PURPOSE: Obesity adversely affects health-related quality of life (HRQoL). Most studies have used body mass index (BMI) to measure obesity. Other measures of obesity, such as waist circumference (WC) or waist-to-hip ratio (WHR), may be better predictors of cardiovascular disease and mortality. We, therefore, examined the associations between other anthropometric measures and HRQoL in a multi-ethnic Asian population. METHODS: In this follow-up study from four previous cross-sectional surveys, HRQoL was measured, at follow-up, using the Short-Form 36 version 2 (SF-36v2) questionnaire. Linear regression was used to assess the relationship between anthropometric measures [BMI, WC, waist residuals (WR) (generated by regressing WC on BMI), WHR, waist-to-height ratio (WHtR) and height (Ht)] and HRQoL. We compared the models' R2, Akaike's information criteria (AIC), and Schwarz Bayesian information criteria (BIC) from the different models. RESULTS: Among 4,981 subjects, 47.6% were men aged 50.6 ± 12.2 and women aged 49.3 ± 11.6 years. All gender-specific anthropometric measures were significantly correlated with BMI, except WR. After adjusting for known determinants of HRQoL, we found significant associations between BMI, WC and WHtR with SF-36v2 Physical Component Summary (PCS) scores in women but not men. In contrast, after adjusting for known determinants of HRQoL, WR and WHR were significantly associated with SF-36v2 Mental component summary (MCS) scores in men, but not women. R², AIC and BIC were similar for all anthropometric measures in the final model. CONCLUSIONS: The associations between measures of central obesity and HRQoL differed between men and women. In women, associations were seen with SF-36v2 PCS, but measures of central obesity did not have significant associations with HRQoL after controlling for BMI. In men, an association between WC and SF-36v2 MCS was statistically significant independent of BMI. These gender differences require further investigation.
PURPOSE:Obesity adversely affects health-related quality of life (HRQoL). Most studies have used body mass index (BMI) to measure obesity. Other measures of obesity, such as waist circumference (WC) or waist-to-hip ratio (WHR), may be better predictors of cardiovascular disease and mortality. We, therefore, examined the associations between other anthropometric measures and HRQoL in a multi-ethnic Asian population. METHODS: In this follow-up study from four previous cross-sectional surveys, HRQoL was measured, at follow-up, using the Short-Form 36 version 2 (SF-36v2) questionnaire. Linear regression was used to assess the relationship between anthropometric measures [BMI, WC, waist residuals (WR) (generated by regressing WC on BMI), WHR, waist-to-height ratio (WHtR) and height (Ht)] and HRQoL. We compared the models' R2, Akaike's information criteria (AIC), and Schwarz Bayesian information criteria (BIC) from the different models. RESULTS: Among 4,981 subjects, 47.6% were men aged 50.6 ± 12.2 and women aged 49.3 ± 11.6 years. All gender-specific anthropometric measures were significantly correlated with BMI, except WR. After adjusting for known determinants of HRQoL, we found significant associations between BMI, WC and WHtR with SF-36v2 Physical Component Summary (PCS) scores in women but not men. In contrast, after adjusting for known determinants of HRQoL, WR and WHR were significantly associated with SF-36v2 Mental component summary (MCS) scores in men, but not women. R², AIC and BIC were similar for all anthropometric measures in the final model. CONCLUSIONS: The associations between measures of central obesity and HRQoL differed between men and women. In women, associations were seen with SF-36v2 PCS, but measures of central obesity did not have significant associations with HRQoL after controlling for BMI. In men, an association between WC and SF-36v2 MCS was statistically significant independent of BMI. These gender differences require further investigation.
Authors: L O Ohlson; B Larsson; K Svärdsudd; L Welin; H Eriksson; L Wilhelmsen; P Björntorp; G Tibblin Journal: Diabetes Date: 1985-10 Impact factor: 9.461
Authors: Anthonia U Chinweuba; Ijeoma L Okoronkwo; Agnes N Anarado; Noreen E Agbapuonwu; Ngozi P Ogbonnaya; Chikaodili N Ihudiebube-Splendor Journal: BMC Womens Health Date: 2018-01-10 Impact factor: 2.809
Authors: Andrea Gonzalez; Michael H Boyle; Katholiki Georgiades; Laura Duncan; Leslie R Atkinson; Harriet L MacMillan Journal: BMC Public Health Date: 2012-09-09 Impact factor: 3.295