Conicity-index predicts all-cause mortality in Chinese older people: a 10-year community follow-up

• Published in: BMC geriatrics Vol. 22; no. 1; p. 971
• Main Authors: Zhang, Anhang, Li, Yingnan, Ma, Shouyuan, Bao, Qiligeer, Sun, Jin, Cai, Shuang, Li, Man, Su, Yongkang, Cheng, Bokai, Dong, Jing, Zhang, Yan, Wang, Shuxia, Zhu, Ping
• Format: Journal Article
• Language: English
• Published: England BioMed Central 16.12.2022; BMC
• Subjects: Abdomen; Abdominal obesity (AO); Activities of daily living; Aged; All-cause mortality; Blood Glucose; Blood Pressure; Body Mass Index; Cardiovascular disease; Cholesterol; Community; Conicity-index (C-index); Creatinine; Diabetes; East Asian People; Female; Follow-Up Studies; Gender; Geriatrics; Glucose; Hemoglobin; High density lipoprotein; Hospitals; Humans; Hypertension; Lipids; Lipoproteins; Low density lipoprotein; Male; Mortality; Obesity; Obesity - epidemiology; Obesity, Abdominal; Older people; Overweight; Population studies; Questionnaires; Regression analysis; Risk Factors; ROC Curve; Statistical analysis; Survival; Survival analysis; Uric Acid; Urine; Variance analysis; Beijing China; China; Conicity-index (C-index); Abdominal obesity (AO); All-cause mortality; Older people; Community
• ISSN: 1471-2318; 1471-2318
• DOI: 10.1186/s12877-022-03664-6

Abdominal obesity (AO) has been regarded as the most dangerous type of obesity. The Conicity-index (C-index) had a high ability to discriminate underlying AO. The purpose of this study was to determine the ability of C-index to predict all-cause mortality among non-cancer Chinese older people. The participants were residents of the Wanshou Road community in Beijing, China. Receiver operating curve (ROC) curves were used to determine the sensitivity and specificity of the best cut-off values for different anthropometric measures for predicting all-cause mortality. The area under the curve (AUC) of the ROC curves were calculated to compare the relative ability of various anthropometric measures to correctly identify older people in the community where all-cause mortality occurs. Included subjects were grouped according to C-index tertiles. The association between C-index and all-cause mortality was verified using Kaplan-Meier survival analysis and different Cox regression models. During a mean follow-up period of 9.87 years, 1821 subjects completed follow-up. The average age was 71.21 years, of which 59.4% were female. The ROC curve results showed that the AUC of the C-index in predicting all-cause mortality was 0.633. Kaplan-Meier survival curves showed a clear dose-response relationship between C-index and all-cause mortality. With the increase of C-index, the survival rate of the study population showed a significant downward trend (P < 0.05). Adjusted for age, gender, hip circumference, systolic blood pressure, diastolic blood pressure, fasting blood glucose (FBG), 2-h postprandial blood glucose (2hPG), glycosylated hemoglobin, high-density lipids protein (LDL), triglyceride, serum creatinine, serum uric acid, urine albumin-creatinine ratio (UACR), Mini-Mental State Examination (MMSE), smoking history, and drinking history, COX regression analysis showed that in the model adjusted for all covariates, the risk of all-cause mortality in tertile 3 was 1.505 times that in tertile 1, and the difference was statistically significant. The C-index is an independent risk factor for all-cause mortality in the non-cancer Chinese older people.