Literature DB >> 36089644

Association of major dietary patterns and different obesity phenotypes in Southwest China: the China Multi-Ethnic Cohort (CMEC) Study.

Yuan Zhang1, Yonglan Wei2, Dan Tang1, Jiaojiao Lu1, Ning Zhang1, Yifan Hu1, Ruifeng He3, Han Guan4, Jingru Xu5, Songmei Wang6, Xing Zhao1, Kangzhuo Baima7,8, Xiong Xiao9.   

Abstract

PURPOSE: Dietary behavior is an important part of lifestyle interventions for obesity and its cardiovascular comorbidities. However, little is known about associations between dietary patterns and obesity phenotypes in Southwest China, a region with unique dietary patterns and significant heterogeneity in obesity.
METHODS: Data from the baseline survey of the China Multi-Ethnic Cohort in Southwest China were analyzed (n = 64,448). Dietary intakes during the past year were measured with the semi-quantitative Food Frequency Questionnaire (s-FFQ). Principal component factor analysis (PCFA) was used to identify dietary patterns. Multinomial logistic regressions were used to examine the associations between dietary patterns and obesity phenotypes and stratified analyses were performed to assess whether the associations differed across demographic variables.
RESULTS: Three dietary patterns were identified and then named according to their apparent regional gathering characteristics: the Sichuan Basin dietary pattern (characterized by high intakes of various foods), the Yunnan-Guizhou Plateau dietary pattern (characterized by agricultural lifestyles), and the Qinghai-Tibet Plateau dietary pattern (characterized by animal husbandry lifestyles), respectively. Higher adherence to the Sichuan Basin dietary pattern was positively associated with metabolically healthy overweight/obesity (MHO, OR 1.13, 95% CI 1.05-1.21) but negatively associated with metabolically unhealthy normal weight (MUNW, OR 0.78, 95% CI 0.65-0.95). Higher adherence to the other two dietary patterns was positively associated with MHO and metabolically unhealthy overweight/obesity (MUO). Besides, differences in socioeconomic status also affected the relationship between dietary patterns and obesity phenotypes.
CONCLUSIONS: Adherence to the more diverse Sichuan basin dietary pattern performed a mixed picture, while the other two may increase the risk of obesity phenotypes, which indicates nutritional interventions are urgently needed.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.

Entities:  

Keywords:  China; Dietary patterns; Factor analysis; Metabolic syndrome; Obesity phenotypes

Year:  2022        PMID: 36089644     DOI: 10.1007/s00394-022-02997-7

Source DB:  PubMed          Journal:  Eur J Nutr        ISSN: 1436-6207            Impact factor:   4.865


  43 in total

Review 1.  Epidemiology and determinants of obesity in China.

Authors:  Xiong-Fei Pan; Limin Wang; An Pan
Journal:  Lancet Diabetes Endocrinol       Date:  2021-06       Impact factor: 32.069

2.  Metabolically healthy obese phenotype and risk of cardiovascular disease: Results from the China Health and Retirement Longitudinal Study.

Authors:  Haibin Li; Dian He; Deqiang Zheng; Endawoke Amsalu; Anxin Wang; Lixin Tao; Jin Guo; Xia Li; Wei Wang; Xiuhua Guo
Journal:  Arch Gerontol Geriatr       Date:  2019-01-25       Impact factor: 3.250

3.  Metabolically healthy obesity increased diabetes incidence in a middle-aged and elderly Chinese population.

Authors:  Yue Wei; Jing Wang; Xu Han; Caizheng Yu; Fei Wang; Jing Yuan; Xiaoping Miao; Ping Yao; Sheng Wei; Youjie Wang; Yuan Liang; Xiaomin Zhang; Huan Guo; Dan Zheng; Yuhan Tang; Handong Yang; Meian He
Journal:  Diabetes Metab Res Rev       Date:  2019-07-18       Impact factor: 4.876

Review 4.  The metabolic syndrome.

Authors:  Robert H Eckel; Scott M Grundy; Paul Z Zimmet
Journal:  Lancet       Date:  2005 Apr 16-22       Impact factor: 79.321

5.  Effects of blood pressure lowering on cardiovascular risk according to baseline body-mass index: a meta-analysis of randomised trials.

Authors:  A Ying; H Arima; S Czernichow; M Woodward; R Huxley; F Turnbull; V Perkovic; B Neal
Journal:  Lancet       Date:  2014-11-04       Impact factor: 79.321

6.  Metabolically healthy obesity: epidemiology, mechanisms, and clinical implications.

Authors:  Norbert Stefan; Hans-Ulrich Häring; Frank B Hu; Matthias B Schulze
Journal:  Lancet Diabetes Endocrinol       Date:  2013-08-30       Impact factor: 32.069

Review 7.  Dyslipidemia in obesity: mechanisms and potential targets.

Authors:  Boudewijn Klop; Jan Willem F Elte; Manuel Castro Cabezas
Journal:  Nutrients       Date:  2013-04-12       Impact factor: 5.717

Review 8.  Prevalence of metabolic syndrome in Mainland China: a meta-analysis of published studies.

Authors:  Ri Li; Wenchen Li; Zhijun Lun; Huiping Zhang; Zhi Sun; Joseph Sam Kanu; Shuang Qiu; Yi Cheng; Yawen Liu
Journal:  BMC Public Health       Date:  2016-04-01       Impact factor: 3.295

9.  Metabolically healthy obesity, transition to unhealthy metabolic status, and vascular disease in Chinese adults: A cohort study.

Authors:  Meng Gao; Jun Lv; Canqing Yu; Yu Guo; Zheng Bian; Ruotong Yang; Huaidong Du; Ling Yang; Yiping Chen; Zhongxiao Li; Xi Zhang; Junshi Chen; Lu Qi; Zhengming Chen; Tao Huang; Liming Li
Journal:  PLoS Med       Date:  2020-10-30       Impact factor: 11.069

10.  Inhibiting calpain 1 and 2 in cyclin G associated kinase-knockout mice mitigates podocyte injury.

Authors:  Xuefei Tian; Kazunori Inoue; Yan Zhang; Ying Wang; C John Sperati; Christopher E Pedigo; Tingting Zhao; Meihua Yan; Marwin Groener; Dennis G Moledina; Karen Ebenezer; Wei Li; Zhenhai Zhang; Dan A Liebermann; Lois Greene; Peter Greer; Chirag R Parikh; Shuta Ishibe
Journal:  JCI Insight       Date:  2020-11-19
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.