Abstract
[Purpose] We aimed to clarify the association between respiratory sarcopenia and attention function, assessed by the Trail Making Test (TMT), in community-dwelling older adults. [Participants and Methods] Fifty-nine older adults were assessed for body composition, respiratory function, and both TMT-A and TMT-B performance times. Respiratory sarcopenia was identified by a reduction in maximal oral pressure and a low skeletal muscle mass index; multiple regression analysis examined the association between respiratory sarcopenia and TMT performance times, adjusting for age and history of respiratory disease. [Results] Respiratory sarcopenia prevalence was 10.2%. This group had significantly lower body weight, body mass index, skeletal muscle mass index, and trunk muscle ratio than the non-respiratory sarcopenia group. We found that the presence of respiratory sarcopenia was significantly associated with a prolonged TMT-A performance time, as opposed to that of TMT-B. [Conclusion] These results indicate that respiratory sarcopenia in community-dwelling older adults was associated with a decline in attention, particularly reduced performance on the TMT-A (reflecting selective and sustained attention), whereas no significant association was found with the TMT-B (reflecting divided attention). We concluded that these findings suggest a potential association between respiratory sarcopenia and specific attention domains in older adults.
Key words: Attention function, Maximum oral pressure, Respiratory sarcopenia
INTRODUCTION
With an aging rate of 29.0%1), Japan is classified as a super-aged society, where extending healthy life expectancy presents a critical challenge. Advancing age is associated with a progressive decline in various physiological functions, including muscle strength, respiratory function, and cognitive function2). Particularly in older adults, cognitive decline not only impairs quality of life3) but also contributes to an increased societal burden4); necessitating urgent measures for prevention and early detection. Given that Mild Cognitive Impairment (MCI) serves as a precursor to dementia, early identification of individuals at risk of transitioning from MCI to dementia is essential for establishing effective intervention strategies.
Among cognitive functions, attention is essential for performing activities of daily living5), and its decline is considered a significant sign of MCI6). The Trail Making Test (TMT) is a neuropsychological test battery that assesses attention and executive functions, such as information processing speed and divided attention7), and it is one of the useful indicators for predicting the transition from MCI to dementia8). The TMT is also listed as one of the assessment scales for evaluating cognitive impairment in the Japanese Clinical Practice Guidelines for Dementia 20179). Therefore, clarifying the factors associated with prolonged TMT performance times would contribute to the risk assessment and development of preventive strategies for cognitive decline.
Meanwhile, cognitive function is closely associated with physical function. Among age-related declines in physical function, muscle weakness (sarcopenia) and a decline in respiratory function have a major impact on overall health status10, 11). In particular, systemic sarcopenia and Chronic Obstructive Pulmonary Disease (COPD) have been suggested to be associated with cognitive decline, including MCI12, 13). It has been reported that these conditions may adversely affect cognitive function through mechanisms such as reduced oxygen supply to the brain, as well as inflammatory responses12, 14).
In recent years, respiratory sarcopenia, a novel pathology characterized by a decline in respiratory muscle strength and mass, has garnered attention15). It is hypothesized that this condition, much like systemic sarcopenia and impaired respiratory function, may be involved in the decline of cognitive functions, including attention. However, the association between respiratory sarcopenia and the TMT has yet to be elucidated. We suggest that although systemic sarcopenia is a recognized risk factor for cognitive decline, assessing respiratory muscle health may provide a more sensitive or independent indicator for early cognitive impairment—specifically, processing speed and attention—which might be overlooked by conventional limb-centered assessments.
Therefore, this study aimed to clarify the association between respiratory sarcopenia and attention function, assessed using the TMT, in community-dwelling older adults.
PARTICIPANTS AND METHODS
The participants in this study were recruited from a health promotion class for community residents conducted over a 4 year period beginning in 2021. This program was initiated in 2021 with the aim of preventing age-related declines in various functions, including physical, motor, and cognitive abilities. The program, run in collaboration with the local community, includes health assessments to measure these functions, feedback sessions based on the results, and specialized workshops. For the present study, 67 individuals who consented to their measurement data from the health assessments being used in an anonymized format for medical statistics and research were initially enrolled. Participants were guaranteed the opportunity to opt out. Of these, seven individuals with a history of cerebrovascular disease or with metal implants (e.g., artificial joints) and one individual who did not complete all assessments were excluded. Consequently, the final analysis included 59 participants (16 men; mean age, 75.7 ± 6.2 years).
Baseline characteristics of the participants were obtained using a self-administered questionnaire, which collected data on age, sex, height, current diseases under treatment, medical history, smoking status, and physical activity. For participants with a history of smoking, the Brinkman Index was calculated by multiplying the average number of cigarettes smoked per day by the number of years smoked. Physical activity was assessed using the short version of the International Physical Activity Questionnaire (IPAQ), for which the reliability and validity have been previously established16). Daily physical activity for each intensity level (low, moderate, and vigorous) and the total daily physical activity (kcal/kg/day) were calculated. This calculation was based on the activity durations obtained from the IPAQ, activity intensity as described by Murase et al.16), one metabolic equivalent (=3.5 mL/kg/min), and an energy expenditure of 0.005 kcal per 1 mL of oxygen uptake.
Body composition was measured using a body composition analyzer (InBody470; InBody Japan, Tokyo, Japan) based on bioelectrical impedance analysis. The parameters used for this study included body weight, body mass index (BMI), body fat percentage, skeletal muscle mass index (SMI), and the truncal muscle ratio, which was calculated as truncal muscle mass divided by height squared.
Respiratory function tests were performed in accordance with the methods established by the Committee on Pulmonary Physiology of the Japanese Respiratory Society17). We measured Forced Vital Capacity (FVC), Forced Expiratory Volume in 1 s (FEV1), and the FEV1/FVC ratio using a diagnostic electronic spirometer (AS-507 Auto Spiro; Minato Medical Science, Osaka, Japan) while monitoring the time-volume curve. The procedure was conducted with participants in a seated position. After quiet breathing stabilized, participants were instructed to inhale from their resting tidal volume to the maximal inspiratory position and then perform a single, maximal forced exhalation until reaching the maximal expiratory position. They were verbally encouraged to continue the exhalation for a minimum of 6 s, and the test was concluded after confirming no change in expiratory volume for at least 2 s. This maneuver was repeated multiple times, and the results from the best flow-volume curve were adopted for analysis. The FVC and FEV1 values were expressed as percentages of their predicted values (%FVC and %FEV1), which were based on the predictive equations published by the Japanese Respiratory Society18).
Respiratory muscle strength was assessed by measuring Maximal Inspiratory Pressure (MIP) and Maximal Expiratory Pressure (MEP) using a respiratory muscle strength meter (IOP-01; Kowata Keiki Co., Ltd., Osaka, Japan). The measurements were performed in accordance with the American Thoracic Society/European Respiratory Society (ATS/ERS) statement19). The tests were conducted with participants in a seated position; for MIP measurement, after quiet breathing stabilized, participants performed a maximal inhalation from the maximal expiratory position. For MEP measurement, after quiet breathing stabilized, participants performed a maximal exhalation from the maximal inspiratory position. Each test was performed at least three times, and the highest value was adopted for analysis. The obtained MIP and MEP values were expressed as percentages of their predicted values (%MIP and %MEP), based on the predictive equations20).
Attention function was assessed using Part A (TMT-A) and Part B (TMT-B) of the Japanese version of the TMT21). TMT scores are associated with other neuropsychological assessments22) and have been studied in various populations with disabilities, including older adults with cognitive decline8). The Japanese version of the TMT has been standardized with normative data (mean and standard deviation) from a healthy population in age groups from their 20s to 80s, with a male-to-female ratio of approximately 1:121). In Japan, it is also used as an indicator of the attention and processing abilities necessary for driving. The TMT-A measures the performance time for connecting numbers from 1 to 25 in sequence, whereas the TMT-B measures the completion time for alternately connecting numbers (1 to 13) and Japanese Hiragana characters (from ‘あ’ [a] to ‘し’ [shi]).
The presence of respiratory sarcopenia was assessed based on the new diagnostic criteria proposed in a 2023 position paper by four professional organizations15). According to these criteria, in this study, participants with “probable respiratory sarcopenia” were classified as having respiratory sarcopenia. This was defined as having both %MIP and %MEP<80% of predicted values23) and an SMI below the established reference values (<7.0 kg/m2 for men and <5.7 kg/m2 for women).
For the statistical analysis, differences in each evaluated parameter based on the presence or absence of respiratory sarcopenia were examined using two-sample t-tests, Mann–Whitney U tests, or Fisher’ s exact test, as appropriate. Furthermore, multiple regression analyses were conducted with TMT-A and TMT-B performance times as the respective dependent variables. The presence or absence of respiratory sarcopenia served as the independent variable, while age and a history of respiratory disease were included as adjustment variables. To address potential multicollinearity, the variance inflation factor for all independent variables was confirmed to be less than 10. Considering that multivariate linear regression analysis requires a minimum of 15 cases per independent variable24), a sample size of at least 45 was necessary for the three variables included in our model. All statistical analyses were performed using IBM SPSS Statistics Version 26.0 (IBM Corp., Armonk, NY, USA), and the level of statistical significance was set at p<0.05.
RESULTS
The data obtained from the analysis are presented as mean ± standard deviation or median (interquartile range) for continuous variables, and as frequency (percentage) for categorical data. Table 1 shows the baseline characteristics, body composition, respiratory function, and attention function results for the 59 participants. Seven participants had a past or present history of treatment for respiratory diseases, which included bronchial asthma (n=3), pneumonia (n=1), interstitial pneumonia (n=2), and pulmonary tuberculosis (n=1). None of the participants were current smokers. Table 2 shows a comparison of the parameters based on the presence or absence of respiratory sarcopenia. Six participants (10.2%) were classified as having respiratory sarcopenia. Compared with the non-respiratory sarcopenia group, the respiratory sarcopenia group had significantly lower body weight (p=0.008), BMI (p=0.018), SMI (p=0.005), and truncal muscle ratio (p=0.025). Additionally, the respiratory sarcopenia group exhibited a significantly longer performance time for the TMT-A (p=0.040), whereas we found no significant difference in TMT-B performance time between the two groups (p=0.067).
Table 1. Information about body composition, respiratory function, and attention function of the study participants.
| Variable | Values (n=59) | ||
| Participants’ information | |||
| Age (years) | 75.7 ± 6.2 | ||
| Male (n, %) | 16 (27.1) | ||
| Height (cm) | 156.4 ± 9.7 | ||
| Respiratory disease (n, %) | 7 (11.9) | ||
| Smoking status | |||
| Non-smokers (n, %) | 45 (76.3) | ||
| Ex-smokers (n, %) | 14 (23.7) | ||
| Smoking index | 0.0 (0.0 to 0.0) | ||
| Total PA (kcal/kg/day) | 2.8 (1.5 to 7.2) | ||
| Low PA (kcal/kg/day) | 1.7 (0.7 to 3.0) | ||
| Moderate to vigorous PA (kcal/kg/day) | 0.9 (0.0 to 3.6) | ||
| Body composition | |||
| Weight (kg) | 54.7 ± 10.7 | ||
| BMI (kg/m2) | 22.3 ± 3.1 | ||
| Body fat percentage (%) | 28.6 ± 7.8 | ||
| Skeletal muscle index (kg/m2) | 6.1 (5.7 to 7.1) | ||
| Trunk muscle ratio (kg/m2) | 6.8 ± 0.8 | ||
| Respiratory function | |||
| FVC (%pred.) | 100.5 ± 18.7 | ||
| FEV1 (%pred.) | 101.4 ± 21.9 | ||
| FEV1/FVC (%) | 79.2 (75.8 to 81.2) | ||
| MIP (%pred.) | 76.0 (62.5 to 93.3) | ||
| MEP (%pred.) | 68.9 ± 27.9 | ||
| Attention function | |||
| TMT-A (sec) | 53.3 (38.5 to 71.7) | ||
| TMT-B (sec) | 94.4 (64.8 to 142.7) | ||
Values were presented as mean ± standard deviation and median (interquartile range 25–75%) for normally and not normally distributed data, respectively. Categorical data are expressed as frequency and percentage.
PA: physical activity; BMI: body mass index; FVC: forced vital capacity; FEV1: forced expiratory volume in one second; MIP: maximal inspiratory pressure; MEP: maximal expiratory pressure; TMT-A: Trail Making Test Part A; TMT-B: Trail Making Test Part B.
Table 2. Comparison between participants with and without respiratory sarcopenia.
| Variables | With respiratory sarcopenia (n=6) | Without respiratory sarcopenia (n=53) | ||
| Participants’ information | ||||
| Age (years) | 77.0 (76.0 to 87.5) | 75.0 (72.0 to 79.0) | ||
| Male (n, %) | 1 (16.7) | 15 (28.3) | ||
| Height (cm) | 150.5 ± 8.0 | 157.0 ± 9.7 | ||
| Respiratory disease (n, %) | 0 (100.0) | 7 (13.2) | ||
| Smoking status | ||||
| Non-smokers (n, %) | 6 (100.0) | 39 (73.6) | ||
| Ex-smokers (n, %) | 0 (0.0) | 14 (26.4) | ||
| Smoking index | 0.0 (0.0 to 0.0) | 0.0 (0.0 to 146.0) | ||
| Total PA (kcal/kg/day) | 1.3 (0.9 to 3.0) | 3.0 (1.8 to 7.6) | ||
| Low PA (kcal/kg/day) | 0.8 (0.4 to 2.7) | 2.0 (0.8 to 3.0) | ||
| Moderate to vigorous PA (kcal/kg/day) | 0.0 (0.0 to 1.1) | 1.2 (0.0 to 4.2) | ||
| Body composition | ||||
| Weight (kg) | 44.0 ± 5.7 | 56.0 ± 10.5** | ||
| BMI (kg/m2) | 19.5 ± 2.9 | 22.6 ± 3.0* | ||
| Body fat percentage (%) | 24.4 ± 11.8 | 29.1 ± 7.2 | ||
| Skeletal muscle index (kg/m2) | 5.5 (5.1 to 5.7) | 6.2 (5.7 to 7.2)** | ||
| Trunk muscle ratio (kg/m2) | 6.2 ± 0.5 | 6.9 ± 0.8* | ||
| Respiratory function | ||||
| FVC (%pred.) | 107.2 (71.8 to 112.7) | 99.2 (88.7 to 114.6) | ||
| FEV1 (%pred.) | 102.2 ± 23.0 | 101.3 ± 22.0 | ||
| FEV1/FVC (%) | 79.8 (76.4 to 82.3) | 79.2 (75.8 to 81.8) | ||
| MIP (%pred.) | 52.6 (27.1 to 75.5) | 78.4 (64.3 to 98.5)* | ||
| MEP (%pred.) | 39.8 ± 14.4 | 72.2 ± 27.2** | ||
| Attention function | ||||
| TMT-A (sec) | 72.0 (53.5 to 112.0) | 49.8 (37.7 to 68.0)* | ||
| TMT-B (sec) | 150.5 (97.6 to 170.8) | 92.2 (64.4 to 128.9) | ||
Values were presented as mean ± standard deviation and median (interquartile range 25–75%) for normally and not normally distributed data, respectively. Categorical data are expressed as frequency and percentage. **p<0.01, *p<0.05.
PA: physical activity; BMI: body mass index; FVC: forced vital capacity; FEV1: forced expiratory volume in one second; MIP: maximal inspiratory pressure; MEP: maximal expiratory pressure; TMT-A: Trail Making Test Part A; TMT-B: Trail Making Test Part B; %pred.: percentage of predicted value.
Table 3 presents the results of the multivariate linear regression analyses for the TMT performance times as the dependent variables. The presence of respiratory sarcopenia was significantly associated with a prolonged TMT-A performance time, independent of age and a history of respiratory disease (adjusted R2=0.352). In contrast, no significant association was found between the presence of respiratory sarcopenia and TMT-B performance time.
Table 3. Result of multiple linear regression analysis of respiratory sarcopenia with TMT.
| Variables | Unadjusted analysis |
Adjusted analysis# |
|||||
| Unstandardized coefficients | Standardized coefficients | 95% CIs | Unstandardized coefficients | Standardized coefficients | 95% CIs | ||
| TMT-A | |||||||
| Respiratory sarcopenia | 28.45 | 0.408** | 11.59 to 45.32 | 21.20 | 0.304** | 5.86 to 36.53 | |
| TMT-B | |||||||
| Respiratory sarcopenia | 29.63 | 0.133 | −28.97 to 88.22 | 4.68 | 0.021 | −51.39 to 60.76 | |
**p<0.01. #Adjusted for age and a history of respiratory disease. TMT-A: Trail Making Test Part A; TMT-B: Trail Making Test Part B.
DISCUSSION
This study is the first to demonstrate an association between respiratory sarcopenia and attention function in community-dwelling older adults. Of the participants, 10.2% had respiratory sarcopenia, and its presence was significantly associated with a decline in attention function as assessed by the TMT-A. These findings suggest that respiratory sarcopenia is a potential factor associated with the risk of cognitive decline in older adults, although further validation is required to determine its reliability as a clinical indicator. Although associations between respiratory sarcopenia, based on the 2023 definition, and factors such as physical function and activities of daily living have been reported25, 26), the findings of the present study, which show an association with attention function—an aspect of cognitive function—are considered novel.
Regarding the mechanism by which respiratory sarcopenia affects attention function, the established mechanisms linking cognitive decline with systemic sarcopenia and respiratory diseases, particularly COPD, are informative. In these pathologies, hypoxia and chronic inflammation are thought to affect brain function12, 27). The present study included no participants with COPD, and the association between respiratory sarcopenia and attention function was observed even after statistically adjusting for the effects of other respiratory diseases. Therefore, we hypothesize that respiratory sarcopenia affects attention function not only through mechanisms common to systemic sarcopenia and respiratory diseases, but also through a complex interplay of multiple factors.
Furthermore, muscles not only function as a locomotor organ but also as an endocrine organ that secretes bioactive substances known as myokines28). The significant decrease in SMI and truncal muscle ratio observed in participants with respiratory sarcopenia in this study could lead to a reduced secretion of myokines that contribute to neuroprotection and brain plasticity29), which may in turn be a cause of the observed decline in attention function. We believe further research, including longitudinal studies, is warranted.
It is also an interesting finding of this study that the association with respiratory sarcopenia was limited to the TMT-A, with no significant association observed for the TMT-B. The TMT-A is generally considered to assess selective and sustained attention, whereas the TMT-B assesses divided attention; the TMT-B is the more complex task and typically requires a longer completion time30). This suggests that respiratory sarcopenia may selectively affect specific, relatively basic cognitive domains rather than having a global impact on the brain. Furthermore, educational history, in addition to age, has been shown to influence cognitive function7). For a multifaceted task such as the TMT-B, the possibility that such other factors masked the effects of respiratory sarcopenia cannot be ruled out. Regardless, it is crucial to use not only the TMT but also a more comprehensive and detailed neuropsychological test battery to identify the specific cognitive domains most affected by respiratory sarcopenia.
This study has several limitations. First, the number of participants with respiratory sarcopenia was small (n=6), suggesting the sample size may have been insufficient. Furthermore, as the majority of participants were females, the potential for gender bias should be considered, and caution is warranted when generalizing the results. Second, the cross-sectional design of this study does not allow for the inference of a causal relationship between respiratory sarcopenia and the decline in attention function. Third, the assessment of cognitive function was limited to the TMT; therefore, we emphasize that these findings are preliminary and should be interpreted with caution. These issues should be addressed in future research.
Conference presentation
The 12th conference of Japanese Society of Physical Therapy for Prevention, https://orbit-cs.net/2025jsptp/abstract_jsptp12.pdf?=ver02
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Conflict of interest
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
REFERENCES
- 1.Cabinet Office: Chapter 1: Situation of aging population. In: Reiwa 5th Edition Aging Society White Paper. https://www8.cao.go.jp/kourei/whitepaper/w-2023/zenbun/pdf/1s1s_01.pdf (in Japanese) (Accessed May 1, 2024)
- 2.Li Q, Xiao N, Zhang H, et al. : Systemic aging and aging-related diseases. FASEB J, 2025, 39: e70430. [DOI] [PubMed] [Google Scholar]
- 3.Lee S, Ho Chung J: The association between subjective cognitive decline and quality of life: a population-based study. J Clin Neurosci, 2022, 98: 60–65. [DOI] [PubMed] [Google Scholar]
- 4.Wimo A, Guerchet M, Ali GC, et al. : The worldwide costs of dementia 2015 and comparisons with 2010. Alzheimers Dement, 2017, 13: 1–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Sohlberg MM, Mateer CA: Introduction to cognitive rehabilitation: theory and practice. New York: The Guilford Press, 1989. [Google Scholar]
- 6.Perry RJ, Hodges JR: Attention and executive deficits in Alzheimer’s disease. A critical review. Brain, 1999, 122: 383–404. [DOI] [PubMed] [Google Scholar]
- 7.Tombaugh TN: Trail Making Test A and B: normative data stratified by age and education. Arch Clin Neuropsychol, 2004, 19: 203–214. [DOI] [PubMed] [Google Scholar]
- 8.Chapman RM, Mapstone M, McCrary JW, et al. : Predicting conversion from mild cognitive impairment to Alzheimer’s disease using neuropsychological tests and multivariate methods. J Clin Exp Neuropsychol, 2011, 33: 187–199. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Japanese Society of Neurology: Chapter 2 Symptoms, rating scales, diagnosis, testing. In: Dementia disease clinical practice guideline 2017. Tokyo: Igaku-shoin, 2017, pp 18–53 (in Japanese). [Google Scholar]
- 10.Beaudart C, Zaaria M, Pasleau F, et al. : Health outcomes of sarcopenia: a systematic review and meta-analysis. PLoS One, 2017, 12: e0169548. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Schünemann HJ, Dorn J, Grant BJ, et al. : Pulmonary function is a long-term predictor of mortality in the general population: 29-year follow-up of the Buffalo Health Study. Chest, 2000, 118: 656–664. [DOI] [PubMed] [Google Scholar]
- 12.Cabett Cipolli G, Sanches Yassuda M, Aprahamian I: Sarcopenia is associated with cognitive impairment in older adults: a systematic review and meta-analysis. J Nutr Health Aging, 2019, 23: 525–531. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Hitaka H, Shiranita S, Uemura Y, et al. : Association between chronic obstructive pulmonary disease and mild cognitive impairment. J Jpn Soc Respir Care Rehabil, 2020, 29: 299–303 (in Japanese). [Google Scholar]
- 14.Chen X, Yu Z, Liu Y, et al. : Chronic obstructive pulmonary disease as a risk factor for cognitive impairment: a systematic review and meta-analysis. BMJ Open Respir Res, 2024, 11: e001709. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Sato S, Miyazaki S, Tamaki A, et al. : Respiratory sarcopenia: a position paper by four professional organizations. Geriatr Gerontol Int, 2023, 23: 5–15. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Murase N, Katsumura T, Ueda C, et al. : Reliability and validity of the Japanese version of the international physical activity questionnaire. Kousei no Shihyou, 2002, 49: 1–9 (in Japanese). [Google Scholar]
- 17.The Committee of Pulmonary Physiology of the Japanese Respiratory Society: Spirometry and flow volume curve. In: Guidelines for pulmonary function tests—spirometry, flow-volume curve, diffusion capacity of the lung—. Tokyo: Medical Review, 2004, pp 1–23 (in Japanese). [PubMed] [Google Scholar]
- 18.The Japanese Respiratory Society: Reference values of spirogram and arterial blood gas levels in Japanese. Nihon Kokyuki Gakkai Zasshi, 2001, 39: 1–17 (in Japanese). [Google Scholar]
- 19.American Thoracic Society/European Respiratory Society: ATS/ERS Statement on respiratory muscle testing. Am J Respir Crit Care Med, 2002, 166: 518–624. [DOI] [PubMed] [Google Scholar]
- 20.Suzuki M, Teramoto S, Sudo E, et al. : [Age-related changes in static maximal inspiratory and expiratory pressures]. Nihon Kyobu Shikkan Gakkai Zasshi, 1997, 35: 1305–1311 (in Japanese). [PubMed] [Google Scholar]
- 21.Japan Society for Higher Brain Dysfunction & Brain Function Test Committee. TMT-J Trail Making Test Japanese version. Tokyo: Shinkoh Igaku Shuppansha, 2019. (in Japanese). [Google Scholar]
- 22.Llinàs-Reglà J, Vilalta-Franch J, López-Pousa S, et al. : The Trail Making Test. Assessment, 2017, 24: 183–196. [DOI] [PubMed] [Google Scholar]
- 23.Miyazaki S, Tamaki A, Wakabayashi H, et al. : Definition, diagnosis, and treatment of respiratory sarcopenia. Curr Opin Clin Nutr Metab Care, 2024, 27: 210–218. [DOI] [PubMed] [Google Scholar]
- 24.Stevens JP: Applied Multivariate Statistics for the Social Sciences, 4th ed. Mahwah: Lawrence Erlbaum Associates, 2002, p 88. [Google Scholar]
- 25.da Costa Teixeira LA, de Carvalho Bastone A, Soares LA, et al. : Physical and inflammatory aspects associated to respiratory sarcopenia in community-dwelling older women. Sci Rep, 2025, 15: 18310. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Moriyama T, Tokunaga M, Hori R, et al. : Probable respiratory sarcopenia decreases activities of daily living in older patients hospitalized with respiratory diseases: a cross-sectional study. Prog Rehabil Med, 2024, 9: 20240014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Dodd JW, Getov SV, Jones PW: Cognitive function in COPD. Eur Respir J, 2010, 35: 913–922. [DOI] [PubMed] [Google Scholar]
- 28.Severinsen MC, Pedersen BK: Muscle-organ crosstalk: the emerging roles of myokines. Endocr Rev, 2020, 41: 594–609. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Pedersen BK, Pedersen M, Krabbe KS, et al. : Role of exercise-induced brain-derived neurotrophic factor production in the regulation of energy homeostasis in mammals. Exp Physiol, 2009, 94: 1153–1160. [DOI] [PubMed] [Google Scholar]
- 30.Takaoka T, Ozaki H: Examination and interpretation of higher brain dysfunction—Trail Making Test. J Clin Rehabil, 2009, 18: 246–250 (in Japanese). [Google Scholar]