Associations Between Serum N‐Terminal Pro‐Brain Natriuretic Peptide Levels and the Prevalence of Sarcopenia in Middle‐Aged and Older Japanese Adults: A Population‐Based Cross‐Sectional Study

ABSTRACT

Aim

Evidence regarding the association between heart failure and sarcopenia in middle‐aged and older community‐dwelling adults is scarce. This study aimed to examine the association between NT‐proBNP levels and sarcopenia among community‐dwelling adults aged 40–74 years.

Methods

This cross‐sectional study was conducted based on the Circulatory Risk in Communities Study, which involved 1675 Japanese residents aged 40–74 years. Serum N‐terminal pro‐brain natriuretic peptide (NT‐proBNP) levels, physical function, and lifestyle information were measured. Participants were categorized according to their NT‐proBNP levels (< 55, 55–124, and ≥ 125 pg/mL). Multivariate‐adjusted logistic regression models were used to calculate the odds ratios for low skeletal muscle mass, muscle strength, walking speed, maximal walking speed, and sarcopenia according to serum NT‐proBNP levels.

Results

Among the analyzed participants, the prevalence was 22.6% for low skeletal muscle mass, 4.3% for low handgrip strength, 14.3% for low walking speed, 24.1% for low maximal walking speed, and 5.9% for sarcopenia. The multivariable odds ratios (95% confidence interval, p for trend) comparing the highest versus lowest groups of serum NT‐proBNP levels were 1.63 (1.07–2.49, p < 0.01) for low skeletal muscle mass, 3.38 (1.70–6.73, p < 0.01) for low handgrip strength, 1.81 (0.96–3.40, p = 0.06) for low walking speed, 1.75 (1.03–2.97, p = 0.06) for low maximal walking speed, and 2.56 (1.07–6.14, p = 0.03) for sarcopenia.

Conclusions

High serum NT‐proBNP levels, which are a surrogate marker for heart failure, were associated with low physical function and sarcopenia.

This cross‐sectional study involving 1675 Japanese community‐based residents aged 40–74 years examined the association between serum NT‐proBNP and sarcopenia. High serum NT‐proBNP levels were significantly associated with low physical function (skeletal muscle mass and muscle strength) and high prevalence of sarcopenia.

1. Introduction

Sarcopenia is a geriatric syndrome characterized by the loss of physical functions such as skeletal muscle mass, walking speed, and handgrip strength, frequently necessitating long‐term care in older individuals [1, 2]. Similarly, heart failure is a common health problem in older people with impaired heart function, resulting in inadequate oxygen supply during exercise. Given that physical inactivity is a common factor that exacerbates both conditions, sarcopenia and heart failure may be mutually associated.

N‐terminal pro‐brain natriuretic peptide (NT‐proBNP), a biomarker associated with the severity of heart failure [3], is synthesized as a prohormone of proBNP in response to ventricular volume overload. NT‐proBNP is a stable form of pro‐brain natriuretic peptide (BNP) that alleviates myocardial stress by promoting natriuretic and vasodilatory effects [4]. Serum NT‐proBNP levels are higher in cases of sarcopenia or skeletal muscle mass loss [5, 6]; therefore, NT‐proBNP is also an indicator of sarcopenia.

A recent meta‐analysis of 10 observational studies in Japan, China, France, and Brazil showed that patients older than 50 with heart failure and sarcopenia exhibited higher NT‐proBNP levels than those without sarcopenia in clinical settings [7]. However, studies of population‐based samples that include middle‐aged adults are limited.

Therefore, we hypothesized that high NT‐proBNP levels and sarcopenia might coexist in community‐dwelling individuals, including middle‐aged and older adults. This cross‐sectional study aimed to elucidate the association between serum NT‐proBNP levels and the prevalence of sarcopenia among residents aged 40–74 years.

2. Methods

2.1. Study Design and Participants

We conducted a cross‐sectional study to examine the association between serum NT‐proBNP levels and sarcopenia and its components in Japanese community‐dwelling adults aged 40–74 years. The Circulatory Risk in Communities Study (CIRCS) is an ongoing dynamic prospective cohort study involving residents of five municipalities [8]. This cross‐sectional study enrolled 1983 participants (1120 in Kyowa, Ibaraki prefecture, and 863 in Ikawa, Akita prefecture) aged between 40 and 74 years who participated in annual health check‐ups conducted in 2022. A total of 308 participants were excluded sequentially because (1) consent for serum NT‐proBNP levels measurement was not obtained (n = 108), (2) serum NT‐proBNP levels measurement was not conducted due to insufficient sample volume (n = 1), (3) consent for physical functions assessment was not obtained (n = 169), and (4) an estimated glomerular filtration rate (eGFR) was < 45 mL/min/1.73 m² (n = 30) because the serum NT‐proBNP levels were largely affected by kidney function deterioration [9]. Therefore, 1675 participants were included.

2.2. Measurements

Blood samples were collected in siliconized vacuum tubes, and the serum was separated immediately by centrifugation. Serum NT‐proBNP levels were measured using a Cobas 8000 analyzer (Roche Diagnostics Corporation, Indianapolis, IN, USA) via an electrochemiluminescence immunoassay. The lower limit of detection for serum NT‐proBNP was 5 pg/mL; values below 5 pg/mL were imputed as 2.5 pg/mL.

The skeletal muscle mass index (SMI) was measured using simultaneous multifrequency impedance measurements (InBody770, InBody, Seoul, Korea) and calculated as the appendicular skeletal muscle mass divided by the square of the height (m). Handgrip strength was measured using a Smedley‐style digital handgrip dynamometer (T.K.K.5401; Takei Scientific Instruments, Niigata, Japan). The participants were instructed to grip as hard as possible. Measurements were taken for both the left and right hands and repeated once per hand if noticeable compensatory movements were observed, such as lifting the hand, pressing the arm against the body, bending the wrist, adopting a stooped posture, or a difference of > 3 kg was noted between the hands. The highest value was used as the maximal handgrip strength. Walking speed was measured using a 6‐m walking path on a slip‐resistant mat, consisting of a 4‐m measurement zone and 2‐m deceleration zone, and a stopwatch with a built‐in printer (SVAS013, Seiko Watch Co., Tokyo, Japan) combined with infrared sensors. Both comfortable and maximum walking speeds were measured. Participants were instructed to walk through the walking path in their usual manner, as comfortably and as fast as possible at maximal walking speed. The measurements began manually as the participants started walking. The transit time at the 4‐m point was recorded automatically as each participant's leg crossed an infrared sensor set at the 4‐m point. Walking speed was calculated as the ratio of walking path length (4 m) to transit time (s).

Information on smoking status, alcohol consumption, and medication use was obtained through face‐to‐face interviews. Blood glucose levels were measured using the hexokinase assay. The creatinine levels were measured using an enzymatic method. Fasting blood glucose was defined as ≥ 8 h after a meal, and non‐fasting blood glucose was defined as < 8 h after a meal. Blood pressure was measured using an automated electronic sphygmomanometer on the right arm of the participant after at least 5 min of rest while sitting. The eGFR was calculated as follows: 194 × (serum creatinine)^−1.094 × (age)^−0.287 (× 0.739 for women) [10].

2.3. Definition of Sarcopenia

Sarcopenia diagnosis was based on the criteria of the Asian Working Group for Sarcopenia (AWGS) 2019, which includes skeletal muscle mass, muscle strength, and physical performance [11]. Following the recommendations of the AWGS 2019 criteria, we used the SMI to assess skeletal muscle mass, handgrip strength for muscle strength, and comfortable walking speed for physical function. In accordance with the AWGS 2019 criteria, low skeletal muscle mass was defined as SMI of < 7.0 kg/m² for men and < 5.7 kg/m² for women; low muscle strength as a maximal handgrip strength of < 28 kg for men and < 18 kg for women; and low physical performance as a comfortable walking speed of < 1.0 m/s for men and women. Participants were diagnosed with sarcopenia if they had low skeletal muscle mass and either low muscle strength and/or physical performance. Participants in Ikawa were excluded from the sarcopenia diagnosis due to lack of physical performance data because walking speed was not measured. In addition to the AWGS 2019 criteria, we defined a low maximal walking speed of < 1.59 m/s as an auxiliary indicator of low physical performance, independent of physical performance based on comfortable walking speed. This cut‐off value for maximal walking speed represented the 25th percentile of the study population. Notably, this evaluation of maximal walking speed was not incorporated into the sarcopenia diagnosis.

2.4. Statistical Analysis

The participants were classified into three groups based on their serum NT‐proBNP levels, with the lowest group being the reference group. The cut‐off points, 55 and 125 pg/mL, were based on the clinical criteria [12]. The participants' characteristics were compared across the serum NT‐proBNP level groups. Differences in mean values were assessed using analysis of covariance adjusted for age and sex, whereas differences in proportions were tested using the chi‐squared test. Logistic regression analysis was conducted to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) for low skeletal muscle mass (combining Kyowa and Ikawa), low muscle strength (combining Kyowa and Ikawa), low physical performance (Kyowa only), and sarcopenia (Kyowa only). In Model 1, ORs and 95% CIs were calculated and adjusted for age (continuous) and sex. In Model 2, adjustments were further made for body mass index (continuous), diabetes mellitus (fasting glucose ≥ 126 mg/dL or non‐fasting glucose ≥ 200 mg/dL and/or taking medication for diabetes mellitus), hypertension (systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥ 90 mmHg and/or taking medication for hypertension), eGFR (continuous), smoking status (never, former, current smoker of 1–19 cigarettes, or 20 or more cigarettes/day), and drinking status (never, former, current drinker of ethanol at 1–22 g, or > 23 g/day; 23 g ethanol corresponds to 1 “go,” a traditional Japanese unit of volume). A test for trend associations between serum NT‐proBNP levels and the prevalence of sarcopenia and its components was conducted using the median serum NT‐proBNP levels for each category. Statistical significance was set at p < 0.05. All analyses were performed using SAS software (version 9.4; SAS Institute, Cary, NC, USA). The authors had full access to all the data in this study and took responsibility for the integrity of the data and the accuracy of the data analysis.

3. Results

The characteristics of the study participants according to their serum NT‐proBNP levels are presented in Table 1. Participants with higher serum NT‐proBNP levels were older and had lower skeletal muscle mass and muscle strength. Fifty‐three cases of sarcopenia were identified. The prevalence of sarcopenia was progressively higher across serum NT‐proBNP levels categories, at 4.1%, 8.3%, and 11.9%, respectively.

TABLE 1.

Participants' characteristics according to serum N‐terminal pro‐brain natriuretic peptide levels.

Serum NT‐proBNP level (pg/mL)	< 55		< 125		≥ 125		p
No. of participants (No. in Kyowa)	1133	(615)	408	(218)	134	(84)
Men	505	(44.6)	121	(28.9)	55	(37.7)	< 0.001
Age (years)	60.8	(9.8)	65.6	(8.0)	67.5	(6.4)	< 0.001
Serum NT‐proBNP level a (pg/mL)	26.0	(16.0–37.0)	72.0	(62.0–90.0)	167.5	(140.0–281.0)	< 0.001
SMI (kg/m2)	6.8	(0.99)	6.5	(1.09)	6.6	(1.08)	< 0.001
Hand grip strength (kg)	32.0	(9.1)	28.2	(8.3)	28.1	(7.9)	< 0.001
Comfortable walking speed (m/s) b	1.25	(0.23)	1.24	(0.23)	1.19	(0.23)	0.26
Maximal walking speed (m/s) b	1.8	(0.30)	1.75	(0.27)	1.72	(0.27)	0.28
Sarcopenia b	25	(4.1)	18	(8.3)	10	(11.9)	0.002
Low skeletal muscle mass	216	(19.1)	119	(29.2)	41	(30.6)	< 0.001
Low muscle strength	31	(2.7)	26	(6.4)	15	(11.2)	< 0.001
Low walking speed b	82	(13.3)	33	(15.1)	16	(19.0)	0.32
Low maximal walking speed b	141	(22.9)	52	(23.9)	27	(32.1)	0.17
eGFR (mL/min/1.73 m2)	72.6	(12.5)	70.3	(12.8)	67.0	(11.0)	0.02
Diabetes mellitus
Normal	770	(68.0)	290	(71.1)	91	(67.9)	0.60
Pre‐diabetes	97	(8.6)	31	(7.6)	8	(6.0)
Diabetes mellitus	266	(23.5)	87	(21.3)	35	(26.1)
Smoking status
Non‐smoker	582	(51.4)	274	(67.2)	71	(53.0)	< 0.001
Former smoker	392	(34.6)	98	(24.0)	35	(26.1)
Current smoker (1–19 cigarettes/day)	107	(9.4)	25	(6.1)	13	(9.7)
Current smoker (≥ 20 cigarettes/day)	52	(4.6)	11	(2.7)	15	(11.2)
Alcohol consumption
Non‐drinker	499	(44.0)	215	(52.7)	59	(44.0)	0.12
Former drinker	148	(13.1)	48	(11.8)	18	(13.4)
Current drinker (1–22 g ethanol/day)	264	(23.3)	79	(19.4)	28	(20.9)
Current drinker (≥ 23 g ethanol/day)	222	(19.6)	66	(16.2)	29	(21.6)
Hypertension
No hypertension	694	(61.3)	218	(53.4)	66	(49.3)	0.002
Hypertension	439	(38.7)	190	(46.6)	68	(50.7)
BMI
< 21	235	(20.7)	125	(30.6)	45	(33.6)	< 0.001
21–23	244	(21.5)	95	(23.3)	17	(12.7)
23–25	262	(23.1)	85	(20.8)	27	(20.1)
25–27	175	(15.4)	59	(14.5)	18	(13.4)
≥ 27	217	(19.2)	44	(10.8)	27	(20.1)

Note: Data are presented as mean (standard deviation).

^a Median (interquartile range), or number (proportion).

^b Only at the Kyowa site.

Regarding outcomes based on the AWGS 2019 criteria, a significant positive association was observed between serum NT‐proBNP levels and each outcome except for low comfortable walking speed (Table 2). Compared to the lowest serum NT‐proBNP level group, the multivariable‐adjusted ORs and 95% CIs for low skeletal muscle mass were significantly higher in both the middle and highest serum NT‐proBNP level groups, at 1.38 (1.04–1.82) and 1.63 (1.07–2.49), respectively. For low handgrip strength and sarcopenia, significantly higher multivariable‐adjusted ORs were observed only in the highest serum NT‐proBNP level group, at 3.38 (1.70–6.73) and 2.56 (1.07–6.14), respectively. The multivariable‐adjusted OR for low comfortable walking speed in the highest serum NT‐proBNP level group compared to the lowest group was 1.81 (0.96–3.40), and that for low maximal walking speed was 1.75 (1.03–2.97). Linear trends between serum NT‐proBNP levels and all outcomes were generally observed, although the trends for low comfortable and maximal walking speeds were of borderline statistical significance.

TABLE 2.

Odds ratios and 95% confidence intervals of the prevalence of sarcopenia and its components according to smerum NT‐proBNP levels.

	Serum NT‐proBNP level (pg/mL)	Number of participants	Number of cases	Model 1		Model 2		p for trend
				OR	95% CI	OR	95% CI
Sarcopenia a	< 55	610	25	Ref.		Ref.		0.03
	55–124	214	18	1.91	(0.99–3.70)	1.61	(0.81–3.20)
	≥ 125	81	10	2.96	(1.33–6.57)	2.56	(1.07–6.14)
Low skeletal muscle mass	< 55	1130	216	Ref.		Ref.		0.008
SMI < 7.0 kg/m2 in men	55–124	406	119	1.38	(1.05–1.81)	1.38	(1.04–1.82)
SMI < 5.7 kg/m2 in women	≥ 125	131	41	1.53	(1.02–2.31)	1.63	(1.07–2.49)
Low handgrip strength	< 55	1129	31	Ref.		Ref.		< 0.001
Handgrip strength < 28 kg in men	55–124	407	26	1.63	(0.94–2.83)	1.60	(0.91–2.80)
Handgrip strength < 18 kg in women	≥ 125	134	15	2.98	(1.54–5.78)	3.38	(1.70–6.73)
Low walking speed a	< 55	614	82	Ref.		Ref.		0.06
Comfortable walking speed ≤ 1.0 m/s	55–124	217	33	1.17	(0.74–1.85)	1.28	(0.80–2.05)
	≥ 125	83	16	1.49	(0.81–2.74)	1.81	(0.96–3.40)
Low maximal walking speed a	< 55	612	141	Ref.		Ref.		0.06
Maximal walking speed ≤ 1.59 m/s	55–124	216	52	0.96	(0.66–1.40)	1.03	(0.69–1.52)
	≥ 125	83	27	1.47	(0.89–2.45)	1.75	(1.03–2.97)

Note: Model 1: Adjusted for age (continuous) and sex.

Model 2, Model 1 + body mass index, diabetes mellitus, hypertension, eGFR, smoking status, and drinking status.

^a Only at the Kyowa site.

4. Discussion

This study is the first to examine the association between serum NT‐proBNP levels and the prevalence of sarcopenia in middle‐aged to older community‐dwelling individuals. A significant positive association was observed between higher serum NT‐proBNP levels and the prevalence of sarcopenia, whereas inverse associations were found with its physical components, specifically skeletal muscle mass, muscle strength, and maximal walking speed.

A previous clinic‐based study with a smaller sample size (38 cases) reported that plasma BNP levels in patients with acute decompensated heart failure (ADHF) and sarcopenia (20 cases) were higher than those in patients without sarcopenia (18 cases). The median plasma BNP levels in patients with ADHF with and without sarcopenia were 1666 and 429 pg/mL, respectively [6]. Another study demonstrated an association between plasma BNP levels and sarcopenia in 433 outpatients with type 2 diabetes mellitus without chronic heart failure, reporting an OR of 1.56 (95% CI: 1.14–2.13) per 10 pg/mL increment in plasma BNP levels [13]. However, these previous studies diagnosed sarcopenia based solely on the SMI [6] or in combination with handgrip strength [13] without incorporating walking speed. Therefore, not all components of the diagnostic criteria for sarcopenia were included.

The association between high serum NT‐proBNP levels and the prevalence of sarcopenia, low muscle strength, and low skeletal muscle mass in the present study may be attributed to a decline in cardiovascular function. Reduced cardiovascular function results in inadequate blood supply to the body, leading to physical inactivity owing to shortness of breath or easy fatigability [14]. Physical inactivity induces attenuated protein synthesis because of the decreased turnover rates of muscle and whole‐body proteins [15]. Physically inactive individuals require a higher protein intake than their physically active counterparts to achieve an equivalent level of postprandial anabolism [16]. Physical activity and nutrition promote protein anabolism and are primary interventions for sarcopenia prevention or treatment [17, 18, 19]. Physical inactivity combined with malnutrition caused by cardiovascular dysfunction likely contributes to the loss of skeletal muscle mass by attenuating protein anabolism. Furthermore, pressure overload on the ventricle induces the secretion of proBNP—a precursor of BNP and NT‐proBNP—and inflammatory cytokines. Hemodynamic overload resulting from hypertension or valvular heart diseases induces micro tissue damage [20]. Chronic inflammation may develop if the underlying cause is not addressed and tissue damage persists [21]. Inflammatory cytokines contribute to promoting protein catabolism [22] and higher tumor necrosis factor‐alpha, C‐reactive protein, and interleukin‐6 levels are associated with a 5‐year decline in thigh muscle area [23]. Therefore, a decline in cardiovascular function likely creates an imbalance in protein metabolism, attenuating protein anabolism while promoting protein catabolism through multiple pathways, ultimately contributing to the loss of skeletal muscle mass and the development of sarcopenia.

Conversely, the loss of skeletal muscle mass or strength, the primary symptoms of sarcopenia, may adversely affect the cardiovascular system. Appendicular skeletal muscles primarily serve as a motor system to generate force and joint movement; however, they also play a supportive role as a muscle pump. The calf muscles, including the gastrocnemius and soleus, are sometimes referred to as the “second heart” because of their pivotal role in returning blood to the heart against gravity [24, 25]. Consequently, the loss of skeletal muscle mass results in not only a reduction in force generation but also a diminished capacity to assist circulation, thereby increasing strain on the heart. Additionally, a reduction in respiratory muscle strength can lead to decreased ventricular capacity [26]. Shortness of breath, commonly observed in individuals with sarcopenia, arises when the oxygen supply is insufficient to meet the exercise demands [26, 27]. Hypoxemia, caused by inadequate ventilation, can cause cardiac tissue damage [28]. Thus, the loss of skeletal muscle mass and strength may contribute to reduced cardiovascular system function by impairing the muscle pump and respiratory function.

In the present study, people with the highest group of serum NT‐proBNP levels had the higher prevalence of low maximal walking speed compared with those with the lowest group. A similar, but borderline significant association was observed for comfortable walking speed. These findings suggest that high serum NT‐proBNP levels may lead to a decline in walking capability. However, it is possible that this relationship is bidirectional. Because walking speed is regarded as the “sixth vital sign,” it reflects overall physical function determined by multiple factors, including neuromuscular control and balance, rather than being limited to muscle strength alone [29, 30]. Consequently, high NT‐proBNP levels may be linked to a systemic decline in physical function, manifested as reduced walking speed, and vice versa. Furthermore, as discussed above regarding the muscle pump, the association between walking speed and NT‐proBNP may be partially mediated by skeletal muscle function. The skeletal muscle pump, particularly in the lower limbs, plays a pivotal role in facilitating venous return and maintaining hemodynamics during ambulation [24]. Reduced muscle function may compromise this pump action, potentially increasing cardiac load and hemodynamic instability, which may be reflected by high NT‐proBNP levels. Previous studies reported that lower‐limb skeletal muscle function correlates with exercise tolerance and cardiac function in patients with heart failure [31]. Taken together, the decline in walking speed in the high NT‐proBNP group may reflect not only general frailty but also the impaired muscle pump function on cardiac stress.

Several strengths distinguish this study. First, in contrast to previous hospital‐based studies that primarily focused on outpatients and inpatients, this study included middle‐aged to older community residents, providing a clearer picture of the association between serum NT‐proBNP levels and the prevalence of sarcopenia. Second, the Asian Working Group for Sarcopenia 2019 criteria were used to diagnose sarcopenia, which requires the measurement of skeletal muscle mass, muscle strength, and physical performance. By measuring SMI, handgrip strength, and walking speed, this study fulfilled the diagnostic criteria and provided comparable data on sarcopenia.

However, this study also had several limitations. First, data on physical performance measured by walking speed were not available at the Ikawa site, which may have led to reduced statistical power for the association of serum NT‐proBNP levels with walking speed and sarcopenia. Second, socioeconomic and psychological factors such as income, education level, employment, and depressed mood were not accounted for. Therefore, the effect of these factors on the association of serum NT‐proBNP levels with physical function and sarcopenia remains unclear.

In conclusion, these findings indicate that high serum NT‐proBNP levels and sarcopenia and its components coexist in community‐dwelling individuals. This study suggests that preventing a decline in physical performance and managing cardiac diseases may have mutually beneficial effects.

Author Contributions

Conceptualization: Ren Sato and Kazumasa Yamagishi. Data curation: Ren Sato, Kazumasa Yamagishi, and Hiroshige Jinnouchi. Investigation: Ren Sato, Kazumasa Yamagishi, Hiroshige Jinnouchi, Isao Muraki, Mikako Yasuoka, Hironobu Kakihana, Sachimi Kubo, Tomomi Kihara, Takumi Matsumura, and Midori Takada. Formal analysis: Ren Sato and Kazumasa Yamagishi. Funding acquisition: Kazumasa Yamagishi and Isao Muraki. Supervision: Kazumasa Yamagishi, Isao Muraki, Yuji Shimizu, Tetsuya Ohira, Takeshi Tanigawa, Hironori Imano, and Hiroyasu Iso. Writing – original draft: Ren Sato and Kazumasa Yamagishi. Writing – review and editing: Hiroshige Jinnouchi, Isao Muraki, Mikako Yasuoka, Hironobu Kakihana, Sachimi Kubo, Tomomi Kihara, Takumi Matsumura, Midori Takada, Yuji Shimizu, Tetsuya Ohira, Takeshi Tanigawa, Hironori Imano, and Hiroyasu Iso.

Funding

This study was supported by the Japan Society for the Promotion of Science (the JSPS Kakenhi grants, grant numbers 22K19663, 23K24609, and 25H01090), the Ministry of Health, Labour and Welfare, Japan (Health and Labour Sciences Research Grant, Grant number 23FA1006), and FULLHAP.

Ethics Statement

This study was conducted in accordance with the Declaration of Helsinki and the Ethical Guidelines for Medical and Biological Research Involving Human Subjects. Appropriate consent was obtained from the participants in Kyowa. In Ikawa, consent was not obtained from the participants; however, opt‐out opportunities were provided during health check‐ups onsite. The Institutional Review Boards of Kindai University (R04‐255), Osaka Center for Cancer and Cardiovascular Disease Prevention (2305‐01), and the University of Tsukuba (2047) approved this study.

Conflicts of Interest

The authors declare no conflicts of interest.

Sato R., Yamagishi K., Jinnouchi H., et al., “Associations Between Serum N‐Terminal Pro‐Brain Natriuretic Peptide Levels and the Prevalence of Sarcopenia in Middle‐Aged and Older Japanese Adults: A Population‐Based Cross‐Sectional Study,” Geriatrics & Gerontology International 26, no. 2 (2026): e70404, 10.1111/ggi.70404.

Data Availability Statement

Research data are not shared. The data collected in this study cannot be made publicly available due to privacy protection concerns. The data contain sensitive information collected based on participant consent, and strict confidentiality is required in accordance with the approval conditions of the Institutional Review Board.