Y Wang1, S He, J He, S Wang, K Liu, X Chen. 1. Department of Cardiovascular Medicine, West China Hospital, Sichuan University, 610041, Chengdu, China.
Abstract
BACKGROUND: The emerging term "visceral adiposity index (VAI)" was reported to be closely correlated with glycemic disturbances and diabetes risk. However, whether VAI could predict future type 2 diabetes mellitus (DM) is unknown. Here, we aimed to assess the predictive value of VAI for DM in a Chinese population via a prospective cohort study. PATIENTS AND METHODS: This prospective cohort study was conducted based on a 15-year follow-up in a general Chinese population from an urban community. In all, 711 subjects underwent a health examination in 1992, and in 2007 the same examination was repeated. Twenty-four subjects were excluded from the analysis because DM was diagnosed at baseline. Waist circumference (WC), body mass index (BMI), VAI, and cardiovascular risk factors were collected at baseline. Hazard ratios (HRs) for DM incidence were estimated applying Cox proportional hazards models. Paired homogeneity tests were used to explore whether there was a statistical difference between the HRs of VAI and the other two indicators. RESULTS: In all, 74 individuals developed DM during a follow-up of 15 years. The risk of future DM increased with increasing levels of VAI. After adjusting for confounders, for each SD increment in natural logarithm-transformed VAI, BMI, and WC the HRs were 1.538 (95 % CI: 1.225-1.930), 1.639 (95 % CI: 1.289-2.084) and 1.858 (95 % CI: 1.458-2.369), respectively. However, paired homogeneity tests showed no statistical difference among the HRs. CONCLUSION: VAI could independently predict DM in the Chinese study population, although the predictive power was not higher than that of simple anthropometric measures (BMI and WC). Our study does not support the clinical application of VAI; however, more studies based on different ethnic groups still need to be performed.
BACKGROUND: The emerging term "visceral adiposity index (VAI)" was reported to be closely correlated with glycemic disturbances and diabetes risk. However, whether VAI could predict future type 2 diabetes mellitus (DM) is unknown. Here, we aimed to assess the predictive value of VAI for DM in a Chinese population via a prospective cohort study. PATIENTS AND METHODS: This prospective cohort study was conducted based on a 15-year follow-up in a general Chinese population from an urban community. In all, 711 subjects underwent a health examination in 1992, and in 2007 the same examination was repeated. Twenty-four subjects were excluded from the analysis because DM was diagnosed at baseline. Waist circumference (WC), body mass index (BMI), VAI, and cardiovascular risk factors were collected at baseline. Hazard ratios (HRs) for DM incidence were estimated applying Cox proportional hazards models. Paired homogeneity tests were used to explore whether there was a statistical difference between the HRs of VAI and the other two indicators. RESULTS: In all, 74 individuals developed DM during a follow-up of 15 years. The risk of future DM increased with increasing levels of VAI. After adjusting for confounders, for each SD increment in natural logarithm-transformed VAI, BMI, and WC the HRs were 1.538 (95 % CI: 1.225-1.930), 1.639 (95 % CI: 1.289-2.084) and 1.858 (95 % CI: 1.458-2.369), respectively. However, paired homogeneity tests showed no statistical difference among the HRs. CONCLUSION:VAI could independently predict DM in the Chinese study population, although the predictive power was not higher than that of simple anthropometric measures (BMI and WC). Our study does not support the clinical application of VAI; however, more studies based on different ethnic groups still need to be performed.
Authors: Nasser M Al-Daghri; Omar S Al-Attas; Majed S Alokail; Khalid M Alkharfy; Paris Charalampidis; Sarantis Livadas; Anastasios Kollias; Shaun Louie Sabico; George P Chrousos Journal: Eur J Clin Invest Date: 2012-12-20 Impact factor: 4.686
Authors: Ralph B D'Agostino; Ramachandran S Vasan; Michael J Pencina; Philip A Wolf; Mark Cobain; Joseph M Massaro; William B Kannel Journal: Circulation Date: 2008-01-22 Impact factor: 29.690
Authors: Gertraud Maskarinec; Phyllis Ash Raquinio; Veronica W Setiawan; Thomas Ernst; Adrian A Franke; Steven D Buchthal; John A Shepherd; Lynne R Wilkens; Unhee Lim; Loïc Le Marchand Journal: Ann Epidemiol Date: 2021-07-21 Impact factor: 6.996