73, 0.99) |
| Quintile 4 | 282.7 | 386 | 60,525.4 | 0.79 (0.69, 0.90) | 0.73 (0.62, 0.85) |
| Quintile 5 | 318.1 | 422 | 59,735.4 | 0.86 (0.75, 0.97) | 0.80 (0.68, 0.93) |
| P for trend | <0.001 | <0.0001 |
Adjusted for age, energy intake (in kcal/d), BMI (in kg/m2), waist-hip ratio, smoking status, alcohol consumption, physical activity, income level, education level, occupation, and hypertension. Cox proportional hazards model was used to assess the effect of calcium and magnesium intakes on the incidence of type 2 diabetes. Tests for trend were performed by entering the categorical variables as continuous parameters in the models.
Adjusted for energy.
Relative risk; 95% CI in parentheses (all such values).
In this population, only 2.78% of participants had ever smoked, and only 2.28% participants had ever consumed alcohol regularly. In analyses restricted to participants who had never smoked or consumed alcohol, we found similar inverse associations of calcium and magnesium with T2D. The RRs for quintiles were 1.00, 0.81, 0.73, 0.65, and 0.73 (P for trend < 0.001) for calcium and 1.00, 0.83, 0.86, 0.78, and 0.84 (P for trend <0.01) for magnesium (data not shown in tables).
We repeated the analysis stratified by menopausal status and found inverse associations between calcium and magnesium intakes and T2D regardless of menopausal status, although the trend for magnesium in postmenopausal women failed to reach significance. In premenopausal women, the RRs for quintiles of calcium intake were 1.00, 0.86, 0.67, 0.66, and 0.61 (P for trend < 0.001), and for magnesium intake they were 1.00, 0.71, 0.86, 0.66, and 0.72 (P for trend <0.01). In postmenopausal women, the RRs for quintiles of calcium intake were 1.00, 0.79, 0.78, 0.68, and 0.84 (P for trend: 0.001), and for magnesium intake they were 1.00, 0.88, 0.88, 0.85, and 0.95 (P for trend: 0.33). The P values for interaction of menopause with calcium and magnesium were not significant (P = 0.43 for calcium; P = 0.73 for magnesium; data not shown in tables).
We evaluated the association between calcium and magnesium derived from animal, plant, and dairy sources and the risk of T2D. We observed that calcium intake, regardless of the source, was inversely associated with the risk of T2D (Table 3). We observed that magnesium from dairy or animal sources was inversely associated with T2D, but no association was observed between magnesium from vegetable sources and risk of T2D (Table 3). Milk intake was associated with a lower risk of T2D, and, in the case of fresh milk, we observed a dose-response association (Table 4).
TABLE 3.
Associations between intakes of calcium and magnesium from animal, plant, and milk sources and risk of type 2 diabetes1
| Calcium |
Magnesium |
|||||||||
| Median intake | Cases | Person-years | All participants | Confirmed diabetes | Median intake | Cases | Person-years | All participants | Confirmed diabetes | |
| mg/d | n | n | mg/d | n | n | |||||
| Animal sources | ||||||||||
| Quintile 1 | 22.7 | 694 | 58,674.2 | 1.00 (reference) | 1.00 (reference) | 15.2 | 655 | 58,456.9 | 1.00 (reference) | 1.00 (reference) |
| Quintile 2 | 38.4 | 471 | 59,458.5 | 0.83 (0.73, 0.93)2 | 0.82 (0.70, 0.95) | 24.6 | 469 | 59,968.9 | 0.87 (0.77, 0.98) | 0.86 (0.74, 1.00) |
| Quintile 3 | 52.1 | 392 | 60,206.1 | 0.76 (0.66, 0.87) | 0.82 (0.70, 0.96) | 32.3 | 382 | 57,817.7 | 0.78 (0.69, 0.90) | 0.79 (0.67, 0.94) |
| Quintile 4 | 68.7 | 375 | 59,726.8 | 0.75 (0.65, 0.86) | 0.85 (0.72, 1.00) | 42.0 | 384 | 62,153.9 | 0.77 (0.67, 0.89) | 0.79 (0.66, 0.93) |
| Quintile 5 | 102.4 | 338 | 59,678.4 | 0.72 (0.62, 0.84) | 0.73 (0.61, 0.88) | 61.3 | 380 | 59,346.9 | 0.80 (0.69, 0.94) | 0.83 (0.68, 1.00) |
| P for trend | <0.001 | <0.01 | <0.001 | 0.02 | ||||||
| Plant sources | ||||||||||
| Quintile 1 | 191.8 | 499 | 59,326.5 | 1.00 (reference) | 1.00 (reference) | 161.5 | 411 | 59,273.7 | 1.00 (reference) | 1.00 (reference) |
| Quintile 2 | 254.2 | 431 | 59,923.3 | 0.86 (0.76, 0.98) | 0.88 (0.75, 1.03) | 194.3 | 407 | 59,965.8 | 0.94 (0.82, 1.09) | 0.93 (0.78, 1.10) |
| Quintile 3 | 306.8 | 376 | 60,192.3 | 0.76 (0.66, 0.87) | 0.74 (0.63, 0.88) | 221.3 | 446 | 59,646.7 | 0.99 (0.86, 1.15) | 0.90 (0.75, 1.09) |
| Quintile 4 | 368.8 | 448 | 59,376.1 | 0.85 (0.74, 0.97) | 0.80 (0.67, 0.95) | 251.0 | 480 | 59,852.1 | 0.99 (0.85, 1.17) | 0.92 (0.76, 1.12) |
| Quintile 5 | 481.0 | 516 | 58,926.2 | 0.87 (0.75, 1.01) | 0.78 (0.65, 0.95) | 303.2 | 380 | 59,006.0 | 0.97 (0.79, 1.18) | 0.87 (0.68, 1.11) |
| P for trend | 0.09 | <0.01 | 0.98 | 0.36 | ||||||
| Milk source | ||||||||||
| None | 0 | 1035 | 76,426.9 | 1.00 (reference) | 1.00 (reference) | 0 | 1035 | 76,426.9 | 1.00 (reference) | 1.00 (reference) |
| Low | 36.5 | 468 | 7146.2 | 0.63 (0.58, 0.72) | 0.69 (0.61, 0.79) | 3.9 | 472 | 71,501.8 | 0.64 (0.57, 0.71) | 0.69 (0.60, 0.79) |
| Medium | 118.8 | 344 | 75,250.9 | 0.44 (0.39, 0.51) | 0.57 (0.49, 0.66) | 12.6 | 339 | 75,349.9 | 0.47 (0.41, 0.53) | 0.58 (0.50, 0.67) |
| High | 208.0 | 423 | 74,606.4 | 0.64 (0.57, 0.73) | 0.67 (0.58, 0.78) | 22.0 | 424 | 74,465.8 | 0.64 (0.57, 0.72) | 0.66 (0.57, 0.77) |
| P for trend | <0.001 | <0.001 | <0.001 | <0.001 | ||||||
Adjusted for age, energy intake (in kcal/d), BMI (in kg/m2), waist-hip ratio, smoking status, alcohol consumption, physical activity, income level, education level, occupation, and hypertension. Cox proportional hazards model was used to assess the effect of calcium and magnesium intakes on the incidence of type 2 diabetes. Tests for trend were performed by entering the categorical variables as continuous parameters in the models.
Relative risk; 95% CI in parentheses (all such values).
TABLE 4.
Associations between milk intake and risk of type 2 diabetes1
| Median intake | Cases | Person-years | All participants | Confirmed diabetes | |
| g/d | n | n | |||
| Fresh milk | |||||
| None | 0 | 1248 | 98,917.5 | 1.00 (reference) | 1.00 (reference) |
| <100 g/d | 34.3 | 336 | 59,380.3 | 0.61 (0.54, 0.69)2 | 0.64 (0.55, 0.75) |
| 100–200 g/d | 150.0 | 652 | 130,002.7 | 0.56 (0.50, 0.62) | 0.64 (0.57, 0.72) |
| >200 g/d | 250.0 | 34 | 9443.9 | 0.46 (0.32, 0.64) | 0.60 (0.41, 0.88) |
| P for trend | <0.001 | <0.001 | |||
| Powdered milk | |||||
| No | 0 | 1784 | 20,8921.9 | 1.00 (reference) | 1.00 (reference) |
| Yes | 4.10 | 486 | 88,822.4 | 0.74 (0.67, 0.82) | 0.85 (0.75, 0.96) |
| P for trend | <0.001 | <0.01 |
Adjusted for age, energy intake (in kcal/d), BMI (in kg/m2), waist-hip ratio, smoking status, alcohol consumption, physical activity, income level, education level, occupation, and hypertension. A Cox proportional hazards model was used to assess the effect of milk intake on the incidence of type 2 diabetes. Tests for trend were performed by entering the categorical variables as continuous parameters in the models.
Relative risk; 95% CI in parentheses (all such values).
We assessed the potential effect modification by BMI (<25 or ≥25), WHR (<0.85 and ≥0.85), exercise participation (yes or no), and vitamin supplement use (yes or no) on the association of calcium and magnesium with the incidence of T2D. No apparent interaction was observed (data not shown in tables).
DISCUSSION
In this large, population-based, prospective study of 64,191 middle-aged Chinese women, a nonlinear inverse association between calcium and magnesium intakes and the incidence of T2D after 7 y of follow-up was observed. Other studies of calcium and magnesium intakes and T2D have found similar results. In the Nurses' Health Study, the RRs for T2D for highest compared with lowest categories of calcium intake were 0.79 (95% CI: 0.70, 0.90) for all sources and 0.82 (95% CI: 0.72, 0.92; P for trend < 0.001) for supplements (23). In the Women's Health Study (WHS) (4), the RR for T2D in women in the highest compared with the lowest quintiles of calcium intake was 0.79 (95% CI: 0.6, 0.94). For magnesium, the Nurses' Health Study and Health Professionals Follow-up Study (HPFS) reported RRs for T2D of 0.66 (95% CI: 0.60, 0.73; P for trend < 0.001) in women and 0.67 (95% CI: 0.56, 0.80; P for trend < 0.001) in men in an 18-y follow-up period (lowest compared with highest quintiles of dietary and supplement magnesium intakes) (8), similar to results reported in the WHS after a 6-y follow-up (9). No effect modification by BMI or physical activity was found in one study (8), similar to our results, whereas in another study, the protective effect of magnesium intake was only seen in women with a BMI ≥ 25 (9). Results from a recent meta-analysis of 6 US studies and 1 Australian study reported a 15% reduction in risk for each 100-mg/d increase in magnesium intake (11). Fasting serum magnesium was lower in participants with prevalent diabetes compared with participants free of disease (24). A graded inverse association between serum magnesium concentrations and T2D over a 6-y follow-up period was also reported (10). Reports on the effect of magnesium supplementation on glucose metabolism in established T2D have been inconsistent (25–27), although in a meta-analysis of 9 randomized, double-blind, controlled trials (28) magnesium appeared to be beneficial for glycemic control.
It has been suggested that calcium plays a role in the development of T2D because of inverse associations observed between calcium intake and body weight (29–32). Calcium is essential for insulin-mediated intracellular processes in insulin-responsive tissues such as skeletal muscle and adipose tissue (33–35), suggesting a potential mechanism to explain associations between calcium insufficiency and the risk of T2D (36). Magnesium may reduce the risk of T2D by improving insulin sensitivity. In a study of 18 nondiabetic volunteers, low serum magnesium was associated with relative insulin resistance, glucose intolerance, and hyperinsulinemia (37). An inverse dose-response relation between magnesium intake and insulin sensitivity was found in one study, with no further benefit observed for intakes >325 mg/d (38). Magnesium deficiency reduces insulin-mediated glucose uptake in rat adipocytes (39), and hypomagnesemic rats show impaired muscle insulin tyrosine kinase activity (40). In the rat, dietary magnesium supplementation can prevent fructose-induced insulin resistance (41), and higher dietary magnesium intake can prevent the development of T2D (42). The inverse association that we found between magnesium intake and T2D could also be explained by dietary fiber intake, which was inversely associated with T2D in our study. The RRs of T2D for quintiles of fiber intake were 1.00, 0.81, 0.77, 0.81, and 0.86 (P for trend: 0.02), and adjustment for fiber attenuated the association of magnesium and T2D. The RRs of T2D for magnesium intake quintiles were 1.00, 0.90, 0.97, 0.91, and 0.94 (P for trend: 0.11), suggesting that the magnesium-T2D association observed in our study could be explained by fiber intake. However, magnesium and fiber intakes were highly correlated (correlation coefficient: 0.84), raising a concern about multicollinearity.
Dairy milk, a good source of both calcium and magnesium, was inversely associated with T2D. In the WHS (4), the association between dairy intake and T2D was limited to low-fat dairy products, similar to results from the HPFS (5). Results from a meta-analysis found an inverse association between dairy intake and T2D incidence (RR: 0.86; 95% CI: 0.79, 0.93) for the highest compared with lowest dairy intake (12). Dairy intake could lower the risk of T2D by affecting insulin sensitivity. A strong inverse association between dairy intake and the risk of the insulin resistance syndrome was reported in one study (43), although in another study dairy intake was not related to insulin sensitivity (38). The beneficial effect of dairy on insulin sensitivity may be due to its vitamin D and calcium content (44). In one report, a combined daily intake of >1200 mg calcium and >800 IU vitamin D was associated with a 33% lower risk of T2D (23). Milk protein has insulinotropic properties (45); however, the saturated fat content in dairy may mitigate any potential benefits, which might explain the weaker and null associations between high-fat dairy product intake and T2D in some studies (5).
The specific sources of calcium and magnesium may play some role in their effect on T2D. Although calcium intake from all sources and magnesium intake from animal and dairy sources were inversely associated with the risk of T2D, no association of magnesium from vegetable sources with T2D was observed. It is possible that vitamin D in animal and dairy food sources favorably affects the absorption of magnesium, thereby strengthening the protective association of dietary magnesium from animal sources or dairy with T2D. In addition, the magnesium content of vegetables changes when they are cooked, which could also explain our results.
Existing data on associations between calcium and magnesium and the risk of T2D come primarily from Western populations, in which food sources of calcium and magnesium differ from those in our population. For example, consumption of whole-grain foods is a good source of magnesium in Western populations and has been associated with a significantly reduced risk of T2D in the Iowa Women's Health Study (46), a Finnish study (47), and the HPFS (48), among others. Lower risk of T2D was associated with consumption of low-fat but not high-fat dairy products in 2 US populations (4, 5). However, a diet low in whole-grain foods and high in high-fat dairy resembles a Western dietary pattern that has been associated with higher risk of T2D (2, 49). Thus, it is difficult to assess the effect of calcium and magnesium on the risk of T2D without confounding from this overall unfavorable dietary pattern typical of Western populations.
Our study provides a unique opportunity to examine the association of calcium and magnesium with risk of T2D and with minimum confounding from a Western dietary pattern. In our study population, the mean intake of magnesium was not different from that in the US population (50–52), whereas consumption of calcium was much lower. Women in Shanghai consume fewer dairy products compared with their US counterparts (52–54), whereas the consumption of soybeans and soy products, rich in both calcium and magnesium, is much higher. Rice, the main staple food in Shanghai, is highly refined, and, in general, the consumption of whole-grain foods is limited. In our population, legumes (soybeans in particular), but not tofu, were associated with lower T2D incidence (55). Vegetable intake was also inversely associated with T2D risk (56), whereas rice intake was associated with a higher incidence of T2D (57). These foods are major contributor of magnesium in Shanghai. With the exception of rice, the inverse trend between magnesium and T2D remained even after adjustment for rice, tofu, seafood, legumes, and vegetables (RRs of T2D for quintiles of magnesium intake: 1.00, 0.88, 0.96, 0.87, and 1.03; P for trend: 0.79). Because rice is also a major contributor to fiber intake in our study population, this result again suggests possible confounding by fiber intake. As with all nutritional epidemiology studies, it is difficult to assess the independent effect of calcium and magnesium on the risk of T2D without confounding from foods rich in calcium and magnesium.
Our study has several strengths. Our participants are representative of the middle-aged, female Chinese population in urban Shanghai. The prospective design of the study and high response rate minimized recall and selection biases. The repeated assessment of diet improved the dietary assessment, and we were able to adjust for a wide range of confounders. Nevertheless, several methodologic limitations should be kept in mind when interpreting our study results. First, although we did adjust for confounders, we cannot exclude the possibility of residual confounding. Misclassification of T2D based on self-reports is likely to be random and could weaken the association between calcium and magnesium intakes and T2D. Misclassification of dietary information is unavoidable, but it would most likely be nondifferential and thus would attenuate the true associations. We lacked information on use of calcium and magnesium supplements and the fat content of milk, although in this population most participants have access to only whole milk. In addition, we did not have information on vitamin D intake; thus, we could not assess the combined effect of vitamin D and calcium intakes on the risk of T2D. Furthermore, we could not disentangle the effect of calcium from magnesium, because the correlation between them was high (r = 0.81).
In conclusion, our findings support the hypothesis that calcium and magnesium play a protective role in the development of T2D. This study adds to the limited data available on associations between calcium and magnesium and risk of T2D in populations with a dietary pattern different from that found in Western populations.
Acknowledgments
We thank the participants and research staff of the Shanghai Women's Health Study for their contributions to the study and Bethanie Hull for technical assistance in the preparation of this manuscript.
The authors' responsibilities were as follows—RV: conducted the statistical analyses and drafted the manuscript; YTG and GY: supervised the data collection; HL: provided critical assistance with the data collection; HC: provided critical assistance with the data analysis; Y-TG, QD, GY, HL, WZ, and XOS: provided critical review of the manuscript; and WZ and XOS: designed the study and secured funding. None of the authors had any financial conflicts of interest to declare.
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