Obesity and lipid indices in relation to physical performance and sarcopenia among older Chinese adults: a cross-sectional study

Abstract

Objectives

Besides body mass index (BMI), various obesity and lipid-related indices may effectively be associated with diminished physical performance (PP) and sarcopenia. However, comparative studies on their association strength power are scarce and yield inconsistent results. The aim of this study was to identify the obesity and lipid-related indices most strongly associated with diminished PP and (pre-) sarcopenia.

Design

Cross-sectional observational studies.

Setting

Tertiary care hospitals.

Participants

Our study population comprised 1323 Chinese community older adults (mean±SD age: 68.0±6.1 years; 58.2% women).

Primary and secondary outcome measures

12 obesity and lipid-related indices, including BMI, waist hip ratio(WHR), waist-to-height ratio (WHtR), Body Roundness Index (BRI), Body-Shape Index (ABSI), Conicity Index (C-index), Hepatic Steatosis Index (HSI), lipid accumulation product, Triglyceride-Glucose (TyG) Index and TyG index-related parameters (TyG-BMI, TyG-WC, TyG-WHtR), were measured and calculated. Sarcopenia is defined by the definition of Asian Working Group for Sarcopenia (2019 Consensus Update); diminished PP was defined by grip strength <28 kg for men and <18 kg for women or walking speed <1.0 m/s or repeated chair stand ≥12 s or Simple PP battery ≤9 with relatively maintained muscle mass.

Results

After multivariate adjustments for all the concomitants (age, gender, weight and other health indicators), we found that higher WHtR, BRI, HSI, TyG-BMI, TyG-WC and TyG-WHtR (p value for trend =0.010, 0.003, 0.014, 0.004, 0.013 and 0.001, respectively) were significantly associated with an increased incidence of diminished PP, while higher ABSI (p value for trend=0.016) was significantly associated with a higher prevalence of sarcopenia. Moreover, higher values of obesity indices (BMI, WHtR, BRI, ABSI, C-index) and TyG-related indices (TyG-BMI, TyG-WC, TyG-WHtR) were associated with a greater number of diminished PP measures in both diminished PP and sarcopenia (OR ranging from 1.722 to 2.772 for two and more; OR ranging from 1.741 to 7.913 for three and more).

Conclusions

The present study indicates that abdominal obesity, along with lipid-related indices, may play a role in the development and advancement of sarcopenia and sarcopenic obesity. Notably, central body shape indices, particularly ABSI and C-index, demonstrated stronger associations with these conditions than traditional measures such as BMI. Consequently, in diagnosing and assessing sarcopenia and sarcopenic obesity, we should take into account not only the loss of muscle mass but also the effects of lipid accumulation and alterations in glycolipid metabolism.

STRENGTHS AND LIMITATIONS OF THIS STUDY.

• We examined 12 obesity and lipid-related indices and observed potential strong associations of central body shape indices, particularly Body-Shape Indebody-shape index and Conicity indIndex, with sarcopenia and sarcopenic obesity.

• This study incorporated considerations regarding the characteristics of individuals who experience a decline in physical performance without a significant loss of muscle mass.

• As a cross-sectional design, we were unable to determine the causal relationships between the indicators.

• Muscle mass diagnosis relied solely on bioelectrical impedance analysis, a method that, while cost-effective, rapid and non-invasive, may not be as precise as CT, MRI or dual-energy X-ray absorptiometry scans.

Introduction

Sarcopenia is a syndrome characterised by progressive and generalised loss of skeletal muscle mass, muscle strength and physical performance (PP), which is linked to the increased risk of adverse outcomes, including falls, frailty, disability, increased morbidity and mortality.¹ According to diverse guidelines and consensus statements, the diagnostic criteria for sarcopenia are primarily based on assessments of muscle mass, grip strength and other PP measures, such as walking speed and the repeated chair stand test.² However, recent studies have demonstrated that PP is not solely related to muscle mass-related indices, such as skeletal muscle mass (SMM) and appendicular skeletal mass index (ASMI),^{3 4} underscoring the significance of lipid infiltration in muscle, which contributes to the decline in these capabilities.^{5 6}

Indeed, the interplay between alterations in muscle and fat mass and sarcopenia is complex and nuanced. The metabaging cycle describes how ageing connects obesity and sarcopenia by causing fat tissue inflammation to redistribute fat, leading to muscle dysfunction, insulin resistance (IR) and a cycle of inflammation and lipid imbalance that promotes sarcopenia and sarcopenic obesity.⁷ Meanwhile, in many cardiometabolic diseases, the ostensibly protective effect of obesity in extremely older adults, also known as the ‘obesity paradox’,⁸ could possibly be explained by this theory that many older adults with normal body mass index (BMI) might actually harbour sarcopenic obesity to various degrees, before it progresses to full-blown severe sarcopenia. This may indicate that current diagnostic criteria may not be fully reliable, as the concurrent loss of muscle and gain in fat among older adults might precipitate a decline in PP prior to a noticeable loss of muscle mass, which could in turn trigger further muscle mass loss.⁹ Consequently, many individuals classified as ‘normal’ in current studies may not be suspected or tested for (pre-) sarcopenia, potentially leading to a significant underestimation of both the prevalence and the impact of ageing changes in muscle and fat mass.

The intricate interactions between muscle and fat mass in older adults reduce the effectiveness of BMI, especially in diagnosing sarcopenic obesity. This calls for the identification of alternative indices that can more accurately measure body fat redistribution and visceral obesity. While CT, MRI and dual-energy X-ray absorptiometry (DEXA) are considered the gold standards for body composition analysis, their high costs and limited accessibility have driven the quest for more feasible and accessible methods for diagnosing sarcopenia.¹⁰ In addition to BMI, various obesity and lipid-related indices have been proposed to be associated with diminished PP and sarcopenia. These include measures of abdominal obesity, such as waist hip ratio (WHR),¹¹ waist-to-height ratio (WHtR),¹² Body Roundness Index (BRI),¹³ Body-Shape Index (ABSI),¹⁴ Conicity Index (C-index)¹⁵; as well as lipid-related indices, such as Hepatic Steatosis Index (HSI),¹⁶ lipid accumulation product (LAP),¹⁷ Triglyceride-Glucose (TyG) Index and TyG index-related parameters (TyG-BMI, TyG-WC, TyG-WHtR).¹⁸ The rationale for investigating these specific indices is grounded in their distinct pathophysiological links to functional decline. Specifically, indices of abdominal obesity (eg, WHR, WHtR, BRI, ABSI, C-index) are hypothesised to better reflect detrimental visceral adiposity, a known driver of chronic inflammation and IR, which in turn directly impairs muscle protein synthesis and physical function.19,21 Similarly, indices that integrate lipid and metabolic components (eg, HSI, LAP, TyG) are postulated to capture underlying dysmetabolism and IR, which are key mechanisms contributing to the development of sarcopenia.22,25 However, there are very few comparative studies on the association between these indices and diminished PP and sarcopenia, with existing studies presenting inconsistent findings.²⁶ Thus, further research is essential to clarify their roles and refine diagnostic approaches.

The aim of this study was to identify the obesity and lipid-related indices most strongly associated with diminished PP and (pre-) sarcopenia. From a public health perspective, deepening our comprehension of the relationship between muscle and fat mass and PP could facilitate the early detection of sarcopenia (characterised by a decline in both muscle mass and function) in obese older adults. This understanding is pivotal in preventing both the development of sarcopenia and sarcopenic obesity, as well as the consequent rise in morbidity and health deterioration.

Methods

Study design

Our study population comprised community older adults (≥60 years old) from China. The exclusion criteria included orthopaedic impediment, severe neurological dysfunction and inability to carry out performance-based assessments. An a priori sample size calculation was conducted with a focus on sarcopenia as the primary outcome. Based on the events-per-variable (EPV) criterion for logistic regression,²⁷ a minimum of 140 events (participants with sarcopenia) was required to robustly fit a model encompassing the 12 primary indices (BMI, WHR, WHtR, BRI, ABSI, C-index, HSI, LAP, TyG index, TyG-BMI, TyG-WC and TyG-WHtR) and two covariates (age and sex), totaling 14 parameters. Given an estimated sarcopenia prevalence of 15% in Asian older adults,²⁸ the minimum required total sample size was calculated to be 934 participants. The required number of events was calculated as (EPV×number of parameters)/prevalence = (10×14)/0.15≈934. 1400 individuals agreed to participate in the survey and had undergone multifrequency bioelectrical impedance analysis (BIA) (In-Body720; Biospace, Seoul, Korea) and other required measurements. We excluded 77 individuals who had data deficiencies. The final study population comprised 1323 individuals (mean±SD age: 68.0±6.1 years; 58.2% women). To compensate for potential non-response, participant attrition and to ensure sufficient power for subgroup analyses, we recruited a total of 1323 individuals, thereby substantially exceeding the initial target. The Ethics Committee for Scientific Research of Tianjin Medical University approved the present study (TMUhMEC20230004) and all study subjects provided written consent.

Anthropometric indices

Body weight and height were measured using the InBody 720 device (Biospace, Seoul, Korea), with values recorded to the closest values of 0.1 kg and 1.0 cm, respectively. After the expiratory breath, waist circumference (WC) was measured on both sides between the iliac crest and the lower ribs.¹² Hip circumference is measured at the widest point of the hips, typically using a flexible tape measure while standing upright.¹² Calf circumference was measured to encircle the largest part of the calf muscle while standing upright using a tape.²⁹ Body composition, including SMM, appendicular SMM (ASM), body fat, percentage body fat (%BF) and visceral fat area (VFA), protein, total body water was measured by BIA (In-Body720; Biospace, Seoul, Korea).

Assessments of diminished PP and sarcopenia

A handheld dynamometer (GRIP-D, Takei, Niigata, Japan) quantified grip strength (kg) and was used to measure lower extremity muscle strength in order to provide the evaluation of knee extension strength (MT-110; SAKAIMED, Japan). Muscle mass was measured using BIA (In-Body720; Biospace, Seoul, Korea). This study provides details of the survey methods used.³⁰ Simple PP battery (SPPB) according to the National Institute on Aging protocol.³¹ SMM in the arms and legs was used to calculate ASM. ASMI was defined as ASM divided by body height in m².³² According to the Asian Working Group for Sarcopenia criteria (2019 Consensus Update),³³ sarcopenia was defined by ASM/Ht² <7.0 kg/m² in men and <5.7 kg/m² in women, with grip strength <28 kg for men and <18 kg for women or walking speed <1.0 m/s or repeated chair stand ≥12 s or SPPB ≤9. Diminished PP was characterised by the same criteria for low muscle strength or poor PP, but in individuals with preserved muscle mass (ASM/Ht² ≥7.0 kg/m² in men and ≥5.7 kg/m² in women). Participants were categorised into three groups based on the objective criteria for sarcopenia and PP: (1) a sarcopenia group, (2) a diminished PP group (preserved muscle mass with poor PP) and (3) a normal group (preserved muscle mass and normal PP).

Assessments of biomarker data

After an overnight fast of at least 10 hours, blood samples were taken from the participants while seated through the antecubital vein, with minimal tourniquet use. After collection, samples were centrifuged for 15 min at 3000 rpm. Using the Roche Modular P (Roche Diagnostic Company, Swiss), alanine aminotransferase (ALT), aspartate aminotransferase (AST), fasting plasma glucose (FPG), creatinine, blood urea nitrogen (BUN), total cholesterol (TC) and triglycerides (TG) were measured. Estimated glomerular filtration rate (eGFR) is defined by Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2021. ³⁴Creatinine clearance (CCr) was also calculated by equation as CCr (mg/mL)= [140−age (y)]*W (kg)/72*Cre (15% less in females).³⁵

Quality control of measurement indicators

To ensure the high reliability of anthropometric measurements, a comprehensive quality control protocol was implemented. This included: (1) standardised training for all staff using established techniques; (2) a mandatory proficiency assessment that each measurer had to pass prior to participating in the study and (3) the assignment of each staff member to a single, dedicated measurement task throughout the entire data collection period. This approach effectively minimised both intraobserver and interobserver variability.

Assessments of obesity and lipid-related indices

BMI was measured with weight (kg)/height² (m). WHR, WHtR, BRI, ABSI and Cindex were defined based on WC with and calibrated with hip circumference, weight, height and BMI. HSI, LAP and TyG index were the result of a computation using ALT, AST, TG or FPG. The formulas for calculating obesity and lipid-related indices are shown in online supplemental appendix.

Relevant covariates

The calcaneus had measurements taken from bone mineral density (g/cm²) by the quantitative ultrasound (QUS; OsteoPro UBD2002A, BMTECH; World Wide, Seoul, Korea). Resting seated blood pressure was measured twice at 1 min intervals using a calibrated electronic monitor (Omron HEM-7052), and the average value was used for analysis. Information on age, sex, daily physical activity, smoking and drinking situation, nutritional status and depressive status was obtained from questionnaire surveys. A history of other physical illness was evaluated on participants’ response (yes or no) to questions about diabetes, hypertension, dyslipidaemia, heart disease, kidney disease and stroke. The Chinese version of the short form of the International Physical Activity Questionnaire (IPAQ) assessed physical activity. Nutritional status could be assessed by short form of Mini Nutritional Assessment (MNA) and depressive status was assessed using the Geriatric Depression Scale (GDS). The survey methods have been detailed in a previous study.³⁰

Statistical evaluation

Using the SPSS V.22.0 software package, statistical analyses took place (SPSS, China). Subject characteristics according to grouping of PP and muscle mass were presented as mean values (with 95% CI) or as percentages. The significance in the differences between variables required examination, using ANOVA for continuous variables or χ² test for categorical variables. Logistic regression analysis used to identify the relationship between obesity/lipid-related indices and diminished PP or sarcopenia. The lowest quarter of obesity/lipid-related indices was classified as one (reference). Multivariate analyses were divided into three statistical models, with model 1 being unadjusted. Model 2 included age and gender. In addition to the covariates in model 2, model 3 included weight, calf circumference, SMM, ASM, total body water, protein, % BF, VFA, T value, ALT, AST, FPG, creatinine, eGFR, CCr, BUN, TC, TG, SBP, DBP, diabetes, hypertension, dyslipidaemia, heart disease, kidney disease, stroke, smoking situation, drinking situation, IPAQ, MNA, GDS. In addition, the association of PPs (grip strength, walking speed, repeated chair stand, SPPB, et al) and obesity/lipid-related indices was examined by logistic regression, with a focus on groups characterised by diminished PP and sarcopenia compare with normal group. Multivariate analyses were divided into two statistical models, crude and adjusted model (including age, gender, weight, calf circumference, SMM, ASM, total body water, protein, % BF, VFA, ALT, AST, FPG, creatinine, eGFR, CCr, BUN, TC, TG, T value, SBP, DBP, diabetes, hypertension, dyslipidaemia, heart disease, kidney disease, stroke, smoking situation, drinking situation, IPAQ, MNA, GDS).

Results

Subject characteristics

Subject characteristics are detailed in table 1. Those with diminished PP, compared with normal group, were older, more often female and had a higher prevalence of hypertension and dyslipidaemia. They also exhibited reduced calf circumference, muscle mass (ASM), creatinine, eGFR, CCr and lower IPAQ and MNA-short form (SF) scores. Additionally, they had increased fat mass (body fat, %BF, VFA), BMI, WHR, WHtR, BRI, TyG-WHtR and GDS-30 scores. Sarcopenic subjects, relative to the normal group, were older, had more hypertension and dyslipidaemia and showed higher AST and BUN levels. They also had lower weight, calf circumference, muscle mass (SMM, SMM/weight, ASM, ASM/height²), protein, total body water, BMI, TyG index, TyG-BMI, creatinine, along with decreased IPAQ and MNA-SF scores. Comparing sarcopenia to diminished PP, individuals with sarcopenia were more likely to have lower weight, WC, muscle mass (SMM, SMM/weight, ASM, ASM/height²), fat mass (body fat, %BF, VFA), protein, total body water, BMI, WHR, WHtR, BRI, TyG index, TyG-BMI, TyG-WHtR, PP, IPAQ scores and higher eGFR. It is noteworthy that these baseline differences, particularly in age and sex, reflect the expected epidemiological features of these conditions and were rigorously adjusted for in subsequent multivariate analyses.

Table 1. Subject characteristics according to grouping of PP and muscle mass.

	Normal (n=417)	Diminished PP (n=693)	Sarcopenia (n=213)	P value
Age, years	65.9±4.7	69.0±6.5*	68.9±6.4*	<0.001
Female, % (n)	52.0 (217)	63.6 (441)*	52.6 (112)	<0.001
Physical measurement
Weight, kg	67.6±10.5	66.3±11.3	63.8±12.8*†	<0.001
WC, cm	90.8±11.9	91.6±15.1	89.3±14.1†	0.097
Calf circumference, cm	34.7±3.9	33.8±5.1*	33.9±4.8*	0.007
Muscle mass
SMM, kg	43.8±8.7	43.7±8.6	37.1±9.9*†	<0.001
SMM/weight,%	66.1±15.8	67.6±16.4	59.4±16.3*†	<0.001
ASM, kg	19.8±4.6	19.2±4.3*	16.7±4.1*†	<0.001
ASM/height,2 kg/m2	7.3±4.5	7.3±1.4	6.3±1.4*†	<0.001
Fat mass
Body fat, kg	19.3±6.6	20.8±7.3*	18.7±7.3†	<0.001
% BF, %	28.4±7.9	31.1±8.6*	29.0±9.2†	<0.001
VFA, cm2	95.8±37.1	108.1±42.5*	96.5±40.9†	<0.001
Bone quality,
T value	−2.9±1.6	−3.0±1.6	−2.3±5.4*†	0.003
Osteoporosis, %(n)	87.2 (364)	87.6 (607)	87.8 (187)	0.129
Other body composition
Protein	9.1±1.8	9.1±1.7	8.1±1.7*†	<0.001
Total body water, %	34.6±6.6	34.7±6.3	30.7±6.3*†	<0.001
Obesity-related indices
BMI	24.8±3.2	25.3±3.6*	24.0±4.1*†	<0.001
WHR	0.917±0.069	0.935±0.075*	0.920±0.067†	<0.001
WHtR	55.1±7.4	56.8±10.0*	55.0±9.0†	<0.001
BRI	4.5±1.4	4.9±1.8*	4.5±1.7†	<0.001
ABSI	0.083±0.008	0.084±0.011	0.084±0.010	0.475
C-index	1.30±0.13	1.32±0.18	1.31±0.16	0.535
Lipid-related indices
HSI	33.7±5.5	34.6±6.3	34.8±9.4	0.446
LAP	52.8±39.7	54.0±49.0	46.6±38.2	0.108
TyG index	8.8±0.5	8.7±0.8	8.4±1.9*†	<0.001
TyG-BMI	218.9±33.9	222.7±36.5	212.2±42.0*†	0.001
TyG-WC	801.2±123.8	805.7±147.4	788.3±143.5	0.293
TyG-WHtR	486.2±77.1	500.0±95.3*	484.6±90.0†	0.014
Blood indicators
ALT, mmol/L	24.9±16.4	25.9±16.5	27.1±23.4	0.334
AST, mmol/L	26.6±13.8	28.1±13.0	30.1±22.6*	0.024
FPG, mmol/L	5.6±1.2	5.6±1.5	5.8±1.7	0.177
Creatinine, μmol/L	91.9±10.7	90.4±11.1*	90.0±11.5*	0.046
eGFR, mL/min/1.73 m2	69.6±12.2	67.3±11.9*	70.1±12.9†	0.001
CCr, min/L	61.5±15.9	59.4±18.1*	60.5±15.6	0.122
BUN, mmol/L	5.3±1.3	5.5±1.4	5.6±1.9*	0.036
TC, mmol/L	5.8±1.2	5.6±1.6	5.6±1.2	0.435
TG, mmol/L	1.7±1.0	1.7±1.2	1.7±0.9	0.734
Resting blood pressure
SBP, mm Hg	136.2±20.2	136.3±21.1	135.5±21.1	0.897
DBP, mm Hg	75.7±10.2	74.1±11.2	74.2±11.3	0.060
Chronic diseases, %(n)
Diabetes	15.6 (65)	18.6 (129)	20.2 (43)	0.284
Hypertension	36.7 (153)	48.8 (338)*	54.9 (117)*	<0.001
Dyslipidaemia	23.9 (99)	31.6 (219)*	30.0 (64)*	0.018
Heart disease	28.8 (120)	27.8 (139)	26.3 (56)	0.805
Kidney disease	28.5 (119)	27.8 (193)	25.4 (54)	0.691
Stroke	5.5 (23)	6.9 (48)	7.5 (16)	0.547
Physical performance
Grip strength, kg	30.2±7.9	22.5±8.4*	23.0±8.9*	<0.001
Grip strength <28 kg for male and <18 kg for female, %(n)	–	49.1 (340)*	53.1 (113) *†	<0.001
Walking speed, m/s	1.15±0.11	0.91±0.17*	0.94±0.19*†	<0.001
Walking speed <1.0 m/s, %(n)	–	71.6 (496) *	62.0 (132) *†	<0.001
Repeated chair stand, s	9.6±1.3	12.3±2.9*	11.8±2.8*†	<0.001
Repeated chair stand ≥12 s, %(n)	–	50.7 (351)*	45.2 (96)*†	<0.001
SPPB scores	11.8±0.4	10.5±1.6*	10.8±1.4*†	<0.001
SPPB ≤9, %(n)	–	11.1 (77)*	7.1 (15)*†	<0.001
Number of poor physical performance				<0.001
1, %(n)	–	47.5 (329)*	47.9 (102)*
2, %(n)	–	30.9 (214)*	35.2 (75) *
3 or more, %(n)	–	21.6 (150)*	16.9 (36)*†
Daily living habits
IPAQ, met/week	6224.3±2247.2	4642.6±1702.5*	3961.5±726.8*	<0.001
IPAQ category, %(n)				<0.001
Low	12.0 (50)	21.8 (151)*	22.1 (47)*
Moderate	33.1 (138)	36.7 (254)	42.3 (90)*†
High	54.9 (229)	41.6 (288)*	35.7 (76)*†
Sedentary time, hour	3.6±2.1	3.8±2.5	4.0±2.6*	0.097
Smoking situation, %(n)				0.183
Current smoker	25.2 (105)	29.1 (202)	34.4 (73)
Ex-smoker	60.6 (253)	56.2 (390)	52.2 (111)
Non-smoker	14.2 (59)	14.6 (101)	13.4 (213)
Drinking situation, %(n)				0.111
Drink everyday	14.2 (59)	10.0 (69)	12.1 (26)
Drink occasionally	12.8 (53)	7.2 (50)	11.1 (24)
Ex-drinker	8.4 (35)	7.2 (50)	10.1 (22)
Non-drinker	64.6 (269)	75.5 (524)	66.7 (142)
MNA-SF, score	13.4±2.5	12.8±2.4*	12.7±2.4*	<0.001
GDS-30, score	5.8±4.5	6.6±5.1*	5.9±4.3	0.027

According to the Asian Working Group for Sarcopenia criteria (2019 Consensus Update), sarcopenia was defined by ASM/Ht2<7.0 kg/m2 in men and <5.7 kg/m2 in women, with grip strength <28 kg for men and <18 kg for women or walking speed <1.0 m/s or repeated chair stand ≥12 s or SPPB ≤9. Diminished PP was characterised by the same criteria for low muscle strength or poor PP, but in individuals with preserved muscle mass (ASM/Ht² ≥7.0 kg/m² in men and ≥5.7 kg/m² in women).

P value for overall difference among the three groups based on one-way analysis of variance (ANOVA) for continuous variables and χ2 test for categorical variables.

^*p<0.05 versus normal.

^†p<0.05 versus diminished PP.

ABSI, Body Shape Index; ALT, alanine aminotransferase; ASM, appendicular skeletal muscle mass; AST, aspartate aminotransferase; %BF, % body fat; BMI, body mass index; BRI, Body Roundness Index; BUN, blood urea nitrogen; CCr, creatinine clearance; C-index, Conicity index; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; GDS, Geriatric Depression Scale; HSI, Hepatic Steatosis Index; TyG index, Triglyceride-Glucose Index; IPAQ, International Physical Activity Questionnaire; LAP, lipid accumulation product; MNA-SF, Mini Nutritional Assessment-Short Form; PP, physical performance; SBP, systolic blood pressure; SMM, skeletal muscle mass; SPPB, simple physical performance battery; TC, total cholesterol; TG, triglyceride; VFA, visceral fat area; WC, waist circumference; WHR, waist hip ratio; WHtR, waist-to-height ratio.

Obesity/lipid-related indices, diminished PP and sarcopenia

Tables2 3 present the ORs from logistic regression analyses examining the association between obesity/lipid-related indices and diminished PP or sarcopenia. In the unadjusted analysis (model 1), higher values of WHR (p value for trend=0.011), HSI (p value for trend=0.046), TyG-WC (p value for trend=0.021), and TyG-WHtR (p value for trend=0.001) were significantly associated with diminished PP. After adjusting for age and gender (model 2), these associations persisted (p value for trend=0.016, 0.031, 0.014 and 0.005, respectively), with additional significant trends observed for WHtR (p value for trend=0.038), BRI (p value for trend=0.027) and TyG-BMI (p value for trend=0.028). However, no significant associations were observed between obesity/lipid-related indices and sarcopenia in model 1 and model 2. After multivariate adjustments for all the concomitants in model 3, higher WHtR, BRI, HSI, TyG-BMI, TyG-WC and TyG-WHtR (p value for trend=0.010, 0.003, 0.014, 0.004, 0.013 and 0.001, respectively) were significantly associated with an increased incidence of diminished PP, while higher ABSI (p value for trend=0.016) was significantly associated with a higher prevalence of sarcopenia.

Table 2. Relationship between obesity-related indices and diminished PP or sarcopenia compared with normal group.

	Diminished PP (n=693)				Sarcopenia (n=213)
	Case % (n)	Model 1 OR (95% CI)	Model 2 OR (95% CI)	Model 3 OR (95% CI)	Case % (n)	Model 1 OR (95% CI)	Model 2 OR (95% CI)	Model 3 OR (95% CI)
BMI
Q1 (<22.54)	23.2 (161)	1 (reference)	1 (reference)	1 (reference)	35.2 (75)	1 (reference)	1 (reference)	1 (reference)
Q2 (22.54–24.96)	23.4 (162)	0.808 (0.570 to 1.146)	0.965 (0.668 to 1.394)	0.979 (0.612 to 1.565)	24.4 (52)	0.557 (0.357 to 0.870)	0.672 (0.422 to 1.069)	0.634 (0.311 to 1.294)
Q3 (24.97–27.29)	24.2 (168)	0.836 (0.591 to 1.183)	1.039 (0.720 to 1.497)	1.034 (0.594 to 1.800)	20.7 (44)	0.467 (0.295 to 0.741)	0.568 (0.351 to 0.918)	0.490 (0.198 to 1.216)
Q4 (>27.29)	29.1 (202)	1.373 (0.959 to 1.966)	1.658 (1.136 to 2.422)	1.576 (0.776 to 3.202)	19.7 (42)*	0.612 (0.380 to 0.987)	0.756 (0.459 to 1.244)	0.592 (0.194 to 1.804)
P for trend		0.426	0.192	0.191		0.286	0.390	0.188
WHR
Q1 (<0.890)	21.2 (147)	1 (reference)	1 (reference)	1 (reference)	30.5 (65)	1 (reference)	1 (reference)	1 (reference)
Q2 (0.890–0.920)	22.5 (156)	1.230 (0.873 to 1.735)	1.534 (1.066 to 2.205)	1.493 (0.991 to 2.250)	24.4 (52)	0.927 (0.593 to 1.450)	1.142 (0.713 to 1.830)	1.547 (0.825 to 2.900)
Q3 (0.930–0.976)	26.3 (182)	1.585 (1.124 to 2.235)	1.687 (1.174 to 2.424)	1.583 (1.028 to 2.440)	23.5 (50)	0.983 (0.624 to 1.549)	1.168 (0.724 to 1.885)	1.633 (0.843 to 3.164)
Q4 (>0.976)	30.0 (208)	1.985 (1.406 to 2.802)	2.047 (1.426 to 2.937)	1.752 (1.137 to 2.699)	21.6 (46)	0.986 (0.619 to 1.571)	1.086 (0.668 to 1.766)	1.373 (0.701 to 2.687)
P for trend		0.011	0.016	0.062		0.996	0.462	0.402
WHtR
Q1 (<52.10)	20.8 (144)	1 (reference)	1 (reference)	1 (reference)	33.3 (71)	1 (reference)	1 (reference)	1 (reference)
Q2 (52.10–56.96)	22.9 (159)	1.048 (0.747 to 1.471)	1.152 (0.807 to 1.644)	1.482 (0.943 to 2.330)	21.1 (45)	0.593 (0.378 to 0.931)	0.672 (0.421 to 1.073)	1.116 (0.574 to 2.170)
Q3 (56.97–62.82)	25.8 (179)	1.497 (1.057 to 2.118)	1.544 (1.070 to 2.228)	2.120 (1.276 to 3.523)	26.8 (57)	0.958 (0.617 to 1.488)	1.073 (0.678 to 1.697)	1.515 (0.739 to 3.105)
Q4 (>62.82)	30.5 (211)	2.258 (1.579 to 3.229)	2.089 (1.422 to 3.069)	2.847 (1.600 to 5.066)	18.8 (40)	0.856 (0.528 to 1.387)	0.950 (0.564 to 1.600)	1.331 (0.554 to 3.193)
P for trend		0.077	0.038	0.010		0.884	0.885	0.241
BRI
Q1 (<3.75)	20.5 (142)	1 (reference)	1 (reference)	1 (reference)	33.3 (71)	1 (reference)	1 (reference)	1 (reference)
Q2 (3.75–4.74)	23.2 (161)	1.053 (0.750 to 1.478)	1.155 (0.809 to 1.648)	1.525 (0.969 to 2.401)	21.1 (45)	0.558 (0.375 to 0.923)	0.674 (0.422 to 1.077)	1.099 (0.564 to 2.140)
Q3 (4.75–5.75)	25.8 (179)	1.487 (1.051 to 2.105)	1.526 (1.058 to 2.201)	2.128 (1.282 to 3.533)	26.8 (57)	0.941 (0.606 to 0.146)	1.048 (0.663 to 1.658)	1.444 (0.707 to 2.947)
Q4 (>5.75)	30.4 (211)	2.254 (1.575 to 3.226)	2.081 (1.416 to 3.058)	2.886 (1.622 to 5.136)	18.8 (40)	0.849 (0.524 to 1.376)	0.944 (0.561 to 1.589)	1.284 (0.536 to 3.074)
P for trend		0.060	0.027	0.003		0.909	0.892	0.258
ABSI
Q1 (<0.08185)	23.2 (161)	1 (reference)	1 (reference)	1 (reference)	23.0 (49)	1 (reference)	1 (reference)	1 (reference)
Q2 (0.08185–0.08486)	21.6 (150)	0.879 (0.628 to 1.230)	0.856 (0.603 to 1.216)	0.974 (0.660 to 1.438)	26.8 (57)	1.098 (0.695 to 1.735)	1.094 (0.682 to 1.755)	1.397 (0.759 to 2.570)
Q3 (0.08487–0.08788)	26.3 (182)	1.348 (0.958 to 1.897)	1.214 (0.851 to 1.733)	1.236 (0.829 to 1.843)	23.0 (49)	1.192 (0.739 to 1.922)	1.183 (0.723 to 1.936)	1.678 (0.885 to 3.181)
Q4 (>0.08788)	28.9 (200)	2.010 (1.405 to 2.877)	1.546 (1.060 to 2.254)	1.753 (1.160 to 2.649)	27.2 (58)	1.913 (1.185 to 3.090)	1.720 (1.043 to 2.837)	2.312 (1.214 to 4.401)
P for trend		0.119	0.157	0.102		0.133	0.112	0.016
C-index
Q1 (<1.29)	21.9 (152)	1 (reference)	1 (reference)	1 (reference)	32.4 (69)	1 (reference)	1 (reference)	1 (reference)
Q2 (1.29–1.33)	24.1 (167)	1.161 (0.835 to 1.615)	1.294 (0.917 to 1.826)	1.335 (0.902 to 1.976)	20.7 (44)	0.674 (0.429 to 1.057)	0.726 (0.455 to 1.159)	0.975 (0.526 to 1.807)
Q3 (1.34–1.38)	24.8 (172)	1.545 (1.097 to 2.176)	1.493 (1.044 to 2.135)	1.429 (0.935 to 2.183)	20.7 (44)	0.870 (0.549 to 1.379)	0.928 (0.576 to 1.494)	1.094 (0.564 to 2.122)
Q4 (>1.38)	29.1 (202)	2.725 (1.890 to 3.929)	2.303 (1.566 to 3.385)	2.344 (1.498 to 3.667)	26.3 (56)	1.661 (1.046 to 2.637)	1.644 (1.013 to 2.666)	2.351 (1.213 to 4.558)
P for trend		0.090	0.054	0.074		0.358	0.321	0.198

According to the Asian Working Group for Sarcopenia criteria (2019 Consensus Update), sarcopenia was defined by ASM/Ht2 <7.0 kg/m2 in men and <5.7 kg/m2 in women, with grip strength <28 kg for men and <18 kg for women or walking speed <1.0 m/s or repeated chair stand ≥12 s or SPPB ≤9. Diminished PP was characterised by the same criteria for low muscle strength or poor PP, but in individuals with preserved muscle mass (ASM/Ht² ≥7.0 kg/m² in men and ≥5.7 kg/m² in women).

Model 1, unadjusted; model 2, adjusted for age and gender; model 3, adjusted model 2 and weight, calf circumference, SMM, ASM, total body water, protein, % BF, VFA, T value, ALT, AST, FPG, creatinine, eGFR, CCr, BUN, TC, TG, SBP, DBP, diabetes, hypertension, dyslipidaemia, heart disease, kidney disease, stroke, smoking situation, drinking situation, IPAQ, MNA, GDS.

*p<0.05, **p<0.01.

ABSI, Body Shape Index; ALT, alanine aminotransferase; ASM, appendicular skeletal muscle mass; AST, aspartate aminotransferase; %BF, % body fat; BMI, body mass index; BRI, Body Roundness Index; BUN, blood urea nitrogen; CCr, creatinine clearance; C-index, Conicity Index; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; GDS, Geriatric Depression Scale; IPAQ, International Physical Activity Questionnaire; MNA, Mini Nutritional Assessment; PP, physical performance; SBP, systolic blood pressure; SMM, skeletal muscle mass; SPPB, Simple Physical Performance Battery; TC, total cholesterol; TG, triglycerides; VFA, visceral fat area; WHR, waist hip ratio; WHtR, waist-to-height ratio.

Table 3. Relationship of lipid-related indices and diminished PP or sarcopenia compared with normal group.

	Diminished PP (n=693)				Sarcopenia (n=213)
	Case % (n)	Model 1 OR (95% CI)	Model 2 OR (95% CI)	Model 3 OR (95% CI)	Case % (n)	Model 1 OR (95% CI)	Model 2 OR (95% CI)	Model 3 OR (95% CI)
HSI
Q1 (<29.86)	21.9 (152)	1 (reference)	1 (reference)	1 (reference)	32.4 (69)	1 (reference)	1 (reference)	1 (reference)
Q2 (29.86–33.71)	23.2 (161)	1.031 (0.730 to 1.457)	1.099 (0.762 to 1.585)	1.098 (0.697 to 1.732)	26.8 (57)	0.804 (0.518 to 1.247)	0.928 (0.586 to 1.468)	1.065 (0.553 to 2.048)
Q3 (33.72–37.70)	26.9 (186)	1.323 (0.936 to 1.871)	1.493 (1.033 to 2.157)	1.366 (0.810 to 2.304)	20.7 (44)	0.689 (0.432 to 1.097)	0.783 (0.480 to 1.278)	1.049 (0.476 to 2.311)
Q4 (>37.70)	28.0 (194)	1.438 (1.016 to 2.036)	1.662 (1.143 to 2.418)	1.600 (0.811 to 3.158)	20.2 (43)	0.701 (0.438 to 1.121)	0.937 (0.567 to 1.550)	1.841 (0.689 to 4.918)
P for trend		0.046	0.031	0.014		0.092	0.544	0.189
LAP
Q1 (<28.60)	23.0 (159)	1 (reference)	1 (reference)	1 (reference)	29.9 (64)	1 (reference)	1 (reference)	1 (reference)
Q2 (28.60–45.80)	24.2 (168)	1.077 (0.761 to 1.524)	0.988 (0.683 to 1.428)	1.045 (0.672 to 1.625)	27.9 (59)	0.952 (0.607 to 1.495)	0.965 (0.603 to 1.545)	1.119 (0.591 to 2.119)
Q3 (45.81–68.00)	26.6 (184)	1.204 (0.852 to 1.700)	1.186 (0.819 to 1.717)	1.164 (0.708 to 1.914)	21.1 (45)	0.733 (0.455 to 1.179)	0.820 (0.499 to 1.347)	0.850 (0.391 to 1.846)
Q4 (>68.00)	26.2 (182)	1.150 (0.815 to 1.623)	1.083 (0.742 to 1.580)	1.197 (0.640 to 2.240)	21.1 (45)	0.712 (0.443 to 1.144)	0.796 (0.480 to 1.320)	0.640 (0.232 to 1.767)
P for trend		0.269	0.473	0.061		0.100	0.084	0.110
TyG index
Q1 (<8.41)	25.3 (175)	1 (reference)	1 (reference)	1 (reference)	24.0 (51)	1 (reference)	1 (reference)	1 (reference)
Q2 (8.41–8.77)	23.4 (162)	0.829 (0.589 to 1.166)	0.801 (0.558 to 1.151)	0.660 (0.436 to 0.999)	28.4 (60)	1.060 (0.667 to 1.686)	1.179 (0.726 to 1.914)	1.074 (0.528 to 1.796)
Q3 (8.78–9.11)	26.9 (186)	1.273 (0.894 to 1.813)	1.141 (0.784 to 1.659)	1.023 (0.639 to 1.638)	25.1 (53)	1.247 (0.767 to 2.026)	1.275 (0.768 to 2.116)	0.780 (0.362 to 1.683)
Q4 (>9.11)	24.4 (169)	0.880 (0.626 to 1.238)	0.907 (0.627 to 1.313)	0.779 (0.425 to 1.430)	22.5 (48)	0.856 (0.528 to 1.387)	0.993 (0.596 to 1.656)	0.543 (0.176 to 1.672)
P for trend		0.995	0.994	0.724		0.728	0.997	0.139
TyG-BMI
Q1 (<193.38)	21.8 (151)	1 (reference)	1 (reference)	1 (reference)	36.8 (78)	1 (reference)	1 (reference)	1 (reference)
Q2 (193.38–220.29)	24.2 (168)	0.971 (0.686 to 1.374)	1.155 (0.799 to 1.671)	1.267 (0.788 to 2.038)	23.0 (49)	0.550 (0.350 to 0.865)	0.673 (0.420 to 1.078)	0.475 (0.231 to 0.977)
Q3 (220.30–245.49)	26.1 (181)	1.126 (0.794 to 1.596)	1.272 (0.881 to 1.837)	1.391 (0.785 to 2.467)	20.6 (44)	0.528 (0.331 to 0.842)	0.601 (0.371 to 0.974)	0.264 (0.103 to 0.677)
Q4 (>245.49)	27.9 (193)	1.347 (0.947 to 1.917)	1.643 (1.126 to 2.398)	1.671 (0.801 to 3.483)	19.6 (42)	0.561 (0.349 to 0.903)	0.716 (0.435 to 1.178)	0.357 (0.111 to 1.150)
P for trend		0.098	0.028	0.004		0.221	0.306	0.153
TyG-WC
Q1 (<732.00)	21.4 (148)	1 (reference)	1 (reference)	1 (reference)	31.9 (68)	1 (reference)	1 (reference)	1 (reference)
Q2 (732.00–812.99)	24.6 (170)	1.249 (0.884 to 1.766)	1.267 (0.880 to 1.826)	1.588 (1.006 to 2.508)	26.5 (56)	0.903 (0.576 to 1.414)	0.977 (0.614 to 1.556)	0.997 (0.508 to 1.955)
Q3 (813.00–888.49)	26.9 (186)	1.394 (0.988 to 1.967)	1.535 (1.067 to 2.208)	2.199 (1.290 to 3.749)	19.6 (42)	0.682 (0.423 to 1.098)	0.775 (0.474 to 1.269)	0.885 (0.388 to 2.020)
Q4 (>888.49)	27.1 (188)	1.459 (1.032 to 2.063)	1.631 (1.129 to 2.356)	2.431 (1.244 to 4.749)	22.0 (47)	0.798 (0.501 to 1.273)	0.939 (0.578 to 1.526)	1.049 (0.367 to 2.995)
P for trend		0.021	0.014	0.013		0.224	0.546	0.930
TyG-WHtR
Q1 (<447.00)	20.7 (143)	1 (reference)	1 (reference)	1 (reference)	30.9 (66)	1 (reference)	1 (reference)	1 (reference)
Q2 (447.00–449.79)	24.0 (166)	1.256 (0.892 to 1.768)	1.250 (0.872 to 1.791)	1.640 (1.044 to 2.576)	25.5 (54)	0.892 (0.570 to 1.398)	0.953 (0.598 to 1.518)	0.986 (0.509 to 1.911)
Q3 (449.80–551.21)	26.3 (182)	1.577 (1.115 to 2.229)	1.532 (1.059 to 2.216)	1.996 (1.184 to 3.365)	24.0 (51)	0.962 (0.608 to 1.523)	1.120 (0.692 to 1.812)	0.964 (0.455 to 2.044)
Q4 (>551.21)	29.0 (201)	1.890 (1.333 to 2.678)	1.772 (1.211 to 2.593)	2.468 (1.331 to 4.576)	19.6 (42)	0.856 (0.529 to 1.386)	0.948 (0.565 to 1.589)	0.979 (0.376 to 2.550)
P for trend		0.007	0.005	0.001		0.244	0.969	0.285

According to the Asian Working Group for Sarcopenia criteria (2019 Consensus Update), sarcopenia was defined by ASM/Ht2 <7.0 kg/m2 in men and <5.7 kg/m2 in women, with grip strength <28 kg for men and <18 kg for women or walking speed <1.0 m/s or repeated chair stand ≥12 s or SPPB ≤9. Diminished PP was characterised by the same criteria for low muscle strength or poor PP, but in individuals with preserved muscle mass (ASM/Ht² ≥7.0 kg/m² in men and ≥5.7 kg/m² in women).

Model 1, unadjusted; model 2, adjusted for age and gender; model 3, adjusted model two and weight, calf circumference, SMM, ASM, total body water, protein, % BF, VFA, T value, ALT, AST, FPG, creatinine, eGFR, CCr, BUN, TC, TG, SBP, DBP, diabetes, hypertension, dyslipidaemia, heart disease, kidney disease, stroke, smoking situation, drinking situation, IPAQ, MNA, GDS.

*p<0.05, **p<0.01.

ALT, alanine aminotransferase; ASM, appendicular skeletal muscle mass; AST, aspartate aminotransferase; % BF, % body fat; BMI, body mass index; BUN, blood urea nitrogen; CCr, creatinine clearance; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; GDS, Geriatric Depression Scale; HSI, hepatic steatosis index; IPAQ, International Physical Activity Questionnaire; LAP, lipid accumulation product; MNA, Mini Nutritional Assessment; PP, physical performance; SBP, systolic blood pressure; SMM, skeletal muscle mass; SPPB, Simple Physical Performance Battery; TC, total cholesterol; TG, triglycerides; TyG index, Triglyceride-Glucose Index; VFA, visceral fat area; WC, waist circumference; WHtR, waist-to-height ratio.

Obesity/lipid-related indices and PP measures

Tables45 display the results of logistic regression analyses examining the association between PP measures and obesity/lipid-related indices among those with diminished PP. After adjusting for various factors including age, gender, weight and other health indicators, we found the highest quartile of WHtR, BRI, HSI, TyG-WC and TyG-WHtR was significantly associated with reduced grip strength and slower walking speed (ORs ranging from 1.701 to 2.458 for grip strength; 1.566–1.860 for walking speed). The highest quartile of ABSI was associated with slower walking speed (OR 1.733), longer time to complete repeated chair stands (OR 1.452) and lower SPPB scores (OR 2.054). The highest quartile of C index was associated with reduced grip strength (OR 1.777), slower walking speed (OR 1.860) and lower SPPB scores (OR 2.130). Additionally, the highest quartile of BMI, WHtR, BRI, ABSI, C-index, TyG-BMI, TyG-WC and TyG-WHtR was significantly associated with a greater number of diminished PP measures (OR ranging from 1.722 to 2.315 for two and more; OR ranging from 1.741 to 2.389 for three and more). The logistic regression analyses of the association of PPs and obesity/lipid-related indices in sarcopenia have been shown in tables67. After multivariate adjustments for all the concomitants (including age, gender, weight and other health indicators), we found the highest quartile of ABSI and C-index was significantly associated with reduced grip strength (OR 1.955; 3.118) and longer time to complete repeated chair stands (OR 2.103; 1.956). Moreover, the highest quartile of WHtR, BRI, ABSI, C-index and TyG-WC was significantly associated with a greater number of diminished PP measures (OR ranging from 2.353 to 2.772 for two and more; OR ranging from 4.627 to 7.913 for three and more).

Table 4. Logistic regression analyses of the association of PP measures and obesity-related indices in diminished PP compared with normal group.

	Poor BMI (>27.46)	Poor WHR (>0.97)	Poor WHtR (>61.39)	Poor BRI (>5.75)	Poor ABSI (>0.08788)	Poor C-index (>1.38)
Grip strength<28 kg for male and<18 kg for female
Crude, OR (95% CI)	0.873 (0.650 to 1.173)	1.187 (0.893 to 1.578)	1.434 (1.080 to 1.905)*	1.434 (1.080 to 1.905)*	1.750 (1.315 to 2.330)*	2.534 (1.603 to 4.005)**
Adjusted model, OR (95% CI)	1.016 (0.667 to 1.548)	1.205 (0.851 to 1.706)	1.769 (1.171 to 2.673)*	1.769 (1.171 to 2.673)*	1.371 (0.977 to 1.926)	1.777 (1.250 to 2.526)*
Walking speed<1.0 m/s
Crude, OR (95% CI)	1.691 (1.290 to 2.217)*	1.545 (1.183 to 2.018)*	2.037 (1.551 to 2.674)**	2.037 (1.551 to 2.674)**	1.851 (1.404 to 2.441)**	2.041 (1.308 to 3.185)*
Adjusted model, OR (95% CI)	1.527 (0.954 to 2.446)	1.242 (0.902 to 1.709)	1.833 (1.252 to 2.682)*	1.833 (1.252 to 2.682)*	1.733 (1.256 to 2.391)*	1.860 (1.338 to 2.585)**
Repeated chair stand≥12 s
Crude, OR (95% CI)	1.523 (1.145 to 2.024)*	1.382 (1.040 to 1.838)*	1.416 (1.062 to 1.886)*	1.416 (1.062 to 1.886)*	1.619 (1.209 to 2.167)*	2.394 (1.433 to 3.999)*
Adjusted model, OR (95% CI)	1.361 (0.833 to 2.22)	1.039 (0.743 to 1.452)	0.877 (0.587 to 1.310)	0.877 (0.587 to 1.310)	1.452 (1.036 to 2.034)*	1.310 (0.931 to 1.844)
SPPB≤9
Crude,OR (95% CI)	0.692 (0.386 to 1.241)	1.145 (0.682 to 1.921)	1.535 (0.933 to 2.525)	1.535 (0.933 to 2.525)	2.302 (1.419 to 3.739)*	3.841 (1.265 to 11.665)*
Adjusted model, OR (95% CI)	0.530 (0.207 to 1.355)	0.852 (0.463 to 1.568)	1.288 (0.651 to 2.549)	1.288 (0.651 to 2.549)	2.054 (1.170 to 3.607)*	2.130 (1.138 to 3.987)*
≥ 2 poor physical performances
Crude, OR (95% CI)	1.707 (1.233 to 2.364)*	1.797** (1.304 to 2.477)	2.291 (1.649 to 3.183)**	2.291 (1.649 to 3.183)**	2.431 (1.742 to 3.391)**	2.632 (1.632 to 4.248)**
Adjusted model, OR (95% CI)	1.824 (1.016 to 3.276)*	1.406 (0.948 to 2.085)	1.779 (1.111 to 2.849)*	1.779 (1.111 to 2.849)*	2.120 (1.424 to 3.156)**	2.315 (1.531 to 3.501)**
≥ 3 poor physical performances
Crude, OR (95% CI)	1.391 (0.902 to 2.144)	1.481 (0.969 to 2.264)	2.275 (1.497 to 3.458)**	2.275 (1.497 to 3.458)**	2.138 (1.394 to 3.279)**	3.917 (1.918 to 8.001)**
Adjusted model, OR (95% CI)	2.230 (1.011 to 4.920)*	1.104 (0.651 to 1.873)	2.153 (1.165 to 3.980)*	2.153 (1.165 to 3.980)*	1.741 (1.033 to 2.933)*	2.237 (1.311 to 3.817)*

According to the Asian Working Group for Sarcopenia criteria (2019 Consensus Update), diminished PP was defined by grip strength <28 kg for men and <18 kg for women or walking speed <1.0 m/s or repeated chair stand ≥12 s or SPPB ≤9 with ASM/Ht2 ≥7.0 kg/m2 in men and ≥5.7 kg/m2 in women.

The adjusted model is adjusted with age, gender, weight, calf circumference, SMM, ASM, total body water, protein, % BF, VFA, ALT, AST, FPG, creatinine, eGFR, CCr, BUN, TC, TG, T value, SBP, DBP, diabetes, hypertension, dyslipidaemia, heart disease, kidney disease, stroke, smoking situation, drinking situation, IPAQ, MNA, GDS.

*p<0.05, **p<0.01.

ABSI, Body Shape Index; ALT, alanine aminotransferase; ASM, appendicular skeletal muscle mass; AST, aspartate aminotransferase; % BF, % body fat; BMI, body mass index; BRI, body roundness index; BUN, blood urea nitrogen; CCr, creatinine clearance; C-index, Conicity Index; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; GDS, Geriatric Depression Scale; IPAQ, International Physical Activity Questionnaire; LAP, lipid accumulation product; MNA, Mini Nutritional Assessment; PP, physical performance; SBP, systolic blood pressure; SMM, skeletal muscle mass; SPPB, Simple Physical Performance Battery; TC, total cholesterol; TG, triglycerides; VFA, visceral fat area; WHR, waist hip ratio; WHtR, waist-to-height ratio.

Table 5. Logistic regression analyses of the association of PP measures and lipid-related indices in diminished PP compared with normal group.

	Poor HSI (>37.70)	Poor LAP (>68.00)	Poor TyG (>9.11)	Poor TyG-BMI (>245.49)	Poor TyG-WC (>888.49)	Poor TyG-WHtR (>551.21)
Grip strength<28 kg for male and<18 kg for female
Crude, OR (95% CI)	0.984 (0.735 to 1.316)	0.885 (0.658 to 1.190)	0.951 (0.708 to 1.278)	0.888 (0.661 to 1.193)	1.018 (0.760 to 1.363)	1.231 (0.924 to 1.639)
Adjusted model, OR (95% CI)	2.003 (1.092 to 3.675)*	1.579 (0.720 to 3.460)	3.358 (0.380 to 29.711)	1.677 (0.972 to 2.892)	2.458 (1.446 to 4.179)*	1.701 (1.069 to 2.707)*
Walking speed<1.0 m/s
Crude, OR (95% CI)	1.457 (1.113 to 1.908)*	1.340* (1.023 to 1.756)	1.239 (0.944 to 1.626)	0.633 (0.483 to 0.829)*	0.624 (0.476 to 0.818)*	1.797 (1.370 to 2.356)**
Adjusted model, OR (95% CI)	1.406 (0.825 to 2.395)	1.143 (0.572 to 2.285)	2.239 (0.378 to 13.271)	1.463 (0.901 to 2.376)	1.733 (1.088 to 2.759)*	1.566 (1.370 to 1.866)*
Repeated chair stand≥12 s
Crude, OR (95% CI)	0.889 (0.661 to 1.194)	1.006 (0.750 to 1.351)	0.743 (0.546 to 1.010)	1.238 (0.927 to 1.654)	1.129 (0.842 to 1.513)	1.163 (0.869 to 1.557)
Adjusted model, OR (95% CI)	0.767 (0.426 to 1.383)	1.590 (0.787 to 3.209)	0.827 (0.574 to 1.192)	1.010 (0.597 to 1.711)	0.966 (0.589 to 1.583)	0.938 (0.597 to 1.474)
SPPB≤9
Crude,OR (95% CI)	0.565 (0.305 to 1.044)	0.586 (0.317 to 1.084)	0.669 (0.368 to 1.218)	0.696 (0.388 to 1.249)	0.483 (0.251 to 0.930)*	1.101 (0.651 to 1.861)
Adjusted model, OR (95% CI)	0.372 (0.097 to 1.426)	0.656 (0.169 to 2.551)	0.863 (0.421 to 1.770)	1.083 (0.427 to 2.750)	0.808 (0.316 to 2.067)	1.263 (0.578 to 2.760)
≥ 2 poor physical performances
Crude, OR (95% CI)	1.229 (0.888 to 1.701)	1.202 (0.875 to 1.652)	0.947 (0.688 to 1.303)	1.457* (1.057 to 2.008)	1.445 (1.051 to 1.987)*	1.767 (1.281 to 2.438)*
Adjusted model, OR (95% CI)	1.646 (0.832 to 3.257)	1.652 (0.701 to 3.893)	1.215 (0.810 to 1.823)	1.546 (0.849 to 2.818)	1.885 (1.058 to 3.360)*	1.722 (1.016 to 2.919)*
≥ 3 poor physical performances
Crude, OR (95% CI)	1.127 (0.731 to 1.738)	0.904 (0.583 to 1.402)	0.881 (0.573 to 1.353)	1.267 (0.828 to 1.940)	1.144 (0.744 to 1.757)	1.579 (1.037 to 2.405)*
Adjusted model, OR (95% CI)	1.567 (0.627 to 3.919)	1.733 (0.582 to 5.161)	1.190 (0.680 to 2.084)	2.389 (1.057 to 5.401)*	2.401 (1.108 to 5.203)*	2.233 (1.115 to 4.472)*

According to the Asian Working Group for Sarcopenia criteria (2019 Consensus Update), diminished PP was defined by grip strength <28 kg for men and <18 kg for women or walking speed <1.0 m/s or repeated chair stand ≥12 s or SPPB ≤9 with ASM/Ht2 ≥7.0 kg/m2 in men and ≥5.7 kg/m2 in women.

The adjusted model is adjusted with age, gender, weight, calf circumference, SMM, ASM, total body water, protein, % BF, VFA, ALT, AST, FPG, creatinine, eGFR, CCr, BUN, TC, TG, T value, SBP, DBP, diabetes, hypertension, dyslipidaemia, heart disease, kidney disease, stroke, smoking situation, drinking situation, IPAQ, MNA and GDS.

*p<0.05, **p<0.01.

ALT, alanine aminotransferase; ASM, appendicular skeletal muscle mass; AST, aspartate aminotransferase; % BF, % body fat; BMI, body mass index; BUN, blood urea nitrogen; CCr, creatinine clearance; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; GDS, Geriatric Depression Scale; HSI, hepatic steatosis index; IPAQ, International Physical Activity Questionnaire; LAP, lipid accumulation product; LAP, lipid accumulation product; MNA, Mini Nutritional Assessment; PP, physical performance; SBP, systolic blood pressure; SMM, skeletal muscle mass; SPPB, Simple Physical Performance Battery; TC, total cholesterol; TG, triglycerides; TyG index, triglyceride-glucose index; VFA, visceral fat area; WC, waist circumference; WHtR, weight-to-height ratio.

Table 6. Logistic regression analyses of the association of PP measures and obesity-related indices in sarcopenia compared with normal group.

	Poor BMI (>27.46)	Poor WHR (>0.97)	Poor WHtR (>61.39)	Poor BRI (>5.75)	Poor ABSI (>0.08788)	Poor C-index (>1.38)
Grip strength <28 kg for male and <18 kg for female
Crude, OR (95% CI)	0.933 (0.559 to 1.557)	1.262 (0.783 to 2.034)	1.229 (0.743 to 2.034)	1.229 (0.743 to 2.034)	2.299 (1.466 to 3.607)*	2.534 (1.603 to 4.005)*
Adjusted model, OR (95% CI)	1.319 (0.472 to 3.687)	1.097 (0.739 to 1.628)	1.776 (0.746 to 4.227)	1.776 (0.746 to 4.227)	1.955 (1.071 to 3.567)*	3.118 (1.623 to 5.990)*
Walking speed <1.0 m/s
Crude, OR (95% CI)	1.066 (0.665 to 1.708)	1.227 (0.780 to 1.931)	1.166 (0.721 to 1.885)	1.166 (0.721 to 1.885)	2.134 (1.385 to 3.288)*	2.041 (1.308 to 3.185)*
Adjusted model, OR (95% CI)	1.097 (0.394 to 3.055)	1.080 (0.698 to 1.669)	1.139 (0.491 to 2.643)	1.139 (0.491 to 2.643)	1.780 (0.993 to 3.191)	1.845 (0.978 to 3.479)
Repeated chair stand ≥12 s
Crude, OR (95% CI)	1.383 (0.814 to 2.352)	1.876 (1.132 to 3.108)*	1.741 (1.025 to 2.955)*	1.741 (1.025 to 2.955)*	2.355 (1.427 to 3.889)*	2.394 (1.433 to 3.999)*
Adjusted model, OR (95% CI)	0.700 (0.265 to 1.851)	1.722 (0.908 to 3.266)	1.262 (0.561 to 2.839)	1.262 (0.561 to 2.839)	2.103 (1.128 to 3.921)*	1.956 (1.015 to 3.770)*
SPPB≤9
Crude, OR (95% CI)	3.355 (1.106 to 10.172)*	2.282 (0.733 to 7.098)	7.285 (2.336 to 22.724)*	7.285 (2.336 to 22.724)*	3.391 (1.118 to 10.285)*	3.841 (1.265 to 11.665)*
Adjusted model, OR (95% CI)	3.549 (0.502 to 25.079)	1.168 (0.300 to 4.556)	4.075 (0.777 to 21.381)	4.075 (0.777 to 21.381)	2.262 (0.601 to 8.521)	1.977 (0.507 to 7.718)
≥ 2 poor physical performances
Crude, OR (95% CI)	1.230 (0.750 to 2.016)	1.428 (0.887 to 2.299)	1.351 (0.816 to 2.236)	1.351 (0.816 to 2.236)	2.538 (1.595 to 4.038)**	2.632 (1.632 to 4.248)**
Adjusted model, OR (95% CI)	1.498 (0.519 to 4.326)	1.507 (0.768 to 2.955)	1.383 (0.574 to 3.333)	1.383 (0.574 to 3.333)	2.353 (1.246 to 4.443)*	2.772 (1.383 to 5.555)*
≥ 3 poor physical performances
Crude, OR (95% CI)	1.683 (0.797 to 3.556)	2.345 (1.153 to 4.769)*	2.810 (1.376 to 5.740)*	2.810 (1.376 to 5.740)*	4.685 (2.325 to 9.439)**	3.917 (1.918 to 8.001)**
Adjusted model, OR (95% CI)	1.646 (0.374 to 7.246)	2.455 (0.926 to 6.506)	4.627 (1.279 to 16.735)*	4.627 (1.279 to 16.735)*	4.720 (1.813 to 12.293)*	4.905 (1.780 to 13.513)*

According to the Asian Working Group for Sarcopenia criteria (2019 Consensus Update), sarcopenia was defined by ASM/Ht2<7.0 kg/m2 in men and <5.7 kg/m2 in women, with grip strength <28 kg for men and <18 kg for women or walking speed <1.0 m/s or repeated chair stand ≥12 s or SPPB≤9.

The adjusted model is adjusted with age, gender, weight, calf circumference, SMM, ASM, total body water, protein, % BF, VFA, ALT, AST, FPG, creatinine, eGFR, CCr, BUN, TC, TG, T value, SBP, DBP, diabetes, hypertension, dyslipidaemia, heart disease, kidney disease, stroke, smoking situation, drinking situation, IPAQ, MNA and GDS.

*p<0.05, **p<0.01.

ABSI, body-shape index; ALT, alanine aminotransferase; ASM, appendicular skeletal muscle mass; AST, aspartate aminotransferase; % BF, % body fat; BMI, body mass index; BRI, body roundness index; BUN, blood urea nitrogen; CCr, creatinine clearance; C-index, Conicity-index; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; GDS, Geriatric Depression Scale; IPAQ, International Physical Activity Questionnaire; MNA, Mini Nutritional Assessment; PP, physical performance; SBP, systolic blood pressure; SMM, skeletal muscle mass; SPPB, Simple Physical Performance Battery; TC, total cholesterol; TG, triglycerides; VFA, visceral fat area; WHR, waist hip ratio; WHtR, waist-to-height ratio.

Table 7. Logistic regression analyses of the association of PP measures and lipid-related indices in sarcopenia compared with normal group.

	Poor HSI (>37.70)	Poor LAP (>68.00)	Poor TyG (>9.11)	Poor TyG-BMI (>245.49)	Poor TyG-WC (>888.49)	Poor TyG-WHtR (>551.21)
Grip strength <28 kg for male and <18 kg for female
Crude, OR (95% CI)	0.999 (0.612 to 1.632)	0.777 (0.462 to 1.306)	0.904 (0.554 to 1.478)	0.890 (0.528 to 1.500)	1.003 (0.609 to 1.654)	1.177 (0.711 to 1.949)
Adjusted model, OR (95% CI)	1.640 (0.590 to 4.564)	0.710 (0.216 to 2.335)	1.407 (0.723 to 2.738)	1.830 (0.603 to 5.552)	2.194 (0.695 to 6.929)	2.214 (0.823 to 5.957)
Walking speed <1.0 m/s
Crude, OR (95% CI)	0.736 (0.451 to 1.201)	0.778 (0.479 to 1.262)	0.780 (0.487 to 1.249)	0.841 (0.513 to 1.377)	0.982 (0.613 to 1.571)	1.028 (0.633 to 1.668)
Adjusted model, OR (95% CI)	0.700 (0.253 to 1.942)	0.724 (0.220 to 2.385)	1.032 (0.537 to 1.984)	1.834 (0.592 to 5.677)	0.951 (0.323 to 2.803)	1.095 (0.402 to 2.987)
Repeated chair stand ≥12 s
Crude, OR (95% CI)	1.486 (0.891 to 2.477)	1.133 (0.670 to 1.918)	0.755 (0.433 to 1.316)	1.338 (0.794 to 2.256)	1.460 (0.876 to 2.433)	1.566 (0.932 to 2.631)
Adjusted model, OR (95% CI)	3.231 (1.081 to 9.655)*	0.819 (0.250 to 2.686)	0.746 (0.361 to 1.538)	1.438 (0.501 to 4.129)	1.940 (0.648 to 5.807)	1.726 (0.684 to 4.358)
SPPB ≤9
Crude, OR (95% CI)	2.930 (0.968 to 8.873)	0.566 (0.124 to 2.586)	0.239 (0.031 to 1.852)	2.202 (0.708 to 6.850)	2.125 (0.683 to 6.607)	3.263 (1.076 to 9.890)*
Adjusted model, OR (95% CI)	3.136 (0.709 to 13.868)	1.011 (0.057 to 17.989)	0.128 (0.008 to 2.115)	6.379 (0.718 to 56.641)	4.998 (0.362 to 69.000)	4.187 (0.672 to 26.105)
≥ 2 poor physical performances
Crude, OR (95% CI)	0.917 (0.553 to 1.521)	0.865 (0.517 to 1.447)	0.783 (0.469 to 1.307)	1.036 (0.621 to 1.729)	1.114 (0.676 to 1.835)	1.197 (0.720 to 1.989)
Adjusted model, OR (95% CI)	1.701 (0.564 to 5.131)	0.962 (0.297 to 3.114)	1.111 (0.543 to 2.274)	2.394 (0.754 to 7.604)	1.727 (0.528 to 5.642)	1.793 (0.664 to 4.845)
≥ 3 poor physical performances
Crude, OR (95% CI)	1.661 (0.801 to 3.446)	0.849 (0.375 to 1.920)	0.769 (0.340 to 1.736)	1.296 (0.603 to 2.783)	1.432 (0.680 to 3.015)	2.083 (1.015 to 4.276)*
Adjusted model, OR (95% CI)	2.888 (0.593 to 14.067)	0.463 (0.064 to 3.329)	0.666 (0.180 to 2.461)	3.294 (0.578 to 18.756)	7.913 (1.346 to 46.517)*	3.873 (0.947 to 15.842)

According to the Asian Working Group for Sarcopenia criteria (2019 Consensus Update), sarcopenia was defined by ASM/Ht2<7.0 kg/m2 in men and <5.7 kg/m2 in women, with grip strength <28 kg for men and <18 kg for women or walking speed <1.0 m/s or repeated chair stand ≥12 s or SPPB≤9.

The adjusted model is adjusted with age, gender, weight, calf circumference, SMM, ASM, total body water, protein, % BF, VFA, ALT, AST, FPG, creatinine, eGFR, CCr, BUN, TC, TG, T value, SBP, DBP, diabetes, hypertension, dyslipidaemia, heart disease, kidney disease, stroke, smoking situation, drinking situation, IPAQ, MNA and GDS.

*p<0.05.

ALT, alanine aminotransferase; ASM, appendicular skeletal muscle mass; AST, aspartate aminotransferase; % BF, % body fat; BMI, body mass index; BUN, blood urea nitrogen; CCr, creatinine clearance; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; GDS, Geriatric Depression Scale; HSI, hepatic steatosis index; IPAQ, International Physical Activity Questionnaire; LAP, lipid accumulation product; MNA, Mini Nutritional Assessment; PP, physical performance; SBP, systolic blood pressure; SPPB, Simple Physical Performance Battery; TC, total cholesterol; TG, triglycerides; TyG index, triglyceride-glucose index; VFA, visceral fat area; WC, waist circumference; WHtR, waist-to-height ratio.

Discussion

Our study indicates that in older adults, indices of abdominal obesity, hepatic steatosis and TyG-related metrics show independent associations with diminished PP, especially in the context of unchanged muscle mass. Moreover, elevated levels of these markers correlate with an increased probability of experiencing reduced PP. To further refine these findings, our evidence allows for a ranking of the 12 indices regarding their strength of association. The indices that consistently demonstrated the strongest and most robust associations across multiple outcomes were ABSI and C index. ABSI was uniquely and independently associated with a diagnosis of sarcopenia itself, while both ABSI and C index were prominently linked to a wider array of PP deficits and with having a greater number of impaired PP measures. Besides, these indicators (particularly, WHtR, BRI, TyG-WC and TyG-WHtR) collectively signal a heightened risk of diminished PP among those with sarcopenia.

Obesity, especially abdominal obesity, is recognised as a significant risk factor for cardiovascular events and all-cause mortality. There is a growing consensus that visceral fat is more detrimental to health than subcutaneous fat, as it poses a higher risk for various diseases which may relate to sarcopenia.^{19 20} However, the studies of the relationship between abdominal obesity, sarcopenia and PP remain inconsistent. A Dutch study demonstrated that in chronic obstructive pulmonary disease (COPD) patients eligible for pulmonary rehabilitation, the presence of abdominal obesity, indicated by a high android/gynoid percentage fat mass ratio, seems to have a protective effect on PP, especially in those with sarcopenia.³⁶ This could be attributed to the varying choices of indicators for abdominal obesity. Therefore, there is a continued need for a simple and effective indicator to better reflect abdominal obesity. Our findings indicate that both WHtR and BRI demonstrate associations with diminished PP, while ABSI and C-index show consistent relationships with onset and progression of sarcopenia. Unlike traditional WC evaluations (WHR), WHtR, BRI, ABSI and C-index consider additional factors like height and BMI, potentially offering a more comprehensive reflection of body shape and visceral fat distribution. Moreover, as newer measures of abdominal obesity, WHtR, BRI, ABSI and C-index have been found to be more effective than other anthropometric indicators in estimating the risk for various diseases, including obesity,³⁷ cardiometabolic disease,38,40 kidney disease41,43 and cancer,^{44 45} which may be associated with sarcopenia or frailty. Therefore, further study is needed to investigate whether abdominal obesity-related indices that include height and BMI can more effectively identify diminished PP and sarcopenia, offering a new direction for studying the ‘obesity paradox’ in sarcopenia.⁸

On the other hand, IR, a prevalent metabolic disorder, is also linked to sarcopenia.²² It hampers glucose uptake in muscle cells, leading to reduced energy and muscle protein loss.23,25 Additionally, IR disrupts muscle metabolism and may provoke inflammation and oxidative stress, further diminishing muscle strength.^{21 46} The TyG index, which considers FPG and TG levels, is a reliable, simpler and more cost-effective proxy for IR.⁴⁷ Recent studies have shown that TyG and related indices were associated with low muscle mass,⁴⁸ sarcopenia¹⁸ and sarcopenic obesity.⁴⁹ However, reports of the relationship between IR-related index and sarcopenia remain controversial. Similarly, the TG/HDL ratio, another indicator of IR, was found to be negatively associated with sarcopenia in the CHARLS study.⁵⁰ In our study, we observed that higher TyG-WC showed associations with several measures of diminished PP in individuals with sarcopenia, although no significant linear association was detected between sarcopenia diagnosis itself and the TyG index or its related indices. Concurrently, we discovered that TyG-related indices (TyG-BMI, TyG-WC and TyG-WHtR) were found to be associated with diminished PP in individuals with relatively maintained muscle mass. This finding could be due to the influence of obesity on the association between muscle strength and IR, where muscle mass is negatively associated with IR in individuals with low fat mass and the protective effect of muscle mass against IR lessens as fat mass increases.⁵¹ This suggests that IR and diabetes might initially manifest in muscle function, especially in obese individuals, which aligns with the findings of our previous research.^{30 52} Furthermore, after adjusting for body composition, indices such as TyG-BMI, TyG-WC and TyG-WHtR showed stronger associations with diminished PP and sarcopenia compared with the TyG index alone.

Non-alcoholic fatty liver disease (NAFLD), sarcopenia and sarcopenic obesity frequently coexist, especially in the ageing population.⁵³ HSI serves as a simple and efficient screening tool for NAFLD⁵⁴ and could be employed to identify individuals at risk for diminished PP and sarcopenia. Despite the potential, research in this area remains limited. A Korean study found that middle-aged men (over 50 years old) and postmenopausal women in the highest quartile of HSI had a 5.63-fold and 3.58-fold higher risk, respectively, of having reduced muscle strength compared with their counterparts in the lowest quartile.⁵⁵ In our study, we observed a significant association between elevated HSI values and diminished PP. However, no statistically significant association was found between HSI and sarcopenia. A prospective study showed that individuals with NAFLD, indicated by an HSI above 36, were more likely to develop low muscle mass (ASM/BMI) and muscle strength (hand grip strength/BMI) after 2 years.⁵⁶ This discrepancy may be attributed to the varying definitions used for muscle mass and muscle strength. To our knowledge, BMI and its components, such as weight and height, are used in identifying HSI, low muscle mass or sarcopenia, potentially leading to interaction effects. Another comparative analysis has also demonstrated that after adjusting for BMI, high HSI value was robustly associated with a higher likelihood of low ALM/BMI.¹⁶ Going forward, further investigation is needed into the use of HSI for predicting diminished PP and sarcopenia, with a focus on the influence of BMI.

The major advantage of this study lies in its systematic evaluation and direct comparison of 12 obesity and lipid-related indices in relation to sarcopenia and diminished PP. Through this comprehensive approach, we identified a pattern of associations in which central body shape indices, particularly ABSI and C-index, demonstrate significantly stronger associations with sarcopenia and functional decline than traditional anthropometric measures such as BMI. Notably, these indices exhibit the capacity to identify early functional deterioration even in the absence of overt muscle loss, suggesting their potential utility in the detection of pre-sarcopenic states. These findings provide new evidence supporting the incorporation of body shape-based indices into risk assessment protocols for sarcopenia and age-related functional decline. However, this study faced several limitations. First, due to its cross-sectional design, we were unable to determine whether obesity and lipid-related clinical changes cause diminished PP and sarcopenia or if the relationship is reversed. This implies that further research is necessary to clarify the directionality of this association. Second, muscle mass diagnosis relied solely on BIA, a method that, while cost-effective, rapid and non-invasive, may not be as precise as CT, MRI or DEXA scans. BIA measurements are subject to various physical assumptions and can be affected by factors such as oedema, skin temperature, sweating and bladder volume. Thirdly, since the assessments were conducted in a public facility, the participants tended to be more active and healthier, which may limit the generalisability of our findings to the broader older adults. Future prospective studies should incorporate a multifactorial approach, enrol a larger and more diverse group of participants, and conduct more comprehensive cohort studies to deepen our understanding of the interplay between obesity, diminished PP and sarcopenia. Fourth, although we recognised the potential for gender differences in the relationship between obesity-lipid indices and functional outcomes, we did not perform formal gender-stratified analyses. This decision was primarily due to the limited sample size of our study, which would have resulted in underpowered subgroups and potentially unreliable estimates. Furthermore, gender-specific cut-off values for several novel indices (eg, BRI and C index) have not been universally established, making interpretation challenging. Future large-scale, multicentre studies are warranted to thoroughly investigate effect modification by gender and to derive and validate sex-specific thresholds for these indices where applicable.

Conclusions

The present study indicates that abdominal obesity, along with lipid-related indices, may play a role in the development and advancement of sarcopenia. Notably, central body shape indices, particularly ABSI and the C index, demonstrated the strongest and most consistent associations with sarcopenia and functional impairment, suggesting their potential utility as sensitive biomarkers in clinical assessment. Consequently, in diagnosing and assessing sarcopenia, we should take into account not only the loss of muscle mass but also the effects of lipid accumulation and alterations in glycolipid metabolism, according to the characteristics of body composition changes in older adults. The integration of these body shape-based measures, especially ABSI and C index, could improve early identification of high-risk individuals even before significant muscle loss occurs. Adopting this holistic approach will bolster our capacity to identify pre-sarcopenia states and enhance the efficacy of sarcopenia prevention and treatment strategies.

Data availability statement

Data are available upon reasonable request.