Literature DB >> 29143718

Prediction of a new body shape index and body adiposity estimator for development of type 2 diabetes mellitus: The Rural Chinese Cohort Study.

Chengyi Han1, Yu Liu2, Xizhuo Sun2, Xinping Luo1, Lu Zhang1, Bingyuan Wang1, Yongcheng Ren1, Junmei Zhou1, Yang Zhao1, Dongdong Zhang1, Xuejiao Liu1, Ming Zhang1, Dongsheng Hu1.   

Abstract

To compare the ability of a body shape index (ABSI) and body adiposity estimator (BAE) to BMI, waist circumference (WC) and waist:height ratio (WHtR) for predicting development of type 2 diabetes mellitus (T2DM) in rural adult Chinese. The prospective cohort study included 11 687 eligible participants who were free of T2DM at baseline. The risk of new-onset T2DM for ABSI, BAE, BMI, WC and WHtR quintiles was estimated by Cox proportional-hazards regression at follow-up. We also compared the power of ABSI and BAE to BMI, WC and WHtR for predicting the development of T2DM. With increasing ABSI, BAE, BMI, WC and WHtR, T2DM incidence was substantially increased (P trend<0·0001). After adjustment for multi-covariates, risk of T2DM was increased from the second to fifth quintile as compared with first quintile for ABSI (1·27; 95 % CI 0·95, 1·69; 1·35; 95 % CI 1·00, 1·82; 1·75; 95 % CI 1·33, 2·32 and 1·87; 95 % CI 1·40, 2·49; P trend<0·0001); BAE (1·82; 95 % CI 1·38, 2·41; 1·93; 95 % CI 1·38, 2·68; 2·73; 95 % CI 1·94, 3·84 and 4·18; 95 % CI 2·98, 5·87; P trend<0·0001); BMI (1·42; 95 % CI 1·03, 1·97; 1·62; 95 % CI 1·18, 2·23; 2·59; 95 % CI 1·92, 3·50 and 3·90; 95 % CI 2·90, 5·26; P trend<0·0001); WC (1·53; 95 % CI 1·08, 2·17; 1·66; 95 % CI 1·18, 2·33; 2·72; 1·97, 3·76 and 4·09; 95 % CI 2·97, 5·62; P trend<0·0001); and WHtR (1·40; 95 % CI 0·98, 1·99; 2·06; 95 % CI 1·47, 2·88; 2·90; 95 % CI 2·10, 4·01 and 4·22; 95 % CI 3·05, 5·85; P trend<0·0001). ABSI, BAE, BMI, WC and WHR were effective and comparable in discriminating cases from non-cases of T2DM. Risk of T2DM was increased with elevated ABSI and BAE, but the predictive ability for T2DM did not differ than that of BMI, WC and WHtR in a rural Chinese population.

Entities:  

Keywords:  ABSI a body shape index; BAE body adiposity estimator; T2DM type 2 diabetes mellitus; WC waist circumference; WHtR waist:height ratio; A body shape index; BMI; Body adiposity estimator; Type 2 diabetes mellitus; Waist circumstance; Waist:height ratio

Mesh:

Year:  2017        PMID: 29143718     DOI: 10.1017/S0007114517002859

Source DB:  PubMed          Journal:  Br J Nutr        ISSN: 0007-1145            Impact factor:   3.718


  10 in total

Review 1.  Association of weight status and the risks of diabetes in adults: a systematic review and meta-analysis of prospective cohort studies.

Authors:  Hong-Jie Yu; Mandy Ho; Xiangxiang Liu; Jundi Yang; Pui Hing Chau; Daniel Yee Tak Fong
Journal:  Int J Obes (Lond)       Date:  2022-02-23       Impact factor: 5.551

2.  Association of body mass index and waist circumference with type 2 diabetes mellitus in older adults: a cross-sectional study.

Authors:  Kaizhi Bai; Xuejiao Chen; Rui Song; Wenlong Shi; Songhe Shi
Journal:  BMC Geriatr       Date:  2022-06-07       Impact factor: 4.070

3.  A Linear Relationship Between a Body Shape Index and Risk of Incident Type 2 Diabetes: A Secondary Analysis Based on a Retrospective Cohort Study in Japan.

Authors:  Wei Zhao; Jing-Jing Tong; Yong-Tong Cao; Jing-Hua Li
Journal:  Diabetes Metab Syndr Obes       Date:  2020-06-22       Impact factor: 3.168

4.  Meta-analytic evaluation for the spatio-temporal patterns of the associations between common risk factors and type 2 diabetes in mainland China.

Authors:  Ting Zhou; Xiang Liu; Yuanyuan Liu; Xiaosong Li
Journal:  Medicine (Baltimore)       Date:  2019-05       Impact factor: 1.817

5.  Body Shape Index Is a Stronger Predictor of Diabetes.

Authors:  Hiba Bawadi; Merna Abouwatfa; Sara Alsaeed; Abdelhamid Kerkadi; Zumin Shi
Journal:  Nutrients       Date:  2019-05-07       Impact factor: 5.717

6.  Samidorphan mitigates olanzapine-induced weight gain and metabolic dysfunction in rats and non-human primates.

Authors:  Jacobi I Cunningham; David J Eyerman; Mark S Todtenkopf; Reginald L Dean; Daniel R Deaver; Connie Sanchez; Mark Namchuk
Journal:  J Psychopharmacol       Date:  2019-07-11       Impact factor: 4.153

7.  Impact of Highly Saturated versus Unsaturated Fat Intake on Carbohydrate Metabolism and Vascular Reactivity in Rat.

Authors:  Youzan Ferdinand Djohan; Fabrice Raynaud; Karen Lambert; Jean-Paul Cristol; Charles Coudray; Christine Feillet-Coudray; Anne Virsolvy; Eric Badia
Journal:  Biochem Res Int       Date:  2022-08-19

8.  Association of anthropometric indices with the development of multimorbidity in middle-aged and older adults: A retrospective cohort study.

Authors:  Shuoji Geng; Xuejiao Chen; Zhan Shi; Kaizhi Bai; Songhe Shi
Journal:  PLoS One       Date:  2022-10-14       Impact factor: 3.752

9.  Relationship between multimorbidity, disease cluster and all-cause mortality among older adults: a retrospective cohort analysis.

Authors:  Kun He; Wenli Zhang; Xueqi Hu; Hao Zhao; Bingxin Guo; Zhan Shi; Xiaoyan Zhao; Chunyu Yin; Songhe Shi
Journal:  BMC Public Health       Date:  2021-06-05       Impact factor: 3.295

Review 10.  Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature Review.

Authors:  Paola Piqueras; Alfredo Ballester; Juan V Durá-Gil; Sergio Martinez-Hervas; Josep Redón; José T Real
Journal:  Front Psychol       Date:  2021-07-09
  10 in total

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