Uric Acid and Grip Strength as Predictors of Mortality in Older Adults: A Sex-Stratified Analysis

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While diminished muscle strength predicts functional deterioration and mortality, elevated serum uric acid's prognostic value remains controversial. This study investigated individual and combined effects of reduced handgrip strength and hyperuricemia on all-cause mortality, focusing on sex-specific differences. Methods This retrospective cohort study evaluated 910 individuals aged ≥ 60 years between 2020–2024 at a university hospital. Participants with confounding conditions or interfering medications were excluded. Uric acid was quantified enzymatically and classified into quartiles. Sarcopenia was defined using EWGSOP2 criteria, including handgrip strength and skeletal muscle mass index from bioelectrical impedance analysis. Cox regression and Kaplan-Meier analyses assessed mortality risk. Results The mean age was 71 years, with 66.9% of participants being female. Reduced handgrip strength and elevated UA levels were correlated with detrimental metabolic indicators. Univariate analysis indicated that both low handgrip strength (HR: 1.91, 95% CI: 1.15–3.18) and the highest quartile of uric acid (UA) levels (HR: 1.86, 95% CI: 1.13–3.08) were significant predictors of mortality. Nevertheless, these correlations diminished following multivariable correction. Sex-stratified studies indicated that hyperuricemia persisted as an independent predictor for mortality in females (HR: 3.08; 95% CI: 1.31–7.26; p = 0.010). Conclusion Both diminished grip strength and elevated uric acid levels are associated with increased mortality in older adults, particularly among females. Routine incorporation of sex-specific metabolic and physical performance assessments may enhance risk stratification strategies in geriatric populations. Uric acid Handgrip strength Mortality Sarcopenia Sex differences Older adults Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Sarcopenia, the age-associated reduction in skeletal muscle mass, strength, and functionality, significantly contributes to frailty, disability, and elevated mortality in older adults [ 1 ]. Among its diagnostic components, handgrip strength (HGS) has emerged as a simple yet highly predictive marker of functional decline and adverse outcomes [ 2 ]. This age-related muscle deterioration is driven by multifactorial processes, including chronic low-grade inflammation, oxidative stress, hormonal dysregulation, and neuromuscular degeneration [ 3 ]. Elevated levels of inflammatory biomarkers such as tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and C-reactive protein (CRP) have been repeatedly associated with reduced muscle strength in older adults [ 4 ]. Uric acid (UA), the end product of purine metabolism, plays a complex role in human health. On one hand, elevated serum UA levels have been implicated in the pathogenesis of cardiovascular and cerebrovascular diseases, hypertension, metabolic syndrome, and increased all-cause mortality, likely due to their pro-inflammatory and oxidative effects [ 5 , 6 ]. On the other hand, UA acts as a potent antioxidant, scavenging oxygen free radicals and mitigating oxidative stress, thereby potentially conferring neuroprotective effects [ 7 ]. Low serum UA levels have been linked to adverse outcomes including increased mortality and higher risk of neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease [ 8 ]. Despite prior research investigating the relationship between UA levels and sarcopenia-related parameters, findings continue to be inconsistent and ambiguous. While some studies report that moderate UA levels are positively associated with muscle strength, others suggest a detrimental impact, particularly at higher UA concentrations [ 9 , 10 ]. To our knowledge, no research has particularly investigated this association within Turkish older adults, a population characterized by unique dietary and metabolic profiles. In this study, we aimed to evaluate the independent and combined associations of serum uric acid levels and handgrip strength with all-cause mortality among older adults. We also examined sex-specific differences to better elucidate the interaction between metabolic and functional determinants of survival in late life. MATERIALS AND METHODS Study population and setting This retrospective cohort study examined the association between serum uric acid levels, handgrip strength, and all-cause mortality in older adults. A total of 910 older adults aged 60 years and above, who were evaluated at the Department of Geriatrics, University Hospital between 2020 and 2024, were included. Participants were primarily community-dwelling older adults undergoing routine health assessments. Exclusion criteria comprised: (1) active malignancy, infection, or recent surgery; (2) history of gout or the use of uric acid-lowering medications or diuretics; (3) end-stage renal disease (eGFR < 30 mL/min/1.73 m²); (4) conditions limiting handgrip strength evaluation (e.g., severe hand osteoarthritis, peripheral neuropathy, advanced dementia); and (5) contraindications to bioelectrical impedance analysis (e.g., cardiac pacemaker, metallic implants, generalized edema). This study was approved by the ethical review board of University Faculty of Medicine and complied with the Helsinki Declaration. All participating patients supplied formal informed consent to engage in the trial. Laboratory and Clinical Assessments The blood samples were collected after a 12 h overnight fast, on the same day that the bioimpedance was performed. Serum UA levels (mg/dL) were analyzed using enzymatic-colorimetric methods. Elevated UA was defined as > 7.0 mg/dL in male and > 6.0 mg/dL in females [ 11 ]. Participants were also stratified into UA quartiles based on the distribution of measured values. Anthropometric measurements included height, weight, body mass index (BMI), and waist circumference. BMI was calculated as weight (kg) divided by height squared (m²), and waist circumference was measured at the midpoint between the lower costal margin and the iliac crest. A questionnaire assessing Activities of Daily Living (ADL) via the Katz index [ 12 ] and Instrumental Activities of Daily Living (IADL) using the Lawton scale [ 13 ] was administered to the patients. For the ADL and IADL assessments, scores of ≤ 6 points and ≤ 8 points indicated dependence, respectively. The nutritional status, depressive mood, cognitive functions, and frailty were evaluated using the Mini Nutritional Assessment (MNA) short form [ 14 ], Geriatrics Depression Scale (GDS) [ 15 ], Standardized Mini-Mental State Examination (SMMSE) [ 16 ], and the FRAIL scale [ 17 ], respectively. Concerning the MNA, GDS, MMSE, and FRAIL scores: for the MNA, scores below 8 indicate malnutrition, scores between 8 and 11 signify malnutrition risk, and scores above 11 are classified as normal; for the GDS, scores exceeding 14 denote a depressive mood; for the MMSE, scores below 24 indicate cognitive impairment; and for the FRAIL scale, scores of 0, 1–2, and 3 or more are categorized as nonfrail, prefrail, and frail, respectively. Sarcopenia Assessment Handgrip strength (HGS) was measured using a digital dynamometer (Takei TKK 5401, Japan). Three trials were performed on the dominant hand, with a minimum interval of one minute between attempts, and the average value was recorded. Muscle mass was assessed via bioelectrical impedance analysis (BIA) using the Bodystat QuadScan 1500. Electrodes were placed according to standard manufacturer guidelines. Skeletal muscle mass (SMM) was calculated using the Janssen equation and normalized by BMI to yield the skeletal muscle mass index (SMMI, kg/BMI). Sarcopenia was defined based on EWGSOP2 criteria as the presence of both low muscle strength and reduced muscle mass. The cut-off values used were: HGS < 32 kg for males and < 22 kg for females; SMMI < 1.049 kg/BMI for males and < 0.823 kg/BMI for females [ 18 , 19 ]. Gait speed was also measured over a 4-meter walk, recorded in seconds. Statistical Analysis Data normality was assessed using histograms, Q–Q plots, and the Shapiro–Wilk test. Risk factors associated with all-cause mortality were first evaluated using univariate Cox proportional hazards regression models in the overall population, as well as separately in female and male participants. Serum uric acid levels were categorized into quartiles. Subsequently, multivariable Cox regression models were constructed to examine the associations between handgrip strength groups (high and low) and serum uric acid quartiles, adjusting for age, sex, BMI, CKD, DM, and CHD. The proportional hazards assumption was checked using the Schoenfeld residuals and log-log plot. Differences in the levels of 18 clinical biomarkers of biological aging across handgrip strength and serum uric acid groups were assessed using one-way analysis of variance (ANOVA) and independent samples t -tests. The Benjamini–Hochberg procedure was applied to control the false discovery rate due to multiple comparisons. For post hoc pairwise comparisons, Tukey’s test and Tamhane’s T2 test were used, as appropriate. Kaplan–Meier survival curves were generated to illustrate differences in survival according to handgrip strength and serum uric acid quartiles. A significance level of p < 0.05 was considered statistically significant. All statistical analyses were performed using R software version 4.0.4 ( www.r-project.org ). RESULTS A total of 910 older adults (mean age: 71.0±6.9 years; 66.9% female) were included in the study. During a median follow-up of 48 months, 103 participants (11.3%) died. Mortality was significantly higher among males compared to females (20.9% vs. 6.6%, p<0.001). Males were older and exhibited significantly lower fat mass and higher muscle mass, skeletal muscle mass index, and handgrip strength compared to females. The prevalence of geriatric syndromes showed substantial sex-based differences. Sarcopenia was more common among males (67.1%) than in females (32.9%, p<0.001), whereas malnutrition (70.9% vs. 29.1%, p = 0.017), polypharmacy (70.9% vs. 29.1%, p=0.017), depressive symptoms (78.5% vs. 21.5%, p<0.001), and frailty (72.3% vs. 27.7%, p<0.001) were more prevalent among females (Table 1). Participants with reduced HGS exhibited higher triglyceride levels, lower LDL cholesterol, and elevated white blood cell counts (adjusted p<0.05). Similarly, individuals in the highest quartile of serum uric acid (UA) showed higher triglyceride and urea levels and significantly lower HDL cholesterol, indicating a more adverse metabolic profile (Figure 1; Supplementary Table S1 and S2). Survival Analyses In univariate Cox regression models, low HGS was associated with an increased risk of all-cause mortality (HR = 1.91, 95% CI: 1.15–3.18, p = 0.013). Similarly, participants in the highest UA quartile (Q4) had a significantly elevated mortality risk compared to those in the lowest quartile (Q1) (HR: 1.86, 95% CI: 1.13–3.08, p = 0.015) (Figure 2). However, after adjustment for confounding variables including age, sex, BMI, CKD, diabetes mellitus, and CHD, these associations were attenuated and no longer statistically significant. Kaplan–Meier survival curves supported these findings demonstrating lower survival probabilities in individuals with reduced HGS (log-rank p = 0.011) and those in the highest UA quartile (log-rank p = 0.00023) (Figure 3). In sex-stratified multivariable Cox regression models, elevated UA (Q4) remained an independent predictor of mortality among females (HR: 3.08; 95% CI: 1.31–7.26; p = 0.010). In contrast, in males, hyperuricemia was not significantly associated with mortality. Instead, significant predictors of mortality in the male subgroup included CKD, CHD, frailty, malnutrition, and cognitive impairment (Table 2 and Table 3). DISCUSSION Low handgrip strength and elevated blood uric acid levels correlated with heightened all-cause mortality, according to this retrospective cohort study of community-dwelling Turkish older adults. The predictive impact of hyperuricemia was most pronounced in female patients, even after controlling for major confounders. These data indicate that muscle strength and metabolic condition, as shown by serum uric acid levels, may function as independent and sex-specific prognostic factors for survival in advanced age. Sarcopenia has repeatedly been associated with negative outcomes in older adults; nevertheless, the use of uric acid as a mortality risk biomarker remains contentious, as prior research has shown conflicting findings. Our findings enhance the existing research by emphasising the cumulative and perhaps collaborative impacts of functional decline and metabolic dysregulation on geriatric prognosis. The literature exhibits conflicting evidence regarding the relationship between UA and muscle strength. Nahas et al. demonstrated a positive and independent correlation between blood uric acid levels and peak isokinetic muscular strength in older males and females, utilising data from the NHANES (1999–2002) cohort [ 20 ]. Individuals in the highest quartile of UA demonstrated approximately 2.2 kg more strength than those in the lowest quintile, indicating a possibly protective role of UA in muscular function. The authors warn that increased UA is linked to cardiovascular risk, suggesting its effects may vary based on the clinical endpoint. Prior research presents inconclusive results concerning the association between serum uric acid and muscular strength. Huang et al. identified an inverted J-shaped correlation in Japanese males, indicating that both low and very high uric acid levels may adversely affect muscle function [ 21 ]. These findings indicate that UA may exert dual effects—offering antioxidative protection at physiological levels but contributing to oxidative stress and inflammation when elevated. Our study supports this dual-action hypothesis, as higher UA levels correlated with unfavorable metabolic markers and increased mortality, particularly in females. In contrast to Huang et al., who concentrated on middle-aged working males, our cohort comprised older individuals with a wider array of comorbidities and functional impairments, potentially elucidating some disparities in strength profiles among uric acid quartiles. In contrast, Macchi et al. conducted a longterm analysis of the InCHIANTI cohort and found that elevated UA levels were prospectively linked to improved handgrip and knee extension strength over a three-year duration [ 22 ]. They suggested that UA might function as a compensatory antioxidant mechanism that mitigates oxidative damage in ageing muscle. The study, while not evaluating mortality, underscores a possible protective function of UA in the preservation of muscle mass. Nonetheless, recent data from Korean cohorts have yielded inconsistent findings. Yi et al. and Suh et al. both established a negative connection between serum uric acid and relative handgrip strength in Korean females, even after controlling for metabolic variables [ 23 , 24 ]. The findings indicate that the correlation between UA and muscle strength may differ according on sex, ethnicity, age, and the assessment of absolute versus relative strength. Suh et al. posited that estrogen-related alterations in uric acid clearance and muscle metabolism following menopause may intensify the identified negative correlation in females. Our study significantly contributes to the existing literature by illustrating that diminished muscle strength and increased uric acid levels are together linked to mortality risk, reinforcing the idea that both factors should be evaluated simultaneously in older individuals. Kawamoto et al. identified a favourable correlation between UA and handgrip strength in older females, indicating a possible advantageous role of UA in muscle preservation in later life. Nonetheless, their conclusions were restricted to functional outcomes and excluded survival data. The discrepancies among these studies may be ascribed to variations in study design (cross-sectional versus longitudinal), age distribution, comorbidities, and the UA thresholds utilised for analysis [ 25 ]. Collectively, our data substantiate the notion of UA as a dual-natured molecule—providing protection against age-related oxidative damage in muscle at modest concentrations, yet proving harmful when persistently raised, especially in susceptible subgroups. The noted sex-specific effects may indicate varying hormonal profiles, antioxidant capacities, or body compositions, all of which necessitate additional mechanistic exploration. These investigations, together with our findings, indicate a limited optimum range for serum UA, wherein its antioxidant qualities may enhance muscular function. When UA levels beyond this physiological threshold, its pro-inflammatory and vasculotoxic actions may prevail, leading to vascular dysfunction and heightened mortality risk. The sex-specific correlation identified in our study—where hyperuricemia forecasted death solely in females—may be due to hormonal factors, sex-related disparities in UA metabolism, or differing endogenous antioxidant capacities, as previously suggested in the literature. This work contributes to existing evidence by showing that elevated UA levels and diminished muscle strength are independently linked to increased mortality risk in older adults, with potential synergistic effects observed in females. Due to the simplicity, affordability, and non-invasive nature of assessing both handgrip strength and serum UA levels, these metrics are promising as practical instruments for evaluating mortality risk in standard geriatric care. However, additional longitudinal and interventional studies are required to accurately delineate the UA threshold at which its function transitions from protective to detrimental, and to investigate whether UA-lowering therapies or muscle-strengthening interventions can significantly enhance survival outcomes in this at-risk population. This research possesses numerous significant strengths. This study is one of the few to concurrently assess the predictive significance of blood uric acid levels and handgrip strength in forecasting all-cause mortality in older adults. Utilising a sex-stratified analytical method, our results underscore significant sex-specific correlations frequently neglected in geriatric prognostic models. A reasonably large cohort of community-dwelling older adults enhances the study, thereby augmenting its external validity. We conducted a comprehensive geriatric assessment that encompassed nutritional status, frailty, cognitive function, depression, and functional capacity, thereby facilitating rigorous multivariable adjustments and reducing residual confounding. Both blood uric acid and handgrip strength are cost-effective, non-invasive, and readily available clinical metrics, rendering the study's findings very relevant to standard geriatric care, especially in resource-constrained environments. However, it is important to acknowledge certain limitations. The study's observational approach prevents causal conclusions. We assessed serum uric acid levels at a single time point, which may not accurately reflect long-term exposure or fluctuations. Furthermore, we did not have access to data regarding dietary purine consumption, alcohol use, or the administration of specific drugs that could affect UA levels (e.g., low-dose aspirin, corticosteroids). Finally, despite our adjustments for significant comorbidities, unmeasured variables may persist. Future longitudinal and interventional studies are needed to clarify causal relationships and to determine whether UA-lowering interventions or muscle-strengthening programs can improve survival in older adults. Abbreviations • UA Uric acid • HGS Handgrip strength • BMI Body mass index • EWGSOP2 European Working Group on Sarcopenia in Older People 2 • HR Hazard ratio • CI Confidence interval • ADL Activities of Daily Living • IADL Instrumental Activities of Daily Living • BIA Bioelectrical impedance analysis • SMM Skeletal muscle mass • SMMI Skeletal muscle mass index Declarations Ethics Approval and Consent to Participate: This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Erciyes University Faculty of Medicine (decision number 2024/243). Written informed consent was obtained from all participants. Consent for Publication: Not applicable. Competing Interests: The authors declare that they have no competing interests. FUNDING STATEMENT This research received no external funding Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Author Contribution ND: Data collection, investigation, writing-review and editing. SA: Conceptualization, methodology, investigation, writing-original draft, supervision. GZ: Statistical analysis, methodology, writing-review and editing. SIYТ: Data collection, investigation, writing-review and editing. All authors read and approved the final manuscript. Acknowledgments: The authors would like to thank the healthcare professionals and administrative staff of the Erciyes University Department of Geriatrics for their valuable support during data collection and patient follow-up. Availability of Data and Materials: The datasets used and analyzed during the current study are available from the corresponding author on reasonable request. References Cruz-Jentoft AJ, Bahat G, Bauer J et al (2019) Sarcopenia: revised European consensus on definition and diagnosis. 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BMC Geriatr 23(1):652. https://doi.org/10.1186/s12877-023-04374-3 Macchi C, Molino-Lova R, Polcaro P et al (2008) Higher circulating levels of uric acid are prospectively associated with better muscle function in older persons. Mech Ageing Dev 129:522–527. https://doi.org/10.1016/j.mad.2008.04.008 Suh CH (2023) Inverse correlation of serum uric acid and relative hand grip strength in Korean adult women. Osteoporos Sarcopenia 9:42. https://doi.org/10.1016/j.afos.2023.03.002 Yi D, Khang AR, Lee HW et al (2023) Reply on Inverse correlation of serum uric acid and relative hand grip strength in Korean adult women. Osteoporos Sarcopenia 9:43. https://doi.org/10.1016/j.afos.2023.03.005 Kawamoto R, Ninomiya D, Kasai Y et al (2016) Serum uric acid is positively associated with handgrip strength among Japanese community-dwelling elderly women. PLoS ONE 11:e0151044. https://doi.org/10.1371/journal.pone.0151044 Tables Table 1. Characteristics of subjects by gender. Characteristics Total n=910 Female n=609 Male n=301 p Age, years 71 (66-76) 71 (66-76) 72 (67-78) 0.002 75 604 (66.4) 306 (33.6) 420 (70) 189 (61.8) 184 (30) 117 (38.2) 0.019 Marital status n(%) Single Married Widow 18 (2) 612 (67.3) 280 (30.7) 11 (61.2) 345 (56.4) 253 (90.4) 7 (38.8) 267 (43.6) 27 (9.6) <0.001 Income n(%) Good Middle Bad 110 (12.1) 700 (77) 100 (10.9) 72 (65.5) 469 (67) 68 (68) 38 (34.5) 231 (33) 32 (32) 0.922 Height, cm, medyan (IQR) 156 ( 151-163) 153 (150-157) 165 (161-170.5) <0.001 Weight, kg, medyan (IQR) 75.05 (66.25-85) 75.1 (65-86) 75 (68-75) 0.548 BMI, kg/m 2 medyan (IQR) 30.3 (26.33-35) 32 (27.9-36) 27.4 (24.8-30.5) <0.001 WC, cm, medyan (IQR) 105 (95-113) 107 (95-115) 101 (95-108) <0.001 Hip circumference, cm, medyan (IQR) 110 (102-120) 115 (106-123) 104 (99-109) <0.001 CC, cm, medyan (IQR) 37 (33-40) 37 (34-41) 35 (32.4-38) <0.001 Muscle mass, kg, medyan (IQR) 20.28 (17.09-25.23) 18.36 (15.86-20.90) 26.04 (23.48-29.39) <0.001 Fat-free mass, kg, medyan (IQR) 42 (37.4-49.9) 40 (35.4-44.6) 51.9 (46.9-58.6) <0.001 Fat mass, kg, medyan (IQR) 31.2( 23.1-38.87) 34.9 (28.1-42.1) 22.9 (18.3-27.4) <0.001 Total fat mass, % medyan (IQR) 43.7 (33-49.3) 47 (42.7-50.7) 30.6 (26.8-34.9) <0.001 Skeletal muscle mass index, medyan (IQR) 8.33 (0.53-0.89) 7.789 (6.862-8.765) 9.585 (8.802-10.576) <0.001 4 m walking test, m/s, medyan (IQR) 0.72 (0.5-0.95) 0.69 (0.5-0.87) 0.8 (0.54-1) <0.001 TUG, s, medyan (IQR) 11.5 (9-15) 12 (9.45-15.83) 10.6 (8.48-14) <0.001 HGS, kg, medyan (IQR) 20 (15-28) 17.4 (13-22.1) 29 (22.15-35) <0.001 GFR, ml/min/1.73m 2 medyan (IQR) 75.84 (63-88.89) 77 (63.5-89.7) 75 (61.3-87.5) 0.046 Glucose, mg/dL medyan (IQR) 108 (94-137.75) 107 (93-137) 111 (95.5-140.5) 0.068 LDL, mg/dL medyan (IQR) 113.7 (90.7-138.8) 118.4 (94.9-144.4) 106.9 (82.2-127 ) <0.001 HDL, mg/dL medyan (IQR) 48.4 (40.85-58.5) 51.4 (43-60.4) 44.5 (37.4-51) <0.001 TG, mg/dL medyan (IQR) 138 (102-191) 138 (105-191) 136.5 (95-192) 0.195 Albumin, g/dL medyan (IQR) 4.46 (4.26-4.68) 4.44 (4.27-4.65) 4.52 (4.21-4.73) 0.128 CRP, mg/L medyan (IQR) 2.9 (1.41-6.68) 3.01 (1.47-6.47) 2.64 (1.26-8.03) 0.867 Vitamin D, ng/mL medyan (IQR) 19 (12.45-28) 19 (11.9-29.1) 19.55 (14.08-26) 0.438 Uric acid, mg/dL medyan (IQR) 5.2 (4.27-6.2) 5 (4.1-6) 5.5 (4.75-6.6) <0.001 Hyperuricemia, n (%) Yes No 213 (23.4) 697 (76.6) 156 (73.2) 453 (65) 57 (26.8) 244 (35) 0.025 Hypertension, n (%) Yes No 617 (67.8) 293 (32.2) 446 (72.3) 163 (55.6) 171 (27.7) 130 (44.4) <0.001 CKD, n (%) Yes No 193 (21.2) 717 ( 78.8) 120 (67.2) 489 (68.2) 73 (37.8) 228 (31.8) 0.114 Diabetes, n (%) Yes No 437 (48) 473 (52) 301 (68.9) 308 (65.1) 136 (31.1) 165 (34.9) 0.228 Stoke history, n (%) Yes No 32 (3.5) 878 (96.5) 19 (59.4) 590 (67.2) 13 (40.6) 288 (32.8) 0.356 CHD, n(%) Yes No 183 (20.1) 727 (79.9) 113 (61.7) 496 (68.2) 70 (38.5) 231 (31.8) 0.096 SBP, mmHg, medyan (IQR) 130 (120-140) 130 (120-140) 130 (120-140) 0.307 DBP, mmHg, medyan (IQR) 80 (70-85) 80 (70-85) 80 (70-85) 0.334 ADL, dependent n(%) Yes No 524 (57.6) 386 (42.4) 341 (65.1) 268 (69.4) 183 (34.9) 118 (30.6) 0.168 IADL, dependent n(%) Yes No 582 (64) 328 (36) 388 (66.7) 221 (67.4) 194 (33.3) 107 (32.6) 0.827 Depressive mood, n(%) Yes No 391 (43) 519 (57) 307 (78.5) 302 (58.2) 84 (21.5) 217 (41.8) <0.001 Cognitive impairment, n(%) Yes No 176 (19.6) 725 (80.4) 120 (68.2) 481 (66.3) 56 (31.9) 244 (33.7) 0.643 Sarcopenia, n(%) Yes No 764 (84) 146 (16) 561 (73.4) 48 (32.9) 203 (26.6) 98 (67.1) <0.001 Malnutrition, n(%) Yes No 477 (53.5) 415 (46.5) 338 (70.9) 263 (63.4) 139 (29.1) 152 (36.6) 0.017 Polypharmacy, n(%) Yes No 463 (50.9) 447 (49.1) 331 (71.5) 278 (62.2) 132 (28.5) 169 (37.8) 0.003 Frailty, n(%) Non-frail Pre-frail Frail 150 (16.5) 475 (52.2) 285 (31.3) 66 (44) 337 (71) 206 (72.3) 84 (56) 138 (29) 79 (27.7) <0.001 Mortality, n(%) Yes No 103 (11.3) 807 (88.7) 40 (38.8) 569 (70.5) 63 (61.2) 238 (29.5) <0.001 Number of drugs, medyan (IQR) 4 (2-6) 4(2-6) 3 (1-5) 0.002 BMI: body mass index; TUG: Timed Up and Go test; LDL: low-density lipoprotein; HDL: high-density lipoprotein; TG: triglyceride; CRP: C-reactive protein; CKD: Chronic kidney disease; CHD: coronary heart disease; ADL: activities of daily living; IADL: instrumental activities of daily living. SBP: Systolic blood pressure; DBP: Diastolic blood pressure. CC:Calf circumference. Statistically significant p values are shown in bold. Table 2. Univariate Cox regression analyses of overall survival among female participants. Variables Univariate Cox HR (95%CI) p- value Age, years 1.11(1.07-1.16) <0.001 Marital status Single Married 1.00 0.54(0.28-1.04) - 0.064 Income High Middle Low 1.00 2.66(0.64-11.09) 4.13(0.86-19.87) - 0.181 0.077 Height (cm) 0.90(0.86-0.95) <0.001 Weight (kg) 0.97(0.95-0.99) 0.009 BMI (kg/m 2 ) 0.97(0.93-1.03) 0.318 Waist circumference (cm) 0.99(0.97-1.02) 0.915 Hip circumference (cm) 0.98(0.97-1.01) 0.294 Calf circumference (cm) 0.96(0.91-1.02) 0.212 Muscle mass (kg) 0.88(0.80-0.96) 0.005 Fat-free mass (kg) 0.92(0.88-0.96) <0.001 Fat mass (kg) 0.99(0.96-1.01) 0.306 Total fat mass, % 1.04(0.99-1.09) 0.132 Skeletal muscle mass index 0.85(0.69-1.04) 0.119 4 m walking test (m/s) 0.35(0.09-1.36) 0.129 TUG, s 1.06(1.02-1.10) 0.001 HGS (kg) 0.94(0.89-0.99) 0.014 HGS (kg), High (females >22 kg, males >36 kg) Low (females≤22 kg, males≤36 kg) 1.00 1.79(0.82-3.90) - 0.142 GFR (ml/min/1.73) m 2 ) 0.97(0.96-0.98) <0.001 Glucose (mg/dL) 1.00(0.99-1.01) 0.514 LDL cholesterol 0.99(0.98-1.00) 0.028 HDL cholesterol 0.96(0.94-0.99) 0.009 TG (mg/dL) 1.00(0.99-1.00) 0.848 Albumin (g/dL) 0.09(0.04-0.20) <0.001 CRP (mg/L) 1.01(1.00-1.02) 0.018 Vitamin D (ng/mL) 0.97(0.94-1.01) 0.108 Uric acid (mg/dL) 1.29(1.11-1.50) 0.001 Uric acid (Quartile) 1.Quartile 2.Quartile 3.Quartile 4.Quartile 1.00 0.71(0.23-2.25) 0.96(0.34-2.74) 3.08(1.31-7.26) - 0.563 0.938 0.010 Hyperuricemia 3.46(1.86-6.44) <0.001 Hypertension 1.80(0.79-4.06) 0.159 CKD 4.51(2.43-8.39) <0.001 Diabetes mellitus 0.81(0.44-1.51) 0.508 Stoke history 2.76(0.98-7.76) 0.055 CHD 2.01(1.02-3.95) 0.044 Systolic blood pressure (mmHg) 0.99(0.98-1.02) 0.821 Diastolic blood pressure (mmHg) 0.99(0.95-1.02) 0.518 ADL, dependent 1.94(0.83-4.51) 0.124 IADL, dependent 1.54(0.67-3.55) 0.315 Depressive mood 1.31(0.70-2.46) 0.393 Cognitive impairment 2.08(1.07-4.04) 0.032 Sarcopenia 3.19(0.44-23.24) 0.252 Malnutrition 2.67(1.22-5.83) 0.014 Polypharmacy 1.83(0.94-3.55) 0.074 Frailty Non-frail Pre-frail Frail 1.00 1.49(0.34-6.51) 4.10(0.97-17.41) - 0.597 0.056 Number of drugs 1.06(0.96-1.18) 0.263 BMI: body mass index; TUG: Timed Up and Go test; LDL: low-density lipoprotein; HDL: high-density lipoprotein; TG: triglyceride; CRP: C-reactive protein; CKD: Chronic kidney disease; CHD: coronary heart disease; ADL: activities of daily living; IADL: instrumental activities of daily living. Statistically significant p values are shown in bold. Table 3. Univariate Cox regression analyses of overall survival among male participants. Variables Univariate Cox HR (%95CI) p- value * Age, years 1.07(1.04-1.11) <0.001 Marital status Single Married 1.00 0.82(0.39-1.73) - 0.605 Income High Middle Low 1.00 0.77(0.40-1.48) 0.75(0.28-2.04) - 0.430 0.575 Height (cm) 0.99(0.96-1.02) 0.391 Weight (kg) 0.98(0.96-1.00) 0.025 BMI (kg/m 2 ) 0.96(0.91-1.01) 0.089 WC (cm) 0.99(0.97-1.01) 0.247 Hip circumference (cm) 0.98(0.96-0.99) 0.003 CC (cm) 0.96(0.92-1.01) 0.130 Muscle mass (kg) 0.95(0.90-1.01) 0.076 Fat-free mass (kg) 0.96(0.94-0.99) 0.006 Fat mass (kg) 1.00(0.96-1.03) 0.819 Total fat mass, % 1.04(1.00-1.07) 0.048 Skeletal muscle mass index 0.85(0.72-1.02) 0.077 4 m walking test (m/s) 0.53(0.23-1.23) 0.140 TUG, s 1.06(1.03-1.09) 22 kg, males >36 kg) Low (females≤22 kg, males ≤36 kg) 1.00 1.57(0.80-3.09) - 0.192 GFR (ml/min/1.73) m 2 ) 0.98(0.97-0.99) <0.001 Glucose (mg/dL) 1.00(0.99-1.00) 0.666 LDL (mg/dL) 0.99(0.98-1.00) 0.027 HDL (mg/dL) 1.00(0.98-1.03) 0.881 TG (mg/dL) 0.99(0.99-1.00) 0.002 Albumin (g/dL) 0.21(0.14-0.33) <0.001 CRP (mg/L) 1.01(1.00-1.02) 0.030 Vitamin D (ng/mL) 1.01(0.99-1.04) 0.342 Uric acid (mg/dL) 1.09(0.94-1.26) 0.268 Uric acid (Quartile) 1.Quartile 2.Quartile 3.Quartile 4.Quartile 1.00 0.82(0.42-1.61) 0.47(0.20-1.08) 1.40(0.74-2.66) - 0.566 0.074 0.301 Hyperuricemia 1.72(0.99-3.00) 0.056 Hypertension 1.28(0.77-2.14) 0.336 CKD 2.12(1.26-3.57) 0.004 Diabetes mellitus 0.84(0.51-1.39) 0.497 Stoke history 0.75(0.24-2.39) 0.627 CHD 1.70(1.01-2.86) 0.044 SBP (mmHg) 0.99(0.97-1.01) 0.380 DBP (mmHg) 1.02(0.99-1.05) 0.124 ADL, dependent 2.38(1.00-5.66) 0.050 IADL, dependent 2.24(0.95-5.29) 0.067 Depressive mood 2.03(1.23-3.36) 0.006 Cognitive impairment 2.22(1.31-3.78) 0.003 Sarcopenia 1.13(0.64-1.97) 0.678 Malnutrition 2.15(1.28-3.64) 0.004 Polypharmacy 1.22(0.74-2.00) 0.435 Frailty Non-frail Pre-frail Frail 1.00 1.83(0.86-3.88) 3.48(1.63-7.42) - 0.115 0.001 Number of drugs 1.05(0.97-1.14) 0.258 BMI: body mass index; LDL: low-density lipoprotein; HDL: high-density lipoprotein; TG: triglyceride; CRP: C-reactive protein; CKD: Chronic kidney disease; CHD: coronary heart disease; ADL: activities of daily living; IADL: instrumental activities of daily living. Statistically significant p values are shown in bold. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTables.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6913893","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":472855011,"identity":"298e2468-dd65-49d0-b1ce-93cd918ca35f","order_by":0,"name":"Neslihan Doğan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABJ0lEQVRIiWNgGAWjYHACxgOJDUDqAIhdAcTMUOEGPHqQtJxB0cKMWwsjTAtjG5LluLSYs7c/OPBwh10e3/H2i58L59nk87fzGD78wWAju+EA/7EPWLRY9pwxOJB4JrlY8syZYumZ29IsZxzmMTbmYUgz3nCAmXkGFi0GN3KAfmljTtxwIydBmnfbYQMDZh4zaQaGw4kgLdgcZnD/+QOglnqQluTfvHP+g7SY//zB8B+3lhsMQIe1Ac28kX5MmrfhANgWBh6g1Ti1nMkBaTmeOPPMGTZrnmPJBhKH2YqleQySjWceZjbGquX48YcPf7ZVJ/Ydb398m6fGzoC///DGjz8q7GT7jjc+xhrKCMBjAGVwABkgNu6YhAH2B+iMUTAKRsEoGAVgAACCcG2AzLInxAAAAABJRU5ErkJggg==","orcid":"","institution":"Erciyes University","correspondingAuthor":true,"prefix":"","firstName":"Neslihan","middleName":"","lastName":"Doğan","suffix":""},{"id":472855012,"identity":"201bff25-9a1c-46f3-8465-e85654cfe0da","order_by":1,"name":"Sibel Akın","email":"","orcid":"","institution":"Erciyes University","correspondingAuthor":false,"prefix":"","firstName":"Sibel","middleName":"","lastName":"Akın","suffix":""},{"id":472855013,"identity":"896da6b9-6705-4e0e-9dd2-5c30157b1c56","order_by":2,"name":"Gökmen Zararsız","email":"","orcid":"","institution":"Erciyes University","correspondingAuthor":false,"prefix":"","firstName":"Gökmen","middleName":"","lastName":"Zararsız","suffix":""},{"id":472855014,"identity":"b3026081-c3bc-420e-948b-8cbddb75c300","order_by":3,"name":"Serra İlayda Yerlitaş Taştan⁴","email":"","orcid":"","institution":"Erciyes University","correspondingAuthor":false,"prefix":"","firstName":"Serra","middleName":"İlayda Yerlitaş","lastName":"Taştan⁴","suffix":""}],"badges":[],"createdAt":"2025-06-17 11:38:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6913893/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6913893/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85370822,"identity":"8d32d23e-29be-4a75-a4c6-b906f485c228","added_by":"auto","created_at":"2025-06-25 07:29:16","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":142347,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap displaying the distribution of laboratory parameters across uric acid quartiles (left) and grip strength levels (right).\u003c/p\u003e\n\u003cp\u003eHierarchical clustering was applied to visualize the patterns of biomarker changes across quartiles of serum uric acid and dichotomized handgrip strength levels. Parameters are grouped by physiological systems (e.g., liver, kidney, cardiovascular) as indicated by the color-coded sidebar.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6913893/v1/6c14b2c1dc39785b1ab32411.jpeg"},{"id":85369614,"identity":"1d86b8ae-73ff-4458-8b4a-6eda97911ff5","added_by":"auto","created_at":"2025-06-25 07:21:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":53537,"visible":true,"origin":"","legend":"\u003cp\u003eAdjusted Hazard Ratios for All-Cause Mortality According to Serum Uric Acid Quartiles and Handgrip Strength Categories\u003c/p\u003e\n\u003cp\u003eForest plots display multivariate-adjusted hazard ratios (HRs) and 95% confidence intervals for all-cause mortality according to (A) serum uric acid quartiles and (B) handgrip strength categories. The first quartile of uric acid and the high handgrip strength group serve as reference categories (HR = 1.00). The highest uric acid quartile (Q4) and low handgrip strength group were significantly associated with increased mortality risk (*p \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6913893/v1/ee81a240ce1bb3335cc6c90b.png"},{"id":85369608,"identity":"a79a06ab-abd8-41dd-96a6-d7b7ea663f87","added_by":"auto","created_at":"2025-06-25 07:21:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":180423,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier Survival Curves According to Handgrip Strength and Serum Uric Acid Quartiles\u003c/p\u003e\n\u003cp\u003eKaplan–Meier plots illustrating all-cause survival probability over time stratified by (A) handgrip strength (high vs. low) and (B) serum uric acid quartiles. Log-rank test showed significantly reduced survival in individuals with low handgrip strength (p = 0.011) and those in the highest uric acid quartile (p = 0.00023). The number of participants at risk during follow-up is presented below each plot.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6913893/v1/64f92a2599f0f6c18d4da8ca.png"},{"id":85608950,"identity":"6da66d92-e9c1-4743-9bd4-524dec561d59","added_by":"auto","created_at":"2025-06-29 09:31:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1790103,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6913893/v1/d947e929-0c5a-4ded-99f5-0ec371bfc4fb.pdf"},{"id":85369603,"identity":"0118948a-ac8f-442c-8cb5-1b5c3db67f10","added_by":"auto","created_at":"2025-06-25 07:21:15","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":18599,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-6913893/v1/cc3aabfbe107a9ec70cbd583.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Uric Acid and Grip Strength as Predictors of Mortality in Older Adults: A Sex-Stratified Analysis","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eSarcopenia, the age-associated reduction in skeletal muscle mass, strength, and functionality, significantly contributes to frailty, disability, and elevated mortality in older adults [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Among its diagnostic components, handgrip strength (HGS) has emerged as a simple yet highly predictive marker of functional decline and adverse outcomes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This age-related muscle deterioration is driven by multifactorial processes, including chronic low-grade inflammation, oxidative stress, hormonal dysregulation, and neuromuscular degeneration [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Elevated levels of inflammatory biomarkers such as tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and C-reactive protein (CRP) have been repeatedly associated with reduced muscle strength in older adults [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUric acid (UA), the end product of purine metabolism, plays a complex role in human health. On one hand, elevated serum UA levels have been implicated in the pathogenesis of cardiovascular and cerebrovascular diseases, hypertension, metabolic syndrome, and increased all-cause mortality, likely due to their pro-inflammatory and oxidative effects [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. On the other hand, UA acts as a potent antioxidant, scavenging oxygen free radicals and mitigating oxidative stress, thereby potentially conferring neuroprotective effects [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Low serum UA levels have been linked to adverse outcomes including increased mortality and higher risk of neurodegenerative diseases such as Alzheimer\u0026rsquo;s and Parkinson\u0026rsquo;s disease [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite prior research investigating the relationship between UA levels and sarcopenia-related parameters, findings continue to be inconsistent and ambiguous. While some studies report that moderate UA levels are positively associated with muscle strength, others suggest a detrimental impact, particularly at higher UA concentrations [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. To our knowledge, no research has particularly investigated this association within Turkish older adults, a population characterized by unique dietary and metabolic profiles.\u003c/p\u003e \u003cp\u003eIn this study, we aimed to evaluate the independent and combined associations of serum uric acid levels and handgrip strength with all-cause mortality among older adults. We also examined sex-specific differences to better elucidate the interaction between metabolic and functional determinants of survival in late life.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population and setting\u003c/h2\u003e \u003cp\u003eThis retrospective cohort study examined the association between serum uric acid levels, handgrip strength, and all-cause mortality in older adults. A total of 910 older adults aged 60 years and above, who were evaluated at the Department of Geriatrics, University Hospital between 2020 and 2024, were included. Participants were primarily community-dwelling older adults undergoing routine health assessments. Exclusion criteria comprised: (1) active malignancy, infection, or recent surgery; (2) history of gout or the use of uric acid-lowering medications or diuretics; (3) end-stage renal disease (eGFR\u0026thinsp;\u0026lt;\u0026thinsp;30 mL/min/1.73 m\u0026sup2;); (4) conditions limiting handgrip strength evaluation (e.g., severe hand osteoarthritis, peripheral neuropathy, advanced dementia); and (5) contraindications to bioelectrical impedance analysis (e.g., cardiac pacemaker, metallic implants, generalized edema). This study was approved by the ethical review board of University Faculty of Medicine and complied with the Helsinki Declaration. All participating patients supplied formal informed consent to engage in the trial.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eLaboratory and Clinical Assessments\u003c/h3\u003e\n\u003cp\u003eThe blood samples were collected after a 12 h overnight fast, on the same day that the bioimpedance was performed. Serum UA levels (mg/dL) were analyzed using enzymatic-colorimetric methods. Elevated UA was defined as \u0026gt;\u0026thinsp;7.0 mg/dL in male and \u0026gt;\u0026thinsp;6.0 mg/dL in females [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Participants were also stratified into UA quartiles based on the distribution of measured values. Anthropometric measurements included height, weight, body mass index (BMI), and waist circumference. BMI was calculated as weight (kg) divided by height squared (m\u0026sup2;), and waist circumference was measured at the midpoint between the lower costal margin and the iliac crest. A questionnaire assessing Activities of Daily Living (ADL) via the Katz index [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and Instrumental Activities of Daily Living (IADL) using the Lawton scale [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] was administered to the patients. For the ADL and IADL assessments, scores of \u0026le;\u0026thinsp;6 points and \u0026le;\u0026thinsp;8 points indicated dependence, respectively. The nutritional status, depressive mood, cognitive functions, and frailty were evaluated using the Mini Nutritional Assessment (MNA) short form [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], Geriatrics Depression Scale (GDS) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], Standardized Mini-Mental State Examination (SMMSE) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], and the FRAIL scale [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], respectively. Concerning the MNA, GDS, MMSE, and FRAIL scores: for the MNA, scores below 8 indicate malnutrition, scores between 8 and 11 signify malnutrition risk, and scores above 11 are classified as normal; for the GDS, scores exceeding 14 denote a depressive mood; for the MMSE, scores below 24 indicate cognitive impairment; and for the FRAIL scale, scores of 0, 1\u0026ndash;2, and 3 or more are categorized as nonfrail, prefrail, and frail, respectively.\u003c/p\u003e\n\u003ch3\u003eSarcopenia Assessment\u003c/h3\u003e\n\u003cp\u003eHandgrip strength (HGS) was measured using a digital dynamometer (Takei TKK 5401, Japan). Three trials were performed on the dominant hand, with a minimum interval of one minute between attempts, and the average value was recorded. Muscle mass was assessed via bioelectrical impedance analysis (BIA) using the Bodystat QuadScan 1500. Electrodes were placed according to standard manufacturer guidelines. Skeletal muscle mass (SMM) was calculated using the Janssen equation and normalized by BMI to yield the skeletal muscle mass index (SMMI, kg/BMI). Sarcopenia was defined based on EWGSOP2 criteria as the presence of both low muscle strength and reduced muscle mass. The cut-off values used were: HGS\u0026thinsp;\u0026lt;\u0026thinsp;32 kg for males and \u0026lt;\u0026thinsp;22 kg for females; SMMI\u0026thinsp;\u0026lt;\u0026thinsp;1.049 kg/BMI for males and \u0026lt;\u0026thinsp;0.823 kg/BMI for females [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Gait speed was also measured over a 4-meter walk, recorded in seconds.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData normality was assessed using histograms, Q\u0026ndash;Q plots, and the Shapiro\u0026ndash;Wilk test. Risk factors associated with all-cause mortality were first evaluated using univariate Cox proportional hazards regression models in the overall population, as well as separately in female and male participants. Serum uric acid levels were categorized into quartiles. Subsequently, multivariable Cox regression models were constructed to examine the associations between handgrip strength groups (high and low) and serum uric acid quartiles, adjusting for age, sex, BMI, CKD, DM, and CHD. The proportional hazards assumption was checked using the Schoenfeld residuals and log-log plot. Differences in the levels of 18 clinical biomarkers of biological aging across handgrip strength and serum uric acid groups were assessed using one-way analysis of variance (ANOVA) and independent samples \u003cem\u003et\u003c/em\u003e-tests. The Benjamini\u0026ndash;Hochberg procedure was applied to control the false discovery rate due to multiple comparisons. For post hoc pairwise comparisons, Tukey\u0026rsquo;s test and Tamhane\u0026rsquo;s T2 test were used, as appropriate. Kaplan\u0026ndash;Meier survival curves were generated to illustrate differences in survival according to handgrip strength and serum uric acid quartiles. A significance level of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. All statistical analyses were performed using R software version 4.0.4 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.r-project.org\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.r-project.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total of 910 older adults (mean age: 71.0\u0026plusmn;6.9 years; 66.9% female) were included in the study. During a median follow-up of 48 months, 103 participants (11.3%) died. Mortality was significantly higher among males compared to females (20.9% vs. 6.6%, p\u0026lt;0.001). Males were older and exhibited significantly lower fat mass and higher muscle mass, skeletal muscle mass index, and handgrip strength compared to females.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe prevalence of geriatric syndromes showed substantial sex-based differences. Sarcopenia was more common among males (67.1%) than in females (32.9%, p\u0026lt;0.001), whereas malnutrition (70.9% vs. 29.1%, p = 0.017), polypharmacy (70.9% vs. 29.1%, p=0.017), depressive symptoms (78.5% vs. 21.5%, p\u0026lt;0.001), and frailty (72.3% vs. 27.7%, p\u0026lt;0.001) were more prevalent among females (Table 1). Participants with reduced HGS exhibited higher triglyceride levels, lower LDL cholesterol, and elevated white blood cell counts (adjusted p\u0026lt;0.05). Similarly, individuals in the highest quartile of serum uric acid (UA) showed higher triglyceride and urea levels and significantly lower HDL cholesterol, indicating a more adverse metabolic profile (Figure 1; Supplementary Table S1 and S2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSurvival Analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn univariate Cox regression models, low HGS was associated with an increased risk of all-cause mortality (HR = 1.91, 95% CI: 1.15\u0026ndash;3.18, \u003cem\u003ep\u003c/em\u003e = 0.013). Similarly, participants in the highest UA quartile (Q4) had a significantly elevated mortality risk compared to those in the lowest quartile (Q1) (HR: 1.86, 95% CI: 1.13\u0026ndash;3.08, p = 0.015) (Figure 2). However, after adjustment for confounding variables including age, sex, BMI, CKD, diabetes mellitus, and CHD, these associations were attenuated and no longer statistically significant. Kaplan\u0026ndash;Meier survival curves supported these findings demonstrating lower survival probabilities in individuals with reduced HGS (log-rank p = 0.011) and those in the highest UA quartile (log-rank p = 0.00023) (Figure 3). In sex-stratified multivariable Cox regression models, elevated UA (Q4) remained an independent predictor of mortality among females (HR: 3.08; 95% CI: 1.31\u0026ndash;7.26; p = 0.010). In contrast, in males, hyperuricemia was not significantly associated with mortality. Instead, significant predictors of mortality in the male subgroup included CKD, CHD, frailty, malnutrition, and cognitive impairment (Table 2 and Table 3).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eLow handgrip strength and elevated blood uric acid levels correlated with heightened all-cause mortality, according to this retrospective cohort study of community-dwelling Turkish older adults. The predictive impact of hyperuricemia was most pronounced in female patients, even after controlling for major confounders. These data indicate that muscle strength and metabolic condition, as shown by serum uric acid levels, may function as independent and sex-specific prognostic factors for survival in advanced age. Sarcopenia has repeatedly been associated with negative outcomes in older adults; nevertheless, the use of uric acid as a mortality risk biomarker remains contentious, as prior research has shown conflicting findings. Our findings enhance the existing research by emphasising the cumulative and perhaps collaborative impacts of functional decline and metabolic dysregulation on geriatric prognosis.\u003c/p\u003e \u003cp\u003eThe literature exhibits conflicting evidence regarding the relationship between UA and muscle strength. Nahas et al. demonstrated a positive and independent correlation between blood uric acid levels and peak isokinetic muscular strength in older males and females, utilising data from the NHANES (1999\u0026ndash;2002) cohort [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Individuals in the highest quartile of UA demonstrated approximately 2.2 kg more strength than those in the lowest quintile, indicating a possibly protective role of UA in muscular function. The authors warn that increased UA is linked to cardiovascular risk, suggesting its effects may vary based on the clinical endpoint.\u003c/p\u003e \u003cp\u003ePrior research presents inconclusive results concerning the association between serum uric acid and muscular strength. Huang et al. identified an inverted J-shaped correlation in Japanese males, indicating that both low and very high uric acid levels may adversely affect muscle function [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. These findings indicate that UA may exert dual effects\u0026mdash;offering antioxidative protection at physiological levels but contributing to oxidative stress and inflammation when elevated. Our study supports this dual-action hypothesis, as higher UA levels correlated with unfavorable metabolic markers and increased mortality, particularly in females. In contrast to Huang et al., who concentrated on middle-aged working males, our cohort comprised older individuals with a wider array of comorbidities and functional impairments, potentially elucidating some disparities in strength profiles among uric acid quartiles.\u003c/p\u003e \u003cp\u003eIn contrast, Macchi et al. conducted a longterm analysis of the InCHIANTI cohort and found that elevated UA levels were prospectively linked to improved handgrip and knee extension strength over a three-year duration [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. They suggested that UA might function as a compensatory antioxidant mechanism that mitigates oxidative damage in ageing muscle. The study, while not evaluating mortality, underscores a possible protective function of UA in the preservation of muscle mass.\u003c/p\u003e \u003cp\u003eNonetheless, recent data from Korean cohorts have yielded inconsistent findings. Yi et al. and Suh et al. both established a negative connection between serum uric acid and relative handgrip strength in Korean females, even after controlling for metabolic variables [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The findings indicate that the correlation between UA and muscle strength may differ according on sex, ethnicity, age, and the assessment of absolute versus relative strength. Suh et al. posited that estrogen-related alterations in uric acid clearance and muscle metabolism following menopause may intensify the identified negative correlation in females. Our study significantly contributes to the existing literature by illustrating that diminished muscle strength and increased uric acid levels are together linked to mortality risk, reinforcing the idea that both factors should be evaluated simultaneously in older individuals.\u003c/p\u003e \u003cp\u003eKawamoto et al. identified a favourable correlation between UA and handgrip strength in older females, indicating a possible advantageous role of UA in muscle preservation in later life. Nonetheless, their conclusions were restricted to functional outcomes and excluded survival data. The discrepancies among these studies may be ascribed to variations in study design (cross-sectional versus longitudinal), age distribution, comorbidities, and the UA thresholds utilised for analysis [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCollectively, our data substantiate the notion of UA as a dual-natured molecule\u0026mdash;providing protection against age-related oxidative damage in muscle at modest concentrations, yet proving harmful when persistently raised, especially in susceptible subgroups. The noted sex-specific effects may indicate varying hormonal profiles, antioxidant capacities, or body compositions, all of which necessitate additional mechanistic exploration.\u003c/p\u003e \u003cp\u003eThese investigations, together with our findings, indicate a limited optimum range for serum UA, wherein its antioxidant qualities may enhance muscular function. When UA levels beyond this physiological threshold, its pro-inflammatory and vasculotoxic actions may prevail, leading to vascular dysfunction and heightened mortality risk. The sex-specific correlation identified in our study\u0026mdash;where hyperuricemia forecasted death solely in females\u0026mdash;may be due to hormonal factors, sex-related disparities in UA metabolism, or differing endogenous antioxidant capacities, as previously suggested in the literature. This work contributes to existing evidence by showing that elevated UA levels and diminished muscle strength are independently linked to increased mortality risk in older adults, with potential synergistic effects observed in females. Due to the simplicity, affordability, and non-invasive nature of assessing both handgrip strength and serum UA levels, these metrics are promising as practical instruments for evaluating mortality risk in standard geriatric care. However, additional longitudinal and interventional studies are required to accurately delineate the UA threshold at which its function transitions from protective to detrimental, and to investigate whether UA-lowering therapies or muscle-strengthening interventions can significantly enhance survival outcomes in this at-risk population.\u003c/p\u003e \u003cp\u003eThis research possesses numerous significant strengths. This study is one of the few to concurrently assess the predictive significance of blood uric acid levels and handgrip strength in forecasting all-cause mortality in older adults. Utilising a sex-stratified analytical method, our results underscore significant sex-specific correlations frequently neglected in geriatric prognostic models. A reasonably large cohort of community-dwelling older adults enhances the study, thereby augmenting its external validity. We conducted a comprehensive geriatric assessment that encompassed nutritional status, frailty, cognitive function, depression, and functional capacity, thereby facilitating rigorous multivariable adjustments and reducing residual confounding. Both blood uric acid and handgrip strength are cost-effective, non-invasive, and readily available clinical metrics, rendering the study's findings very relevant to standard geriatric care, especially in resource-constrained environments. However, it is important to acknowledge certain limitations. The study's observational approach prevents causal conclusions. We assessed serum uric acid levels at a single time point, which may not accurately reflect long-term exposure or fluctuations. Furthermore, we did not have access to data regarding dietary purine consumption, alcohol use, or the administration of specific drugs that could affect UA levels (e.g., low-dose aspirin, corticosteroids). Finally, despite our adjustments for significant comorbidities, unmeasured variables may persist. Future longitudinal and interventional studies are needed to clarify causal relationships and to determine whether UA-lowering interventions or muscle-strengthening programs can improve survival in older adults.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; UA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUric acid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; HGS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHandgrip strength\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; BMI\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\u0026bull; EWGSOP2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEuropean Working Group on Sarcopenia in Older People 2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; HR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHazard ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; CI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; ADL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eActivities of Daily Living\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; IADL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInstrumental Activities of Daily Living\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; BIA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBioelectrical impedance analysis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; SMM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSkeletal muscle mass\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u0026bull; SMMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSkeletal muscle mass index\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\u003eThis study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Erciyes University Faculty of Medicine (decision number 2024/243). Written informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eCompeting Interests:\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch3\u003eFUNDING STATEMENT\u003c/h3\u003e\n\u003cp\u003eThis research received no external funding\u003c/p\u003e\n\u003ch3\u003eFunding:\u003c/h3\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eND: Data collection, investigation, writing-review and editing. SA: Conceptualization, methodology, investigation, writing-original draft, supervision. GZ: Statistical analysis, methodology, writing-review and editing. SIYТ: Data collection, investigation, writing-review and editing. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgments:\u003c/h2\u003e\n\u003cp\u003eThe authors would like to thank the healthcare professionals and administrative staff of the Erciyes University Department of Geriatrics for their valuable support during data collection and patient follow-up.\u003c/p\u003e\n\u003ch2\u003eAvailability of Data and Materials:\u003c/h2\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCruz-Jentoft AJ, Bahat G, Bauer J et al (2019) Sarcopenia: revised European consensus on definition and diagnosis. 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Clin Nutr 35:1557\u0026ndash;1563. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.clnu.2016.02.002\u003c/span\u003e\u003cspan address=\"10.1016/j.clnu.2016.02.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBahat G, Kilic C, Eris S et al (2020) Cut-off points for height, weight and body mass index adjusted bioimpedance analysis measurements of muscle mass with use of different threshold definitions. 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Clin Nutr 40:4386\u0026ndash;4393. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.clnu.2020.12.043\u003c/span\u003e\u003cspan address=\"10.1016/j.clnu.2020.12.043\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang YC, Chen SL, Dong Y, Shi Y (2023) Association between elevated serum uric acid levels and high estimated glomerular filtration rate with reduced risk of low muscle strength in older people: a retrospective cohort study. BMC Geriatr 23(1):652. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12877-023-04374-3\u003c/span\u003e\u003cspan address=\"10.1186/s12877-023-04374-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMacchi C, Molino-Lova R, Polcaro P et al (2008) Higher circulating levels of uric acid are prospectively associated with better muscle function in older persons. Mech Ageing Dev 129:522\u0026ndash;527. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.mad.2008.04.008\u003c/span\u003e\u003cspan address=\"10.1016/j.mad.2008.04.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuh CH (2023) Inverse correlation of serum uric acid and relative hand grip strength in Korean adult women. Osteoporos Sarcopenia 9:42. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.afos.2023.03.002\u003c/span\u003e\u003cspan address=\"10.1016/j.afos.2023.03.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYi D, Khang AR, Lee HW et al (2023) Reply on Inverse correlation of serum uric acid and relative hand grip strength in Korean adult women. Osteoporos Sarcopenia 9:43. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.afos.2023.03.005\u003c/span\u003e\u003cspan address=\"10.1016/j.afos.2023.03.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKawamoto R, Ninomiya D, Kasai Y et al (2016) Serum uric acid is positively associated with handgrip strength among Japanese community-dwelling elderly women. PLoS ONE 11:e0151044. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0151044\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0151044\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Characteristics of subjects by gender.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"107%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en=910\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en=609\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en=301\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eAge, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e71 (66-76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e71 (66-76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e72 (67-78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003e\u0026lt;74\u003c/p\u003e\n \u003cp\u003e\u0026gt;75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e604 (66.4)\u003c/p\u003e\n \u003cp\u003e306 (33.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e420 (70)\u003c/p\u003e\n \u003cp\u003e189 (61.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e184 (30)\u003c/p\u003e\n \u003cp\u003e117 (38.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eMarital status n(%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Single\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Married\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Widow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e18 (2)\u003c/p\u003e\n \u003cp\u003e612 (67.3)\u003c/p\u003e\n \u003cp\u003e280 (30.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e11 (61.2)\u003c/p\u003e\n \u003cp\u003e345 (56.4)\u003c/p\u003e\n \u003cp\u003e253 (90.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7 (38.8)\u003c/p\u003e\n \u003cp\u003e267 (43.6)\u003c/p\u003e\n \u003cp\u003e27 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eIncome n(%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Good\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Middle\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Bad\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e110 (12.1)\u003c/p\u003e\n \u003cp\u003e700 (77)\u003c/p\u003e\n \u003cp\u003e100 (10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e72 (65.5)\u003c/p\u003e\n \u003cp\u003e469 (67)\u003c/p\u003e\n \u003cp\u003e68 (68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e38 (34.5)\u003c/p\u003e\n \u003cp\u003e231 (33)\u003c/p\u003e\n \u003cp\u003e32 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e0.922\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eHeight, cm, medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e156 ( 151-163)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e153 (150-157)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e165 (161-170.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eWeight, kg, medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e75.05 (66.25-85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e75.1 (65-86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e75 (68-75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e0.548\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eBMI, kg/m\u003csup\u003e2\u0026nbsp;\u003c/sup\u003emedyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e30.3 (26.33-35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e32 (27.9-36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e27.4 (24.8-30.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eWC, cm, medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e105 (95-113)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e107 (95-115)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e101 (95-108)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eHip circumference, cm, medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e110 (102-120)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e115 (106-123)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e104 (99-109)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eCC, cm, medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e37 (33-40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e37 (34-41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e35 (32.4-38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eMuscle mass, kg, medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e20.28 (17.09-25.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e18.36 (15.86-20.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e26.04 (23.48-29.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eFat-free mass, kg, medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e42 (37.4-49.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e40 (35.4-44.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e51.9 (46.9-58.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eFat mass, kg, medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e31.2( 23.1-38.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e34.9 (28.1-42.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e22.9 (18.3-27.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eTotal fat mass, % medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e43.7 (33-49.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e47 (42.7-50.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e30.6 (26.8-34.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eSkeletal muscle mass index, medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e8.33 (0.53-0.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e7.789 (6.862-8.765)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e9.585 (8.802-10.576)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003e4 m walking test, m/s, medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e0.72 (0.5-0.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e0.69 (0.5-0.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e0.8 (0.54-1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eTUG, s, medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e11.5 (9-15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e12 (9.45-15.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e10.6 (8.48-14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eHGS, kg, medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e20 (15-28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e17.4 (13-22.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e29 (22.15-35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eGFR, ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e75.84 (63-88.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e77 (63.5-89.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e75 (61.3-87.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eGlucose, mg/dL medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e108 (94-137.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e107 (93-137)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e111 (95.5-140.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eLDL, mg/dL medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e113.7 (90.7-138.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e118.4 (94.9-144.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e106.9 (82.2-127 )\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eHDL, mg/dL medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e48.4 (40.85-58.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e51.4 (43-60.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e44.5 (37.4-51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eTG, mg/dL medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e138 (102-191)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e138 (105-191)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e136.5 (95-192)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e0.195\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eAlbumin, g/dL medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e4.46 (4.26-4.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e4.44 (4.27-4.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e4.52 (4.21-4.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eCRP, mg/L medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e2.9 (1.41-6.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e3.01 (1.47-6.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e2.64 (1.26-8.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e0.867\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eVitamin D, ng/mL medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e19 (12.45-28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e19 (11.9-29.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e19.55 (14.08-26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e0.438\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eUric acid, mg/dL medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e5.2 (4.27-6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e5 (4.1-6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e5.5 (4.75-6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eHyperuricemia, n (%)\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e213 (23.4)\u003c/p\u003e\n \u003cp\u003e697 (76.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e156 (73.2)\u003c/p\u003e\n \u003cp\u003e453 (65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e57 (26.8)\u003c/p\u003e\n \u003cp\u003e244 (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.025\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eHypertension, n (%)\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e617 (67.8)\u003c/p\u003e\n \u003cp\u003e293 (32.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e446 (72.3)\u003c/p\u003e\n \u003cp\u003e163 (55.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e171 (27.7)\u003c/p\u003e\n \u003cp\u003e130 (44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eCKD, n (%)\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e193 (21.2)\u003c/p\u003e\n \u003cp\u003e717 ( 78.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e120 (67.2)\u003c/p\u003e\n \u003cp\u003e489 (68.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e73 (37.8)\u003c/p\u003e\n \u003cp\u003e228 (31.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eDiabetes, n (%)\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e437 (48)\u003c/p\u003e\n \u003cp\u003e473 (52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e301 (68.9)\u003c/p\u003e\n \u003cp\u003e308 (65.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e136 (31.1)\u003c/p\u003e\n \u003cp\u003e165 (34.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e0.228\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eStoke history, n (%)\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e32 (3.5)\u003c/p\u003e\n \u003cp\u003e878 (96.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e19 (59.4)\u003c/p\u003e\n \u003cp\u003e590 (67.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e13 (40.6)\u003c/p\u003e\n \u003cp\u003e288 (32.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e0.356\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eCHD, n(%)\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e183 (20.1)\u003c/p\u003e\n \u003cp\u003e727 (79.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e113 (61.7)\u003c/p\u003e\n \u003cp\u003e496 (68.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e70 (38.5)\u003c/p\u003e\n \u003cp\u003e231 (31.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eSBP, mmHg, medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e130 (120-140)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e130 (120-140)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e130 (120-140)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e0.307\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eDBP, mmHg, medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e80 (70-85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e80 (70-85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e80 (70-85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e0.334\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eADL, dependent n(%)\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e524 (57.6)\u003c/p\u003e\n \u003cp\u003e386 (42.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e341 (65.1)\u003c/p\u003e\n \u003cp\u003e268 (69.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e183 (34.9)\u003c/p\u003e\n \u003cp\u003e118 (30.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e0.168\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eIADL, dependent n(%)\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e582 (64)\u003c/p\u003e\n \u003cp\u003e328 (36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e388 (66.7)\u003c/p\u003e\n \u003cp\u003e221 (67.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e194 (33.3)\u003c/p\u003e\n \u003cp\u003e107 (32.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e0.827\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eDepressive mood, n(%)\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e391 (43)\u003c/p\u003e\n \u003cp\u003e519 (57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e307 (78.5)\u003c/p\u003e\n \u003cp\u003e302 (58.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e84 (21.5)\u003c/p\u003e\n \u003cp\u003e217 (41.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eCognitive impairment, n(%)\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e176 (19.6)\u003c/p\u003e\n \u003cp\u003e725 (80.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e120 (68.2)\u003c/p\u003e\n \u003cp\u003e481 (66.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e56 (31.9)\u003c/p\u003e\n \u003cp\u003e244 (33.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e0.643\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eSarcopenia, n(%)\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e764 (84)\u003c/p\u003e\n \u003cp\u003e146 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e561 (73.4)\u003c/p\u003e\n \u003cp\u003e48 (32.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e203 (26.6)\u003c/p\u003e\n \u003cp\u003e98 (67.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eMalnutrition, n(%)\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e477 (53.5)\u003c/p\u003e\n \u003cp\u003e415 (46.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e338 (70.9)\u003c/p\u003e\n \u003cp\u003e263 (63.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e139 (29.1)\u003c/p\u003e\n \u003cp\u003e152 (36.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003ePolypharmacy, n(%)\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e463 (50.9)\u003c/p\u003e\n \u003cp\u003e447 (49.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e331 (71.5)\u003c/p\u003e\n \u003cp\u003e278 (62.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e132 (28.5)\u003c/p\u003e\n \u003cp\u003e169 (37.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eFrailty, n(%)\u003c/p\u003e\n \u003cp\u003eNon-frail\u003c/p\u003e\n \u003cp\u003ePre-frail\u003c/p\u003e\n \u003cp\u003eFrail\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e150 (16.5)\u003c/p\u003e\n \u003cp\u003e475 (52.2)\u003c/p\u003e\n \u003cp\u003e285 (31.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e66 (44)\u003c/p\u003e\n \u003cp\u003e337 (71)\u003c/p\u003e\n \u003cp\u003e206 (72.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e84 (56)\u003c/p\u003e\n \u003cp\u003e138 (29)\u003c/p\u003e\n \u003cp\u003e79 (27.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eMortality, n(%)\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e103 (11.3)\u003c/p\u003e\n \u003cp\u003e807 (88.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e40 (38.8)\u003c/p\u003e\n \u003cp\u003e569 (70.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e63 (61.2)\u003c/p\u003e\n \u003cp\u003e238 (29.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.2371%;\"\u003e\n \u003cp\u003eNumber of drugs, medyan (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.4639%;\"\u003e\n \u003cp\u003e4 (2-6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5567%;\"\u003e\n \u003cp\u003e4(2-6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.4021%;\"\u003e\n \u003cp\u003e3 (1-5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3402%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eBMI: body mass index; TUG: Timed Up and Go test; LDL: low-density lipoprotein; HDL: high-density lipoprotein; TG: triglyceride; CRP: C-reactive protein; CKD: Chronic kidney disease; CHD: coronary heart disease; ADL: activities of daily living; IADL: instrumental activities of daily living. SBP: Systolic blood pressure; DBP: Diastolic blood pressure. CC:Calf circumference. Statistically significant \u003cem\u003ep\u0026nbsp;\u003c/em\u003evalues are shown in bold.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Univariate Cox regression analyses of overall survival among female participants.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 44px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate Cox\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR (95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep-\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003evalue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eAge, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.11(1.07-1.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Single\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e0.54(0.28-1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eIncome\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; High\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Middle\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e2.66(0.64-11.09)\u003c/p\u003e\n \u003cp\u003e4.13(0.86-19.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e0.181\u003c/p\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eHeight (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.90(0.86-0.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eWeight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.97(0.95-0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.97(0.93-1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.318\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eWaist circumference (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.99(0.97-1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.915\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eHip circumference (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.98(0.97-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.294\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eCalf circumference (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.96(0.91-1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.212\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eMuscle mass (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.88(0.80-0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eFat-free mass (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.92(0.88-0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eFat mass (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.99(0.96-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.306\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eTotal fat mass, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.04(0.99-1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.132\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eSkeletal muscle mass index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.85(0.69-1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.119\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e4 m walking test (m/s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.35(0.09-1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eTUG, s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.06(1.02-1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eHGS (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.94(0.89-0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eHGS (kg),\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; High (females \u0026gt;22 kg, males \u0026gt;36 kg)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Low \u0026nbsp; \u0026nbsp; (females\u0026le;22 kg, males\u0026le;36 kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e1.79(0.82-3.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e0.142\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eGFR (ml/min/1.73) m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.97(0.96-0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eGlucose (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.00(0.99-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.514\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eLDL cholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.99(0.98-1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.028\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eHDL cholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.96(0.94-0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eTG (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.00(0.99-1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.848\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eAlbumin (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.09(0.04-0.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eCRP (mg/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.01(1.00-1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eVitamin D (ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.97(0.94-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.108\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eUric acid (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.29(1.11-1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eUric acid (Quartile)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 1.Quartile\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 2.Quartile\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 3.Quartile\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 4.Quartile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e0.71(0.23-2.25)\u003c/p\u003e\n \u003cp\u003e0.96(0.34-2.74)\u003c/p\u003e\n \u003cp\u003e3.08(1.31-7.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e0.563\u003c/p\u003e\n \u003cp\u003e0.938\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eHyperuricemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e3.46(1.86-6.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.80(0.79-4.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.159\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eCKD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e4.51(2.43-8.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eDiabetes mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.81(0.44-1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.508\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eStoke history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e2.76(0.98-7.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eCHD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e2.01(1.02-3.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.044\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eSystolic blood pressure (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.99(0.98-1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.821\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eDiastolic blood pressure (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.99(0.95-1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.518\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eADL, dependent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.94(0.83-4.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eIADL, dependent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.54(0.67-3.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.315\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eDepressive mood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.31(0.70-2.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.393\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eCognitive impairment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e2.08(1.07-4.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.032\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eSarcopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e3.19(0.44-23.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.252\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eMalnutrition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e2.67(1.22-5.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003ePolypharmacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.83(0.94-3.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eFrailty\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Non-frail\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Pre-frail\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Frail\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e1.49(0.34-6.51)\u003c/p\u003e\n \u003cp\u003e4.10(0.97-17.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e0.597\u003c/p\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eNumber of drugs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.06(0.96-1.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.263\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eBMI: body mass index; TUG: Timed Up and Go test; \u0026nbsp; LDL: low-density lipoprotein; HDL: high-density lipoprotein; TG: triglyceride; CRP: C-reactive protein; CKD: Chronic kidney disease; CHD: coronary heart disease; ADL: activities of daily living; IADL: instrumental activities of daily living. Statistically significant \u003cem\u003ep\u0026nbsp;\u003c/em\u003evalues are shown in bold.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Univariate Cox regression analyses of overall survival among male participants.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate Cox\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHR (%95CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep-\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003evalue\u003csup\u003e*\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eAge, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.07(1.04-1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Single\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e0.82(0.39-1.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e0.605\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eIncome\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; High\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Middle\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e0.77(0.40-1.48)\u003c/p\u003e\n \u003cp\u003e0.75(0.28-2.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e0.430\u003c/p\u003e\n \u003cp\u003e0.575\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eHeight (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.99(0.96-1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.391\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eWeight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.98(0.96-1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.025\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.96(0.91-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eWC (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.99(0.97-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.247\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eHip circumference (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.98(0.96-0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eCC (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.96(0.92-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.130\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eMuscle mass (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.95(0.90-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eFat-free mass (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.96(0.94-0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eFat mass (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.00(0.96-1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.819\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eTotal fat mass, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.04(1.00-1.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.048\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eSkeletal muscle mass index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.85(0.72-1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e4 m walking test (m/s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.53(0.23-1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.140\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eTUG, s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.06(1.03-1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eHGS (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.97(0.94-0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eHGS (kg),\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; High (females \u0026gt;22 kg, males \u0026gt;36 kg)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Low \u0026nbsp; \u0026nbsp; (females\u0026le;22 kg, males \u0026le;36 kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e1.57(0.80-3.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e0.192\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eGFR (ml/min/1.73) m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.98(0.97-0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eGlucose (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.00(0.99-1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.666\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eLDL (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.99(0.98-1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.027\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eHDL (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.00(0.98-1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.881\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eTG (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.99(0.99-1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eAlbumin (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.21(0.14-0.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eCRP (mg/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.01(1.00-1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.030\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eVitamin D (ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.01(0.99-1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.342\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eUric acid (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.09(0.94-1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.268\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eUric acid (Quartile)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 1.Quartile\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 2.Quartile\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 3.Quartile\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; 4.Quartile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e0.82(0.42-1.61)\u003c/p\u003e\n \u003cp\u003e0.47(0.20-1.08)\u003c/p\u003e\n \u003cp\u003e1.40(0.74-2.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e0.566\u003c/p\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003cp\u003e0.301\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eHyperuricemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.72(0.99-3.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.28(0.77-2.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.336\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eCKD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e2.12(1.26-3.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eDiabetes mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.84(0.51-1.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.497\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eStoke history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.75(0.24-2.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.627\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eCHD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.70(1.01-2.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.044\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eSBP (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e0.99(0.97-1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.380\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eDBP (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.02(0.99-1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eADL, dependent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e2.38(1.00-5.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.050\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eIADL, dependent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e2.24(0.95-5.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eDepressive mood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e2.03(1.23-3.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eCognitive impairment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e2.22(1.31-3.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eSarcopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.13(0.64-1.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.678\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eMalnutrition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e2.15(1.28-3.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003ePolypharmacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.22(0.74-2.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.435\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eFrailty\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Non-frail\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Pre-frail\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Frail\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003cp\u003e1.83(0.86-3.88)\u003c/p\u003e\n \u003cp\u003e3.48(1.63-7.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e0.115\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNumber of drugs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 26px;\"\u003e\n \u003cp\u003e1.05(0.97-1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.258\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eBMI: body mass index; LDL: low-density lipoprotein; HDL: high-density lipoprotein; TG: triglyceride; CRP: C-reactive protein; CKD: Chronic kidney disease; CHD: coronary heart disease; ADL: activities of daily living; IADL: instrumental activities of daily living. Statistically significant \u003cem\u003ep\u003c/em\u003e values are shown in bold.\u003c/strong\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Uric acid, Handgrip strength, Mortality, Sarcopenia, Sex differences, Older adults","lastPublishedDoi":"10.21203/rs.3.rs-6913893/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6913893/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eSarcopenia and hyperuricemia correlate with negative outcomes in older adults, including increased mortality. While diminished muscle strength predicts functional deterioration and mortality, elevated serum uric acid's prognostic value remains controversial. This study investigated individual and combined effects of reduced handgrip strength and hyperuricemia on all-cause mortality, focusing on sex-specific differences.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective cohort study evaluated 910 individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years between 2020\u0026ndash;2024 at a university hospital. Participants with confounding conditions or interfering medications were excluded. Uric acid was quantified enzymatically and classified into quartiles. Sarcopenia was defined using EWGSOP2 criteria, including handgrip strength and skeletal muscle mass index from bioelectrical impedance analysis. Cox regression and Kaplan-Meier analyses assessed mortality risk.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe mean age was 71 years, with 66.9% of participants being female. Reduced handgrip strength and elevated UA levels were correlated with detrimental metabolic indicators. Univariate analysis indicated that both low handgrip strength (HR: 1.91, 95% CI: 1.15\u0026ndash;3.18) and the highest quartile of uric acid (UA) levels (HR: 1.86, 95% CI: 1.13\u0026ndash;3.08) were significant predictors of mortality. Nevertheless, these correlations diminished following multivariable correction. Sex-stratified studies indicated that hyperuricemia persisted as an independent predictor for mortality in females (HR: 3.08; 95% CI: 1.31\u0026ndash;7.26; p\u0026thinsp;=\u0026thinsp;0.010).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eBoth diminished grip strength and elevated uric acid levels are associated with increased mortality in older adults, particularly among females. Routine incorporation of sex-specific metabolic and physical performance assessments may enhance risk stratification strategies in geriatric populations.\u003c/p\u003e","manuscriptTitle":"Uric Acid and Grip Strength as Predictors of Mortality in Older Adults: A Sex-Stratified Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-25 07:21:10","doi":"10.21203/rs.3.rs-6913893/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":"cc2993d1-6fb9-405a-afae-eb7e5bcf5df5","owner":[],"postedDate":"June 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-29T09:23:29+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-25 07:21:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6913893","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6913893","identity":"rs-6913893","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}