Literature DB >> 33324082

Forecasting the Populations of Overweight and Obese Chinese Adults.

Ruhai Bai1,2, Wentao Wu3, Wanyue Dong3,4, Jinli Liu3, Lili Yang5, Jun Lyu1.   

Abstract

PURPOSE: The objective of this study was to forecast the prevalence rates and the populations of overweight and obese in Chinese adults for 2030.
MATERIALS AND METHODS: Nine waves of China Health and Nutrition Survey (CHNS) data from 1991 to 2015 were used. A polynomial regression model was fitted to obtain the average BMI change trajectory of the population born in different years according to different sexes and residence areas (urban and rural). The model fitted to CHNS 2015 survey data was used to forecast the distribution of BMI and the prevalence rates of overweight and obesity in 15 years. The United Nations population forecast was then used to predict the proportions of overweight obese adults in all age groups in China in 2030.
RESULTS: The prevalence rates of overweight and obesity were projected to increase in both sexes and all geographic areas in future. By 2030, urban males will have the highest prevalence of overweight, 50.7% (95% CI: 47.5%, 53.9%). Except urban males, the prevalence of overweight and obesity in rural areas will exceed that in urban for both sexes. In 2030, the numbers of overweight and obese people in China aged 20-89 years will reach 540 million and 150 million, respectively, which are 2.8 and 7.5 times higher compared to prevalences in 2000. In 2030, the number of overweight and obese people in China aged 60-89 years will reach 200 million and 40 million, respectively, 6.3 and 8.5 times increments from the year 2000.
CONCLUSION: The prevalence rates of overweight and obese in Chinese adults are projected to increase further, by 2030 more than half of adult males living in urban areas will be overweight. Combined with changes in the population age structure, overweight and obesity will have a huge impact on the health of the Chinese population over the next 15 years.
© 2020 Bai et al.

Entities:  

Keywords:  BMI; aging; population; overweight; obesity; prediction

Year:  2020        PMID: 33324082      PMCID: PMC7733397          DOI: 10.2147/DMSO.S274110

Source DB:  PubMed          Journal:  Diabetes Metab Syndr Obes        ISSN: 1178-7007            Impact factor:   3.168


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