ABSTRACT
Objectives@#To determine the prevalence of sarcopenia obesity (SO) in healthy Indian adults and delineate the relative impact of the 3 indices of obesity [body mass index (BMI), waist circumference (WC), fat mass percent (FM%)] with regards to inter-definitional agreement and their relationship with usual gait speed (GS). @*Methods@#Apparently healthy adults (aged ≥ 20 years) with no background history of comorbidities were enrolled from the community by door-to-door survey. Following blood investigations, individuals with biochemical abnormalities were excluded. Enrolled participants underwent dual-energy X-ray absorptiometry (DXA). Sarcopenia was defined according to EWGSOP2 consensus based on indigenous cut-offs obtained from the Sarcopenia-Chandigarh Urban Bone Epidemiological Study (Sarco-CUBES). Obesity was defined based on BMI (≥ 25.0 kg/m2) or WC (> 90 cm in men, > 80 cm in women) or DXA-derived FM% (> 32% in men, > 40% in women). @*Results@#Data of 804 participants were analyzed after exclusion. The mean ± SD for BMI, WC, and FM% were 26.5 ± 2.7 kg/m2, 86.8 ± 9.6, and 34.7 ± 7.3%, respectively. Prevalence of sarcopenia was 3.2%. Based on BMI, WC, and FM%, the prevalence of SO in elderly subjects (≥65 years) was 5.4%, 5.4%, and 6.3%, respectively. Using Cohen’s kappa, inter-definitional agreement between the 3 groups was ‘almost perfect’. FM%, and not BMI/WC, emerged as a significant predictor of GS on multiple linear regression analysis. @*Conclusions@#The prevalence of SO in healthy elderly Indian adults is 5.4%–6.3%. Either BMI/WC/FM% can be used to correctly identify individuals with SO.
ABSTRACT
Objectives@#To determine the prevalence of sarcopenia obesity (SO) in healthy Indian adults and delineate the relative impact of the 3 indices of obesity [body mass index (BMI), waist circumference (WC), fat mass percent (FM%)] with regards to inter-definitional agreement and their relationship with usual gait speed (GS). @*Methods@#Apparently healthy adults (aged ≥ 20 years) with no background history of comorbidities were enrolled from the community by door-to-door survey. Following blood investigations, individuals with biochemical abnormalities were excluded. Enrolled participants underwent dual-energy X-ray absorptiometry (DXA). Sarcopenia was defined according to EWGSOP2 consensus based on indigenous cut-offs obtained from the Sarcopenia-Chandigarh Urban Bone Epidemiological Study (Sarco-CUBES). Obesity was defined based on BMI (≥ 25.0 kg/m2) or WC (> 90 cm in men, > 80 cm in women) or DXA-derived FM% (> 32% in men, > 40% in women). @*Results@#Data of 804 participants were analyzed after exclusion. The mean ± SD for BMI, WC, and FM% were 26.5 ± 2.7 kg/m2, 86.8 ± 9.6, and 34.7 ± 7.3%, respectively. Prevalence of sarcopenia was 3.2%. Based on BMI, WC, and FM%, the prevalence of SO in elderly subjects (≥65 years) was 5.4%, 5.4%, and 6.3%, respectively. Using Cohen’s kappa, inter-definitional agreement between the 3 groups was ‘almost perfect’. FM%, and not BMI/WC, emerged as a significant predictor of GS on multiple linear regression analysis. @*Conclusions@#The prevalence of SO in healthy elderly Indian adults is 5.4%–6.3%. Either BMI/WC/FM% can be used to correctly identify individuals with SO.
