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Dairy Products Consumption and Risk of Type 2 Diabetes: Systematic Review and Dose-Response Meta-Analysis

Author

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  • Dengfeng Gao
  • Ning Ning
  • Congxia Wang
  • Yuhuan Wang
  • Qing Li
  • Zhe Meng
  • Yang Liu
  • Qiang Li

Abstract

Background: The consumption of dairy products may influence the risk of type 2 diabetes mellitus (T2DM), but inconsistent findings have been reported. Moreover, large variation in the types of dairy intake has not yet been fully explored. Methods and Results: We conducted a systematic review and meta-analysis to clarify the dose–response association of dairy products intake and T2DM risk. We searched PubMed, EMBASE and Scopus for studies of dairy products intake and T2DM risk published up to the end of October 2012. Random-effects models were used to estimate summary relative risk (RR) statistics. Dose-response relations were evaluated using data from different dairy products in each study. We included 14 articles of cohort studies that reported RR estimates and 95% confidence intervals (95% CIs) of T2DM with dairy products intake. We found an inverse linear association of consumption of total dairy products (13 studies), low-fat dairy products (8 studies), cheese (7 studies) and yogurt (7 studies) and risk of T2DM. The pooled RRs were 0.94 (95% CI 0.91–0.97) and 0.88 (0.84–0.93) for 200 g/day total and low-fat dairy consumption, respectively. The pooled RRs were 0.80 (0.69–0.93) and 0.91 (0.82–1.00) for 30 g/d cheese and 50 g/d yogurt consumption, respectively. We also found a nonlinear association of total and low-fat dairy intake and T2DM risk, and the inverse association appeared to be strongest within 200 g/d intake. Conclusion: A modest increase in daily intake of dairy products such as low fat dairy, cheese and yogurt may contribute to the prevention of T2DM, which needs confirmation in randomized controlled trials.

Suggested Citation

  • Dengfeng Gao & Ning Ning & Congxia Wang & Yuhuan Wang & Qing Li & Zhe Meng & Yang Liu & Qiang Li, 2013. "Dairy Products Consumption and Risk of Type 2 Diabetes: Systematic Review and Dose-Response Meta-Analysis," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-15, September.
    • Handle: RePEc:plo:pone00:0073965
    DOI: 10.1371/journal.pone.0073965
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    References listed on IDEAS

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    1. Nicola Orsini & Rino Bellocco & Sander Greenland, 2006. "Generalized least squares for trend estimation of summarized dose–response data," Stata Journal, StataCorp LLC, vol. 6(1), pages 40-57, March.
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    2. María Angélica Arbeláez & Alejandro Becerra & Miguel Benítez & Ximena Cadena & María José Mejía, 2021. "Elementos para el diseno de un impuesto a alimentos y bebidas altos en sodio, grasas y/o azúcares en Colombia," Coyuntura Económica, Fedesarrollo, vol. 51, pages 37-79, December.
    3. Chandra Yogal & Sunila Shakya & Biraj Karmarcharya & Rajendra Koju & Astrid Kamilla Stunes & Mats Peder Mosti & Miriam K. Gustafsson & Bjørn Olav Åsvold & Berit Schei & Unni Syversen, 2022. "Diabetes Prevalence and Associated Risk Factors among Women in a Rural District of Nepal Using HbA1c as a Diagnostic Tool: A Population-Based Study," IJERPH, MDPI, vol. 19(12), pages 1-15, June.
    4. Siekmans,Kendra & Fracassi,Patrizia & Kato,Tomoko & Seow,Ti Kian & Carter,Diana & Horton,Susan E. & Dizon,Felipe Jr Fadullon & Shibata Okamura,Kyoko, 2024. "Understanding the Links between Diet Quality, Malnutrition, and Economic Costs : An Evidence Review for LMICs," Policy Research Working Paper Series 10747, The World Bank.
    5. Li Lin & Ciyong Lu & Weiqing Chen & Vivian Yawei Guo, 2021. "Daytime Napping and Nighttime Sleep Duration with Incident Diabetes Mellitus: A Cohort Study in Chinese Older Adults," IJERPH, MDPI, vol. 18(9), pages 1-13, May.

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