This cross-sectional comparative study was conducted to investigate the association between sarcopenia and heart failure (HF) phenotypes in older adults. The study was performed at a tertiary referral hospital in Makassar, Indonesia, involving both outpatient and inpatient participants. Participant recruitment began in December 2025 and continued until the required sample size was achieved in April 2026. Primary data were collected directly from eligible participants during the study period. All variables, including HF status and sarcopenia assessment, were measured concurrently at the time of enrollment.

Participants were adults aged 60 years or older. The HF group consisted of patients with a confirmed diagnosis of chronic HF, whereas the comparison group consisted of older adults without a diagnosis of HF. Consecutive sampling was used to recruit all eligible participants who attended the study site during the recruitment period until the target sample size was reached. A total of 140 participants were enrolled, including 70 participants with chronic HF and 70 participants without HF.

Participants were adults aged 60 years or older. The HF group consisted of patients with a confirmed diagnosis of chronic HF, whereas the comparison group consisted of older adults without a diagnosis of HF. Consecutive sampling was used until the target sample size was achieved. Inclusion criteria for the HF group were age 60 years or older, chronic HF diagnosed according to the 2023 Indonesian Heart Association guideline, ⁵ clinical stability, and written informed consent. The comparison group included individuals aged 60 years or older without HF. Exclusion criteria for both groups were end-stage chronic kidney disease requiring dialysis, active malignancy or ongoing antineoplastic therapy, liver cirrhosis with active decompensation, acute infection, acute decompensated HF at assessment, Diabetes melitus and clinically evident peripheral edema.

Chronic HF was diagnosed according to the 2023 guideline of the Indonesian Heart Association (PERKI) on the basis of symptoms and/or signs of HF together with objective evidence of cardiac dysfunction on echocardiography. ⁵ Only participants with established HF for at least 3 months who were clinically stable and had no evidence of peripheral edema at the time of evaluation were included. HF phenotypes were classified according to left ventricular ejection fraction (LVEF) as follows: HFrEF, LVEF ≤40%; HFmrEF, LVEF 41%–49%; HFpEF, LVEF ≥50% with echocardiographic evidence of diastolic dysfunction. ⁵

Sarcopenia was assessed according to AWGS 2019 criteria. ⁶ Muscle mass was measured using a seca mBCA 525 medical Body Composition Analyzer (seca GmbH & Co. KG, Hamburg, Germany). Participants were assessed while clinically stable and without peripheral edema to reduce fluid-related measurement bias. ASM was adjusted for height squared to calculate ASMI. Low muscle mass was defined as ASMI <7.0 kg/m2 for men and < 5.7 kg/m2 for women. Muscle strength was assessed using a Jamar hydraulic hand dynamometer (Patterson Medical/Sammons Preston, Warrenville, IL, USA). Measurements were performed with the participant seated, elbow flexed at approximately 90 degrees, and the best value from repeated attempts on the dominant hand was recorded. Low handgrip strength was defined as <28 kg for men and < 18 kg for women. Physical performance was evaluated using the five-times sit-to-stand test, with >12 seconds indicating poor performance. Sarcopenia was diagnosed when low muscle mass was accompanied by low muscle strength and/or poor physical performance. Severe sarcopenia was defined by the combined presence of low muscle mass, low muscle strength, and poor physical performance.

Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared (kg/m ²). Nutritional status was classified using the Asia-Pacific BMI criteria for Asian populations. ⁷ Participants were categorized as non-obese if their BMI was <25.0 kg/m ² and obese if their BMI was ≥25.0 kg/m ².

Age was analyzed as a categorical variable (60–69 years vs. ≥ 70 years). This cut-off was chosen to distinguish younger-old from older-old participants and to allow clinically meaningful stratification of age-related vulnerability to sarcopenia.

To reduce selection bias, consecutive sampling was applied throughout the recruitment period. To reduce measurement bias related to body fluid imbalance, only clinically stable patients with chronic HF without peripheral edema were included in the body composition assessment. Potential confounding factors were addressed by multivariable logistic regression analysis.

The minimum required sample size was calculated based on an expected odds ratio of 3.0, with 80% power and a 2-sided alpha of 0.05, yielding a minimum of 126 participants. To ensure adequate sample size, 140 participants were ultimately enrolled.

Statistical analysis

All statistical analyses were performed using IBM SPSS Statistics version 26.0 (IBM Corp., Armonk, NY, USA). Descriptive statistics were used to summarize participant characteristics. Categorical variables were presented as number (percentage). Associations between categorical variables were analyzed using the chi-square test. Multivariable logistic regression analysis was then performed to identify factors independently associated with sarcopenia, with results reported as odds ratios (ORs) and 95% confidence intervals (CIs). A 2-sided p-value <0.05 was considered statistically significant.

The participant recruitment process is shown in Figure 1, A total of 140 participants were enrolled, comprising 70 older adults with chronic heart failure (HF) and 70 without HF. The mean age of the study population was 66 ± 5 years (range, 60–86 years). Most participants were aged 60–69 years (106/140, 75.7%), while 34/140 (24.3%) were aged 70 years or older. Men accounted for 52.9% of the study population. Based on the predefined body mass index categories used in this study, 35.7% of participants were classified as obese and 64.3% as non-obese. The overall prevalence of sarcopenia was 40.0% (56/140) ( Table 1).

Sarcopenia was more prevalent among participants with chronic HF than among those without HF (58.6% vs. 21.4%; p < 0.001). Chronic HF was significantly associated with sarcopenia, with an odds ratio (OR) of 5.2 (95% confidence interval [CI], 2.47–10.90) ( Table 2).

HF phenotype was significantly associated with the presence of sarcopenia (p = 0.041). Among the HF phenotypes, the highest prevalence of sarcopenia was observed in participants with HFpEF (76.2%), followed by HFrEF (62.5%) and HFmrEF (40.0%) ( Table 2).

The distribution of sarcopenia severity did not differ significantly across HF phenotypes (p = 0.575). Severe sarcopenia was observed in 73.3% of participants with HFrEF, 70.0% of those with HFmrEF, and 56.3% of those with HFpEF. The corresponding proportions of non-severe sarcopenia were 26.7%, 30.0%, and 43.8%, respectively ( Table 3).

Sex was not significantly associated with sarcopenia (p = 0.240), although sarcopenia was more frequent in men than in women (44.6% vs. 34.8%). In contrast, age was significantly associated with sarcopenia (p = 0.003). Participants aged 70 years or older had a higher prevalence of sarcopenia than those aged 60–69 years (61.8% vs. 33.0%), with an OR of 3.3 (95% CI, 1.47–7.30). Nutritional status was also significantly associated with sarcopenia (p = 0.031). Sarcopenia was more common in non-obese participants than in obese participants (46.7% vs. 28.0%), with an OR of 2.3 (95% CI, 1.07–4.73) ( Table 4).

Multivariable logistic regression analysis including chronic HF, age, and nutritional status showed that all 3 variables were independently associated with sarcopenia. Chronic HF showed the strongest association (adjusted OR, 6.1; 95% CI, 2.70–13.73; p < 0.001), followed by non-obese status (adjusted OR, 3.3; 95% CI, 1.40–7.83; p = 0.006) and age 70 years or older (adjusted OR, 3.2; 95% CI, 1.30–7.74; p = 0.011) ( Table 5).

This study also has several limitations. First, its single-center hospital-based design may limit the generalizability of the findings to broader community-dwelling older populations. Second, cross-sectional design precludes causal inference and does not allow determination of the temporal relationship between HF and sarcopenia. Third, bioelectrical impedance analysis may be influenced by fluid status, although only clinically stable participants were included, and those with peripheral edema were excluded to reduce this potential bias. Fourth, because of the cross-sectional design, temporal and causal relationships between chronic heart failure and sarcopenia could not be determined. Finally, biomarker and longitudinal follow-up data were not available, limiting further mechanistic and prognostic interpretation. Future multicenter studies with prospective follow-up are needed to clarify the temporal relationship between HF phenotype and sarcopenia progression.