OBJECTIVE: This study aimed to estimate utility-based quality of life (UQoL) differences between healthy body weight and excess body weight categories. DESIGN AND METHODS: Cross-sectional analysis of 10,959 adults, participating in baseline data collection of the nationally representative Australian Diabetes, Obesity, and Lifestyle (AusDiab) Study was undertaken. Height and weight were measured by trained personnel. Body weight categories were assigned as healthy weight, overweight, and obesity subclasses I, II and III. UQoL was assessed using the SF-6D, which captures physical functioning, role limitation, social functioning, pain, mental health, and vitality on a score of 0.00-1.00 (worst-best). The relationship between body weight categories and UQoL was assessed using linear regression, adjusting for age, sex, education, and smoking. RESULTS: Relative to the healthy weight group (mean UQoL score 0.77), mean adjusted UQoL differences (95% confidence intervals) were 0.001 (-0.008, 0.010) for overweight, -0.012 (-0.022, -0.001) for class-I obese, -0.020 (-0.041, 0.001) for class-II obese, and -0.069 (-0.099, -0.039) for class-III obese groups. Adding metabolic syndrome markers to the covariates had little impact on these differences. CONCLUSION: Results confirmed an inverse dose-response relationship between body weight and UQoL in this study of Australian adults. This highlights the need to incorporate UQoL measures which are sensitive to the subclasses of obesity when evaluating obesity interventions.
OBJECTIVE: This study aimed to estimate utility-based quality of life (UQoL) differences between healthy body weight and excess body weight categories. DESIGN AND METHODS: Cross-sectional analysis of 10,959 adults, participating in baseline data collection of the nationally representative Australian Diabetes, Obesity, and Lifestyle (AusDiab) Study was undertaken. Height and weight were measured by trained personnel. Body weight categories were assigned as healthy weight, overweight, and obesity subclasses I, II and III. UQoL was assessed using the SF-6D, which captures physical functioning, role limitation, social functioning, pain, mental health, and vitality on a score of 0.00-1.00 (worst-best). The relationship between body weight categories and UQoL was assessed using linear regression, adjusting for age, sex, education, and smoking. RESULTS: Relative to the healthy weight group (mean UQoL score 0.77), mean adjusted UQoL differences (95% confidence intervals) were 0.001 (-0.008, 0.010) for overweight, -0.012 (-0.022, -0.001) for class-I obese, -0.020 (-0.041, 0.001) for class-II obese, and -0.069 (-0.099, -0.039) for class-III obese groups. Adding metabolic syndrome markers to the covariates had little impact on these differences. CONCLUSION: Results confirmed an inverse dose-response relationship between body weight and UQoL in this study of Australian adults. This highlights the need to incorporate UQoL measures which are sensitive to the subclasses of obesity when evaluating obesity interventions.
Authors: Ana Carolina Proença da Fonseca; Guilherme Proença da Fonseca; Bruna Marchesini; Danielle Dutra Voigt; Mario Campos Junior; Verônica Marques Zembrzuski; João Regis Ivar Carneiro; José Firmino Nogueira Neto; Pedro Hernan Cabello; Giselda Maria Kalil Cabello Journal: Obes Facts Date: 2020-04-23 Impact factor: 3.942
Authors: Luca Busetto; John Dixon; Maurizio De Luca; Scott Shikora; Walter Pories; Luigi Angrisani Journal: Obes Surg Date: 2014-04 Impact factor: 4.129
Authors: Kelly R Ylitalo; Carrie Karvonen-Gutierrez; Candace McClure; Samar R El Khoudary; Elizabeth A Jackson; Barbara Sternfeld; Siobán D Harlow Journal: Diabetes Metab Res Rev Date: 2015-12-10 Impact factor: 4.876