Prospective study of dietary carbohydrates, glycemic index, glycemic load, and incidence of type 2 diabetes mellitus in middle-aged Chinese women
Abstract
BACKGROUND: Much uncertainty exists about the role of dietary glycemic index and glycemic load in the development of type 2 diabetes mellitus, especially in populations that traditionally subsist on a diet high in carbohydrates. METHODS: We observed a cohort of 64,227 Chinese women with no history of diabetes or other chronic disease at baseline for 4.6 years. In-person interviews were conducted to collect data on dietary habits, physical activity, and other relevant information using a validated questionnaire. Incident diabetes cases were identified via in-person follow-up. Associations between dietary carbohydrate intake, glycemic index, and glycemic load and diabetes incidence were evaluated using multivariable Cox proportional hazards models. RESULTS: We identified 1,608 incident cases of type 2 diabetes mellitus in 297,755 person-years of follow-up. Dietary carbohydrate intake and consumption of rice were positively associated with risk of developing type 2 diabetes mellitus. The multivariable-adjusted estimates of relative risk comparing the highest vs the lowest quintiles of intake were 1.28 (95% confidence interval, 1.09-1.50) for carbohydrates and 1.78 (95% confidence interval, 1.48-2.15) for rice. The relative risk for increasing quintiles of intake was 1.00, 1.04, 1.02, 1.09, and 1.21 (95% confidence interval, 1.03-1.43) for dietary glycemic index and 1.00, 1.06, 0.97, 1.23, and 1.34 (95% confidence interval, 1.13-1.58) for dietary glycemic load. CONCLUSION: High intake of foods with a high glycemic index and glycemic load, especially rice, the main carbohydrate-contributing food in this population, may increase the risk of type 2 diabetes mellitus in Chinese women.
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High intake of foods with a high glycemic index or glycemic load, especially white rice, is associated with increased risk of diabetes (RR comparing highest to lowest quintile of white rice intake: 1.78 [95% CI 1.48-2.15]).
“Findings from the Shanghai Women's Health Study (SWHS) indicate that high intake of foods with a high GI or GL, especially white rice, is associated with increased risk of diabetes (RR comparing highest to lowest quintile of white rice intake: 1.78 [95% CI 1.48–2.15]) (22).”
From Globalization of Diabetes (2011) · cites this paper as [22]
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- Authors
- Villegas, R., Liu, S., Gao, Y.-T., Yang, G., Li, H., Zheng, W., & Shu, X. O.
- Affiliations
- Vanderbilt University Medical Center (US)
- University of California, Los Angeles (US)
- Venue
- Archives of Internal Medicine
- Publisher
- American Medical Association (AMA)
- Published
- 2007-11-26
- Volume
- 167
- Issue
- 21
- Pages
- 2310
- ISSN
- 0003-9926 (ISSN-L)
- OpenAlex
- W2090757087
- Cited by
- 431
- References
- 43
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 21 · 2023: 16 · 2022: 19 · 2021: 28 · 2020: 31 · 2019: 20 · 2018: 37 · 2017: 18 · 2016: 27 · 2015: 30 · 2014: 32 · 2013: 32 · 2012: 31
- FWCI
- 14.86
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Archives of Internal Medicine (publishedVersion)
- PubMed (publishedVersion)
- Funders
- U.S. Public Health Service (R01 NL079123)
- National Cancer Institute (R01 CA70867, R01CA070867)
- Topics
- Health Sciences › Nursing › Nutrition and Dietetics › Food composition and properties
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diet, Metabolism, and Disease
- Keywords
- type 2 diabetes, dietary glycemic index, glycemic load, dietary carbohydrates, rice consumption, middle-aged women, Chinese women, diabetes incidence, high-carbohydrate diet
- MeSH terms
- Adult, Aged, Blood Glucose, China, Data Collection, Diabetes Mellitus, Type 2, Dietary Carbohydrates, Female, Follow-Up Studies, Humans, Middle Aged, Prospective Studies, Surveys and Questionnaires, Oryza, Risk Factors, Time Factors, Cohort Studies, Incidence, Multivariate Analysis, Proportional Hazards Models, Glycemic Index
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