Bidirectional transitions of sarcopenia, obesity, and sarcopenic obesity: Transitional patterns in older adults from the CHARLS study

Abstract

To the Editor: Sarcopenia, defined by the European Working Group on Sarcopenia in Older People (EWGSOP) as the presence of both low muscle mass and low muscle strength or performance, has emerged as a critical public health concern in aging populations.[1] Moreover, sarcopenic obesity (SO), first characterized by Baumgartner as the coexistence of sarcopenia and obesity, was another high-risk geriatric syndrome.[2] Obesity and sarcopenia often coexist in the aging population and exhibit strong bidirectional associations. A recent meta-analysis encompassing 106 clinical studies (N = 167,151 older individuals) reported a pooled SO prevalence of 9% in both sexes.[3] Importantly, it revealed a 51% increased risk of all-cause mortality (pooled hazard ratio [HR] = 1.51, 95% confidence intetal [CI] 1.14–2.02, P <0.001) among individuals with SO compared to their healthy counterparts.[3] Given its adverse health implications, emerging research underscores the need to approach SO as a distinct, multifactorial phenotype. Consequently, identifying robust predictors of SO is imperative for targeted interventions. This study investigated the progression of SO and the factors influencing its dynamic nature. Such insights could be critical for identifying optimal intervention targets and determining the most effective time windows for tailored treatments. Since sarcopenia and obesity share several pathophysiological mechanisms and may exacerbate each other, this study aimed to investigate five-year transitions among sarcopenia, obesity, SO, and normal stages. In addition, we evaluated potential factors associated with these transitions in adults aged ≥50 years using data from the China Health and Retirement Longitudinal Study (CHARLS). The Biomedical Ethics Review Committee of Peking University approved the CHARLS study (approval number IRB00001052–11015), and all interviewees were required to provide informed consent. Initially, 17,705 participants were included in 2011. From this cohort, we identified 5631 individuals aged ≥50 years who had complete objectively assessed data on walking speed, grip strength, height, weight, and waist circumference. Subsequently, 2420 individuals were excluded due to loss to follow-up or missing anthropometric data in 2013 or 2015, resulting in a final sample of 3211 participants. Sarcopenia was assessed at baseline and each follow-up in accordance with the criteria of the Asian Working Group for Sarcopenia (AWGS2019). Muscle mass was quantified using the skeletal mass index (SMI), calculated as the appendicular skeletal muscle mass (ASM) divided by the square of the height in meters. ASM was estimated as follows: ASM = 0.193 × body weight + 0.107 × height – 4.157 × gender – 0.037 × age – 2.631 (where body weight is in kg, height in cm, age in years, and gender is coded as 1 for men and 2 for women).[4] Low muscle mass was defined as SMI <7.0 kg/m2 for men and <5.7 kg for women. In addition, gait speed was considered low if it fell below 1.0 m/s. Following the AWGS2019 algorithm, sarcopenia was classified under the presence of “low muscle mass and low muscle strength” or “low muscle mass and low physical performance”. “Severe sarcopenia” was defined as the combination of low muscle strength, low muscle mass, and low physical performance. “Non-sarcopenia” was defined as the presence of normal muscle mass and strength. Obesity was assessed using waist circumference (WC), which was measured at the midpoint between the lower ribs and the ilium with participant standing upright. Obesity was defined as WC ≥80 cm for females and WC ≥90 cm for males.[5] Cognitive function was assessed by the Telephone Interview of Cognitive Status (TICS-10), word recall, and figure drawing, with data from the CHARLS. To identify factors associated with transitions toward and away from sarcopenic obesity, we examined previously established risk factors. The following baseline (Year 1) variables were included: age, sex, sleep duration,