Obesity Measures and Definitions of Sarcopenic Obesity in Singaporean Adults – the Yishun Study

Abstract

Background: The prevalence of sarcopenic obesity (SO) and its effect on functional disability is of particular concern. Due to the lack of a uniform obesity definition, there is marked variability in reported SO prevalence and inconsistent data on observed adverse health outcomes.Objectives: We compare SO prevalence and the associations of SO with physical function using sarcopenia according to current AWGS guidelines with different obesity measures. We recommend that the most optimal SO diagnostic formulation would be one that is most significantly associated with reduced physical function.Design: 542 healthy, community-dwelling Singaporeans were recruited (21-90 years old, 57.9% women). We assessed anthropometry, body composition, and questionnaire-based physical and cognitive factors, and estimated SO prevalence with obesity defined according to waist circumference (WC), percentage body fat (PBF), fat mass index (FMI) and fat mass/fat-free mass ratio (FM/FFM). Muscle function was compared among phenotypes and obesity definitions using ANOVA. Differences across obesity measures were further ascertained using multiple linear regressions to determine their associations with the Short Physical Performance Battery (SPPB).Results: Overall prevalence of SO was 7.6% (WC-based), 5.1% (PBF-based), 2.7% (FMI-based), and 1.5% (FM/FFM-based). The SO phenotype consistently performed poorer than the obese group (p<.05) except for FM/FFM-based measure, and performed poorer than the sarcopenic group in SPPB (p<.05) only in the PBF and FMI-based measures. SO was significantly associated with SPPB only in the FMI and FM/FFM models (p<.05).Conclusions: Our findings suggest FMI as the most preferred measure for obesity and support its use as a diagnostic criteria for sarcopenic obesity.

Coexistence of osteoporosis, sarcopenia and obesity in community-dwelling adults – The Yishun Study

“…ALMI, muscle strength and physical function were measured using a dual-energy X-ray absorptiometry (DXA) scan, maximal handgrip strength and habitual gait speed tests respectively, with detailed methods described in an earlier paper [ 14 ]. Obesity was assessed using the DXA scan, and defined using the 2 upper quintiles of population-derived sex-specific percentage body fat (PBF) and fat mass index (FMI) values [ 15 ]. We have previously shown that FMI is the more favourable approach for assessing adiposity as a component of sarcopenic obesity [ 15 ].…”

“…Obesity was assessed using the DXA scan, and defined using the 2 upper quintiles of population-derived sex-specific percentage body fat (PBF) and fat mass index (FMI) values [ 15 ]. We have previously shown that FMI is the more favourable approach for assessing adiposity as a component of sarcopenic obesity [ 15 ]. Osteopenia and osteoporosis were indicated by a population-derived lumbar spinal bone mineral density (BMD LS ) T-score of −1 to −2.5 and ≤ −2.5 respectively [ 4 ].…”

“…In recent years, OSO has been proposed as a cumulative triad of the adverse effects of its components: impaired bone health, muscle health, and excess adiposity [ 6 ]. We have recently reported population prevalence of osteopenia, osteoporosis [ 13 ], sarcopenia [ 14 ], obesity and SO [ 15 ], and provided reference values for BMD [ 13 ], skeletal muscle, strength and function [ 14 ], and compared different adiposity measures [ 15 ]. Additionally, we have also shown that SO further exacerbates poor physical function when compared to sarcopenia or obesity alone [ 15 ].…”

“…We have recently reported population prevalence of osteopenia, osteoporosis [ 13 ], sarcopenia [ 14 ], obesity and SO [ 15 ], and provided reference values for BMD [ 13 ], skeletal muscle, strength and function [ 14 ], and compared different adiposity measures [ 15 ]. Additionally, we have also shown that SO further exacerbates poor physical function when compared to sarcopenia or obesity alone [ 15 ]. However, there is contrasting evidence regarding the value of OSO in predicting for functional decline (ie, physical performance and frailty) [ 5 , 16 ], risk of adverse clinical outcomes (ie, fractures and falls risks) [ 17 , 18 ] and mortality [ 19 ] over sarcopenia, osteopenia/osteoporosis, or SO alone.…”

Associations of fat mass and muscle function but not lean mass with cognitive impairment: The Yishun Study

“…The aforementioned studies have used percentage body fat [ 21 , 22 ], and waist circumference [ 9 ] to determine obesity. Recently, we presented data to show that fat mass index (FMI) may be the most optimal criterion for SO among the obesity measures, as it accounts for body size differences and improves the association between adiposity and physical function [ 24 ]. To date, no studies have examined the relationship between cognition and SO based on FMI.…”