Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Dec;40(12):1685-1694.
doi: 10.2337/dc17-0571. Epub 2017 Oct 18.

Time Trends of Dietary and Lifestyle Factors and Their Potential Impact on Diabetes Burden in China

Affiliations

Time Trends of Dietary and Lifestyle Factors and Their Potential Impact on Diabetes Burden in China

Yanping Li et al. Diabetes Care. 2017 Dec.

Erratum in

Abstract

Objective: To examine the secular trends in risk factors, estimate their impact on type 2 diabetes burden from 1991 to 2011, and project trends in the next 20 years.

Research design and methods: Risk factor distributions were based on data from the China Health and Nutrition Survey 1991-2011. Diabetes cases attributable to all nonoptimal levels of each risk factor were estimated by applying the comparative risk assessment method.

Results: In 2011, high BMI was the leading individual attributable factor for diabetes cases in China responsible for 43.8 million diabetes cases with a population-attributable fraction of 46.8%. Low whole-grain intake and high refined grain intake were the leading dietary risk factors in China responsible for 37.8 million and 21.8 million diabetes-attributable cases, respectively. The number of attributable diabetes cases associated with low physical activity, high blood pressure, and current smoking was 29.5, 21.6, and 9.8 million, respectively. Although intakes of low-fat dairy products, nuts, fruit, vegetables, and fish and seafood increased moderately over time, the average intake was below optimal levels in 2011 and were responsible for 15.8, 11.3, 9.9, 6.0, 3.6, and 2.6 million diabetes cases, respectively. Meanwhile, intakes of processed meat, red meat, and sugar-sweetened beverage showed increasing trends over time and were responsible for 2.8, 1.8, and 0.5 million diabetes cases, respectively, in 2011.

Conclusions: A high BMI and low intake of whole grains but high intake of refined grains are the most important individual risk factors related to Chinese diabetes burden; low physical activity and high blood pressure also significantly contributed.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Diabetes cases attributable to 14 individual risk factors in 2011.
Figure 2
Figure 2
Time trends and estimated diabetes cases attributable to high BMI (A), low physical activity (B), high SBP (C), and smoking (D). The mean (SE) of each risk factor distribution at each time point was standardized by age and sex distribution using the 2010 Chinese Population Census data as the standard.
Figure 3
Figure 3
Time trends and estimated diabetes cases attributable to a high intake of moderate dietary components (A) and a low intake of adequate dietary components (B). A.a: Refined grain. A.b: Processed meat. A.c: Red meat. A.d: SSBs. B.a: Whole grains. B.b: Low-fat dairy products. B.c: Nuts. B.d: Fruit. B.e: Vegetables. B.f: Fish and seafood. Solid bars represent diabetes cases; circles represent mean values; and bars represent SEs of each risk factor distribution at each time point, which were standardized by age and sex distribution using the 2010 Chinese Population Census.
Figure 3
Figure 3
Time trends and estimated diabetes cases attributable to a high intake of moderate dietary components (A) and a low intake of adequate dietary components (B). A.a: Refined grain. A.b: Processed meat. A.c: Red meat. A.d: SSBs. B.a: Whole grains. B.b: Low-fat dairy products. B.c: Nuts. B.d: Fruit. B.e: Vegetables. B.f: Fish and seafood. Solid bars represent diabetes cases; circles represent mean values; and bars represent SEs of each risk factor distribution at each time point, which were standardized by age and sex distribution using the 2010 Chinese Population Census.

Comment in

Similar articles

Cited by

References

    1. Yang W, Lu J, Weng J, et al. .; China National Diabetes and Metabolic Disorders Study Group . Prevalence of diabetes among men and women in China. N Engl J Med 2010;362:1090–1101 - PubMed
    1. Wang L, Gao P, Zhang M, et al. . Prevalence and ethnic pattern of diabetes and prediabetes in China in 2013. JAMA 2017;317:2515–2523 - PMC - PubMed
    1. National Diabetes Prevention Collaborative Group A mass survey of diabetes mellitus in a population of 300,000 in 14 provinces and municipalities in China. Zhonghua Nei Ke Za Zhi 1981;20:678–683 [author's translation] - PubMed
    1. Pan XR, Yang WY, Li GW, Liu J; National Diabetes Prevention and Control Cooperative Group . Prevalence of diabetes and its risk factors in China, 1994. Diabetes Care 1997;20:1664–1669 - PubMed
    1. Li LM, Rao KQ, Kong LZ, et al. .; Technical Working Group of China National Nutrition and Health Survey . A description on the Chinese national nutrition and health survey in 2002. Zhonghua Liu Xing Bing Xue Za Zhi 2005;26:478–484 [in Chinese] - PubMed

MeSH terms

Substances