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Lee, Heo, and Park: Association between extracellular-to-intracellular water ratio and type 2 diabetes mellitus in Korean males aged 19-80 years: analysis of KNHANES 2022-2023

Abstract

[Purpose]

The extracellular-to-intracellular water (ECW/ICW) ratio is a known indicator of metabolic health; however, few studies have examined its association with type 2 diabetes mellitus (T2DM). This study investigated the relationship between the ECW/ICW ratio and T2DM prevalence using data from the Korea National Health and Nutrition Examination Survey (KNHANES).

[Methods]

We analyzed the data of 2,281 Korean males aged 19-80 years who participated in the 9th KNHANES (2022-2023) and had no history of kidney disease. The participants were classified as normal, prediabetic, or diabetic based on their fasting glucose levels, Hemoglobin A1c levels, and physician diagnosis. The ECW/ICW ratio was divided into tertiles. One-way analysis of variance (ANOVA) with Bonferroni post hoc tests was used to compare group differences in general and body composition characteristics. Logistic regression analyses were used to assess the association between ECW/ICW tertiles and T2DM prevalence.

[Results]

The diabetes group had significantly higher age, body mass index (BMI), waist circumference, and body fat percentage, and lower fat-free mass and grip strength than the other groups (p <.001). They had lower ICW values and higher ECW/total body water (TBW) and ECW/ICW ratios. Compared to the lowest tertile group, the middle tertile group showed a significantly higher risk of diabetes (OR = 1.661, 95% CI, 1.104-2.499), whereas the highest tertile did not reach statistical significance (OR = 1.417, 95% CI: 0.880-2.280) in the model adjusted for age, BMI, and grip strength.

[Conclusion]

This study identified a significant association between a higher ECW/ICW ratio and the prevalence of T2DM in Korean males, independent of age, BMI, and muscle strength. The ECW/ICW ratio reflects both metabolic and musculoskeletal characteristics and may be useful in describing diabetes-related body composition profiles.

INTRODUCTION

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease characterized by impaired insulin secretion. This results in sustained hyperglycemia and an increased risk of complications such as cardiovascular disease, kidney disease, and neuropathy. The global prevalence of diabetes continues to increase. For example, in Korea, the prevalence among adults aged 30 years has reached 15.5%. Males have a notably higher prevalence (18.1%) than females (13.0) [1]. Furthermore, the prevalence of prediabetes among individuals in their 30s was 29.3%, which increased sharply with advancing age. As diabetes may become a leading cause of mortality if left undiagnosed or unmanaged, early identification and management of at-risk populations are essential for effective prevention and control [2].
Individuals with diabetes often experience an imbalance in body water distribution [3]. Skeletal muscle accounts for approximately 75% of total body water (TBW), consisting of intracellular water (ICW) and extracellular water (ECW) [4]. Healthy adults normally maintain a ratio of approximately 62% to 38%. However, patients with diabetes tend to show an increase in ECW and a decrease in ICW because of osmotic changes caused by hyperglycemia [5]. Recent studies have shown that individuals with diabetes have significantly higher ECW/ICW and ECW/TBW ratios than those without diabetes [6]. This study compared fluid composition using bioelectrical impedance analysis (BIA) in 36 Korean patients with T2DM and 21 healthy controls [6]. The results showed that the ECW/ICW ratios were significantly higher in the T2DM group than those in the control group, confirming the changes in fluid composition in patients with T2DM. This suggests that the ECW/ICW ratio may be an important indicator of impaired cellular function and decreased cell mass [7]. These findings suggest that fluid imbalance in patients with diabetes is associated with impaired kidney function and the deterioration of metabolic health. However, this study had a small sample size and a cross-sectional design, which limits its generalizability to a broader population.
T2DM is strongly associated with reduced skeletal muscle function and altered body composition [8]. Skeletal muscle, a key insulin-sensitive tissue, plays a vital role in glucose metabolism [9,10]. Chronic hyperglycemia and insulin resistance in diabetes lead to increased protein degradation, decreased GLUT4 expression, impaired glucose uptake, and worsened insulin sensitivity [11]. We hypothesized that individuals with a higher ECW/ICW ratio would have a significantly higher prevalence of T2DM, reflecting potential fluid imbalance and metabolic dysfunction.
To further explore the physiological relevance of body composition in T2DM, this study used data from the 9th Korea National Health and Nutrition Examination Survey (KNHANES; 2022-2023) to analyze the association between the ECW/ICW and the prevalence of T2DM.

METHODS

Sample and design

This study used cross-sectional data from the first and second years (2022-2023) of the 9th KNHANES conducted by the Korea Disease Control and Prevention Agency (KDCA). The KNHANES is a nationally representative survey that is updated every three years and includes a health interview, health examination, and nutrition survey. All survey procedures were conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of the KDCA (approval number: 2022-11-02-PE-A). All participants provided written informed consent before participation. The study design and data resource profiles followed the methods described in the Guidelines for Use of KNHANES Raw Data and the final report of the sampling framework [12].
A total of 13,194 individuals participated in the KNHANES during the 2022-2023 cycle. Among them, male adults aged 19-80 years who underwent body composition assessments using bioelectrical impedance analysis (BIA) and had no self-reported or physician-diagnosed renal diseases were initially selected. Participants with missing data on key variables, including fasting blood glucose, hemoglobin A1c (HbA1c), handgrip strength, and body composition indicators, were excluded. The final sample comprised 2,281 males.
Participants were classified into three groups based on fasting plasma glucose and HbA1c levels and physician diagnosis of diabetes, according to the diagnostic criteria of the American Diabetes Association: normal (n = 997), prediabetes (n = 827), and diabetes (n = 457).

Measurements

Since the beginning of its ninth term in 2022, the KNHANES has conducted all health screenings using mobile examination units. These screenings involved standardized procedures, including direct anthropometric measurements and biological sample analyses. In this study, body composition was assessed using physical measurements, such as height and weight, as well as data obtained from body composition analysis. Muscle strength was evaluated using the handgrip strength test. Diabetes status was classified based on fasting blood glucose levels, HbA1c levels, and physician diagnosis according to established diagnostic criteria (Figure 1).

Body composition

Body composition was assessed using BIA with an In-Body 970 device (InBody Co., Ltd., Seoul, Korea). Body weight, BMI, fat free mass (FFM), body fat mass, body fat percentage, TBW, ICW, and ECW were measured. ECW/TBW and ECW/ICW ratios were calculated.

Handgrip strength

Handgrip strength was measured using a digital handgrip dynamometer (model TKK 5401; Takei Scientific Instruments Co., Ltd., Niigata, Japan). Two measurements were taken for each hand, and the highest value was used for the analysis. Participants with missing or paralyzed arms, hands, or thumbs; those wearing casts; and those who had experienced hand pain, numbness, or stiffness within the past seven days were excluded from the measurement.

Classification of diabetes status

We defined diabetes as having at least one of the following: fasting blood glucose level of at least 126 mg/dL, HbA1c level of at least 6.5%, or a physician’s diagnosis of diabetes. Prediabetes was defined as a fasting blood glucose level of 100-125 mg/dL or an HbA1c level of 5.7% and 6.4%. Patients who did not meet any of these criteria were classified as normal.
HbA1c was measured using high-performance liquid chromatography, a method widely adopted internationally owing to its accuracy and precision in quantifying glycated hemoglobin. The analysis was conducted with the HLC-723G11 system (Tosoh, Japan) using specific reagents, including G11 Elution Buffer HSi No.1, HSi No.2, HSi No.3, and HSi Hemolysis & Wash Solution, all manufactured by Tosoh. The reportable range for HbA1c was 2.6-19.2%, with a lower limit of detection (LOD) of 2.6%. Whole blood treated with ethylenediaminetetraacetic acid (EDTA) was used as the sample type, which was refrigerated and transported to the designated laboratory for analysis.
Fasting blood glucose was measured using the hexokinase ultraviolet assay, a standardized biochemical method that enables accurate and reliable quantification of serum glucose concentration. A Cobas 8000 automated analyzer (Roche, Germany) was used for this purpose, along with Glucose HK Gen.3 reagents from the same manufacturer. The reportable range of the assay was 2-1500 mg/dL, and the LOD was 2 mg/dL. Blood samples were collected after at least 8 h of fasting, and the serum was refrigerated and delivered to the testing facility for analysis.

Statistical analysis

Statistical analyses were conducted using IBM SPSS Statistics for Windows, version 23.0 (IBM Corp., Armonk, NY, USA), which accommodates a complex sample design. Variables are reported as mean ± standard error. Correlation analyses were conducted to examine the relationship between body water composition and diabetes-related variables. Pearson’s correlation was used for associations between continuous variables, whereas Spearman’s rank correlation was used for ordinal variables. One-way analysis of variance (ANOVA) and Bonferroni post-hoc tests were used to compare groups. The ECW/ICW ratio was divided into tertiles, and logistic regression analysis was performed to evaluate its association with type 2 diabetes. The analysis was adjusted for age, BMI, and handgrip strength. Statistical significance was set at p <0.05.

RESULTS

General characteristics of participants

The general characteristics of the participants are listed in Table 1. Compared to the normal and prediabetes groups, the diabetes group had a significantly higher mean age (62.6 ± 0.82 years), BMI (25.6 ± 0.23 kg/m²), waist circumference (WC) (93.0 ± 0.56 cm), and body fat percentage (27.3 ± 0.33%) (p <0.05). Meanwhile, height (168.7 ± 0.32 cm) and fat-free mass (52.8 ± 0.46 kg) were significantly lower. Statistically significant differences were observed among the groups for all variables except weight (p <0.05).

Differences in handgrip strength and body water composition according to diabetes status

Differences in handgrip strength and body water indices among the study participants are provided in Table 2. The diabetes group had significantly lower handgrip strength (37.4 ± 0.46 kg), total body water (38.9 ± 0.34 L), and ICW (24.0 ± 0.22 L) than the normal and prediabetes groups. Meanwhile, ECW/TBW (0.383 ± 0.0005) and ECW/ICW (0.622 ± 0.0012) in the diabetes group were significantly higher than those in the normal and prediabetes groups (p <0.05). Significant differences in extracellular water were observed among some variables between the groups; however, no statistically significant differences were observed between the diabetic and prediabetic groups.

Correlation between the body water composition and diabetes-related indicators

Correlation analysis revealed that the ECW/ICW ratio was significantly associated with diabetes-related and physiological variables. The ratio showed a strong positive correlation with age (r = 0.706; p <0.01) and moderate negative correlations with BMI (r = -0.228; p <0.01) and FFM (r = -0.432; p <0.01).
For metabolic markers, the ratio demonstrated positive correlations with fasting blood glucose (r = 0.150, p <0.01), HbA1c (r = 0.221, p <0.01), and diabetes prevalence (r = 0.263, p <0.01). Furthermore, fasting blood glucose was positively associated with age (r = 0.206, p <0.01) and BMI (r = 0.091, p <0.01) and negatively associated with FFM (r = -0.044, p <0.05). HbA1c was positively correlated with age (r = 0.283, p <0.01) and BMI (r = 0.093, p <0.01) and negatively correlated with FFM (r = -0.074, p <0.01). Diabetes prevalence was most strongly associated with age (r = 0.336, p <0.01), followed by BMI (r = 0.128, p <0.01), and was negatively associated with FFM (r = -0.094, p <0.01).

Differences in body composition and diabetes-related indicators according to ECW/ICW levels

Differences in body composition and metabolic risk factors according to the ECW/ICW ratio are provided in Table 3. The participants were categorized into three groups based on their ECW/ICW ratio tertiles: lowest (n = 760), middle (n = 759), and highest (n = 762). Significant differences were observed among the groups in terms of age, height, weight, BMI, body fat, FFM, fasting blood glucose, HbA1c, and handgrip strength (p <0.001), but not in terms of WC. The upper group was older and had lower height, weight, BMI, FFM, and handgrip strength than the lower and middle groups (p <0.001). Additionally, the upper group had significantly higher body fat, fasting blood glucose, and HbA1c levels than the lower group (p <0.001).

Association between ECW/ICW ratio and Diabetes

The prevalence of diabetes among males according to the ECW/ICW ratio tertiles is provided in Table 4. Diabetes prevalence increased across tertiles, being highest in the group with the highest ECW/ICW ratio (30.1%), followed by the middle group (20.7%) and lowest in the group with the lowest ECW/ICW ratio (9.3%), indicating a clear positive trend. In Model 1 (unadjusted), the odds of diabetes were significantly higher in both the middle group (odds ratio [OR] = 2.794, 95% confidence interval [CI] = 1.999-3.903) and the highest group (OR = 4.814, 95% CI = 3.507-6.608) compared to the lowest group. In Model 2, after adjusting for age and BMI, the middle group showed a significantly elevated risk (OR = 1.703, 95% CI = 1.133-2.559), whereas the highest group showed no statistically significant association (OR = 1.536, 95% CI = 0.962-2.454). In Model 3, with additional adjustment for handgrip strength, the middle group maintained a significant association (OR = 1.661, 95% CI = 1.104-2.499), whereas the highest group showed a non-significant association (OR = 1.417, 95% CI = 0.880-2.280).

DISCUSSION

Based on data from the 9th KNHANES (2022-2023), this study investigated the association between the ECW/ICW ratio and the prevalence of T2DM in Korean males aged 19-80 years without kidney disease. In the unadjusted model (Model 1), individuals in the middle and highest tertiles of the ECW/ICW ratio had approximately 2.8-fold and 4.8-fold higher odds of developing T2DM, respectively, compared to those in the lowest tertile. After adjusting for age, BMI, and handgrip strength, individuals in the middle tertile still exhibited more than approximately 1.7 times the odds of diabetes relative to those in the lowest tertile, highlighting the potential relevance of altered body fluid distribution in the development of T2DM.
Analysis of general characteristics by diabetes status revealed that individuals with diabetes were older and had a higher BMI, waist circumference, and body fat percentage. They had lower FFM than those in the normal and prediabetic groups. Age increased as the disease progressed, and decreased FFM suggested a possible association with reduced muscle function. These results indicate that demographic and physical characteristics can be clearly distinguished according to the diabetes status. An increase in body fat percentage leads to higher insulin resistance and inflammatory responses, thereby negatively affecting blood glucose control [13], and the current findings are consistent with this findings.
Handgrip strength was significantly lower in individuals with diabetes than in those without. This finding is consistent with previous studies, including those by Cho et al. [14], who reported a higher risk of T2DM in groups with lower grip strength, and Li et al. [15], who reported a reduced risk of diabetes in those with higher muscle strength. Kunutsor et al. [16] reported similar findings in the general population. Skeletal muscle plays a major role in glucose metabolism [10], and reduced GLUT4 expression in skeletal muscle is associated with impaired glucose transport [11].
In terms of body water composition, individuals with diabetes had significantly lower TBW and ICW and a higher ECW/ICW ratio. These findings suggest that an altered fluid distribution, as reflected by a higher ECW/ICW ratio, may be associated with metabolic dysfunction. Our results are consistent with those of earlier studies, including one comparing 36 Korean T2DM patients and 21 healthy controls, in which a significantly elevated ECW/ICW ratio was observed in the T2DM group [5]. Another study on 321 Korean patients with T2DM showed that the phase angle was negatively correlated with both glycemic indicators and the ECW/ICW ratio [6].
Previous studies have linked fluid distribution to muscle function. For example, Taniguchi et al. [3] reported a negative correlation between the ECW/ICW ratio and grip strength in older Japanese females, whereas Hioaka et al. [9] reported that higher ECW/ICW ratios were associated with reduced muscle strength and slower walking speed. Although these studies focused on female populations, the current study observed similar patterns in males, demonstrating that higher ECW/ICW ratios were associated with lower fat-free mass and reduced grip strength.
Based on the current analysis, the correlation analysis revealed that both ECW/ICW were positively associated with age and diabetes-related markers and diabetes prevalence. In contrast, these ratios were negatively associated with body composition indicators such as BMI and FFM. In addition, fasting blood glucose and HbA1c levels were negatively associated with FFM. These findings indicate that, in this study, fluid distribution ratios showed weak but consistent associations with age, body composition, and diabetes-related parameters.
Although both ECW/ICW and ECW/TBW ratios were associated with the prevalence of diabetes in the current dataset, the analysis primarily focused on the ECW/ICW ratio. This decision was based on the observation that the tertile classifications of ECW/ICW and ECW/TBW were identical, rendering separate analyses using ECW/TBW statistically redundant within the current framework. Moreover, the ECW/ICW ratio offers a more refined reflection of cellular-level fluid shifts, particularly in skeletal muscles, and has been strongly linked to muscle mass, muscle strength, and metabolic health in previous studies [11,17]. Although ECW/TBW is a well-established indicator of systemic fluid imbalance and is commonly used to detect generalized edema or dehydration, it has a distinct clinical role [10,18]. Therefore, although ECW/TBW-specific results were not included in this analysis, their exclusion was acknowledged as a limitation. Future studies should incorporate both indices to comprehensively evaluate alterations in body fluid distribution and their potential metabolic implications.
In this study, the prevalence of diabetes increased across the ECW/ICW tertiles, with the highest prevalence observed in the highest tertile group. In the unadjusted analyses, both the middle and highest tertiles had significantly higher odds of developing diabetes than the lowest tertile. However, after adjusting for age, BMI, and handgrip strength, only the middle tertiles remained significant. This attenuation in the highest tertile may be explained by the group’s demographic and physiological characteristics, namely, older age, lower muscle mass, and reduced muscle strength, which are associated with higher ECW/ICW ratios and increased diabetes risk. These overlapping risk factors may have confounded the direct relationship between ECW/ICW and diabetes in this group. Previous research has demonstrated that the ECW/ICW ratio increases with age, largely due to a disproportionate decline in intracellular water [19,20], with more pronounced shifts observed beyond the ages of 40-50 years, accelerating over the past 70 years [19]. By contrast, individuals in the middle tertile were relatively younger and showed moderately elevated ECW/ICW ratios without substantial muscle deterioration. The persistence of a significant association between ECW/ICW and diabetes in this group, even after adjusting for key covariates, suggests that early-stage fluid imbalance may contribute to metabolic dysregulation, independent of advanced age or muscle loss. These findings imply that the clinical relevance of ECW/ICW may vary with age-related physiological context and underscore the potential value of this marker in detecting early metabolic alterations.
This study utilized nationally representative data from Korean males aged 19-80 years and observed that a higher ECW/ICW ratio was associated with older age, lower body fat mass, reduced grip strength, and a higher prevalence of T2DM. Although previous studies have investigated these factors separately, few have examined their interrelationships. By classifying the participants into ECW/ICW tertiles, this study identified a stepwise increase in the prevalence of diabetes corresponding to higher fluid imbalance levels, a pattern that may not have been captured using dichotomous or linear models.
This study has certain limitations. First, its cross-sectional design precludes causal inferences. Second, the sample was limited to Korean males, which may limit the generalizability of our findings. Third, although BIA is a practical and widely used method for assessing body composition and fluid status, it may lack the accuracy of more sophisticated techniques such as dual-energy X-ray absorptiometry (DEXA).
In conclusion, this study observed that a higher ECW/ICW ratio was significantly associated with an increased prevalence of T2DM among Korean males, independent of age, BMI, and muscle strength. These findings suggest that the ECW/ICW ratio may serve as a non-invasive marker of both metabolic and musculoskeletal health. Given its simplicity and accessibility via BIA, this measure can be incorporated into routine screening to identify individuals at a higher risk of diabetes. Future longitudinal studies are warranted to clarify causal pathways and evaluate the utility of fluid distribution metrics in predicting diabetes progression and related complications.

Acknowledgments

This study was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2024S1A5A2A01023585).
The authors declare that they have no financial, consulting, institutional, or other relationships that may lead to bias or conflicts of interest.

Figure 1.

Flow diagram of the participant selection process.

pan-2025-0017f1.jpg
Table 1.
General characteristics by diabetes status
Normal (n = 997) Prediabetes (n = 827) Diabetes (n = 457) p value
Age (years) 43.9 ± 0.74 55.9 ± 0.82 62.6 ± 0.82a,b <.001
Height (cm) 172.4 ± 0.27 170.7 ± 0.30 168.7 ± 0.32a,b <.001
Weight (kg) 72.4 ± 0.53 74.0 ± 0.51 73.3 ± 0.81 0.708
BMI (kg/m²) 24.3 ± 0.15 25.3 ± 0.13 25.6 ± 0.23a <.001
WC (cm) 86.0 ± 0.39 90.3 ± 0.33 93.0 ± 0.56a,b <.001
Body Fat (%) 23.6 ± 0.23 25.8 ± 0.19 27.3 ± 0.33a,b <.001
FFM (kg) 54.8 ± 0.33 54.6 ± 0.36 52.8 ± 0.46a,b <.001

Data are expressed as mean ± standard error (SE). One-way ANOVA with Bonferroni post hoc test was used. BMI = body mass index; WC = waist circumference; FFM = fat-free mass, Reference group is diabetes. Superscripts indicate significant differences vs the diabetes group:

a p <0.05 (Normal vs Diabetes),

b p <0.05 (Prediabetes vs Diabetes).

Table 2.
Differences in handgrip strength and body water composition by diabetes status
Normal (n = 997) Prediabetes (n = 827) Diabetes (n = 457) p value
Handgrip Strength (kg) 41.4 ± 0.34 40.4 ± 0.39 37.4 ± 0.46a,b <.001
TBW (L) 40.3 ± 0.24 40.1 ± 0.26 38.9 ± 0.34a,b <.001
ICW (L) 25.1 ± 0.16 24.9 ± 0.17 24.0 ± 0.22a,b <.001
ECW (L) 15.2 ± 0.09 15.2 ± 0.09 14.9 ± 0.12a .048
ECW/TBW ratio 0.377 ± 0.0003 0.380 ± 0.0004 0.383 ± 0.0005a,b <.001
ECW/ICW ratio 0.606 ± 0.0008 0.612 ± 0.0010 0.622 ± 0.0012a,b <.001

Data are reported as mean ± standard error (SE). One-way ANOVA with Bonferroni post hoc test was used. TBW = total body water; ICW = intracellular water; ECW = extracellular water, Reference group is diabetes. Superscripts indicate significant differences vs the diabetes group:

a p <0.05 (Normal vs Diabetes),

b p <0.05 (Prediabetes vs Diabetes).

Table 3.
General characteristics by ECW/ICW ratio tertile group
ECW/ICW ratio tertile
p value
Lowest Group (n = 760) Middle Group (n = 759) Highest Group (n = 762)
Age (years) 39.6 ± 0.51 54.3 ± 0.74 70.3 ± 0.50a,b <.001
Height (cm) 172.9 ± 0.28 171.2 ± 0.32 168.0 ± 0.29a,b <.001
Weight (kg) 77.1 ± 0.55 71.8 ± 0.61 67.2 ± 0.42a,b <.001
BMI (kg/m²) 25.8 ± 0.16 24.4 ± 0.17 23.8 ± 0.12a,b <.001
WC (cm) 89.2 ± 0.40 87.9 ± 0.49 88.7 ± 0.36 .097
Body Fat (%) 24.7 ± 0.24 24.7 ± 0.28 26.1 ± 0.24a,b <.001
FFM (kg) 57.7 ± 0.33 53.6 ± 0.36 49.3 ± 0.28a,b <.001
Fasting Blood Glucose (mg/dL) 98.5 ± 0.61 107.9 ± 1.20 108.8 ± 1.17a <.001
HbA1c (%) 5.41 ± 0.02 5.75 ± 0.04 5.89 ± 0.04a <.001
Handgrip Strength (kg) 43.6 ± 0.35 40.1 ± 0.34 34.3 ± 0.36a,b <.001

Data are expressed as mean ± standard error (SE). One-way analysis of variance (ANOVA) with a Bonferroni post-hoc test was used. BMI, body mass index; WC, waist circumference; FFM, fat-free mass, The reference group scored highest. Superscripts indicate significant differences vs the highest group:

a p <0.05 (Lowest group vs Highest group),

b p <0.05 (Middle group vs Highest group).

Table 4.
Association between ECW/ICW ratio tertiles and type 2 diabetes prevalence
ECW/ICW ratio tertile Diabetes (n, %) Model 1 OR (95% CI) Model 2 OR (95% CI) Model 3 OR (95% CI)
Lowest Group (n = 760) 71 (9.3%) 1.00 (ref) 1.00 (ref) 1.00 (ref)
Middle Group (n = 759) 157 (20.7%) 2.794 (1.999-3.903) 1.703 (1.133-2.559) 1.661 (1.104-2.499)
Highest Group (n = 762) 229 (30.1%) 4.814 (3.507-6.608) 1.536 (0.962-2.454) 1.417 (0.880-2.280)

Model 1: Unadjusted.

Model 2: Adjusted for age and BMI.

Model 3: Model 2 + handgrip strength.

ICW = intracellular water; ECW = extracellular water; OR = odds ratio; CI = confidence interval.

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