Irisin-to-leptin ratio as a novel biomarker of favourable body composition and insulin sensitivity in elderly residents: A prospective pilot study

Irisin-to-leptin ratio as a novel biomarker of favourable body composition and insulin sensitivity in elderly residents: A prospective pilot study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Irisin-to-leptin ratio as a novel biomarker of favourable body composition and insulin sensitivity in elderly residents: A prospective pilot study Yu-Hsin Wu, Yu-Jia Shih, Li-Chen Huang, Hsin-Yu Chen, Yu-Fong Syu, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7879242/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Sarcopenic obesity poses a growing concern among older adults due to its complex interplay between muscle loss, adiposity and metabolic dysfunction. Whereas irisin and leptin are key regulators of muscle–fat cross-talk, their combined predictive utility in ageing populations remains unclear. This study aimed to investigate the association between the serum irisin-to-leptin (I/L) ratio and body composition, insulin sensitivity and adipokines profiles in a super-aged Taiwanese population, and to assess the impact of nutrition education with or without protein supplementation on these metabolic markers. Methods A prospective pilot study was conducted among 36 elderly residents with a mean age of approximately 78 years, residing in senior homes in Northern Taiwan. Sarcopenia was defined using the Asian Working Group for Sarcopenia 2019 criteria. Anthropometric parameters were measured via bioelectrical impedance analysis. Fasting serum levels of irisin, leptin, adiponectin and insulin, and Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) were measured. Participants were stratified by sarcopenia status and median I/L ratio. A subset of participants underwent a 3-month nutrition intervention with or without high-protein supplementation. Multivariate linear regression was performed to assess associations between I/L ratio and metabolic indices. Results A higher I/L ratio was associated with significantly lower fat mass, fat mass index, per cent body fat, HOMA-IR and insulin, triglycerides, very-low-density lipoprotein cholesterol and high-sensitivity C-reactive protein levels (all p < 0.05), and with higher adiponectin levels and adiponectin/leptin ratio. Multivariate analysis confirmed that a higher I/L ratio independently predicted lower fat mass index (B = −0.164, p = 0.004), lower HOMA-IR (B = −0.036, p = 0.030) and higher adiponectin levels (B = 0.144, p = 0.002). Interestingly, despite a higher prevalence of sarcopenia, individuals with higher I/L ratios exhibited more favourable metabolic profiles. Nutrition education was associated with increased irisin levels ( p = 0.033), while protein supplementation selectively increased adiponectin levels ( p = 0.006) without affecting body composition. Conclusion A higher I/L ratio was associated with lower adiposity, improved insulin sensitivity and reduced inflammation, suggesting a distinct metabolic phenotype among super-aged adults. The I/L ratio may serve as a novel integrative biomarker of metabolic resilience in ageing populations. Nutrition education alone may enhance irisin levels, highlighting the potential of dietary strategies in modulating endocrine function and metabolic health in older adults. Trial registration: Not applicable. Irisin-to-leptin ratio Sarcopenic obesity Insulin sensitivity Adiponectin Nutritional intervention Elderly population Figures Figure 1 1. Introduction Sarcopenia and sarcopenic obesity are prevalent phenotypes in older adults and have been associated with increased all-cause mortality [ 1 , 2 ]. First described by Rosenberg in 1989 [ 3 ], sarcopenia is characterized by the progressive and generalized loss of skeletal muscle mass and strength with advancing age, representing a major geriatric syndrome [ 4 ]. It is linked to numerous adverse health outcomes, including physical disability, diminished quality of life, elevated risks of falls and fractures, hospitalization and mortality [ 2 , 5 – 7 ]. Sarcopenic obesity, defined by reduced muscle mass and function along with excess adiposity, has emerged as a growing concern due to its association with mortality, comorbidities and geriatric syndromes [ 8 – 10 ]. These conditions are often associated with adverse outcomes, such as insulin resistance, systemic inflammation and frailty [ 11 – 14 ]. While sarcopenia and sarcopenic obesity share overlapping risk factors, their underlying metabolic signatures remain complex and poorly understood, particularly in elderly populations [ 2 , 8 , 15 ]. Recent studies have focused on endocrine signals originating from muscle and adipose tissue, especially irisin and leptin, as potential biomarkers reflecting the association between muscle anabolism and adiposity. Irisin, which is a myokine secreted by skeletal muscles during physical activity [ 16 ], and leptin, which is an adipokine produced by the adipose tissue [ 17 ], are key regulators of energy metabolism [ 18 – 20 ]. Although the physiological role of irisin remains unclear, it is known to promote the browning of white fat and improve insulin sensitivity [ 16 , 20 ]. Leptin exhibits a dualistic role, characterized by elevated levels of obesity and inflammation, but reduced levels of malnutrition, reflecting both metabolic excess and deficiency [ 21 – 23 ]. This complexity limits its interpretive value, especially in older adults [ 24 ]. Adiponectin, another adipokine, is consistently linked to enhanced insulin sensitivity [ 25 , 26 ], while insulin resistance, often assessed using Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), increases with age and muscle decline [ 27 , 28 ]. Nevertheless, given the biological complexity and context-dependent variability of these hormone levels, their individual interpretation may be limited in ageing populations with diverse body compositions and nutritional states. To address this issue, we sought to investigate whether the irisin-to-leptin (I/L) ratio could be used as a more integrative biomarker, capturing the relative balance between muscle- and adipose-derived signals. Preliminary findings from a cross-sectional study in patients with familial partial lipodystrophy suggested that a higher I/L ratio may be associated with more favourable metabolic profiles, including reduced adiposity, improved insulin sensitivity and increased adiponectin levels [ 29 ]. Given that irisin or leptin alone may lack sufficient discriminatory power because of confounding factors, such as adiposity, inflammation or malnutrition, their combined ratio may serve as a more informative biomarker for the interplay between anabolic and catabolic hormonal activity [ 30 – 32 ]. However, this ratio has not been extensively investigated in super-aged populations, especially in relation to sarcopenia and longitudinal nutritional interventions. This pilot study aimed to explore the association between serum irisin, leptin, the I/L ratio, and indicators of metabolic health, body composition, and sarcopenia status in super-aged Taiwanese adults residing in senior citizen homes. To further examine the potential impact of nutritional support on these biomarkers and body composition parameters, a 3-month nutrition education intervention was implemented. Our findings may provide insights into the utility of the I/L ratio as a novel biomarker for identifying favourable metabolic phenotypes in geriatric populations. 2. Materials and methods 2.1. Participants This prospective pilot study was conducted between August and December 2018 among community-dwelling geriatric people aged ≥ 65 years, recruited from senior citizen homes in Northern Taiwan. A total of 40 older adults who met the inclusion criteria were enrolled. Participants were excluded if they had severe cognitive impairment diagnosed by a neurology specialist and receiving pharmacologic treatment, acute inflammatory conditions, severe renal or hepatic disease, active malignancy, conditions significantly affecting muscle mass (e.g., muscular dystrophy, prolonged high-dose corticosteroid use) or inability to undergo bioelectrical impedance analysis (BIA; such as those who had a pacemaker). Finally, 36 elderly people were enrolled in the study programme. The study protocol was approved by the Institutional Review Board of Chang Gung Memorial Hospital (IRB No.: 201800483A3). Written informed consent was obtained from all participants. 2.2. Study design and data collection Comprehensive data were collected through structured interviews and physical assessments. Information included demographic characteristics, medical history and lifestyle habits. Nutritional status was assessed using the Mini-Nutritional Assessment questionnaire, with malnutrition risk defined as a score ≤ 23.5. Anthropometric measurements were obtained by trained personnel using BIA, and body mass index (BMI; kg/m²) and lean and fat mass were also assessed. All participants received a 3-month nutrition education programme, which included individualized dietary counselling and group-based educational sessions on balanced nutrition, protein intake and dietary strategies for preserving muscle health. Nutrition education was delivered by a registered dietitian and reinforced monthly. In participants with low baseline protein intake or malnutrition risk, the intervention was supplemented with oral nutritional supplements containing protein, vitamins and essential nutrients. Adherence was monitored and reinforced through follow-up phone calls and in-person check-ins during the study period. 2.3. Sarcopenia diagnosis and body composition assessment Body composition was assessed via multi-frequency BIA using the InBody 270 analyzer (Biospace Co. Ltd., Seoul, Korea). Skeletal muscle mass index (SMI) was calculated as appendicular skeletal muscle mass (kg) divided by height squared (m²). Fat mass index (FMI) was similarly calculated using total fat mass (kg) from the BIA data. Sarcopenia was diagnosed according to the updated 2019 criteria of the Asian Working Group for Sarcopenia [ 2 ], defined by low muscle mass (SMI < 7.0 kg/m 2 for men and < 5.7 kg/m 2 for women). Obesity was defined as a body fat percentage ≥ 20 in men and ≥ 30 in women or a BMI ≥ 25 kg/m 2 according to the World Health Organization criteria for Asian populations. 2.4. Biochemical measurements Fasting venous blood samples (10 mL) were collected in the morning after an overnight fast of at least 8 hours. Samples were centrifuged at 3000 rpm for 15 minutes at 4 °C, and serum was aliquoted and stored at −80 °C until analysis. Serum irisin, leptin, adiponectin and insulin levels (mg/dL) were measured using commercial enzyme-linked immunosorbent assay (ELISA) kits (e.g., Abcam, UK for irisin; BioVendor for leptin; R&D Systems for adiponectin and Abbott for insulin). Serum irisin levels were measured using a commercially available human ELISA kit (Abcam, UK, Ltd., Taiwan). The assay demonstrated an intra-assay and inter-assay coefficient of variation 2.0 µg/mL. All procedures were performed in accordance with the manufacturer’s instructions. Fasting plasma glucose (mg/dL) levels were measured using standard laboratory methods. Insulin resistance was estimated using the HOMA-IR, calculated as follows: HOMA-IR = [fasting insulin (mg/dL) × fasting glucose (mg/dL)] / 405. The I/L ratio was calculated by dividing serum irisin concentration (mg/dL) by serum leptin concentration (mg/dL). 2.5. Statistical analysis Data were analysed using SPSS Statistics version 24.0 (IBM Corp., Armonk, NY, USA). Continuous variables are presented as median (25th and 75th quartiles) and compared using the Mann–Whitney U test. Categorical data are presented as numbers (percentages) and compared using the chi-square test. Multivariate linear regression analyses were performed to determine the association of the I/L ratio (independent variable) with FMI, HOMA-IR and adiponectin levels, adjusting for age, sex, history of hypertension and diabetes. To assess the impact of the 3-month intervention, pre- and post-intervention data (including body composition and biochemical markers) were compared using the Wilcoxon signed-rank test for paired samples. Changes were evaluated within participants to determine the effectiveness of nutrition education with or without nutrient supplementation. Results were considered statistically significant at a two-sided p-value < 0.05. 3. Results 3.1. Baseline characteristics of elderly participants with and without sarcopenia in Northern Taiwan A total of 36 older adults (18 women and 18 men) were included in the final analysis. The median age of participants in the non-sarcopenic group (n = 23) was 76 years, whereas that in the sarcopenic group (n = 13, 36.1%) was 79 years. Baseline characteristics stratified by sarcopenia status are presented in Table 1. Although the sarcopenic group was slightly older than the non-sarcopenic group (79 vs. 76 years), the difference was not statistically significant. As expected, individuals with sarcopenia had significantly lower BMI (22.2 vs. 25.3 kg/m 2 , p = 0.005), lower skeletal muscle mass (20.0 vs. 25.3 kg, p = 0.008) and SMI (5.3 vs. 7.3 kg/m 2 , p < 0.001). Interestingly, no significant differences were observed in other biochemical markers, including lipid profile, insulin levels, HOMA-IR and leptin and adiponectin levels (Table 1). Table 1 Comparisons of baseline characteristics between non-sarcopenia and sarcopenia groups (n = 36). Characteristics Non-sarcopenia (n = 23) SMI ≧ 7.3 kg/m2 in male or 5.54 kg/m2 in female Sarcopenia (n = 13) SMI < 7.3 kg/m 2 in male or 5.54 kg/m 2 in female p -value Age 76.0 (71.0, 84.0) 79.0 (76.5, 83.0) 0.379 Gender (n, %) 0.729 Female 11 (47.8) 7 (53.8) Male 12 (52.2) 6 (46.2) Hypertension (n, %) 19 (82.6) 9 (69.2) 0.354 Diabetes (n, %) 4 (17.4) 2 (15.4) 0.877 Dyslipidemia (n, %) 2 (8.7) 1 (7.7) 0.917 Weight (kg) 65.0 (59.7, 74.0) 55.3 (48.1, 58.7) 0.001* BMI (kg/m 2 ) 25.3 (23.6, 29.8) 22.2 (19.7, 25.6) 0.005* Body fat mass (kg) 22.0 (15.4, 25.1) 18.8 (9.0, 22.2) 0.07 Skeletal muscle mass (kg) 23.5 (20.3, 27.0) 20.2 (16.4, 21.9) 0.008* Per cent body fat (%) 33.4 (26.7, 38.5) 32.6 (19.6, 38.7) 0.474 SMI (kg/m2) 7.3 (6.2, 8.1) 5.3 (5.0, 6.6) < 0.001* FMI (kg/m2) 8.6 (6.3, 10.6) 8.0 (3.9, 9.0) 0.169 Obesity prevalence (n, %) 9 (39.1) 5 (38.5) 0.967 MNA scores 26.0 (23.5, 27.0) 22.0 (19.8, 27.0) 0.055 Haemoglobin (g/dL) 12.9 (12.5, 14.3) 13.5 (12.8, 14.6) 0.397 Alanine transaminase (U/L) 21.0 (13.0, 23.0) 19.0 (14.0, 25.5) 0.948 Total cholesterol (mg/dL) 161.0 (141.0, 182.0) 163.0 (152.0, 192.5) 0.312 Triglycerides (mg/dL) 107.0 (84.0, 148.0) 75.5 (128.0, 176.0) 0.795 Fasting glucose (mg/dL) 98.0 (92.0, 103.0) 92.0 (82.5, 106.0) 0.267 HDL-cholesterol (mg/dL) 54.0 (41.0, 61.0) 49.0 (41.0, 55.0) 0.58 LDL-cholesterol (mg/dL) 105.0 (88.0, 119.0) 107.0 (101.5, 120.0) 0.397 Insulin (µU/mL) 9.5 (5.7, 13.4) 7.4 (4.2, 9.3) 0.169 HOMA-IR 2.2 (1.4, 3.1) 1.8 (0.9, 2.6) 0.19 TSH (mIU/L) 1.9 (1.4, 2.8) 2.0 (1.4, 2.3) 0.897 Creatinine (mg/dL) 1.1 (0.9, 1.4) 0.9 (0.7, 1.2) 0.087 hsCRP (mg/L) 2.0 (1.0, 3.5) 1.0 (0.6, 5.7) 0.58 Adiponectin (µg/mL) 4.0 (2.7, 7.8) 6.9 (3.3, 9.6) 0.379 Leptin (ng/mL) 11.9 (3.6, 44.6) 6.4 (1.7, 15.9) 0.488 Abbreviations: BMI, body mass index; SMI, skeletal mass index; FMI, fat mass index; MNA, mini-nutritional assessment; HDL: high density lipoprotein lipase cholesterol; LDL: low density lipoprotein lipase cholesterol; HOMA-IR, homeostatic model assessment for insulin resistance; TSH, thyroid-stimulating hormone; hsCRP: high-sensitivity C reactive protein. Continuous data are reported as median (25th and 75th quartile) and compared using the Mann-Whitney U Test; categorical data are shown as numbers (percentages) and compared using the chi-square test. * Indicates a significant difference between non-sarcopenia and sarcopenia groups. BMI = body weight (kg)/height (m 2 ); SMI = skeletal muscle mass (kg)/height (m 2 ); FMI = fat mass (kg)/height (m 2 ) using body impedence analysis. Sarcopenia was defined as the lowest two quintiles of SMI categorized by gender. Obesity was defined as body fat percentage ≧ 20 in males or 30 in females according to the WHO criteria for Asian populations. 3.2. A higher irisin-to-leptin ratio is associated with favourable body composition, improved insulin sensitivity and metabolic health in a super-aged elderly population Table 2 illustrates the baseline characteristics of elderly participants stratified by high and normal values of the I/L ratio. Participants in the high I/L ratio group (≥ 2.212) exhibited a significantly more favourable metabolic and body composition profile than those with a normal I/L ratio (< 2.212). Individuals with a high I/L ratio had significantly lower body fat mass (median, 16.8 vs. 22.5 kg; p = 0.031), per cent body fat (median, 29.0% vs. 35.8%; p = 0.031) and FMI (median, 7.0 vs. 8.9 kg/m²; p = 0.029), indicating a leaner body composition, than those with a normal I/L ratio. Obesity prevalence was also significantly lower in the high I/L ratio group (66.7% vs. 94.4%; p = 0.035). Table 2 Baseline characteristics between groups with and without higher ratio of serum irisin/leptin level (n = 36). Characteristics Normal ratio of irisin/leptin (n = 18) Irisin/leptin < 2.212 Higher ratio of irisin/leptin (n = 18) Irisin/leptin ≧ 2.212 p -value Age 78.0 (72.5, 83.25) 78.5 (74.8, 84.0) 0.521 Gender (n, %) 1 Female 9 (50.0) 9 (50.0) Male 9 (50.0) 9 (50.0) Hypertension (n, %) 15 (83.3) 13 (72.2) 0.423 Diabetes (n, %) 3 (16.7) 3 (16.7) 1 Dyslipidemia (n, %) 1 (5.6) 2 (11.1) 0.546 Weight (kg) 63.1 (55.3, 73.6) 57.1 (50.5, 65.9) 0.134 BMI (kg/m 2 ) 25.6 (23.5, 29.9) 23.5 (21.6, 26.0) 0.059 Body fat mass (kg) 22.5 (18.3, 26.5) 16.8 (13.2, 22.5) 0.031* Skeletal muscle mass (kg) 21.5 (20.0, 26.4) 21.3 (16.8, 25.9) 0.65 Per cent body fat (%) 35.8 (28.9, 40.2) 29.0 (22.0, 36.1) 0.031* Basal metabolic rate 1227 (1176.5, 1400.0) 1227.5 (1071.0, 1392.8) 0.743 Waist to hip ratio 0.88 (0.74, 0.90) 0.85 (0.78, 0.87) 0.091 SMI (kg/m2) 7.1 (6.1, 7.8) 6.5 (5.2, 7.3) 0.252 FMI (kg/m2) 8.9 (7.0, 11.1) 7.0 (5.1, 8.8) 0.029* Obesity prevalence (n, %) 17 (94.4) 12 (66.7) 0.035* MNA scores 25.5 (22.4, 27.1) 24.0 (22.3, 27.0) 0.501 Haemoglobin (g/dL) 13.0 (12.6, 14.0) 13.4 (12.5, 14.9) 0.606 Alanine transaminase (U/L) 20.5 (14.5, 25.0) 18.0 (13.0, 23.0) 0.462 Total cholesterol (mg/dL) 169.0 (153.3, 186.8) 153.0 (140.0, 192.3) 0.118 Triglycerides (mg/dL) 141.0 (100.5, 184.5) 96.5 (78.0, 129.5) 0.024* Fasting glucose (mg/dL) 100.0 (92.0, 104.3) 95.0 (88.0, 105.0) 0.293 HDL-cholesterol (mg/dL) 47.0 (39.8, 61.0) 52.0 (45.8, 58.0) 0.424 VLDL-cholesterol (mg/dL) 28.5 (20.5, 36.8) 19.0 (15.8, 26.3) 0.022* LDL-cholesterol (mg/dL) 109.0 (103.8, 121.3) 101.5 (86.0, 116.8) 0.068 Insulin (µU/mL) 11.2 (8.1, 16.3) 6.0 (4.4, 9.5) 0.007* HOMA-IR 3.0 (2.0, 4.1) 1.4 (1.0, 2.4) 0.009* TSH (mIU/L) 2.1 (1.5, 2.8) 1.8 (1.4, 2.3 0.339 Creatinine (mg/dL) 1.3 (0.9, 1.4) 1.0 (0.7, 1.1) 0.161 hsCRP (mg/L) 2.5 (1.0, 6.6) 1.1 (0.5, 1.8) 0.029* Adiponectin (µg/mL) 3.8 (2.6, 6.9) 6.9 (3.6, 15.9) 0.017* Leptin (ng/mL) 13.7 (10.0, 49.8) 3.4 (1.7, 13.5) 0.001* Adiponectin/Leptin 0.21 (0.06, 0.70) 1.73 (0.49, 6.25) < 0.001* Irisin (µg/mL) 6.5 (4.4, 7.9) 77.8 (6.6, 211.7) 0.004* Irisin/leptin 0.4 (0.2, 0.8) 7.7 (3.4, 38.6) < 0.001* Abbreviations: BMI, body mass index; SMI, skeletal mass index; FMI, fat mass index; MNA, mini-nutritional assessment; HDL: high density lipoprotein lipase cholesterol; LDL: low density lipoprotein lipase cholesterol; HOMA-IR, homeostatic model assessment for insulin resistance; TSH, thyroid-stimulating hormone; hsCRP: high-sensitivity C reactive protein Continuous data are reported as median (25th and 75th quartile) and compared using the Mann-Whitney U Test; categorical data are shown as numbers (percentages) and compared using the chi-square test. * Indicates a significant difference between non-sarcopenia and sarcopenia groups. BMI = body weight (kg)/height (m 2 ); SMI = skeletal muscle mass (kg)/height (m 2 ); FMI = fat mass (kg)/height (m 2 ) using body impedence analysis. Higher ratio of irisin/leptin referred to the upper half of the serum irisin/leptin distribution, whereas normal ratio of irisin/leptin referred to the lower half of the serum irisin/leptin level. Obesity was defined as body fat percentage ≧ 20 in males or 30 in females according to the WHO criteria for Asian populations. In terms of metabolic markers, the high I/L ratio group demonstrated significantly reduced serum triglyceride levels (median, 96.5 vs. 141.0 mg/dL; p = 0.024) and lower VLDL-cholesterol levels (19.0 vs. 28.5 mg/dL; p = 0.022), reflecting a more favourable lipid profile. Furthermore, markers of insulin resistance were markedly improved among those in the high I/L ratio group. These individuals had significantly lower fasting insulin levels (median, 6.0 vs. 11.2 µg/mL; p = 0.007) and HOMA-IR (median, 1.4 vs. 3.0; p = 0.009), indicating enhanced insulin sensitivity. Systemic inflammation, as measured using high-sensitivity C-reactive protein (hsCRP), was also significantly lower (median, 1.1 vs. 2.5 µg/mL; p = 0.029) in the high I/L ratio group than in the normal I/L ratio group, suggesting a lower systemic inflammatory burden in these participants (Table 2 and Fig. 1 ). Notably, adipokine profiles were altered between the two groups. The elderly participants in the high I/L ratio group had significantly lower leptin levels (median, 3.4 vs. 13.7 ng/mL; p = 0.001), higher adiponectin levels (median, 6.9 vs. 3.8 µg/mL; p = 0.017) and a markedly elevated adiponectin-to-leptin ratio (median, 1.73 vs. 0.21; p < 0.001). These findings further support a metabolically favourable state in the high I/L ratio group. Lastly, circulating irisin levels were substantially higher in the high I/L ratio group (median, 77.8 vs. 6.5 µg/mL; p = 0.004), and the I/L ratio itself was significantly elevated (median, 7.7 vs. 0.4; p < 0.001), validating the stratification. Collectively, our findings indicate that a high I/L ratio is strongly associated with reduced adiposity, improved lipid and glucose metabolism, enhanced insulin sensitivity and lower inflammation in a super-aged elderly population. This suggests the potential utility of the I/L ratio as a biomarker for metabolic health and body composition in ageing populations. 3.3. Association between irisin-to-leptin ratio and adiposity, insulin resistance and adiponectin Multivariate linear regression analyses were conducted to evaluate the association between the I/L ratio and key metabolic indicators, including FMI, HOMA-IR and adiponectin levels (Table 3). All models were adjusted for relevant covariates, such as age, sex, history of hypertension and diabetes. A higher I/L ratio was significantly associated with a lower FMI. Notably, each 1-unit increase in the I/L ratio was associated with a 0.164-unit decrease in FMI (B = −0.164, 95% confidence interval [CI]: −0.273 to −0.056, p = 0.004), indicating a leaner body composition independent of age, sex and comorbidities. Similarly, the I/L ratio was inversely associated with insulin resistance. An increase in the I/L ratio corresponded to a 0.036-unit decrease in HOMA-IR (B = −0.036, 95% CI: −0.069F to −0.004, p = 0.030), suggesting improved insulin sensitivity among individuals with a higher ratio, even after adjusting for confounders (Table 3). Table 3 Multivariate linear regression analysis of ratio of irisin/leptin for different variables. Multivariate linear regression of ratio of irisin/leptin for fat mass index a B value SD β value 95% CI p -value Irisin/leptin -0.164 0.053 -0.467 -0.273 to -0.056 0.004* Multivariate linear regression of ratio of irisin/leptin for HOMA-IR a B value SD β value 95% CI p -value Irisin/leptin -0.036 0.016 -0.361 -0.069 to -0.004 0.030* Multivariate linear regression of ratio of irisin/leptin for adiponectin b B value SD β value 95% CI p -value Irisin/leptin 0.144 0.042 0.475 0.058 to 0.23 0.002* History of hypertension -4.89 2.149 -0.319 -9.272 to -0.526 0.029* a The multivariate regression model was adjusted for age, gender, history of hypertension or diabetes. b The multivariate regression model was adjusted for age, gender, history of diabetes. * indicates a significant difference in statistical analysis. In contrast, the I/L ratio was positively associated with circulating adiponectin levels, a favourable adipokine linked to metabolic health. For every 1-unit increase in the I/L ratio, adiponectin levels increased by 0.144 µg/mL (B = 0.144, 95% CI: 0.058 to 0.23, p = 0.002). In addition, a history of hypertension was independently and negatively associated with adiponectin levels (B = −4.89, 95% CI: −9.27 to −0.53, p = 0.029), underscoring the complex interplay between vascular and metabolic health. Taken together, these findings support the hypothesis that a higher I/L ratio reflects a more favourable metabolic phenotype characterized by reduced adiposity, enhanced insulin action and higher adiponectin levels in a super-aged elderly population. 3.4. Comparative effects of nutrition education with and without high-protein supplementation on body composition and metabolic health To further evaluate the effects of nutrition education alone versus in combination with high-protein supplementation on body composition and metabolic health, we conducted a 3-month intervention programme incorporating nutrition education with or without high-protein supplementation. Subgroup analysis revealed notable baseline differences in body composition and inflammation between participants receiving nutrition education alone (n = 19) and those receiving nutrition education plus high-protein supplementation (n = 17; Table 4). Individuals in the high-protein supplement group had significantly lower body weight (median, 54.0 vs. 72.0 kg; p < 0.001), BMI (23.1 vs. 25.8 kg/m²; p = 0.002), skeletal muscle mass (18.9 vs. 24.8 kg; p < 0.001) and SMI (5.9 vs. 7.3 kg/m²; p < 0.001). The prevalence of obesity was significantly lower in the supplement group (29.4% vs. 63.2%; p = 0.043). No significant differences were observed between the groups in terms of insulin, HOMA-IR or I/L ratio before a 3-month nutrition education with or without high-protein supplementation. Table 4 Baseline characteristics of participants receiving nutritional education alone versus nutritional education with high-protein supplementation (n = 36). Characteristics Nutritional education group (n = 19) Nutritional education plus high-protein supplements (n = 17) p -value Age 77.0 (71.0, 84.0) 79.0 (75.0, 83.5) 0.684 Gender (n, %) 0.317 Female 8 (42.1%) 10 (58.8%) Male 11 (57.9%) 7 (41.2%) Hypertension (n, %) 16 (84.2%) 12 (70.6%) 0.326 Diabetes (n, %) 4 (21.1%) 2 (11.8%) 0.455 Dyslipidemia (n, %) 1 (5.3%) 2 (11.8%) 0.481 Weight (kg) 72.0 (61.5, 76.3) 54.0 (50.0, 58.7) < 0.001* BMI (kg/m 2 ) 25.8 (23.9, 30.0) 23.1 (21.2, 25.3) 0.002* Body fat mass (kg) 22.0 (15.5, 29.0) 18.8 (12.3, 22.6) 0.066 Skeletal muscle mass (kg) 24.8 (20.9, 27.2) 18.9 (16.5, 21.5) < 0.001* Per cent body fat (%) 32.8 (25.7, 38.2) 33.5 (25.6, 39.3) 0.975 SMI (kg/m2) 7.3 (6.7, 8.1) 5.9 (5.2, 6.6) < 0.001* Obesity prevalence (n, %) 12 (63.2%) 5 (29.4%) 0.043* MNA scores 26.0 (23.0, 27.5) 23.5 (21.8, 27.0) 0.196 Total cholesterol (mg/dL) 162.0 (141.0, 189.0) 161.0 (148.5, 189.0) 0.925 Triglycerides (mg/dL) 107.0 (90.0, 171.0) 119.0 (78.5, 165.5) 0.925 Fasting glucose (mg/dL) 95.0 (90.0, 102.0) 100.0 (91.5, 112.5) 0.346 HDL-cholesterol (mg/dL) 47.0 (40.0, 58.0) 51.0 (44.5, 59.0) 0.573 Insulin (µU/mL) 8.4 (5.1, 14.1) 8.0 (4.8, 11.8) 0.531 HOMA-IR 2.1 (1.0, 3.1) 2.0 (1.2, 3.0) 0.876 Creatinine (mg/dL) 1.1 (0.9, 1.4) 1.0 (0.7, 1.3) 0.114 hsCRP (mg/L) 2.5 (1.2, 6.5) 1.0 (0.6, 1.7) 0.025* Adiponectin (µg/mL) 3.8 (2.7, 9.4) 5.8 (3.3, 9.6) 0.471 Leptin (ng/mL) 11.8 (6.4, 41.2) 3.2 (1.8, 19.7) 0.081 Irisin (µg/mL) 7.3 (5.0, 93.0) 9.1 (5.0, 126.4) 0.9 Irisin/leptin 0.9 (0.3, 3.8) 3.0 (0.5, 28.0) 0.156 Continuous data are reported as median (25th and 75th quartile) and compared using the Mann-Whitney U Test ; categorical data are shown as numbers (percentages) and compared using the chi-square test. * Indicates a significant difference between non-sarcopenia and sarcopenia groups. Obesity was defined as BMI ≧ 25 kg/m 2 according to the WHO criteria for Asian populations. Abbreviations: BMI, body mass index; HDL: high density lipoprotein lipase cholesterol; LDL: low density lipoprotein lipase cholesterol; hsCRP: high-sensitivity C reactive protein. 3.5. Nutrition education alone promotes adipokine activity despite increased adiposity, whereas high-protein supplementation enhances adiponectin with minimal body composition changes Table 5 shows the within-group effects of the interventions. In the nutrition education-only group, participants experienced significant increases in BMI ( p = 0.007), body fat mass ( p = 0.013), FMI ( p = 0.016) and key adipokine levels, including adiponectin ( p = 0.047), leptin ( p = 0.009) and irisin ( p = 0.022) levels. Although the I/L ratio showed a substantial rise post-intervention (from 0.8 to 7.4), this change did not reach statistical significance ( p = 0.053). These findings suggest that nutrition alone was associated with improved metabolic activity, as reflected by favourable changes in adipokine levels, despite increased adiposity. Table 5 Effects of nutritional education and protein supplementation on adipokines and body composition (n = 36). Characteristics Pre-intervention Post-intervention p -value Nutritional education (n = 19) BMI (kg/m 2 ) 25.8 (23.9, 25.8) 27.4 (24.3, 31.1) 0.007* Body fat mass (kg) 22.0 (15.5, 29.0) 23.2 (17.9, 30.2) 0.013* Skeletal muscle mass (kg) 24.8 (20.9, 27.2) 25.4 (21.6, 28.3) 0.532 Per cent body fat (%) 32.8 (25.7, 38.2) 36.4 (28.1, 39.6) 0.064 SMI (kg/m2) 7.3 (6.7, 8.1) 7.1 (6.7, 8.2) 0.568 FMI (kg/m2) 8.5 (5.5, 11.3) 10.2 (6.8, 12.0) 0.016* Adiponectin (µg/mL) 3.8 (2.7, 9.4) 5.1 (3.6, 11.2) 0.047* Leptin (ng/mL) 11.8 (6.4, 41.2) 17.5 (6.8, 42.6) 0.009* Irisin (µg/mL) 7.3 (5.0, 93.0) 91.7 (62.1, 169.1) 0.022* Irisin/leptin 0.8 (0.3, 3.8) 7.4 (1.9, 28.7) 0.053 Nutritional education plus high-protein supplements (n = 17) BMI (kg/m 2 ) 23.1 (21.2, 25.3) 23.0 (21.3, 25.4) 0.148 Body fat mass (kg) 18.8 (12.3, 22.6) 18.8 (10.9, 22.6) 0.619 Skeletal muscle mass (kg) 18.9 (16.5, 21.5) 20.5 (16.0, 22.9) 0.538 Per cent body fat (%) 33.5 (25.6, 39.3) 32.6 (21.6, 41.4) 0.538 SMI (kg/m2) 5.9 (5.2, 6.6) 5.9 (5.0, 6.7) 0.72 FMI (kg/m2) 8.0 (5.4, 9.1) 7.7 (4.6, 9.8) 0.469 Adiponectin (µg/mL) 5.8 (3.3, 9.6) 6.2 (3.7, 13.2) 0.006* Leptin (ng/mL) 3.2 (1.8, 19.7) 6.3 (3.7, 18.9) 0.74 Irisin (µg/mL) 9.1 (4.9, 126.4) 118.1 (81.2, 167.7) 0.068 Irisin/leptin 3.0 (0.5, 28.0) 12.3 (6.7, 35.7) 0.586 Comparison of pre- and post-intervention data was conducted using the Wilcoxon test. The data are reported as median (25th and 75th quartile) . * Indicates a significant difference in each variable between pre- and post-intervention. Abbreviations: BMI, body mass index; SMI, skeletal muscle mass index; FMI, fat mass index. In contrast, the nutrition education plus high-protein supplementation group did not exhibit significant changes in BMI, body fat mass, skeletal muscle mass or irisin levels after the 3-month intervention. However, a significant increase was noted in adiponectin levels ( p = 0.006), indicating that high-protein supplementation may selectively impart metabolic benefits, particularly through enhanced adiponectin secretion, despite minimal changes in overall body composition. Collectively, these findings indicate that whereas nutrition education alone may lead to increased adiposity, it also triggers favourable changes in metabolic hormones. High-protein supplementation appears to attenuate weight gain and inflammation while modestly improving adiponectin levels, highlighting the potential complementary role of protein-enriched strategies in nutritional interventions for elderly populations. 4. Discussion In this prospective-cohort pilot study conducted in a super-aged Taiwanese population, we explored the potential of an elevated I/L ratio as a surrogate biomarker indicative of favourable body composition and metabolic health. Our findings demonstrated that a high I/L ratio (≥ 2.212) was significantly associated with lower body fat mass (median, 16.8 vs. 22.5 kg; p = 0.031), lower per cent body fat (29.0% vs. 35.8%; p = 0.031) and lower FMI (7.0 vs. 8.9 kg/m²; p = 0.029) compared with a normal I/L ratio. Correspondingly, the prevalence of obesity was markedly reduced in the high I/L ratio group (66.7% vs. 94.4%; p = 0.035), indicating that a higher I/L ratio is associated with a leaner body composition. These findings align with previous reports suggesting that irisin enhances browning of white adipose tissue and improves lipid metabolism [ 16 , 30 ]. Furthermore, individuals in the high I/L ratio group exhibited significantly lower fasting insulin levels (6.0 vs. 11.2 mg/dL; p = 0.007) and HOMA-IR (1.4 vs. 3.0; p = 0.009), indicating better insulin sensitivity. They also had lower hsCRP levels (1.1 vs. 2.5 µg/mL; p = 0.029), suggesting a less inflamed metabolic state. In contrast, levels of adiponectin, which is an anti-inflammatory adipokine, were significantly higher in the high I/L ratio group (6.9 vs. 3.8 mg/dL; p = 0.017), as was the adiponectin/leptin ratio (1.73 vs. 0.21; p < 0.001). These findings support the predictive role of irisin and its ratio to leptin for metabolic inflammation and glucose homeostasis [ 33 , 34 ]. Interestingly, while skeletal muscle mass and SMI did not differ significantly between groups, the serum irisin levels in the high I/L ratio group were markedly higher (median 77.8 vs. 6.5 mg/dL; p = 0.004). These findings may be associated with how irisin modulates muscle endocrine activity and hormonal interplay. Some experimental studies have demonstrated that irisin enhances glucose uptake in skeletal muscles via activation of adenosine monophosphate-activated protein kinase and translocation of the glucose transporter type 4 protein to the cell membrane, thereby promoting improved insulin sensitivity and glycogen storage in muscles [ 35 – 38 ]. Irisin also promotes inter-organ communication, affecting adipose tissue by inducing browning via integrin-mediated signalling (e.g., αVβ5), increasing thermogenesis and energy expenditure [ 39 ]. Finally, irisin integrates muscle–bone–fat cross-talk and affects hormonal networks; for instance, it improves insulin signalling, decreases inflammation and promotes bone formation via wingless-related integration site protein/β-catenin pathways [ 40 ]. These mechanisms involving irisin contribute to improved muscle endocrine activity and systemic metabolic homeostasis, which may explain the findings of our study. A notable feature of our study was the implementation of a structured 3-month nutrition education intervention, after which participants demonstrated a 17.6% increase in serum irisin levels (from 4.08 ± 1.14 to 4.80 ± 1.20 µg/mL, p = 0.033). This finding suggests that dietary optimization, potentially through enhanced protein intake, micronutrient adequacy or anti-inflammatory dietary patterns, may stimulate irisin secretion and improve insulin sensitivity. Previous reports regarding diet support these findings of increased irisin levels after nutrition education. Sajoux et al. found that a very-low-calorie ketogenic diet increased circulating myokine levels, including irisin, in patients with obesity [ 41 ]. A systematic review by Pinho-Jr et al. also reported positive correlations between various healthy dietary patterns and higher irisin levels [ 42 ]. These findings suggest the potential of dietary optimization alone to improve muscle–endocrine cross-talk and metabolic health in elderly populations. Taken together, these findings indicate that the I/L ratio is a promising integrative biomarker that reflects not only body composition but also metabolic resilience in elderly individuals. The ratio captures key endocrine signals from both muscle and adipose tissue, providing an accessible and physiologically relevant index for screening metabolic risk in the geriatric population. Future studies with larger, longitudinal cohorts are required to validate these complex associations, investigate different sarcopenia phenotypes and understand the mechanistic links between the I/L ratio, adiponectin, insulin sensitivity, body composition and muscle health in diverse elderly populations, including those in Taiwan and other parts of Asia [ 43 – 45 ]. 4.1. Strengths and limitations The present study is strengthened by its prospective longitudinal design, multidimensional assessment of anthropometry, functional status and biochemical markers in a well-characterized elderly cohort. The integration of the I/L ratio into sarcopenia and obesity phenotyping adds a novel biomarker perspective. However, study limitations include the small sample size, cross-sectional study design and potential variability in irisin assay accuracy. The specific characteristics of this Taiwanese cohort (recruited from senior citizen homes, potentially with specific health and nutritional profiles) may not be generalizable. Future longitudinal and interventional studies are warranted to confirm causality and evaluate the predictive validity of the I/L ratio. 5. Conclusion This pilot study in a super-aged Taiwanese population demonstrated that a higher serum I/L ratio was associated with lower fat mass, reduced insulin resistance, elevated adiponectin levels and a more favourable metabolic profile, despite a higher prevalence of sarcopenia, compared with a normal I/L ratio. These findings suggest the presence of a distinct metabolic phenotype in older adults, potentially mediated by enhanced muscle–adipose endocrine cross-talk. The I/L ratio may serve as a novel integrative biomarker reflecting both body composition and metabolic resilience in older adults. Moreover, nutrition education was associated with increased irisin levels, highlighting the potential of dietary interventions to modulate endocrine function and metabolic health in ageing populations. Further longitudinal studies in larger cohorts are required to validate the utility of the I/L ratio in clinical risk stratification and to better understand its role in the pathophysiology of sarcopenia and metabolic ageing. Abbreviations I/L irisin-to-leptin ratio BMI body mass index SMI skeletal muscle mass index FMI fat mass index MNA mini-nutritional assessment HDL high-density lipoprotein cholesterol LDL low-density lipoprotein cholesterol HOMA-IR homeostasis model assessment of insulin resistance TSH thyroid-stimulating hormone hsCRP high-sensitivity C-reactive protein ELISA enzyme-linked immunosorbent assay Declarations Ethics approval and consent to participate The study protocol was approved by the Institutional Review Board of Chang Gung Memorial Hospital (IRB No.: 201800483A3). Written informed consent was obtained from all participants. The study was conducted in accordance with the Declaration of Helsinki. Clinical trial number Not applicable. Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analysed during the current study are not publicly available due to participant privacy and institutional policy but are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research was supported by the Wang Zhan Yang Charitable Trust. Author contributions YWT conceived of the study concept and developed the study design. YHW and YJS drafted the manuscript. YHW, YJS and LCH led the statistical analysis. HYC, YFS and YCK were responsible for data collection. YWT was responsible for data interpretation and revised the final draft. All authors approved the final version to be published. 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08:43:05","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1306289,"visible":true,"origin":"","legend":"","description":"","filename":"IrisintoleptinratioBMCgeriatrics20251024.docx","url":"https://assets-eu.researchsquare.com/files/rs-7879242/v1/634fc166c8435faf9ff3e9aa.docx"},{"id":95517403,"identity":"a68cdd22-ee1c-4400-9e89-358c745afe9a","added_by":"auto","created_at":"2025-11-10 08:43:05","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":10520,"visible":true,"origin":"","legend":"","description":"","filename":"add986f1637f4be69d8ed98a2d1c16e1.json","url":"https://assets-eu.researchsquare.com/files/rs-7879242/v1/5e6508548b1615a45b6ec386.json"},{"id":95517405,"identity":"af93a3d1-55d9-4e2c-b70c-287de856c875","added_by":"auto","created_at":"2025-11-10 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10:16:19","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":127968,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7879242/v1/eed0da88ad9c84f1af90dcad.png"},{"id":95529312,"identity":"edca5e3b-126b-4fb2-a30b-637dd221d7d8","added_by":"auto","created_at":"2025-11-10 10:16:58","extension":"xml","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":167870,"visible":true,"origin":"","legend":"","description":"","filename":"add986f1637f4be69d8ed98a2d1c16e11structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7879242/v1/c9e8b7e2ad55260c0d6ab571.xml"},{"id":95517407,"identity":"d89296d9-59f1-4e94-9118-d1609f0f8130","added_by":"auto","created_at":"2025-11-10 08:43:05","extension":"html","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":182935,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7879242/v1/fe87ed382f4a0d8df8364079.html"},{"id":95517401,"identity":"0025d894-db82-46a2-a951-0a4af0c27f63","added_by":"auto","created_at":"2025-11-10 08:43:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":191108,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of metabolic and body composition markers by irisin-to-leptin ratio group in elderly. Box plots display group-wise distributions of body fat mass (kg), fat mass index (FMI), insulin levels (mg/dL), homeostatic model assessment for insulin resistance (HOMA-IR) and high-sensitivity C-reactive protein levels (hsCRP, mg/mL) among participants with a normal irisin-to-leptin (I/L) ratio (\u0026lt; 2.212) and those with a higher I/L ratio (³ 2.212). Individuals in the high I/L ratio group demonstrated significantly lower fat mass, insulin levels, HOMA-IR and hsCRP levels, indicating a more favourable metabolic and inflammatory profile. Data are presented as box plots showing median and interquartile range; comparisons were performed using the Mann–Whitney \u003cem\u003eU\u003c/em\u003e test.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7879242/v1/1441b04da016d943a6fae136.png"},{"id":96710782,"identity":"a6c4c401-b68c-4b48-84d8-885fcdcdfc52","added_by":"auto","created_at":"2025-11-25 10:11:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2820860,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7879242/v1/5de59dae-13c1-4a1c-b705-5c4a3c9fc8d2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Irisin-to-leptin ratio as a novel biomarker of favourable body composition and insulin sensitivity in elderly residents: A prospective pilot study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSarcopenia and sarcopenic obesity are prevalent phenotypes in older adults and have been associated with increased all-cause mortality [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. First described by Rosenberg in 1989 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], sarcopenia is characterized by the progressive and generalized loss of skeletal muscle mass and strength with advancing age, representing a major geriatric syndrome [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. It is linked to numerous adverse health outcomes, including physical disability, diminished quality of life, elevated risks of falls and fractures, hospitalization and mortality [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Sarcopenic obesity, defined by reduced muscle mass and function along with excess adiposity, has emerged as a growing concern due to its association with mortality, comorbidities and geriatric syndromes [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. These conditions are often associated with adverse outcomes, such as insulin resistance, systemic inflammation and frailty [\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. While sarcopenia and sarcopenic obesity share overlapping risk factors, their underlying metabolic signatures remain complex and poorly understood, particularly in elderly populations [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRecent studies have focused on endocrine signals originating from muscle and adipose tissue, especially irisin and leptin, as potential biomarkers reflecting the association between muscle anabolism and adiposity. Irisin, which is a myokine secreted by skeletal muscles during physical activity [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], and leptin, which is an adipokine produced by the adipose tissue [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], are key regulators of energy metabolism [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Although the physiological role of irisin remains unclear, it is known to promote the browning of white fat and improve insulin sensitivity [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Leptin exhibits a dualistic role, characterized by elevated levels of obesity and inflammation, but reduced levels of malnutrition, reflecting both metabolic excess and deficiency [\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. This complexity limits its interpretive value, especially in older adults [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Adiponectin, another adipokine, is consistently linked to enhanced insulin sensitivity [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], while insulin resistance, often assessed using Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), increases with age and muscle decline [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Nevertheless, given the biological complexity and context-dependent variability of these hormone levels, their individual interpretation may be limited in ageing populations with diverse body compositions and nutritional states.\u003c/p\u003e\u003cp\u003eTo address this issue, we sought to investigate whether the irisin-to-leptin (I/L) ratio could be used as a more integrative biomarker, capturing the relative balance between muscle- and adipose-derived signals. Preliminary findings from a cross-sectional study in patients with familial partial lipodystrophy suggested that a higher I/L ratio may be associated with more favourable metabolic profiles, including reduced adiposity, improved insulin sensitivity and increased adiponectin levels [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Given that irisin or leptin alone may lack sufficient discriminatory power because of confounding factors, such as adiposity, inflammation or malnutrition, their combined ratio may serve as a more informative biomarker for the interplay between anabolic and catabolic hormonal activity [\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. However, this ratio has not been extensively investigated in super-aged populations, especially in relation to sarcopenia and longitudinal nutritional interventions.\u003c/p\u003e\u003cp\u003eThis pilot study aimed to explore the association between serum irisin, leptin, the I/L ratio, and indicators of metabolic health, body composition, and sarcopenia status in super-aged Taiwanese adults residing in senior citizen homes. To further examine the potential impact of nutritional support on these biomarkers and body composition parameters, a 3-month nutrition education intervention was implemented. Our findings may provide insights into the utility of the I/L ratio as a novel biomarker for identifying favourable metabolic phenotypes in geriatric populations.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Participants\u003c/h2\u003e\u003cp\u003eThis prospective pilot study was conducted between August and December 2018 among community-dwelling geriatric people aged \u0026ge; 65 years, recruited from senior citizen homes in Northern Taiwan. A total of 40 older adults who met the inclusion criteria were enrolled. Participants were excluded if they had severe cognitive impairment diagnosed by a neurology specialist and receiving pharmacologic treatment, acute inflammatory conditions, severe renal or hepatic disease, active malignancy, conditions significantly affecting muscle mass (e.g., muscular dystrophy, prolonged high-dose corticosteroid use) or inability to undergo bioelectrical impedance analysis (BIA; such as those who had a pacemaker). Finally, 36 elderly people were enrolled in the study programme. The study protocol was approved by the Institutional Review Board of Chang Gung Memorial Hospital (IRB No.: 201800483A3). Written informed consent was obtained from all participants.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Study design and data collection\u003c/h2\u003e\u003cp\u003eComprehensive data were collected through structured interviews and physical assessments. Information included demographic characteristics, medical history and lifestyle habits. Nutritional status was assessed using the Mini-Nutritional Assessment questionnaire, with malnutrition risk defined as a score \u0026le; 23.5. Anthropometric measurements were obtained by trained personnel using BIA, and body mass index (BMI; kg/m\u0026sup2;) and lean and fat mass were also assessed.\u003c/p\u003e\u003cp\u003eAll participants received a 3-month nutrition education programme, which included individualized dietary counselling and group-based educational sessions on balanced nutrition, protein intake and dietary strategies for preserving muscle health. Nutrition education was delivered by a registered dietitian and reinforced monthly. In participants with low baseline protein intake or malnutrition risk, the intervention was supplemented with oral nutritional supplements containing protein, vitamins and essential nutrients. Adherence was monitored and reinforced through follow-up phone calls and in-person check-ins during the study period.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Sarcopenia diagnosis and body composition assessment\u003c/h2\u003e\u003cp\u003eBody composition was assessed via multi-frequency BIA using the InBody 270 analyzer (Biospace Co. Ltd., Seoul, Korea). Skeletal muscle mass index (SMI) was calculated as appendicular skeletal muscle mass (kg) divided by height squared (m\u0026sup2;). Fat mass index (FMI) was similarly calculated using total fat mass (kg) from the BIA data. Sarcopenia was diagnosed according to the updated 2019 criteria of the Asian Working Group for Sarcopenia [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], defined by low muscle mass (SMI\u0026thinsp;\u0026lt;\u0026thinsp;7.0 kg/m\u003csup\u003e2\u003c/sup\u003e for men and \u0026lt;\u0026thinsp;5.7 kg/m\u003csup\u003e2\u003c/sup\u003e for women). Obesity was defined as a body fat percentage \u0026ge; 20 in men and \u0026ge; 30 in women or a BMI \u0026ge; 25 kg/m\u003csup\u003e2\u003c/sup\u003e according to the World Health Organization criteria for Asian populations.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Biochemical measurements\u003c/h2\u003e\u003cp\u003eFasting venous blood samples (10 mL) were collected in the morning after an overnight fast of at least 8 hours. Samples were centrifuged at 3000 rpm for 15 minutes at 4 \u0026deg;C, and serum was aliquoted and stored at \u0026minus;80 \u0026deg;C until analysis. Serum irisin, leptin, adiponectin and insulin levels (mg/dL) were measured using commercial enzyme-linked immunosorbent assay (ELISA) kits (e.g., Abcam, UK for irisin; BioVendor for leptin; R\u0026amp;D Systems for adiponectin and Abbott for insulin). Serum irisin levels were measured using a commercially available human ELISA kit (Abcam, UK, Ltd., Taiwan). The assay demonstrated an intra-assay and inter-assay coefficient of variation\u0026thinsp;\u0026lt;\u0026thinsp;10%. The kit, designed for the quantification of human fibronectin type III domain-containing protein 5 (FNDC5/irisin), had a detection range of 0.2 to \u0026gt;\u0026thinsp;2.0 \u0026micro;g/mL. All procedures were performed in accordance with the manufacturer\u0026rsquo;s instructions. Fasting plasma glucose (mg/dL) levels were measured using standard laboratory methods.\u003c/p\u003e\u003cp\u003eInsulin resistance was estimated using the HOMA-IR, calculated as follows:\u003c/p\u003e\u003cp\u003eHOMA-IR = [fasting insulin (mg/dL) \u0026times; fasting glucose (mg/dL)] / 405. The I/L ratio was calculated by dividing serum irisin concentration (mg/dL) by serum leptin concentration (mg/dL).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Statistical analysis\u003c/h2\u003e\u003cp\u003eData were analysed using SPSS Statistics version 24.0 (IBM Corp., Armonk, NY, USA). Continuous variables are presented as median (25th and 75th quartiles) and compared using the Mann\u0026ndash;Whitney \u003cem\u003eU\u003c/em\u003e test. Categorical data are presented as numbers (percentages) and compared using the chi-square test. Multivariate linear regression analyses were performed to determine the association of the I/L ratio (independent variable) with FMI, HOMA-IR and adiponectin levels, adjusting for age, sex, history of hypertension and diabetes. To assess the impact of the 3-month intervention, pre- and post-intervention data (including body composition and biochemical markers) were compared using the Wilcoxon signed-rank test for paired samples. Changes were evaluated within participants to determine the effectiveness of nutrition education with or without nutrient supplementation. Results were considered statistically significant at a two-sided p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Baseline characteristics of elderly participants with and without sarcopenia in Northern Taiwan\u003c/h2\u003e\u003cp\u003eA total of 36 older adults (18 women and 18 men) were included in the final analysis. The median age of participants in the non-sarcopenic group (n\u0026thinsp;=\u0026thinsp;23) was 76 years, whereas that in the sarcopenic group (n\u0026thinsp;=\u0026thinsp;13, 36.1%) was 79 years. Baseline characteristics stratified by sarcopenia status are presented in Table\u0026nbsp;1. Although the sarcopenic group was slightly older than the non-sarcopenic group (79 vs. 76 years), the difference was not statistically significant. As expected, individuals with sarcopenia had significantly lower BMI (22.2 vs. 25.3 kg/m\u003csup\u003e2\u003c/sup\u003e, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005), lower skeletal muscle mass (20.0 vs. 25.3 kg, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008) and SMI (5.3 vs. 7.3 kg/m\u003csup\u003e2\u003c/sup\u003e, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Interestingly, no significant differences were observed in other biochemical markers, including lipid profile, insulin levels, HOMA-IR and leptin and adiponectin levels (Table\u0026nbsp;1).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTable\u0026nbsp;1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eComparisons of baseline characteristics between non-sarcopenia and sarcopenia groups (n\u0026thinsp;=\u0026thinsp;36).\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eNon-sarcopenia (n\u0026thinsp;=\u0026thinsp;23)\u003c/span\u003e\u003c/p\u003e\u003cp\u003e SMI\u0026thinsp;≧\u0026thinsp;7.3 kg/m2 in male or 5.54 kg/m2 in female\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eSarcopenia (n\u0026thinsp;=\u0026thinsp;13)\u003c/span\u003e\u003c/p\u003e\u003cp\u003eSMI\u0026thinsp;\u0026lt;\u0026thinsp;7.3 kg/m\u003csup\u003e2\u003c/sup\u003e in male or 5.54 kg/m\u003csup\u003e2\u003c/sup\u003e in female\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e76.0 (71.0, 84.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e79.0 (76.5, 83.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.379\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender (n, %)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.729\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e11 (47.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e7 (53.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e12 (52.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e6 (46.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHypertension\u003c/b\u003e \u003cb\u003e(n, %)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e19 (82.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e9 (69.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.354\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDiabetes (n, %)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e4 (17.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e2 (15.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.877\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDyslipidemia (n, %)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e2 (8.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1 (7.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.917\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWeight (kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e65.0 (59.7, 74.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e55.3 (48.1, 58.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBMI (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e25.3 (23.6, 29.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e22.2 (19.7, 25.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.005*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBody fat mass\u003c/b\u003e \u003cb\u003e(kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e22.0 (15.4, 25.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e18.8 (9.0, 22.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSkeletal muscle mass\u003c/b\u003e \u003cb\u003e(kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e23.5 (20.3, 27.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e20.2 (16.4, 21.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.008*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePer cent body fat (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e33.4 (26.7, 38.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e32.6 (19.6, 38.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.474\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSMI (kg/m2)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e7.3 (6.2, 8.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e5.3 (5.0, 6.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFMI (kg/m2)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e8.6 (6.3, 10.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e8.0 (3.9, 9.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.169\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eObesity prevalence (n, %)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e9 (39.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e5 (38.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.967\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMNA scores\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e26.0 (23.5, 27.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e22.0 (19.8, 27.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.055\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHaemoglobin (g/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e12.9 (12.5, 14.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e13.5 (12.8, 14.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.397\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAlanine transaminase (U/L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e21.0 (13.0, 23.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e19.0 (14.0, 25.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.948\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal cholesterol (mg/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e161.0 (141.0, 182.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e163.0 (152.0, 192.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.312\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTriglycerides (mg/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e107.0 (84.0, 148.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e75.5 (128.0, 176.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.795\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFasting glucose (mg/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e98.0 (92.0, 103.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e92.0 (82.5, 106.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.267\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHDL-cholesterol (mg/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e54.0 (41.0, 61.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e49.0 (41.0, 55.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.58\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLDL-cholesterol (mg/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e105.0 (88.0, 119.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e107.0 (101.5, 120.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.397\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eInsulin (\u0026micro;U/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e9.5 (5.7, 13.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e7.4 (4.2, 9.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.169\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHOMA-IR\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e2.2 (1.4, 3.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.8 (0.9, 2.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTSH (mIU/L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1.9 (1.4, 2.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e2.0 (1.4, 2.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.897\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCreatinine (mg/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1.1 (0.9, 1.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0.9 (0.7, 1.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.087\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ehsCRP (mg/L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e2.0 (1.0, 3.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.0 (0.6, 5.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.58\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAdiponectin (\u0026micro;g/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e4.0 (2.7, 7.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e6.9 (3.3, 9.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.379\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLeptin (ng/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e11.9 (3.6, 44.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e6.4 (1.7, 15.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.488\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eAbbreviations: BMI, body mass index; SMI, skeletal mass index; FMI, fat mass index; MNA, mini-nutritional assessment; HDL: high density lipoprotein lipase cholesterol; LDL: low density lipoprotein lipase cholesterol; HOMA-IR, homeostatic model assessment for insulin resistance; TSH, thyroid-stimulating hormone; hsCRP: high-sensitivity C reactive protein.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eContinuous data are reported as median (25th and 75th quartile) and compared using the Mann-Whitney U Test; categorical data are shown as numbers (percentages) and compared using the chi-square test. \u003c/p\u003e\u003cp\u003e\u003csup\u003e*\u003c/sup\u003e Indicates a significant difference between non-sarcopenia and sarcopenia groups. \u003c/p\u003e\u003cp\u003eBMI\u0026thinsp;=\u0026thinsp;body weight (kg)/height (m\u003csup\u003e2\u003c/sup\u003e); SMI\u0026thinsp;=\u0026thinsp;skeletal muscle mass (kg)/height (m\u003csup\u003e2\u003c/sup\u003e); FMI\u0026thinsp;=\u0026thinsp;fat mass (kg)/height (m\u003csup\u003e2\u003c/sup\u003e) using body impedence analysis.\u003c/p\u003e\u003cp\u003eSarcopenia was defined as the lowest two quintiles of SMI categorized by gender. \u003c/p\u003e\u003cp\u003eObesity was defined as body fat percentage\u0026thinsp;≧\u0026thinsp;20 in males or 30 in females according to the WHO criteria for Asian populations.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e3.2. A higher irisin-to-leptin ratio is associated with favourable body composition, improved insulin sensitivity and metabolic health in a super-aged elderly population\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eillustrates the baseline characteristics of elderly participants stratified by high and normal values of the I/L ratio. Participants in the high I/L ratio group (\u0026ge; 2.212) exhibited a significantly more favourable metabolic and body composition profile than those with a normal I/L ratio (\u0026lt;\u0026thinsp;2.212). Individuals with a high I/L ratio had significantly lower body fat mass (median, 16.8 vs. 22.5 kg; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031), per cent body fat (median, 29.0% vs. 35.8%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031) and FMI (median, 7.0 vs. 8.9 kg/m\u0026sup2;; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.029), indicating a leaner body composition, than those with a normal I/L ratio. Obesity prevalence was also significantly lower in the high I/L ratio group (66.7% vs. 94.4%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.035).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eBaseline characteristics between groups with and without higher ratio of serum irisin/leptin level (n\u0026thinsp;=\u0026thinsp;36).\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eNormal ratio of irisin/leptin (n\u0026thinsp;=\u0026thinsp;18)\u003c/span\u003e\u003c/p\u003e\u003cp\u003e Irisin/leptin\u0026thinsp;\u0026lt;\u0026thinsp;2.212\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eHigher ratio of irisin/leptin (n\u0026thinsp;=\u0026thinsp;18)\u003c/span\u003e\u003c/p\u003e\u003cp\u003e Irisin/leptin\u0026thinsp;≧\u0026thinsp;2.212\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e78.0 (72.5, 83.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e78.5 (74.8, 84.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.521\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender (n, %)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e9 (50.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e9 (50.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e9 (50.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e9 (50.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHypertension\u003c/b\u003e \u003cb\u003e(n, %)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e15 (83.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e13 (72.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.423\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDiabetes (n, %)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3 (16.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e3 (16.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDyslipidemia (n, %)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1 (5.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e2 (11.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.546\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWeight (kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e63.1 (55.3, 73.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e57.1 (50.5, 65.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.134\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBMI (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e25.6 (23.5, 29.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e23.5 (21.6, 26.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.059\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBody fat mass\u003c/b\u003e \u003cb\u003e(kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e22.5 (18.3, 26.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e16.8 (13.2, 22.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.031*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSkeletal muscle mass\u003c/b\u003e \u003cb\u003e(kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e21.5 (20.0, 26.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e21.3 (16.8, 25.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePer cent body fat (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e35.8 (28.9, 40.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e29.0 (22.0, 36.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.031*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBasal metabolic rate\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1227 (1176.5, 1400.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1227.5 (1071.0, 1392.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.743\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWaist to hip ratio\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e0.88 (0.74, 0.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0.85 (0.78, 0.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.091\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSMI (kg/m2)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e7.1 (6.1, 7.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e6.5 (5.2, 7.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.252\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFMI (kg/m2)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e8.9 (7.0, 11.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e7.0 (5.1, 8.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.029*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eObesity prevalence (n, %)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e17 (94.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e12 (66.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.035*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMNA scores\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e25.5 (22.4, 27.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e24.0 (22.3, 27.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.501\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHaemoglobin (g/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e13.0 (12.6, 14.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e13.4 (12.5, 14.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.606\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAlanine transaminase (U/L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e20.5 (14.5, 25.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e18.0 (13.0, 23.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.462\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal cholesterol (mg/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e169.0 (153.3, 186.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e153.0 (140.0, 192.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.118\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTriglycerides (mg/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e141.0 (100.5, 184.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e96.5 (78.0, 129.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.024*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFasting glucose (mg/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e100.0 (92.0, 104.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e95.0 (88.0, 105.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.293\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHDL-cholesterol (mg/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e47.0 (39.8, 61.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e52.0 (45.8, 58.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.424\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVLDL-cholesterol (mg/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e28.5 (20.5, 36.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e19.0 (15.8, 26.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.022*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLDL-cholesterol (mg/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e109.0 (103.8, 121.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e101.5 (86.0, 116.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.068\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eInsulin (\u0026micro;U/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e11.2 (8.1, 16.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e6.0 (4.4, 9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.007*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHOMA-IR\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3.0 (2.0, 4.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.4 (1.0, 2.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.009*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTSH (mIU/L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e2.1 (1.5, 2.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.8 (1.4, 2.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.339\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCreatinine (mg/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1.3 (0.9, 1.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.0 (0.7, 1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.161\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ehsCRP (mg/L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e2.5 (1.0, 6.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.1 (0.5, 1.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.029*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAdiponectin (\u0026micro;g/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3.8 (2.6, 6.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e6.9 (3.6, 15.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.017*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLeptin (ng/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e13.7 (10.0, 49.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e3.4 (1.7, 13.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAdiponectin/Leptin\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e0.21 (0.06, 0.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.73 (0.49, 6.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIrisin (\u0026micro;g/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e6.5 (4.4, 7.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e77.8 (6.6, 211.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.004*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIrisin/leptin\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e0.4 (0.2, 0.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e7.7 (3.4, 38.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eAbbreviations: BMI, body mass index; SMI, skeletal mass index; FMI, fat mass index; MNA, mini-nutritional assessment; HDL: high density lipoprotein lipase cholesterol; LDL: low density lipoprotein lipase cholesterol; HOMA-IR, homeostatic model assessment for insulin resistance; TSH, thyroid-stimulating hormone; hsCRP: high-sensitivity C reactive protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eContinuous data are reported as median (25th and 75th quartile) and compared using the Mann-Whitney U Test; categorical data are shown as numbers (percentages) and compared using the chi-square test. \u003c/p\u003e\u003cp\u003e\u003csup\u003e*\u003c/sup\u003e Indicates a significant difference between non-sarcopenia and sarcopenia groups. \u003c/p\u003e\u003cp\u003eBMI\u0026thinsp;=\u0026thinsp;body weight (kg)/height (m\u003csup\u003e2\u003c/sup\u003e); SMI\u0026thinsp;=\u0026thinsp;skeletal muscle mass (kg)/height (m\u003csup\u003e2\u003c/sup\u003e); FMI\u0026thinsp;=\u0026thinsp;fat mass (kg)/height (m\u003csup\u003e2\u003c/sup\u003e) using body impedence analysis.\u003c/p\u003e\u003cp\u003eHigher ratio of irisin/leptin referred to the upper half of the serum irisin/leptin distribution, whereas normal ratio of irisin/leptin referred to the lower half of the serum irisin/leptin level. Obesity was defined as body fat percentage\u0026thinsp;≧\u0026thinsp;20 in males or 30 in females according to the WHO criteria for Asian populations.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn terms of metabolic markers, the high I/L ratio group demonstrated significantly reduced serum triglyceride levels (median, 96.5 vs. 141.0 mg/dL; p\u0026thinsp;=\u0026thinsp;0.024) and lower VLDL-cholesterol levels (19.0 vs. 28.5 mg/dL; p\u0026thinsp;=\u0026thinsp;0.022), reflecting a more favourable lipid profile.\u003c/p\u003e\u003cp\u003eFurthermore, markers of insulin resistance were markedly improved among those in the high I/L ratio group. These individuals had significantly lower fasting insulin levels (median, 6.0 vs. 11.2 \u0026micro;g/mL; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007) and HOMA-IR (median, 1.4 vs. 3.0; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009), indicating enhanced insulin sensitivity. Systemic inflammation, as measured using high-sensitivity C-reactive protein (hsCRP), was also significantly lower (median, 1.1 vs. 2.5 \u0026micro;g/mL; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.029) in the high I/L ratio group than in the normal I/L ratio group, suggesting a lower systemic inflammatory burden in these participants (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eNotably, adipokine profiles were altered between the two groups. The elderly participants in the high I/L ratio group had significantly lower leptin levels (median, 3.4 vs. 13.7 ng/mL; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), higher adiponectin levels (median, 6.9 vs. 3.8 \u0026micro;g/mL; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017) and a markedly elevated adiponectin-to-leptin ratio (median, 1.73 vs. 0.21; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These findings further support a metabolically favourable state in the high I/L ratio group. Lastly, circulating irisin levels were substantially higher in the high I/L ratio group (median, 77.8 vs. 6.5 \u0026micro;g/mL; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004), and the I/L ratio itself was significantly elevated (median, 7.7 vs. 0.4; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), validating the stratification.\u003c/p\u003e\u003cp\u003eCollectively, our findings indicate that a high I/L ratio is strongly associated with reduced adiposity, improved lipid and glucose metabolism, enhanced insulin sensitivity and lower inflammation in a super-aged elderly population. This suggests the potential utility of the I/L ratio as a biomarker for metabolic health and body composition in ageing populations.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Association between irisin-to-leptin ratio and adiposity, insulin resistance and adiponectin\u003c/h2\u003e\u003cp\u003eMultivariate linear regression analyses were conducted to evaluate the association between the I/L ratio and key metabolic indicators, including FMI, HOMA-IR and adiponectin levels (Table\u0026nbsp;3). All models were adjusted for relevant covariates, such as age, sex, history of hypertension and diabetes. A higher I/L ratio was significantly associated with a lower FMI. Notably, each 1-unit increase in the I/L ratio was associated with a 0.164-unit decrease in FMI (B\u0026thinsp;=\u0026thinsp;\u0026minus;0.164, 95% confidence interval [CI]: \u0026minus;0.273 to \u0026minus;0.056, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004), indicating a leaner body composition independent of age, sex and comorbidities. Similarly, the I/L ratio was inversely associated with insulin resistance. An increase in the I/L ratio corresponded to a 0.036-unit decrease in HOMA-IR (B\u0026thinsp;=\u0026thinsp;\u0026minus;0.036, 95% CI: \u0026minus;0.069F to \u0026minus;0.004, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.030), suggesting improved insulin sensitivity among individuals with a higher ratio, even after adjusting for confounders (Table\u0026nbsp;3).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTable\u0026nbsp;3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003eMultivariate linear regression analysis of ratio of irisin/leptin for different variables.\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003eMultivariate linear regression of ratio of irisin/leptin for fat mass index\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eB value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eβ value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIrisin/leptin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.164\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.053\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.467\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e-0.273 to -0.056\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.004*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMultivariate linear regression of ratio of irisin/leptin for HOMA-IR\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eB value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eβ value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIrisin/leptin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.361\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e-0.069 to -0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.030*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMultivariate linear regression of ratio of irisin/leptin for adiponectin\u003c/b\u003e\u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eB value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eβ value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIrisin/leptin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.144\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.475\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0.058 to 0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.002*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHistory of hypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-4.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e2.149\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.319\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e-9.272 to -0.526\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.029*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e The multivariate regression model was adjusted for \u003cb\u003eage, gender, history of hypertension or diabetes.\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e The multivariate regression model was adjusted for age, gender, history of diabetes.\u003c/p\u003e\u003cp\u003e* indicates a significant difference in statistical analysis.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn contrast, the I/L ratio was positively associated with circulating adiponectin levels, a favourable adipokine linked to metabolic health. For every 1-unit increase in the I/L ratio, adiponectin levels increased by 0.144 \u0026micro;g/mL (B\u0026thinsp;=\u0026thinsp;0.144, 95% CI: 0.058 to 0.23, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002). In addition, a history of hypertension was independently and negatively associated with adiponectin levels (B\u0026thinsp;=\u0026thinsp;\u0026minus;4.89, 95% CI: \u0026minus;9.27 to \u0026minus;0.53, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.029), underscoring the complex interplay between vascular and metabolic health. Taken together, these findings support the hypothesis that a higher I/L ratio reflects a more favourable metabolic phenotype characterized by reduced adiposity, enhanced insulin action and higher adiponectin levels in a super-aged elderly population.\u003c/p\u003e\u003cp\u003e\u003cem\u003e3.4. Comparative effects of nutrition education with and without high-protein supplementation on body composition and metabolic health\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTo further evaluate the effects of nutrition education alone versus in combination with high-protein supplementation on body composition and metabolic health, we conducted a 3-month intervention programme incorporating nutrition education with or without high-protein supplementation. Subgroup analysis revealed notable baseline differences in body composition and inflammation between participants receiving nutrition education alone (n\u0026thinsp;=\u0026thinsp;19) and those receiving nutrition education plus high-protein supplementation (n\u0026thinsp;=\u0026thinsp;17; Table\u0026nbsp;4). Individuals in the high-protein supplement group had significantly lower body weight (median, 54.0 vs. 72.0 kg; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), BMI (23.1 vs. 25.8 kg/m\u0026sup2;; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002), skeletal muscle mass (18.9 vs. 24.8 kg; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and SMI (5.9 vs. 7.3 kg/m\u0026sup2;; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The prevalence of obesity was significantly lower in the supplement group (29.4% vs. 63.2%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.043). No significant differences were observed between the groups in terms of insulin, HOMA-IR or I/L ratio before a 3-month nutrition education with or without high-protein supplementation.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabc\" border=\"1\"\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTable\u0026nbsp;4\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eBaseline characteristics of participants receiving nutritional education alone versus nutritional education with high-protein supplementation (n\u0026thinsp;=\u0026thinsp;36).\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCharacteristics\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eNutritional education group (n\u0026thinsp;=\u0026thinsp;19)\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eNutritional education plus high-protein supplements (n\u0026thinsp;=\u0026thinsp;17)\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003cb\u003e-value\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e77.0 (71.0, 84.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e79.0 (75.0, 83.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.684\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender (n, %)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.317\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e8 (42.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e10 (58.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e11 (57.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e7 (41.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHypertension\u003c/b\u003e \u003cb\u003e(n, %)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e16 (84.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e12 (70.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.326\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDiabetes (n, %)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e4 (21.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e2 (11.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.455\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDyslipidemia (n, %)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1 (5.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e2 (11.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.481\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWeight (kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e72.0 (61.5, 76.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e54.0 (50.0, 58.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBMI (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e25.8 (23.9, 30.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e23.1 (21.2, 25.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.002*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBody fat mass\u003c/b\u003e \u003cb\u003e(kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e22.0 (15.5, 29.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e18.8 (12.3, 22.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.066\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSkeletal muscle mass\u003c/b\u003e \u003cb\u003e(kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e24.8 (20.9, 27.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e18.9 (16.5, 21.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePer cent body fat (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e32.8 (25.7, 38.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e33.5 (25.6, 39.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.975\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSMI (kg/m2)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e7.3 (6.7, 8.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e5.9 (5.2, 6.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eObesity prevalence (n, %)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e12 (63.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e5 (29.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.043*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMNA scores\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e26.0 (23.0, 27.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e23.5 (21.8, 27.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.196\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal cholesterol (mg/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e162.0 (141.0, 189.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e161.0 (148.5, 189.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.925\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTriglycerides (mg/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e107.0 (90.0, 171.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e119.0 (78.5, 165.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.925\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFasting glucose (mg/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e95.0 (90.0, 102.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e100.0 (91.5, 112.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.346\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHDL-cholesterol (mg/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e47.0 (40.0, 58.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e51.0 (44.5, 59.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.573\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eInsulin (\u0026micro;U/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e8.4 (5.1, 14.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e8.0 (4.8, 11.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.531\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHOMA-IR\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e2.1 (1.0, 3.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e2.0 (1.2, 3.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.876\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCreatinine (mg/dL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e1.1 (0.9, 1.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.0 (0.7, 1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.114\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ehsCRP (mg/L)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e2.5 (1.2, 6.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.0 (0.6, 1.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.025*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAdiponectin (\u0026micro;g/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3.8 (2.7, 9.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e5.8 (3.3, 9.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.471\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLeptin (ng/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e11.8 (6.4, 41.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e3.2 (1.8, 19.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.081\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIrisin (\u0026micro;g/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e7.3 (5.0, 93.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e9.1 (5.0, 126.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIrisin/leptin\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e0.9 (0.3, 3.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e3.0 (0.5, 28.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.156\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eContinuous data are reported as median (25th and 75th quartile) and compared using the Mann-Whitney U Test ; categorical data are shown as numbers (percentages) and compared using the chi-square test. \u003c/p\u003e\u003cp\u003e\u003csup\u003e*\u003c/sup\u003e Indicates a significant difference between non-sarcopenia and sarcopenia groups. \u003c/p\u003e\u003cp\u003eObesity was defined as BMI\u0026thinsp;≧\u0026thinsp;25 kg/m\u003csup\u003e2\u003c/sup\u003e according to the WHO criteria for Asian populations.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eAbbreviations: BMI, body mass index; HDL: high density lipoprotein lipase cholesterol; LDL: low density lipoprotein lipase cholesterol; hsCRP: high-sensitivity C reactive protein.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e3.5. Nutrition education alone promotes adipokine activity despite increased adiposity, whereas high-protein supplementation enhances adiponectin with minimal body composition changes\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTable 5 shows the within-group effects of the interventions. In the nutrition education-only group, participants experienced significant increases in BMI (\u003cem\u003ep\u003c/em\u003e = 0.007), body fat mass (\u003cem\u003ep\u003c/em\u003e = 0.013), FMI (\u003cem\u003ep\u003c/em\u003e = 0.016) and key adipokine levels, including adiponectin (\u003cem\u003ep\u003c/em\u003e = 0.047), leptin (\u003cem\u003ep\u003c/em\u003e = 0.009) and irisin (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.022) levels. Although the I/L ratio showed a substantial rise post-intervention (from 0.8 to 7.4), this change did not reach statistical significance (\u003cem\u003ep\u003c/em\u003e = 0.053). These findings suggest that nutrition alone was associated with improved metabolic activity, as reflected by favourable changes in adipokine levels, despite increased adiposity.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eEffects of nutritional education and protein supplementation on adipokines and body composition (n\u0026thinsp;=\u0026thinsp;36).\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCharacteristics\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003ePre-intervention\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003ePost-intervention\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003cb\u003e-value\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNutritional education (n\u0026thinsp;=\u0026thinsp;19)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBMI (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e25.8 (23.9, 25.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e27.4 (24.3, 31.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.007*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBody fat mass\u003c/b\u003e \u003cb\u003e(kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e22.0 (15.5, 29.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e23.2 (17.9, 30.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.013*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSkeletal muscle mass\u003c/b\u003e \u003cb\u003e(kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e24.8 (20.9, 27.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e25.4 (21.6, 28.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.532\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePer cent body fat (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e32.8 (25.7, 38.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e36.4 (28.1, 39.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.064\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSMI (kg/m2)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e7.3 (6.7, 8.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e7.1 (6.7, 8.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.568\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFMI (kg/m2)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e8.5 (5.5, 11.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e10.2 (6.8, 12.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.016*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAdiponectin (\u0026micro;g/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3.8 (2.7, 9.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e5.1 (3.6, 11.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.047*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLeptin (ng/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e11.8 (6.4, 41.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e17.5 (6.8, 42.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.009*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIrisin (\u0026micro;g/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e7.3 (5.0, 93.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e91.7 (62.1, 169.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.022*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIrisin/leptin\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e0.8 (0.3, 3.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e7.4 (1.9, 28.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.053\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNutritional education plus high-protein supplements (n\u0026thinsp;=\u0026thinsp;17)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBMI (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e23.1 (21.2, 25.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e23.0 (21.3, 25.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.148\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBody fat mass\u003c/b\u003e \u003cb\u003e(kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e18.8 (12.3, 22.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e18.8 (10.9, 22.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.619\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSkeletal muscle mass\u003c/b\u003e \u003cb\u003e(kg)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e18.9 (16.5, 21.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e20.5 (16.0, 22.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.538\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePer cent body fat (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e33.5 (25.6, 39.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e32.6 (21.6, 41.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.538\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSMI (kg/m2)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e5.9 (5.2, 6.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e5.9 (5.0, 6.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFMI (kg/m2)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e8.0 (5.4, 9.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e7.7 (4.6, 9.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.469\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAdiponectin (\u0026micro;g/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e5.8 (3.3, 9.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e6.2 (3.7, 13.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.006*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLeptin (ng/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3.2 (1.8, 19.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e6.3 (3.7, 18.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIrisin (\u0026micro;g/mL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e9.1 (4.9, 126.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e118.1 (81.2, 167.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.068\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIrisin/leptin\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e3.0 (0.5, 28.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e12.3 (6.7, 35.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.586\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eComparison of pre- and post-intervention data was conducted using the Wilcoxon test. The data are reported as median (25th and 75th quartile) .\u003c/p\u003e\u003cp\u003e\u003csup\u003e*\u003c/sup\u003e Indicates a significant difference in each variable between pre- and post-intervention.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eAbbreviations: BMI, body mass index; SMI, skeletal muscle mass index; FMI, fat mass index.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn contrast, the nutrition education plus high-protein supplementation group did not exhibit significant changes in BMI, body fat mass, skeletal muscle mass or irisin levels after the 3-month intervention. However, a significant increase was noted in adiponectin levels (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006), indicating that high-protein supplementation may selectively impart metabolic benefits, particularly through enhanced adiponectin secretion, despite minimal changes in overall body composition.\u003c/p\u003e\u003cp\u003eCollectively, these findings indicate that whereas nutrition education alone may lead to increased adiposity, it also triggers favourable changes in metabolic hormones. High-protein supplementation appears to attenuate weight gain and inflammation while modestly improving adiponectin levels, highlighting the potential complementary role of protein-enriched strategies in nutritional interventions for elderly populations.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn this prospective-cohort pilot study conducted in a super-aged Taiwanese population, we explored the potential of an elevated I/L ratio as a surrogate biomarker indicative of favourable body composition and metabolic health. Our findings demonstrated that a high I/L ratio (\u0026ge; 2.212) was significantly associated with lower body fat mass (median, 16.8 vs. 22.5 kg; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031), lower per cent body fat (29.0% vs. 35.8%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031) and lower FMI (7.0 vs. 8.9 kg/m\u0026sup2;; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.029) compared with a normal I/L ratio. Correspondingly, the prevalence of obesity was markedly reduced in the high I/L ratio group (66.7% vs. 94.4%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.035), indicating that a higher I/L ratio is associated with a leaner body composition. These findings align with previous reports suggesting that irisin enhances browning of white adipose tissue and improves lipid metabolism [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Furthermore, individuals in the high I/L ratio group exhibited significantly lower fasting insulin levels (6.0 vs. 11.2 mg/dL; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007) and HOMA-IR (1.4 vs. 3.0; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009), indicating better insulin sensitivity. They also had lower hsCRP levels (1.1 vs. 2.5 \u0026micro;g/mL; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.029), suggesting a less inflamed metabolic state. In contrast, levels of adiponectin, which is an anti-inflammatory adipokine, were significantly higher in the high I/L ratio group (6.9 vs. 3.8 mg/dL; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017), as was the adiponectin/leptin ratio (1.73 vs. 0.21; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These findings support the predictive role of irisin and its ratio to leptin for metabolic inflammation and glucose homeostasis [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Interestingly, while skeletal muscle mass and SMI did not differ significantly between groups, the serum irisin levels in the high I/L ratio group were markedly higher (median 77.8 vs. 6.5 mg/dL; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004).\u003c/p\u003e\u003cp\u003eThese findings may be associated with how irisin modulates muscle endocrine activity and hormonal interplay. Some experimental studies have demonstrated that irisin enhances glucose uptake in skeletal muscles via activation of adenosine monophosphate-activated protein kinase and translocation of the glucose transporter type 4 protein to the cell membrane, thereby promoting improved insulin sensitivity and glycogen storage in muscles [\u003cspan additionalcitationids=\"CR36 CR37\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Irisin also promotes inter-organ communication, affecting adipose tissue by inducing browning via integrin-mediated signalling (e.g., αVβ5), increasing thermogenesis and energy expenditure [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Finally, irisin integrates muscle\u0026ndash;bone\u0026ndash;fat cross-talk and affects hormonal networks; for instance, it improves insulin signalling, decreases inflammation and promotes bone formation via wingless-related integration site protein/β-catenin pathways [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. These mechanisms involving irisin contribute to improved muscle endocrine activity and systemic metabolic homeostasis, which may explain the findings of our study.\u003c/p\u003e\u003cp\u003eA notable feature of our study was the implementation of a structured 3-month nutrition education intervention, after which participants demonstrated a 17.6% increase in serum irisin levels (from 4.08 \u0026plusmn; 1.14 to 4.80 \u0026plusmn; 1.20 \u0026micro;g/mL, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.033). This finding suggests that dietary optimization, potentially through enhanced protein intake, micronutrient adequacy or anti-inflammatory dietary patterns, may stimulate irisin secretion and improve insulin sensitivity. Previous reports regarding diet support these findings of increased irisin levels after nutrition education. Sajoux et al. found that a very-low-calorie ketogenic diet increased circulating myokine levels, including irisin, in patients with obesity [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. A systematic review by Pinho-Jr et al. also reported positive correlations between various healthy dietary patterns and higher irisin levels [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. These findings suggest the potential of dietary optimization alone to improve muscle\u0026ndash;endocrine cross-talk and metabolic health in elderly populations.\u003c/p\u003e\u003cp\u003eTaken together, these findings indicate that the I/L ratio is a promising integrative biomarker that reflects not only body composition but also metabolic resilience in elderly individuals. The ratio captures key endocrine signals from both muscle and adipose tissue, providing an accessible and physiologically relevant index for screening metabolic risk in the geriatric population.\u003c/p\u003e\u003cp\u003eFuture studies with larger, longitudinal cohorts are required to validate these complex associations, investigate different sarcopenia phenotypes and understand the mechanistic links between the I/L ratio, adiponectin, insulin sensitivity, body composition and muscle health in diverse elderly populations, including those in Taiwan and other parts of Asia [\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Strengths and limitations\u003c/h2\u003e\u003cp\u003eThe present study is strengthened by its prospective longitudinal design, multidimensional assessment of anthropometry, functional status and biochemical markers in a well-characterized elderly cohort. The integration of the I/L ratio into sarcopenia and obesity phenotyping adds a novel biomarker perspective. However, study limitations include the small sample size, cross-sectional study design and potential variability in irisin assay accuracy. The specific characteristics of this Taiwanese cohort (recruited from senior citizen homes, potentially with specific health and nutritional profiles) may not be generalizable. Future longitudinal and interventional studies are warranted to confirm causality and evaluate the predictive validity of the I/L ratio.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis pilot study in a super-aged Taiwanese population demonstrated that a higher serum I/L ratio was associated with lower fat mass, reduced insulin resistance, elevated adiponectin levels and a more favourable metabolic profile, despite a higher prevalence of sarcopenia, compared with a normal I/L ratio. These findings suggest the presence of a distinct metabolic phenotype in older adults, potentially mediated by enhanced muscle\u0026ndash;adipose endocrine cross-talk. The I/L ratio may serve as a novel integrative biomarker reflecting both body composition and metabolic resilience in older adults. Moreover, nutrition education was associated with increased irisin levels, highlighting the potential of dietary interventions to modulate endocrine function and metabolic health in ageing populations.\u003c/p\u003e\u003cp\u003eFurther longitudinal studies in larger cohorts are required to validate the utility of the I/L ratio in clinical risk stratification and to better understand its role in the pathophysiology of sarcopenia and metabolic ageing.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eI/L\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eirisin-to-leptin ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ebody mass index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eSMI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eskeletal muscle mass index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eFMI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003efat mass index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eMNA\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003emini-nutritional assessment\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eHDL\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ehigh-density lipoprotein cholesterol\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eLDL\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003elow-density lipoprotein cholesterol\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eHOMA-IR\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ehomeostasis model assessment of insulin resistance\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eTSH\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ethyroid-stimulating hormone\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003ehsCRP\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ehigh-sensitivity C-reactive protein\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eELISA\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eenzyme-linked immunosorbent assay\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the Institutional Review Board of Chang Gung Memorial Hospital (IRB No.: 201800483A3). Written informed consent was obtained from all participants. The study was conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are not publicly available due to participant privacy and institutional policy but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting\u0026nbsp;interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no\u0026nbsp;competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the Wang Zhan Yang Charitable Trust.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYWT conceived of the study concept and developed the study design. YHW and YJS drafted the manuscript. YHW, YJS and LCH led the statistical analysis. HYC, YFS and YCK were responsible for data collection. YWT was responsible for data interpretation and revised the final draft. All authors approved the final version to be published.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Wang Zhan Yang Charitable Trust and Chang Gung Memorial Hospital Research Projects (CORPG3P0622, PARPG3Q0091, PARPG3Q0341)\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBenz E, Pinel A, Guillet C, Capel F, Pereira B, De Antonio M, et al. Sarcopenia and Sarcopenic Obesity and Mortality Among Older People. JAMA Netw Open. 2024;7:e243604.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCruz-Jentoft AJ, Sayer AA, Sarcopenia. 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Development and validation of the sarcopenia composite index: A comprehensive approach for assessing sarcopenia in the ageing population. Ann Acad Med Singap. 2025;54:101\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu LK, Lee WJ, Chen LY, Hwang AC, Lin MH, Peng LN, et al. Sarcopenia, and its association with cardiometabolic and functional characteristics in Taiwan: results from I-Lan Longitudinal Aging Study. Geriatr Gerontol Int. 2014;14(Suppl 1):36\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Irisin-to-leptin ratio, Sarcopenic obesity, Insulin sensitivity, Adiponectin, Nutritional intervention, Elderly population","lastPublishedDoi":"10.21203/rs.3.rs-7879242/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7879242/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eSarcopenic obesity poses a growing concern among older adults due to its complex interplay between muscle loss, adiposity and metabolic dysfunction. Whereas irisin and leptin are key regulators of muscle\u0026ndash;fat cross-talk, their combined predictive utility in ageing populations remains unclear. This study aimed to investigate the association between the serum irisin-to-leptin (I/L) ratio and body composition, insulin sensitivity and adipokines profiles in a super-aged Taiwanese population, and to assess the impact of nutrition education with or without protein supplementation on these metabolic markers.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA prospective pilot study was conducted among 36 elderly residents with a mean age of approximately 78 years, residing in senior homes in Northern Taiwan. Sarcopenia was defined using the Asian Working Group for Sarcopenia 2019 criteria. Anthropometric parameters were measured via bioelectrical impedance analysis. Fasting serum levels of irisin, leptin, adiponectin and insulin, and Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) were measured. Participants were stratified by sarcopenia status and median I/L ratio. A subset of participants underwent a 3-month nutrition intervention with or without high-protein supplementation. Multivariate linear regression was performed to assess associations between I/L ratio and metabolic indices.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eA higher I/L ratio was associated with significantly lower fat mass, fat mass index, per cent body fat, HOMA-IR and insulin, triglycerides, very-low-density lipoprotein cholesterol and high-sensitivity C-reactive protein levels (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and with higher adiponectin levels and adiponectin/leptin ratio. Multivariate analysis confirmed that a higher I/L ratio independently predicted lower fat mass index (B\u0026thinsp;=\u0026thinsp;\u0026minus;0.164, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004), lower HOMA-IR (B\u0026thinsp;=\u0026thinsp;\u0026minus;0.036, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.030) and higher adiponectin levels (B\u0026thinsp;=\u0026thinsp;0.144, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002). Interestingly, despite a higher prevalence of sarcopenia, individuals with higher I/L ratios exhibited more favourable metabolic profiles. Nutrition education was associated with increased irisin levels (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.033), while protein supplementation selectively increased adiponectin levels (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006) without affecting body composition.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eA higher I/L ratio was associated with lower adiposity, improved insulin sensitivity and reduced inflammation, suggesting a distinct metabolic phenotype among super-aged adults. The I/L ratio may serve as a novel integrative biomarker of metabolic resilience in ageing populations. Nutrition education alone may enhance irisin levels, highlighting the potential of dietary strategies in modulating endocrine function and metabolic health in older adults.\u003c/p\u003e\u003ch2\u003eTrial registration:\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e","manuscriptTitle":"Irisin-to-leptin ratio as a novel biomarker of favourable body composition and insulin sensitivity in elderly residents: A prospective pilot study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-10 08:43:00","doi":"10.21203/rs.3.rs-7879242/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0e6b7b1f-cb6f-427f-b6d3-725d8fa5dd5e","owner":[],"postedDate":"November 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-25T04:38:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-10 08:43:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7879242","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7879242","identity":"rs-7879242","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}