![]() |
|
|
3 Department of Medicine, Vanderbilt Epidemiology Center, Institute for Medicine and Public Health, Nashville, TN 37203-1738; 4 Shanghai Cancer Institute, Shanghai, 200032, China; and 5 Department of Medicine, Diabetes Research and Training Center, Nashville, TN 37232
* To whom correspondence should be addressed. E-mail: xiao-ou.shu{at}vanderbilt.edu.
| ABSTRACT |
|---|
|
|
|---|
| Introduction |
|---|
|
|
|---|
Data regarding the associations between fruit and vegetable intake and the risk of T2D are limited and inconsistent (3) and some studies were not properly adjusted for potential confounders (4–6). This is a problem because fruit and vegetable consumption may act as a marker for a healthy lifestyle. To our knowledge, only 3 studies have evaluated associations between specific subgroups of vegetables and hemoglobin A1c (HbA1c) and T2D incidence (3,7,8).
Asian populations traditionally have a lower risk of T2D and obesity than Western populations. However, that appears to be changing. The prevalence of both obesity and T2D have been increasing in Asian populations in recent years (9). In the baseline survey of the Shanghai Women's Health Study (SWHS) (10) conducted between 1997 and 2000, we found that the prevalence of T2D was 5.7%, the prevalence of BMI
23 kg/m2 was 59.1%, and that of BMI
25kg/m2 was 35.2% (our unpublished data). Change in dietary patterns is also taking place in China, including increased meat intake and decreased vegetable intake (11). Higher vegetable intake has been associated with less weight gain (12,13), a strong predictor for T2D, in Western populations. However, the association of vegetable intake with T2D risk in Chinese populations has not been well studied (14).
We evaluated the association of fruit and vegetable intake levels with the incidence of T2D in a large, population-based prospective study of middle-aged women conducted in Shanghai, China, where consumption of vegetables, especially leafy green vegetables, is high. We explored whether specific subgroups of vegetables differentially affect T2D risk and we evaluated the potential interactions of fruit and vegetable intake with obesity and physical activity categories.
| Methods |
|---|
|
|
|---|
Fruit and vegetable intake. Usual dietary intake was assessed through a personal interview using a validated FFQ at the baseline recruitment survey and again at the first follow-up survey (15). If women had a history of T2D, cancer, or cardiovascular disease reported between the baseline and follow-up surveys, we used dietary data from the baseline FFQ in the analysis. For other participants, we used the mean of the baseline and follow-up FFQ data. The means of the daily intake of individual food items (g/d) were summed to compute total fruit and vegetable intake. Soy beans, dried beans, and other legumes were not included as vegetables and were evaluated in a separate report. We created specific vegetable groups, including cruciferous vegetables, green leafy vegetables, yellow vegetables, tomatoes, allium vegetables, and other vegetables and fruit groups, including citrus, watermelon, and other fruits. (see Appendix). We used the Chinese Food Composition Tables (16) to estimate energy intake (kJ/d) and nutrient intakes. Of 64,227 participants who were free of T2D and other chronic diseases at baseline, we excluded participants who had extreme values for total energy intake (<2090 or >14,630 kJ/d; n = 36) (17), which left 64,191 participants for the final analysis.
|
A detailed assessment of physical activity was conducted using a validated questionnaire (19). The questionnaire evaluated regular exercise and sports participation during the last 5 y, daily activity, and the daily round-trip commute to work. We calculated the metabolic equivalents (MET) for each activity using a compendium of physical activity values (20). One MET (h/d) is roughly equivalent to 4.18 kJ·kg–1·d–1 or
15 min of moderate intensity (4 MET) activity for an average adult (20). We combined each of the exercise and lifestyle activity indices to derive a quantitative estimate of overall nonoccupational activity (MET-h/d). Occupation-related physical activity was not related to T2D in this population and thus was not included in the current analysis.
Information on sociodemographic factors such as age, level of education (none, elementary school, middle/high school, college), family income in yuan/y (<10,000, 10,000–19,999, 20,000–29,999,
30,000), occupation (professional, clerical, manual worker/other, housewife/retired), smoking (smoked at least 1 cigarette per day for >6 mo continuously), and alcohol consumption (ever drank beer, wine, or spirits at least 3 times per week), and presence of hypertension at baseline was collected by using a structured questionnaire.
Outcome ascertainment.
Incident T2D was identified through the follow-up surveys by asking study participants whether they had been diagnosed by a physician as having diabetes since the baseline recruitment and asking about their glucose test history and/or use of hypoglycemic medication. A total of 1608 study participants reported having a T2D diagnosis since the baseline survey. We considered a case of T2D as confirmed if a participant reported having been diagnosed with T2D and met at least 1 of the following criteria as recommended by the American Diabetes Association (21): fasting glucose level
7 mmol/L on at least 2 separate occasions; an oral glucose tolerance test with a value
11.1 mmol/L; and/or use of hypoglycemic medication (i.e. insulin or oral hypoglycemic drugs). Of the 1608 self-reported cases, a total of 896 participants met the study outcome criteria and are referred to herein as confirmed cases of T2D. We performed analyses with both confirmed and probable T2D cases and found similar results.
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 second follow-up survey. The Cox proportional hazards model was used to assess the association of fruit and vegetable intake with the incidence of T2D. Food groups (g/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. In all models, we adjusted for the following potential confounding variables: age, BMI, WHR, total energy, meat intake (all entered as continuous variables), as well as income level, education level, occupation, physical activity, smoking status, alcohol consumption status, and presence of hypertension at baseline (as categorical variables).
We conducted analyses stratified by BMI, WHR, and physical activity categories. The log-likelihood ratio test was used to evaluate multiplicative interactions between fruit and vegetable intake and categories of BMI, WHR, and physical activity.
We also conducted analyses adjusting for antioxidants (vitamin C, carotene, and vitamin E) and fiber. To reduce measurement error and to adjust for extraneous variation due to total energy intake, we adjusted these nutrients by total energy intake using the residual method described by Willett and Stampfer (22).
All analyses were performed using SAS (version 9.1) and all tests of statistical significance were based on 2-sided probability.
| Results |
|---|
|
|
|---|
23 kg/m2 was 56.7%, a BMI
25 kg/m2 was 32.64%, and BMI
27.5 kg/m2 was 13.10%.
|
|
In analyses restricted to confirmed diabetes cases, we found similar results (Table 3). We excluded participants who had been diagnosed with T2D during the first year of follow-up. The adjusted RR for T2D across quintiles relative to the lowest quintile were 1.00, 0.76, 0.68, 0.69, and 0.68 (P < 0.001) for vegetables and 1.00, 0.81, 0.83, 0.88, and 1.08 (P = 0.31) for fruit.
|
25) and WHR (<0.85 and >0.85) and physical activity levels (using the lower 25% quartile as the cut-off point of the MET distribution) with fruit and vegetable intake (Table 4). BMI, WHR, or physical activity did not modify the association between fruit and vegetable intake and T2D.
|
| Discussion |
|---|
|
|
|---|
Our study adds to the limited and conflicting data available on fruit and vegetable intake and the risk of T2D. An inverse association between vegetable, but not fruit, intake and glucose intolerance has been found in cross-sectional (6) and prospective studies (3,4,23) similar to our study. Inverse associations between both fruit and vegetable intake and the risk of glucose intolerance (5,8,24) and HbA1c (7) have been also been reported. However, other studies have found no association between fruit and/or vegetable intake and T2D risk (5,14,25–27) or levels of HBA1c (28). In a randomized control trial among 577 participants with impaired glucose tolerance conducted in China, a diet high in fruits and vegetables appeared to reduce the incidence of T2D by 24% (29). A diet high in fruit and vegetables was also associated with a higher insulin sensitivity in the Dietary Approaches to Stop Hypertension intervention trial (30).
Few studies have looked at individual vegetable groups and the risk of T2D. Yellow and dark-green vegetable intake has been associated with lower HbA1c levels and T2D incidence (3,7). In a middle-aged Finnish population, green vegetables but not yellow/red vegetables were associated with a lower incidence of T2D (8). In the Women's Health Study, BMI appeared to be an effect modifier on the association between green or dark-yellow vegetable intake and T2D (3). In our study, both green and yellow vegetable intakes were inversely associated with T2D. We found that neither BMI nor WHR modified the effect of vegetable intake on risk of T2D.
Several studies investigating the association between fruit and vegetable intake were based on cross-sectional surveys and adjusted for a limited number of confounders. For example, in the Seven Countries study, an inverse relationship between vegetable intake and 2-h glucose concentration in an oral glucose tolerance test was found, but the analyses were adjusted for only cohort, age, BMI, and energy intake (4). In a cross-sectional study of a Canadian native population, a protective effect of vegetables on impaired glucose tolerance or T2D was reported (OR = 0.41; 95%CI: 0.18–0.91) (5). This analysis, however, was adjusted for only age and sex. Another cross-sectional study in the UK found a decreased risk of T2D associated with salad and raw vegetable consumption (OR = 0.16; 95%CI: 0.04–0.81) with adjustment for age, sex, and family history of T2D (6). When BMI was adjusted for, the association was attenuated. None of these studies adjusted for smoking habits, physical activity, or meat intake.
The mechanism by which vegetables affect glucose tolerance has not been clearly defined but may be associated with the high content of antioxidants, (1) fiber (2), and magnesium (31) or the low glycemic index in vegetables (32). Chronic administration of vitamin E has been reported to improve insulin sensitivity (33) and vitamin C was associated with higher insulin action in both healthy and diabetic people (34). However, in the Health Professionals Follow-Up Study, there was no association with the incidence of T2D after 12 y of supplementation with β-carotene (35). In our study, the inverse association between vegetable intake and T2D persisted after adjustment for vitamin C, vitamin E, carotene, and fiber intake. Further adjustment for magnesium intake did not alter the association. Taking this evidence into consideration, it appears that the beneficial effects of vegetable consumption on the risk of T2D cannot be entirely explained by antioxidant vitamins, magnesium, or fiber intake. Vegetables also contain other compounds such as phytates, lignans, and isoflavones that might have an additive or synergistic effect on lowering the risk of T2D.
Our data suggest that fruit consumption is not associated with a lower risk of T2D in this population. Other studies have found similar results (3,6,23,27). We do not have a ready explanation as to why fruit was not associated with a lower risk of T2D in our study population. We speculate that the high fructose content of fruit may counteract the protective effect of antioxidants, fiber, and other antidiabetic compounds of fruit. It has been suggested that sugars containing fructose may play a major role in the development of hypertension, obesity, diabetes, the metabolic syndrome, and in the subsequent development of kidney disease (36). However, high serum uric acid concentrations, which have been associated with the metabolic syndrome (37), were not found to be related to fruit juice intake in a recent study using NHANES data (38). More research is needed to investigate the association between fructose in fruit and health outcomes.
Several alternative explanations should be considered when interpreting our findings. First, the exact benefit of fruit and vegetable intake is very difficult to assess when multiple factors such as exercise, not smoking, and maintaining a healthy weight may also be contributing a beneficial effect (the healthy lifestyle bias) and protecting participants from developing T2D. Fruit and vegetable consumption may act as a marker for a healthy lifestyle and healthy dietary pattern in general (6,39). This is a potential problem in many observational studies of diet and disease and it is difficult to exclude. However, in China, dietary patterns are quite different from Western societies. Vegetables are widely consumed in Shanghai and less correlated with socio-economic status. Fruit intake, on the other hand, is associated with higher socioeconomic factors in this population. Although we adjusted for education and income in the analysis, residual confounding remains a possible concern for our results, together with potential unmeasured confounders.
Participants in the SWHS are a representative sample of the Chinese, middle-aged female population in Shanghai. The prospective design, high participation rate, and high follow-up rates minimized the possibility of selection or recall bias. The repeated dietary measurements improved the quality of the dietary information and the extensive information available allowed us to adjust for a wide range of potentially confounding variables. An important limitation of our study is reliance on self-reports of T2D. Analyses restricted to participants whose diagnosis of T2D was confirmed according to our study criteria showed inverse associations between vegetable intake and the incidence of T2D. Recall of dietary intake is subject to misclassification. This kind of nondifferential misclassification would tend to weaken associations between fruit and vegetable intake and T2D. The prediagnostic or preclinical manifestations of T2D might have lead to changes in diet. After we excluded probable cases of T2D and participants diagnosed within the first year of follow-up, our analyses showed a clearer linear association of vegetable intake with T2D than analyses that included the total population. Further follow-up of the cohort would provide a more definite assessment of the vegetable and T2D association.
Our study adds to the limited and conflicting data of the associations between fruit and vegetable intake and the risk of T2D. A higher intake of vegetables, rich in fiber, antioxidants, and magnesium and with a low glycemic index, was associated with a decreased risk of T2D.
| FOOTNOTES |
|---|
2 Author disclosures: R. Villegas, X. O. Shu, Y.-T. Gao, G. Yang, T. Elasy, H. Li, and W. Zheng, no conflicts of interest. ![]()
6 Abbreviations used: HbA1c, hemoglobin A1c; MET, metabolic equivalent; RR, risk ratio; SWHS, Shanghai Women's Health Study; T2D, type 2 diabetes; WHR, waist-to-hip ratio. ![]()
Manuscript received 27 July 2007. Initial review completed 22 September 2007. Revision accepted 20 December 2007.
| LITERATURE CITED |
|---|
|
|
|---|
1. Walker KZ, O'Dea K, Nicholson GC, Muir JG. Dietary composition, body weight, and NIDDM. Comparison of high-fiber, high-carbohydrate, and modified-fat diets. Diabetes Care. 1995;18:401–3.[Abstract]
2. Hu FB, van Dam RM, Liu S. Diet and risk of Type II diabetes: the role of types of fat and carbohydrate. Diabetologia. 2001;44:805–17.[Medline]
3. Liu S, Serdula M, Janket SJ, Cook NR, Sesso HD, Willett WC, Manson JE, Buring JE. A prospective study of fruit and vegetable intake and the risk of type 2 diabetes in women. Diabetes Care. 2004;27:2993–6.
4. Feskens EJ, Virtanen SM, Rasanen L, Tuomilehto J, Stengard J, Pekkanen J, Nissinen A, Kromhout D. Dietary factors determining diabetes and impaired glucose tolerance. A 20-year follow-up of the Finnish and Dutch cohorts of the Seven Countries Study. Diabetes Care. 1995;18:1104–12.[Abstract]
5. Gittelsohn J, Wolever TM, Harris SB, Harris-Giraldo R, Hanley AJ, Zinman B. Specific patterns of food consumption and preparation are associated with diabetes and obesity in a Native Canadian community. J Nutr. 1998;128:541–7.
6. Williams DE, Wareham NJ, Cox BD, Byrne CD, Hales CN, Day NE. Frequent salad vegetable consumption is associated with a reduction in the risk of diabetes mellitus. J Clin Epidemiol. 1999;52:329–35.[Medline]
7. Sargeant LA, Khaw KT, Bingham S, Day NE, Luben RN, Oakes S, Welch A, Wareham NJ. Fruit and vegetable intake and population glycosylated haemoglobin levels: the EPIC-Norfolk Study. Eur J Clin Nutr. 2001;55:342–8.[Medline]
8. Montonen J, Jarvinen R, Heliovaara M, Reunanen A, Aromaa A, Knekt P. Food consumption and the incidence of type II diabetes mellitus. Eur J Clin Nutr. 2005;59:441–8.[Medline]
9. Yoon KH, Lee JH, Kim JW, Cho JH, Choi YH, Ko SH, Zimmet P, Son HY. Epidemic obesity and type 2 diabetes in Asia. Lancet. 2006;368:1681–8.[Medline]
10. Zheng W, Chow WH, Yang G, Jin F, Rothman N, Blair A, Li HL, Wen W, Ji BT, Li Q, Shu XO, Gao YT. The Shanghai Women's Health Study: rationale, study design, and baseline characteristics. Am J Epidemiol. 2005;162:1123–31.
11. Popkin BM, Du S. Dynamics of the nutrition transition toward the animal foods sector in China and its implications: a worried perspective. J Nutr. 2003; 133(11 Suppl 2)3898–906.
12. He K, Hu FB, Colditz GA, Manson JE, Willett WC, Liu S. Changes in intake of fruits and vegetables in relation to risk of obesity and weight gain among middle-aged women. Int J Obes Relat Metab Disord. 2004;28:1569–74.[Medline]
13. Bes-Rastrollo M, Martinez-Gonzalez MA, Sanchez-Villegas A, de la Fuente AC, Martinez JA. Association of fiber intake and fruit/vegetable consumption with weight gain in a Mediterranean population. Nutrition. 2006;22:504–11.[Medline]
14. Woo J, Ho SC, Sham A, Sea MM, Lam KS, Lam TH, Janus ED. Diet and glucose tolerance in a Chinese population. Eur J Clin Nutr. 2003;57:523–30.[Medline]
15. Shu XO, Yang G, Jin F, Liu D, Kushi L, Wen W, Gao YT, Zheng W. Validity and reproducibility of the food frequency questionnaire used in the Shanghai Women's Health Study. Eur J Clin Nutr. 2004;58:17–23.[Medline]
16. Yang G, Wang G, Pan X. China food composition. Beijing: Peking University Medical Press; 2002.
17. Joshipura KJ, Hu FB, Manson JE, Stampfer MJ, Rimm EB, Speizer FE, Colditz G, Ascherio A, Rosner B, Spiegelman D, Willett WC. The effect of fruit and vegetable intake on risk for coronary heart disease. Ann Intern Med. 2001;134:1106–14.
18. Zhang X, Shu XO, Gao YT, Yang G, Matthews CE, Li Q, Li H, Jin F, Zheng W. Anthropometric predictors of coronary heart disease in Chinese women. Int J Obes Relat Metab Disord. 2004;28:734–40.[Medline]
19. Matthews CE, Shu XO, Yang G, Jin F, Ainsworth BE, Liu D, Gao YT, Zheng W. Reproducibility and validity of the Shanghai Women's Health Study physical activity questionnaire. Am J Epidemiol. 2003;158:1114–22.
20. Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, O'Brien WL, Bassett Jr DR, Schmitz KH, Emplaincourt PO, Jacobs Jr DR, Leon AS. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. 2000; 32 Suppl 9:S498–504.
21. ADA. Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care. 1997;20:1183–97.[Medline]
22. Willet W, Stampfer M. Implications of total energy intake for epidemiological analysis. In: Willet W, editor. Nutritional epidemiology. New York: Oxford University Press. 1998.
23. Colditz GA, Manson JE, Stampfer MJ, Rosner B, Willett WC, Speizer FE. Diet and risk of clinical diabetes in women. Am J Clin Nutr. 1992;55:1018–23.
24. Ford ES, Mokdad AH. Fruit and vegetable consumption and diabetes mellitus incidence among U.S. adults. Prev Med. 2001;32:33–9.[Medline]
25. Hodge AM, English DR, O'Dea K, Giles GG. Glycemic index and dietary fiber and the risk of type 2 diabetes. Diabetes Care. 2004;27:2701–6.
26. Lundgren H, Bengtsson C, Blohme G, Isaksson B, Lapidus L, Lenner RA, Saaek A, Winther E. Dietary habits and incidence of noninsulin-dependent diabetes mellitus in a population study of women in Gothenburg, Sweden. Am J Clin Nutr. 1989;49:708–12.
27. Meyer KA, Kushi LH, Jacobs DR Jr, Slavin J, Sellers TA, Folsom AR. Carbohydrates, dietary fiber, and incident type 2 diabetes in older women. Am J Clin Nutr. 2000;71:921–30.
28. Gulliford MC, Ukoumunne OC. Determinants of glycated haemoglobin in the general population: associations with diet, alcohol and cigarette smoking. Eur J Clin Nutr. 2001;55:615–23.[Medline]
29. Pan XR, Li GW, Hu YH, Wang JX, Yang WY, An ZX, Hu ZX, Lin J, Xiao JZ, et al. Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance. The Da Qing IGT and Diabetes Study. Diabetes Care. 1997;20:537–44.[Abstract]
30. Ard JD, Grambow SC, Liu D, Slentz CA, Kraus WE, Svetkey LP. The effect of the PREMIER interventions on insulin sensitivity. Diabetes Care. 2004;27:340–7.
31. Lopez-Ridaura R, Willett WC, Rimm EB, Liu S, Stampfer MJ, Manson JE, Hu FB. Magnesium intake and risk of type 2 diabetes in men and women. Diabetes Care. 2004;27:134–40.
32. Jenkins DJ, Wolever TM, Buckley G, Lam KY, Giudici S, Kalmusky J, Jenkins AL, Patten RL, Bird J, et al. Low-glycemic-index starchy foods in the diabetic diet. Am J Clin Nutr. 1988;48:248–54.
33. Paolisso G, D'Amore A, Giugliano D, Ceriello A, Varricchio M, D'Onofrio F. Pharmacologic doses of vitamin E improve insulin action in healthy subjects and non-insulin-dependent diabetic patients. Am J Clin Nutr. 1993;57:650–6.
34. Paolisso G, D'Amore A, Balbi V, Volpe C, Galzerano D, Giugliano D, Sgambato S, Varricchio M, D'Onofrio F. Plasma vitamin C affects glucose homeostasis in healthy subjects and in non-insulin-dependent diabetics. Am J Physiol. 1994;266:261–8.
35. Liu S, Ajani U, Chae C, Hennekens C, Buring JE, Manson JE. Long-term beta-carotene supplementation and risk of type 2 diabetes mellitus: a randomized controlled trial. JAMA. 1999;282:1073–5.
36. Johnson RJ, Segal MS, Sautin Y, Nakagawa T, Feig DI, Kang DH, Gersch MS, Benner S, Sanchez-Lozada LG. Potential role of sugar (fructose) in the epidemic of hypertension, obesity and the metabolic syndrome, diabetes, kidney disease, and cardiovascular disease. Am J Clin Nutr. 2007;86:899–906.
37. Hayden MR, Tyagi SC. Uric acid: a new look at an old risk marker for cardiovascular disease, metabolic syndrome, and type 2 diabetes mellitus: the urate redox shuttle. Nutr Metab (Lond). 2004;1:10.[Medline]
38. Gao X, Qi L, Qiao N, Choi HK, Curhan G, Tucker KL, Ascherio A. Intake of added sugar and sugar-sweetened drink and serum uric acid concentration in US men and women. Hypertension. 2007;50:306–12.
39. Williams DE, Prevost AT, Whichelow MJ, Cox BD, Day NE, Wareham NJ. A cross-sectional study of dietary patterns with glucose intolerance and other features of the metabolic syndrome. Br J Nutr. 2000;83:257–66.[Medline]
This article has been cited by other articles:
![]() |
B. N. Hopping, E. Erber, A. Grandinetti, M. Verheus, L. N. Kolonel, and G. Maskarinec Dietary Fiber, Magnesium, and Glycemic Load Alter Risk of Type 2 Diabetes in a Multiethnic Cohort in Hawaii J. Nutr., January 1, 2010; 140(1): 68 - 74. [Abstract] [Full Text] [PDF] |
||||
![]() |
R. Villegas, Y.-T. Gao, Q. Dai, G. Yang, H. Cai, H. Li, W. Zheng, and X. O. Shu Dietary calcium and magnesium intakes and the risk of type 2 diabetes: the Shanghai Women's Health Study Am. J. Clinical Nutrition, April 1, 2009; 89(4): 1059 - 1067. [Abstract] [Full Text] [PDF] |
||||
![]() |
R. Ramon, F. Ballester, C. Iniguez, M. Rebagliato, M. Murcia, A. Esplugues, A. Marco, M. G. de la Hera, and J. Vioque Vegetable but Not Fruit Intake during Pregnancy Is Associated with Newborn Anthropometric Measures J. Nutr., March 1, 2009; 139(3): 561 - 567. [Abstract] [Full Text] [PDF] |
||||
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||