Mahsa Sardarinia1, Roya Ansari1, Feridoun Azizi2, Farzad Hadaegh1, Mohammadreza Bozorgmanesh3. 1. Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 2. Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 3. Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Electronic address: Mr_bozorgmanesh@endocrine.ac.ir.
Abstract
OBJECTIVES: A body shape index (ABSI) based on waist circumference (WC) adjusted for height and weight has been shown to be a risk factor for premature mortality. The aim of this study was to demonstrate that ABSI predicts mortality hazard better than other anthropometric measures in an Iranian population. METHODS: The study population included 9242 Iranian participants in Tehran, aged ≥30 y, followed for a median 10 y. The risk for mortality was estimated by incorporating ABSI, body mass index (BMI), WC, waist-to-hip ratio (WHpR), and waist-to-height ratio (WHtR), one at a time, into multivariate models as well as in terms of the effect size, calibration, discrimination, and added predictive ability. RESULTS: We documented 487 deaths with the annual incidence rate of mortality per 1000 persons being 3.9 for women and 8.2 for men. ABSI was associated with all-cause mortality in a curvilinear fashion. ABSI was more strongly associated with all-cause mortality than were BMI, WC, and WHtR. Among women, however, WHpR was observed to be a stronger predictor of all-cause mortality than ABSI. Among both men and women, ABSI improved the risk classification based on other anthropometric measures, the only exception being WHpR. None of the anthropometric measures studied could add any value to the predictive ability of the Framingham's general cardiovascular disease algorithm. CONCLUSION: ABSI was the strongest predictor of all-cause mortality among the anthropometric measurements, except WHpR in women. When ABSI was added to the Framingham general cardiovascular disease algorithm, it failed to improve the predictive ability. Copyright Â
OBJECTIVES: A body shape index (ABSI) based on waist circumference (WC) adjusted for height and weight has been shown to be a risk factor for premature mortality. The aim of this study was to demonstrate that ABSI predicts mortality hazard better than other anthropometric measures in an Iranian population. METHODS: The study population included 9242 Iranian participants in Tehran, aged ≥30 y, followed for a median 10 y. The risk for mortality was estimated by incorporating ABSI, body mass index (BMI), WC, waist-to-hip ratio (WHpR), and waist-to-height ratio (WHtR), one at a time, into multivariate models as well as in terms of the effect size, calibration, discrimination, and added predictive ability. RESULTS: We documented 487 deaths with the annual incidence rate of mortality per 1000 persons being 3.9 for women and 8.2 for men. ABSI was associated with all-cause mortality in a curvilinear fashion. ABSI was more strongly associated with all-cause mortality than were BMI, WC, and WHtR. Among women, however, WHpR was observed to be a stronger predictor of all-cause mortality than ABSI. Among both men and women, ABSI improved the risk classification based on other anthropometric measures, the only exception being WHpR. None of the anthropometric measures studied could add any value to the predictive ability of the Framingham's general cardiovascular disease algorithm. CONCLUSION: ABSI was the strongest predictor of all-cause mortality among the anthropometric measurements, except WHpR in women. When ABSI was added to the Framingham general cardiovascular disease algorithm, it failed to improve the predictive ability. Copyright Â
Authors: Sofia Christakoudi; Konstantinos K Tsilidis; David C Muller; Heinz Freisling; Elisabete Weiderpass; Kim Overvad; Stefan Söderberg; Christel Häggström; Tobias Pischon; Christina C Dahm; Jie Zhang; Anne Tjønneland; Jytte Halkjær; Conor MacDonald; Marie-Christine Boutron-Ruault; Francesca Romana Mancini; Tilman Kühn; Rudolf Kaaks; Matthias B Schulze; Antonia Trichopoulou; Anna Karakatsani; Eleni Peppa; Giovanna Masala; Valeria Pala; Salvatore Panico; Rosario Tumino; Carlotta Sacerdote; J Ramón Quirós; Antonio Agudo; Maria-Jose Sánchez; Lluís Cirera; Aurelio Barricarte-Gurrea; Pilar Amiano; Ensieh Memarian; Emily Sonestedt; Bas Bueno-de-Mesquita; Anne M May; Kay-Tee Khaw; Nicholas J Wareham; Tammy Y N Tong; Inge Huybrechts; Hwayoung Noh; Elom K Aglago; Merete Ellingjord-Dale; Heather A Ward; Dagfinn Aune; Elio Riboli Journal: Sci Rep Date: 2020-09-03 Impact factor: 4.379
Authors: Jia Liu; Lap Ah Tse; Zhiguang Liu; Sumathy Rangarajan; Bo Hu; Lu Yin; Darryl P Leong; Wei Li Journal: J Am Heart Assoc Date: 2019-08-09 Impact factor: 5.501