AUTHOR=Fan Yu-Jun , Feng Yi-Jin , Meng Ya , Su Zhen-Zhen , Wang Pei-Xi 

TITLE=The relationship between anthropometric indicators and health-related quality of life in a community-based adult population: A cross-sectional study in Southern China

JOURNAL=Frontiers in Public Health

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2022.955615

DOI=10.3389/fpubh.2022.955615

ISSN=2296-2565

ABSTRACT=Background: This study was designed to analysed the relationship of waist circumference (WC), body mass index (BMI), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), relative fat mass (RFM), lipid accumulation product (LAP) and health-related quality of life (HRQoL) in the community-dwelling population of southern China and to explore the independent contribution of socio-demographic characteristics, number of chronic diseases and anthropometric indicators to HRQoL in that population.
Methods: This community-based cross-sectional survey studied 2,663 adults aged 18 years and older. HRQoL was assessed by the 3-level EuroQol 5-dimensional scale (EQ-5D-3L), and health utility values were calculated using the Chinese EQ-5D-3L value set. The outcome variable was the EQ-5D-3L score (health utility value). Cluster regression was used to analyse the independent contribution of each obesity indicator to HRQoL.
Results: A total of 2,663 people participated in this study, and their mean EQ-5D-3L score was 0.938 ± 0.072. In this study, according to the results of the one-way ANOVA, the subjects’ HRQoL gradually decreased as WHtR, WHR, RFM, and LAP increased, and the difference was statistically significant. The independent contributions of socio-demographic factors, number of chronic diseases and anthropometric measures to HRQoL in the whole population accounted for 76.2%, 7.9%, and 15.9% of the total effect, respectively.
Conclusion: RFM and LAP were found to have a previously unreported negative impact on HRQoL in a community-dwelling population. In future studies, RFM and LAP could be used as new indicators of obesity to predict quality of life in humans.