Association between Walking Habit and Physical Frailty among Community-Dwelling Older Adults
1
Department of Behavior and Health Sciences, Graduate School of Human-Environment Studies, Kyushu University, Fukuoka 819-0395, Japan
2
Faculty of Arts and Science, Kyushu University, Fukuoka 819-0395, Japan
3
Center for Health Science and Counseling, Kyushu University, Fukuoka 819-0395, Japan
*
Author to whom correspondence should be addressed.
Healthcare 2022, 10(8), 1396; https://doi.org/10.3390/healthcare10081396
Submission received: 5 July 2022
/
Revised: 23 July 2022
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Accepted: 25 July 2022
/
Published: 27 July 2022
(This article belongs to the Special Issue Frailty in Community-Dwelling Older People)
Abstract
:The aim of this cross-sectional study was to determine whether older adults who practice walking have a lower risk of physical frailty than those who do not. The study subjects were 846 older adults and were not certified as needing support or nursing care. The subjects were classified as being physically frail or pre-frail or being robust, according to the revision of the Cardiovascular Health Study criteria. We classified the subjects by questionnaire into a no-exercise group, walking-only group, walking plus other exercise group, and exercise other than walking group. In logistic regression analyses, the odds ratio (OR) and 95% confidence interval (95%CI) were shown. Compared to the no-exercise group, the OR (95%CI) for physical frailty was 0.85 (0.48–1.49) for the walking-only group, 0.54 (0.36–0.83) for the walking plus other exercise group, and 0.67 (0.47–0.97) for the exercise other than walking group. In the components of physical frailty, the walking plus other exercise group and the exercise other than group had significantly lower ORs for exhaustion. Older adults who only practiced walking as an exercise do not have lower risks of physical frailty and pre-frailty. Older adults who combine walking with other exercises or practice non-walking exercises have lower risks of them.
1. Introduction
Japan has the highest aging rate in the world, and the rate is expected to continue to rise. Accordingly, the costs of social security benefits in Japan, including pensions, medical care, and welfare, are reported to be on the rise [1]. Among the costs of social security benefits, the rate of increase in long-term care costs is remarkable [2]. However, there are no sufficient social environment and social security systems that enable older people to extend their healthy longevity at this time.
Frailty is one of the factors leading to the need for long-term care; it is defined as a state of decreased physiological reserve and increased vulnerability to stress in old age [3]. Frailty has various aspects, and the severity of physical frailty, among other aspects, is directly related to the need for long-term care [4]. Chen et al. reported that older adults with physical frailty at baseline had a significantly higher risk of requiring long-term care within ~6 years compared to robust individuals [5]. The prediction of physical frailty is thus important to reduce the need for long-term care and extend healthy longevity.
The amount of exercise and physical activity can be objectively expressed in terms of frequency, duration, and metabolic equivalents (METs). Japan’s Ministry of Health, Labour, and Welfare recommends that older adults should be physically active for ≥10 METs/hour per week [6]. The World Health Organization recommends ≥ 300 min per week of aerobic physical activity [7]. A review of randomized controlled trials reported that exercise or physical activity is the most effective intervention for preventing frailty [8]. However, the specific optimal exercise modalities for preventing frailty—such as the specific exercise type(s), frequency, and duration — are not clear. While considering these factors, it is necessary to establish one or more methods that can achieve the recommended amount of exercise that can be practiced continuously by many older adults and thus contribute to reducing the risk of physical frailty.
Among the many types of exercise, our research group has focused on walking. In community-dwelling older adults, it is reported that those who spend more time walking have a better life expectancy [9]; the practice of aerobic exercise such as walking improves carotid compliance [10], and older adults with a walking habit have higher physical function. Walking is safe, low-cost, and easily disseminated, and these advantages may contribute to the postponement of physical frailty by regular walking. However, to the best of our knowledge, there have been no investigations of the association between walking and physical frailty. The relatively few studies of the relationship between walking and physical function did not consider the influence of physical activity levels other than walking [11].
We conducted the present study to determine whether older adults who walk for exercise have a lower risk of physical frailty than those who do not. We also investigated exercise types, duration, and frequency in a population with a lower risk of physical frailty and pre-frailty compared to a population not engaging in exercise.
2. Materials and Methods
2.1. Study Design and Subjects
This was a cross-sectional study using baseline survey data from an epidemiological cohort study of community-dwelling older adults in Itoshima City, Fukuoka, Japan. The participants were men and women aged 65–75 years who lived in this city and responded to a community needs survey conducted in September 2016 [12] and who were not certified as requiring nursing support or care. Considering the size of the district, 5000 respondents were randomly selected and mailed the survey invitation and questionnaire. We included the 949 respondents who participated in the measurement sessions from September to December 2017 [13]. A final total of 846 subjects (399 men and 447 women) who met the criteria for valid data on physical activity (≥4 days and ≥10 h of wear time) of a tri-axis accelerometer (Active style Pro HJA-350IT, Omron Healthcare, Kyoto, Japan) and had no missing data on physical frailty or exercise habit were included in the final analysis of this study (Figure 1). This study was approved by the Institutional Review Board of Kyushu University (Ref No. 201708), and informed consent was obtained from all subjects involved in the study.
2.2. Measures
2.2.1. Physical Frailty
Physical frailty was defined according to the revision of the Cardiovascular Health Study (CHS) criteria, using the definition applied in the Sasaguri Genkimon study [3,14]. The CHS criteria consist of five items: shrinking, exhaustion, weakness, slowness, and low physical activity. Table 1 shows a specific assessment method for the five items. Weakness was assessed using BMI and maximum grip strength. The grip strength was measured using a Smedley grip strength meter (GRIP-D, T.K.K. 5401; Takei Scientific Instruments Co. Ltd., Niigata, Japan) in an upright posture with the arm directly down, left and right, and the maximum value was used. Slowness was evaluated based on height and maximum walking speed results at 5 m. To measure walking speed, an 11 m walking path was created, and the subjects were instructed to walk a distance of 11 m at maximum speed from a stationary standing position. The time was measured from 3rd to 8th meter. Exhaustion and shrinking were measured with a questionnaire. Low physical activity was assessed by measuring physical activity energy expenditure (kcal) using a triaxial accelerometer. The subjects were instructed to wear the accelerometer on the right or left side of their waist for seven consecutive days and remove it only before going to bed or participating in water activities.
2.2.2. Walking Assessment
We divided the subjects into four groups: the no-exercise group (N group), the walking-only group (W group), the walking plus other exercise group (W + O group), and the exercise other than walking group (O group). For the determination of each subject’s exercise habit, we asked “Have you exercised in the past month?”. Another question asked the subject to select up to 3 of the 19 exercise activities commonly performed by elderly Japanese, and we investigated their exercise frequency per week and the duration per session for each session of exercise. The 19 activities include Japanese sampo (i.e., strolling, including dog walking), walking, hiking, cycling, gymnastics (including stretching), yoga, golf, hitting practice golf balls, ground golf, table tennis, ballroom dancing, aerobic dancing, tai chi, underwater exercise, volleyball, catch-ball, bowling, muscle strength training, and others.
2.2.3. Other Assessment
We obtained the following information from each subject via questionnaire: age, sex, body mass index (BMI), medical history (presence/absence of osteoporosis, hypertension, dyslipidemia, diabetes, cerebral infarction, cardiac disease, and other diseases, respectively), number of pain locations (presence/absence of each shoulder, elbow, wrist, hip, knee, ankle, waist, and neck), years of education, activities of daily living (ADLs; eating, moving, toileting, walking, climbing stairs, dressing, defecating, urinating, bathing, and grooming), residence area (selected from the city’s residential districts: Maebaru, Nijo, and Shima), smoking habit (selected from “almost every day”, “sometimes”, “used to smoke but quit”, and “never”), and alcohol consumption (selected from “almost every day”, “sometimes”, “rarely”, and “never”). The subjects’ cognitive function was measured with the Mini-Mental State Examination (MMSE). If a subject was engaging in more than one exercise type, we used the average duration per exercise type (minutes per session). The frequency of exercise per week (number of times per week) was calculated by adding up the number of exercise days per week for each exercise if the subject performed more than one exercise type. Sedentary time (ST; activity intensity < 1.5 METs), light physical activity (LPA; activity intensity of 1.5 METs to <3.0 METs), and moderate-to-vigorous physical activity (MVPA; activity intensity of ≥3.0 METs) were measured with the above-mentioned tri-axis accelerometer.
2.2.4. Statistical Analyses
The subjects’ characteristics are expressed as the mean ± standard deviation (SD) or n (%), and a one-way analysis of variance (ANOVA) or χ2 test was performed. A post hoc Bonferroni test was used for multiple comparisons among the four exercise groups. Physical frailty and physical pre-frailty were set together as “at risk”, and a binary variable between that status and the robust status was created and used for logistic regression analysis. The analysis was used to calculate the odds ratio (OR) and 95% confidence interval (CI) for comparing the N group as the reference group with the other three groups. The risk of each component of physical frailty was also examined by a logistic regression analysis. Adjustment factors in the logistic regression analysis were those reported to be associated with physical frailty in previous studies: age, gender, BMI, number of medical histories, number of pain locations, years of education, a total ADL score, the MMSE score, smoking habit (almost daily or occasional smoking), drinking habit (almost daily or occasional drinking), and the three residential districts. Moreover, MVPA and ST were also included as adjustment factors to exclude the effects of daily living activities other than walking and of sitting time during exercise breaks and non-exercise time. The distribution of exercise types in the W + O and the O groups was determined. The distribution of frequency of exercise per week and duration of exercise per session were also assessed, including the W group, and comparisons between groups were tested by the post hoc Bonferroni test. The statistical analyses were conducted using Statistical Analysis Software (SAS) ver. 9.4 (SAS Institute, Cary, NC, USA). The computation was carried out using the computer resource offered under the category of General Projects by the Research Institute for Information Technology, Kyushu University. The statistical significance level was set at p < 0.05.
3. Results
3.1. The Caracteristics of Exercise Behavior Groups
A summary of the four exercise groups’ characteristics is provided in Table 2. Compared to the no-exercise/reference N group, the W group had significantly higher MMSE scores and more MVPA. The W + O group had significantly fewer pain locations, longer years of education, and more MVPA. The W + O group exercised significantly more frequently than the W and O groups. The mean exercise duration was significantly longer in the O group than in the W and W + O groups.
3.2. Association between Exericise Behavior and Physical Frailty or Pre-Frailty
The results concerning the relationship between exercise and physical frailty or pre-frailty and its components are given in Table 3. In the N group, 114 of the 212 subjects were physically frail or pre-frail. In the W group, 33 of the 75 subjects (44.0%) were physical frailly or pre-frail. The OR (95%CI, p-value) for physical frailty or pre-frailty in the W group compared to the N group was 0.77 (0.44–1.33, p = 0.35), with no significant difference. On the other hand, in the W + O group, 71 of the 204 subjects (34.8%) were physically frail or pre-frail, with a significantly lower OR at 0.51 (0.33–0.77, p = 0.0014). Similar results were observed in the O group (OR: 0.66, 95%CI: 0.46–0.94, p = 0.02), in which 146 of the 355 subjects (41.2%) were physically frail or pre-frail. Regarding the association with the components of physical frailty, the W + O group had a significantly lower OR at 0.30 (95%CI: 0.15–0.59, p = 0.0005) for exhaustion and 0.20 (95%CI: 0.06–0.71, p = 0.01) for slowness. The O group also had a significantly lower OR for exhaustion (OR: 0.51, 95%CI: 0.31–0.84, p = 0.008) and a lower trend for slowness (OR: 0.47, 95%CI: 0.22–1.01, p = 0.054).
Table 4 shows the results of the association between exercise and physical frailty or pre-frailty after the addition of ST and MVPA as adjusting factors. The W group showed no significant association with physical frailty or pre-frailty (OR: 0.85, 95%CI: 0.48–1.49, p = 0.57). This relationship was unchanged from before the adjustment for these two factors. The risk of physical frailty or pre-frailty in the W + O group also showed no change in association and was significantly lower than that in the N group (OR: 0.54, 95%CI: 0.36–0.83, p = 0.0048). The risk in the O group was also significantly lower than that in the N group (OR: 0.67, 95%CI: 0.47–0.97, p = 0.03). Regarding the association with the components of physical frailty, the significantly lower OR of exhaustion that we observed in the W + O and O groups did not change after adjusting for ST and MVPA (OR: 0.30, 95%CI: 0.15–0.59, p = 0.0006 for the W + O group, and OR: 0.51, 95%CI: 0.31–0.85, p = 0.009 for the O group). In contrast, the OR for slowness in both W + O and O groups was attenuated; it was marginal in the W + O group and no longer significantly associated in the O group.
3.3. Distribution of Exercise Types Other Than Walking
The most common types of exercise used together in the W + O group were gymnastics (including stretching) at 46.1% and strength training at 15.2%. The most common exercise activities for the O group were sampo (including dog walking) at 37.7% and gymnastics (including stretching) at 37.5%.
4. Discussion
The results of our analyses demonstrated that the risk of physical frailty or pre-frailty in the W(alking) group was not significantly different from that in the N(o-exercise) group. On the other hand, the risk of physical frailty or pre-frailty was significantly lower in the W + O and O(ther) groups compared to the N group. This relationship remained unchanged after adjustment for the subjects’ sedentary time and moderate-to-vigorous physical activity. The lower risk found in the W + O and O groups was due to a significantly lower risk of exhaustion, a component of physical frailty.
These results contradict our hypothesis that the subjects with a walking habit alone would not be at a lower risk of physical frailty. The reasons for this outcome could be due to walking’s low intensity of exercise, the little amount of exercise duration per session and the low frequency of exercise per week in the W group, and the lack of statistical power due to the small sample size of the group (n = 75). It has been reported that older adults with a walking habit had significantly longer 6 min walk test distances [15]. The American College of Sports Medicine guidelines indicate that exercise tolerance improves by 10% with exercise intensity equivalent to ≥60% of exercise tolerance [16]. However, it has been reported that the walking intensity of community-living older adults is 40% of their maximum oxygen uptake [17]. It is therefore possible that walking alone may not reach the intensity necessary to improve exercise tolerance, which is associated with exhaustion, a component of physical frailty.
Regarding the frequency of exercise, the older adults who engaged in regular walking only in this study had a lower frequency of exercise per week than the other groups. It has been reported that walking improves depression, anxiety, psychological health, and mental health [18] and that more frequent exercise was associated with lower depressive symptoms [19]. In intervention studies, healthy individuals who exercised more frequently had significantly higher rates of improvement in muscle strength and muscle mass [20,21]. Since we used the Kessler-6, a method of assessing psychological stress [22], to assess exhaustion, we speculate that the risk of exhaustion was not lowered by the lack of positive effects of infrequent exercise on mental and muscles.
The duration of exercise per session was shorter in the W group than in the other groups, which is also characteristic of older adults who engage in walking exclusively. In a 10-year prospective follow-up study, older women who walked ≥40 min/day had a lower risk of developing depression than older women who walked <30 min/week [23]. A cross-sectional study of older adults showed a lower risk of depression with greater total exercise time per week [24], and a cross-sectional study of subjects aged 19–89 years showed that the longer the exercise duration, the higher the maximal oxygen uptake [25]. It is thus possible that the duration of exercise per session in our W-group subjects was insufficient to improve mental and exercise tolerance.
In this study, the risk of exhaustion was lower among the subjects who combined walking with other exercises. In a cross-sectional study, the subjects who combined aerobic physical activity with strength training had significantly lower depressive symptoms compared to engaging in either of these activities alone [26]. Gymnastics and strength training were the most common disciplines used in combination by the present study’s subjects. Earlier investigations revealed that participating in gymnastics classes improved quality of life, ikigai (positive attitude) [27], and exercise self-efficacy [28], suggesting that the combined use of gymnastics has a positive impact on mental health. Lower-limb muscle strength, a factor associated with exercise tolerance, is improved by strength training and gymnastics [29,30]. The presence of these in combination with walking in our W + O subjects may thus have resulted in better mental status and muscle strength plus reduced exhaustion.
Engaging in multiple types of exercise also significantly increased the frequency of exercise compared to the W and O groups. We suspect that the greater frequency of exercise may have contributed to the lower risk of exhaustion. This association was also observed when the analysis was adjusted for ST and MVPA, suggesting that the combination of walking and other exercises in itself contributes to the reduction in risk of exhaustion regardless of the sedentary time or the degree of moderate-to-vigorous intensity exercise or lifestyle activity. The risk of exhaustion was also lower among the present older adults who engaged in exercise other than walking. Many of the subjects in this group were walking or doing gymnastics. As noted above, participating in gymnastics has a positive effect on mental health [27,28] and reduces exhaustion. Although sampo is similar to walking, the subjects who used the more leisurely sampo pace had a longer duration of exercise per session, which may have contributed to their lower risk of exhaustion.
To the best of our knowledge, this is the first study to focus on walking and its association with physical frailty. The older adult subjects were analyzed separately as those who engage in only a walking habit and those who used walking plus other physical activities. The analysis excluded the influence of a number of factors, including the subjects’ objectively measured ST and MVPA. Exercise activities other than walking and the exercises’ frequency and duration were evaluated to identify the characteristics of the exercise group that was at a low risk of developing physical frailty. However, there are several study limitations to address: (1) This was a cross-sectional study, and the causal relationship between walking and physical frailty is unclear. (2) The small number of people in the W group (n = 75) may have resulted in insufficient statistical power. (3) The intensity of exercise, including walking, was unknown in this study. (4) Depending on the exercise category, the amount of time that the subjects reported engaging in exercise may have included rest time. However, the results were adjusted for sedentary time, and thus, the subjects’ break time during exercise is not likely to have affected the results. In this study, exercise habit was not associated with the components of physical frailty: grip strength, weight loss, and decreased activity. Therefore, these components require further investigation, such as combining them with factors other than exercise. It is also necessary to clearly assess the intensity of exercise itself in community-dwelling older adults.
5. Conclusions
Older adults who only practiced walking as an exercise do not have lower risks of physical frailty and pre-frailty. However, our findings suggest that engaging in a high frequency of walking in combination with other exercises or maintaining a longer duration of exercise other than walking is associated with a lower risk of exhaustion and a lower risk of physical pre-frailty or frailty.
Author Contributions
Conceptualization, T.Y. and H.K.; methodology, T.Y., T.C., X.L. and H.K.; software, T.Y., H.Y., T.C., X.L. and H.K.; validation, T.Y. and H.K.; formal analysis, T.Y. and H.K.; investigation, T.Y., H.Y., T.C., X.L. and H.K.; resources, H.K.; data curation, H.Y. and X.L.; writing—original draft preparation, T.Y.; writing—review and editing, T.Y., H.Y., T.C., X.L. and H.K.; visualization, T.Y.; supervision, H.K.; project administration, H.K.; funding acquisition, H.K. All authors have read and agreed to the published version of the manuscript.
Funding
This study was supported in part by Grants-in-Aid for Scientific Research (B) (nos. JP 20H04016 and JP 20H04030) and (C) (nos. JP 20K102692, JP 20K11446, and JP 20K12510) and for Activity Start-up (no. JP19K24259) from the Ministry of Education, Culture, Sports, Science, and Technology of Japan; Itoshima City (2021-0032), Asanohi Orthopaedic Clinic (2020-0528), NTT Docomo Inc. (2021-0085), and CB Co., Ltd. (2021-0271). None of the funding sources had any role in the study design, data analysis, data interpretation, writing of the manuscript, or decision on the submission of this manuscript.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Kyushu University (Ref No. 201708).
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
Data sharing not applicable.
Acknowledgments
We thank all of the subjects who participated in this study, the faculty and laboratory members who advised us on this research, and the staff of the Division of Health and Wel-fare of Itoshima City.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Cabinet Office. Impact of Aging on Social Security Benefits. 2015. Available online: https://www8.cao.go.jp/kourei/whitepaper/w-2019/html/zenbun/s1_1_6.html (accessed on 20 May 2021).
- Social Security Council. Future Social Security Reform. 2018. Available online: https://www.mhlw.go.jp/content/12601000/000474989.pdf (accessed on 1 January 2022).
- Fried, L.P.; Tangen, C.M.; Walston, J.; Newman, A.B.; Hirsch, C.; Gottdiener, J.; Seeman, T.; Tracy, R.; Kop, W.J.; Burke, G.; et al. Frailty in Older adults: Evidence for a phenotype. J. Gerontol. Ser. A Biol. Sci. Med. Sci. 2001, 56, M146–M156. [Google Scholar] [CrossRef] [PubMed]
- Iijima, K., VII. Community-dwelling Elderly and Frailty Prevention (Including Oral Frailty). Nihon Naika Gakkai Zasshi 2018, 107, 2469–2477. [Google Scholar] [CrossRef] [Green Version]
- Chen, S.; Honda, T.; Narazaki, K.; Chen, T.; Kishimoto, H.; Kumagai, S. Physical Frailty and Risk of Needing Long-Term Care in Community-Dwelling Older Adults: A 6-Year Prospective Study in Japan. J. Nutr. Health Aging 2019, 23, 856–861. [Google Scholar] [CrossRef] [PubMed]
- Ministry of Health, Labour and Welfare. Report of the Study Group on the Revision of Exercise Standards and Guidelines. 2012. Available online: https://www.mhlw.go.jp/stf/shingi/other-kenkou_128596.html (accessed on 1 May 2021).
- World Health Organization. Guidelines on Physical Activity and Sedentary Behaviour. 2020. Available online: https://www.who.int/publications/i/item/9789240015111 (accessed on 10 January 2021).
- Negm, A.M.; Kennedy, C.C.; Thabane, L.; Veroniki, A.-A.; Adachi, J.D.; Richardson, J.; Cameron, I.D.; Giangregorio, A.; Petropoulou, M.; Alsaad, S.M.; et al. Management of Frailty: A Systematic Review and Network Meta-analysis of Randomized Controlled Trials. J. Am. Med Dir. Assoc. 2019, 20, 1190–1198. [Google Scholar] [CrossRef] [PubMed]
- Landi, F.; Russo, A.; Cesari, M.; Pahor, M.; Liperoti, R.; Danese, P.; Bernabei, R.; Onder, G. Walking one hour or more per day prevented mortality among older persons: Results from ilSIRENTE study. Prev. Med. 2008, 47, 422–426. [Google Scholar] [CrossRef] [PubMed]
- Matsubara, T.; Miyaki, A.; Akazawa, N.; Choi, Y.; Ra, S.-G.; Tanahashi, K.; Kumagai, H.; Oikawa, S.; Maeda, S. Aerobic exercise training increases plasma Klotho levels and reduces arterial stiffness in postmenopausal women. Am. J. Physiol. Circ. Physiol. 2014, 306, H348–H355. [Google Scholar] [CrossRef] [Green Version]
- Yokote, T.; Kishimoto, H. Association between walking exercise and physical function: In community-dwelling older people. Int. J. Phys. Med. Rehabil. 2021, 9, 1–12. [Google Scholar] [CrossRef]
- Chen, S.; Chen, T.; Kishimoto, H.; Susaki, Y.; Kumagai, S. Development of a Fried Frailty Phenotype Questionnaire for Use in Screening Community-Dwelling Older Adults. J. Am. Med. Dir. Assoc. 2019, 21, 272–276. [Google Scholar] [CrossRef]
- Yatsugi, H.; Chen, T.; Chen, S.; Liu, X.; Kishimoto, H. The Associations between Objectively Measured Physical Activity and Physical Function in Community-Dwelling Older Japanese Men and Women. Int. J. Environ. Res. Public Health 2021, 19, 369. [Google Scholar] [CrossRef]
- Chen, S.; Honda, T.; Chen, T.; Narazaki, K.; Haeuchi, Y.; Supartini, A.; Kumagai, S. Screening for frailty phenotype with objectively-measured physical activity in a west Japanese suburban community: Evidence from the Sasaguri Genkimon Study. BMC Geriatr. 2015, 15, 36–45. [Google Scholar] [CrossRef] [Green Version]
- Arai, T.; Kuwabara, K.; Meguro, T.; Watanabe, S.; Fujita, H. The Relationship between Walking Frequency and Physical Function in Community-Dwelling Elderly People. Rigakuryoho Kagaku 2011, 26, 655–659. [Google Scholar] [CrossRef] [Green Version]
- Riebe, D.; Ehrman, J.K.; Liguori, G.; Magal, M. ACSM’s Guidelines for Exercise Testing and Prescription, 10th ed.; Wolters Kluwer: Alphen Aan Den Rijn, The Netherlands, 2017; pp. 142–166. [Google Scholar]
- Nose, H. Interval Walking Ttaining for Middle-Aged and Older People: The Effects and the Evidence. J. Jpn. Soc. Stomatognath. Funct. 2012, 19, 1–9. [Google Scholar] [CrossRef]
- Kelly, P.; Williamson, C.; Niven, A.; Hunter, R.; Mutrie, N.; Richards, J. Walking on sunshine: Scoping review of the evidence for walking and mental health. Br. J. Sports Med. 2018, 52, 800–806. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hallgren, M.; Kandola, A.; Stubbs, B.; Nguyen, T.-T.; Wallin, P.; Andersson, G.; Ekblom-Bak, E. Associations of exercise frequency and cardiorespiratory fitness with symptoms of depression and anxiety—A cross-sectional study of 36595 adults. Ment. Health Phys. Act. 2020, 19, 100351. [Google Scholar] [CrossRef]
- Grgic, J.; Schoenfeld, B.J.; Davies, T.B.; Lazinica, B.; Krieger, J.W.; Pedisic, Z. Effect of Resistance Training Frequency on Gains in Muscular Strength: A Systematic Review and Meta-Analysis. Sports Med. 2018, 48, 1207–1220. [Google Scholar] [CrossRef]
- Kemmler, W.; von Stengel, S. Exercise Frequency, Health Risk Factors, and Diseases of the Elderly. Arch. Phys. Med. Rehabil. 2013, 94, 2046–2053. [Google Scholar] [CrossRef] [PubMed]
- Kessler, R.C.; Andrews, G.; Colpe, L.J.; Hiripi, E.; Mroczek, D.K.; Normand, S.-L.; Walters, E.E.; Zaslavsky, A.M. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol. Med. 2002, 32, 959–976. [Google Scholar] [CrossRef]
- Lucas, M.; Mekary, R.; Pan, A.; Mirzaei, F.; O’Reilly, É.J.; Willett, W.C.; Koenen, K.; Okereke, O.I.; Ascherio, A. Relation between Clinical Depression Risk and Physical Activity and Time Spent Watching Television in Older Women: A 10-Year Prospective Follow-up Study. Am. J. Epidemiol. 2011, 174, 1017–1027. [Google Scholar] [CrossRef] [Green Version]
- Lee, H.-Y.; Yu, C.-P.; Wu, C.-D.; Pan, W.-C. The Effect of Leisure Activity Diversity and Exercise Time on the Prevention of Depression in the Middle-Aged and Elderly Residents of Taiwan. Int. J. Environ. Res. Public Health 2018, 15, 654. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Nes, B.M.; Janszky, I.; Aspenes, S.T.; Bertheussen, G.F.; Vatten, L.J.; Wisløff, U. Exercise Patterns and Peak Oxygen Uptake in a Healthy Population. Med. Sci. Sports Exerc. 2012, 44, 1881–1889. [Google Scholar] [CrossRef] [Green Version]
- Bennie, J.A.; Teychenne, M.J.; De Cocker, K.; Biddle, S.J. Associations between aerobic and muscle-strengthening exercise with depressive symptom severity among 17839 U.S. adults. Prev. Med. 2019, 121, 121–127. [Google Scholar] [CrossRef] [PubMed]
- Tsujishita, S.; Wakui, T. Impact of a Monthly 3-Month Preventive Exercise Program on the Quality of Life, Ikigai (meaning for life) and Positive Attitudes of Older Women with Different Levels of Life Purpose. Rigakuryoho Kagaku 2021, 36, 337–343. [Google Scholar] [CrossRef]
- Matsumoto, H.; Osaka, H.; Inoue, K.; Park, D.; Hagino, H. Relationship between exercise, self-efficacy for exercise, and grade of frailty in community dwelling older adults—A cross-sectional observation study. Rigakuryohogaku 2019, 46, 429–436. [Google Scholar] [CrossRef]
- McCartney, N.; Hicks, A.L.; Martin, J.; Webber, C.E. Long-term Resistance Training in the Elderly: Effects on Dynamic Strength, Exercise Capacity, Muscle, and Bone. J. Gerontol. Ser. A 1995, 50, B97–B1041. [Google Scholar] [CrossRef] [PubMed]
- Kim, S.; Lee, E.-J.; Kim, H.-O. Effects of a Physical Exercise Program on Physiological, Psychological, and Physical Function of Older Adults in Rural Areas. Int. J. Environ. Res. Public Health 2021, 18, 8487. [Google Scholar] [CrossRef]
Figure 1.
Participant flow chart in the analysis.
Table 1.
Definition of physical frailty.
| Shrinking | Unintentional weight loss > 2–3 kg in the prior 6 months |
| Weakness | Grip strength stratified by gender and BMI (kg/m2) |
| Men | ≤25.00 kg for BMI < 18.5, ≤30.00 kg for 18.5 ≤ BMI < 25, ≤31.50 kg for 25 ≤ BMI < 30, ≤33.00 kg for BMI ≥ 30 |
| Women | ≤17.50 kg for BMI < 18.5, ≤19.50 kg for 18.5 ≤ BMI < 25, ≤20.50 kg for BMI 25 ≤ BMI < 30, ≤19.75 kg for BMI ≥ 30 |
| Exhaustion | Positive answer to either of two self-reported questions. Participants were asked how they felt during the past 30 days: “Did you feel that everything you did was an effort?” and “Did you feel exhausted without any reason?” |
| Slowness | Time of 5 m walk test at one’s maximum waking speed stratified by gender and standing height (gender-specific cutoff: a medium height). |
| Men | Time ≥ 3.56 s for height < 162.0 cm or Time ≥ 3.21 s for height ≥ 162.0 cm |
| Women | Time ≥ 4.25 s for height < 148.7 cm or Time ≥ 3.61 s for height ≥ 148.7 cm |
| Low physical activity | Energy expenditure of physical activity by a triaxial accelerometer; quantified as kilocalories/kg (body weight), stratified by gender. |
| Men | ≤6.20 kcal/kg/day |
| Women | ≤7.13 kcal/kg/day |
| Overall frailty status | Robust: 0 affected component. Pre-frailty: 1–2 affected components. Frailty ≥ 3 affected components. |
Table 2.
The characteristics of the four exercise behavior groups of community-dwelling older Japanese adults (n = 846).
Table 2.
The characteristics of the four exercise behavior groups of community-dwelling older Japanese adults (n = 846).
| N Group n = 212 (25.1%) | W Group n = 75 (8.9%) | W + O Group n = 204 (24.1%) | O Group n = 355 (42.0%) | |
|---|---|---|---|---|
| Age, y | 70.8 ± 3.1 | 70.9 ± 3.3 | 71.1 ± 3.2 | 70.9 ± 3.0 |
| Men | 95 (44.8) | 34 (45.3) | 101 (49.5) | 169 (20.0) |
| Residential district: | ||||
| Shima | 55 (25.9) | 12 (16.0) | 41 (20.1) | 86 (24.2) |
| Nijo | 57 (26.9) | 23 (30.7) | 51 (25.0) | 91 (25.6) |
| Maebaru | 100 (47.2) | 40 (53.3) | 112 (54.9) | 178 (50.1) |
| BMI, kg/m2 | 23.0 ± 3.3 | 23.0 ± 3.2 | 22.7 ± 2.9 | 22.9 ± 3.2 |
| Presence of disease | 99 (46.7) | 34 (45.3) | 104 (51.0) | 159 (44.8) |
| No. of pain sites | 1.9 ± 2.1 | 1.3 ± 1.6 | 1.4 ± 1.7 * | 1.7 ± 1.8 |
| Education, y | 12.5 ± 2.3 | 12.7 ± 2.2 | 13.3 ± 2.6 * | 13 ± 2.3 |
| ADL score | 10.1 ± 0.6 | 10.1 ± 0.6 | 10.1 ± 0.5 | 10.1 ± 0.3 |
| MMSE score | 27.5 ± 2.2 | 28.3 ± 1.7 * | 28.0 ± 2.1 | 27.8 ± 2.1 |
| Sedentary time (minutes/day) | 440.6 ± 121.2 | 454.5 ± 111.3 | 445.2 ± 102.4 | 445.0 ± 103.9 |
| Moderate and Vigorous physical activity, min/day | 44.6 ± 33.6 | 67.4 ± 33.5 * | 59.4 ± 30.0 * | 50.6 ± 31.0 |
| Light physical activity, min/day | 350.1 ± 96.8 | 339.9 ± 110.3 | 336.1 ± 88.8 | 343.3 ± 90.1 |
| Alcohol consumption, any level | 101 (47.6) | 33 (44.0) | 113 (55.4) | 180 (50.7) |
| Smoking habit, any level | 23 (10.9) | 4 (5.3) | 9 (4.4) | 25 (7.0) |
| Frequency of exercise, ×/week | 0 | 4.8 ± 2.4 | 7.9 ± 4.3 †,§ | 5.0 ± 3.6 |
| Duration of exercise, min/session | 0 | 73.7 ± 57.4 | 91.2 ± 54.5 | 106.3 ± 75.9 †,‡ |
Data are the number of subjects (percentage) or mean ± standard deviation. N group, no-exercise group; W group, walking only group; W + O group, walking plus other exercise group; O group, exercise other than walking group. * p < 0.05 vs. N group, † p < 0.05 vs. W group. ‡ p < 0.05 vs. W + O group. § p < 0.05 vs. O group. Presence of disease, the percentage of those who have at least one of the following: osteoporosis, hypertension, dyslipidemia, diabetes, stroke, heart disease, or other disease; Alcohol consumption, the percentage of respondents who answered “I drink almost every day” or “I drink sometimes”; Smoking habit, the percentage of respondents who answered “I smoke almost every day” or “I smoke sometimes”; ADL, activities of daily living; BMI, body mass index; MMSE, Mini-Mental State Examination.
Table 3.
The relationship between exercise behavior and physical frailty or pre-frailty and its components.
Table 3.
The relationship between exercise behavior and physical frailty or pre-frailty and its components.
| N Group | W Group | W + O Group | O Group | |
|---|---|---|---|---|
| Physical frailty or pre-frailty, n (%): | 114 (53.8) | 33 (44.0) | 71 (34.8) | 146 (41.1) |
| OR | 1.00 | 0.77 | 0.51 | 0.66 |
| 95%CI | Ref. | 0.44–1.33 | 0.33–0.77 | 0.46–0.94 |
| p-value | – | 0.35 | 0.0014 | 0.02 |
| Components of physical frailty: | ||||
| Shrinking, n (%): | 31 (14.6) | 7 (9.3) | 23 (11.3) | 35 (9.9) |
| OR | 1.00 | 0.63 | 0.84 | 0.67 |
| 95%CI | Ref. | 0.26–1.51 | 0.46–1.53 | 0.40–1.14 |
| p-value | – | 0.29 | 0.57 | 0.14 |
| Exhaustion, n (%): | 45 (21.2) | 8 (10.7) | 13 (6.4) | 40 (11.3) |
| OR | 1.00 | 0.51 | 0.30 | 0.51 |
| 95%CI | Ref. | 0.22–1.19 | 0.15–0.59 | 0.31–0.84 |
| p-value | – | 0.12 | 0.0005 | 0.008 |
| Weakness, n (%): | 40 (18.9) | 14 (18.7) | 31 (15.2) | 62 (17.5) |
| OR | 1.00 | 1.04 | 0.84 | 0.95 |
| 95%CI | Ref. | 0.52–2.10 | 0.49–1.46 | 0.59–1.51 |
| p-value | – | 0.91 | 0.54 | 0.82 |
| Slowness, n (%): | 18 (8.6) | 2 (2.7) | 3 (1.5) | 15 (4.3) |
| OR | 1.00 | 0.37 | 0.2 | 0.47 |
| 95%CI | Ref. | 0.08–1.70 | 0.06–0.71 | 0.22–1.01 |
| p-value | – | 0.20 | 0.01 | 0.054 |
| Low physical activity, n (%): | 29 (13.6) | 6 (8.0) | 16 (7.8) | 41 (11.6) |
| OR | 1.00 | 0.66 | 0.54 | 0.96 |
| 95%CI | Ref. | 0.24–1.78 | 0.26–1.12 | 0.55–1.69 |
| p-value | – | 0.41 | 0.10 | 0.89 |
N group, no-exercise group; W group, walking only group; W + O group, walking plus other exercise group; O group, exercise other than walking group. Adjusted for age, sex, BMI, number of diseases, number of pain locations, years of education, the total ADL score, the total Mini-Mental State Examination score, residential district, smoking habit, and alcohol consumption. OR, odds ratio; CI, confidence interval.
Table 4.
The relationship between exercise and physical frailty or pre-frailty and its components after adjusting for sedentary time (ST) and moderate-to-vigorous physical activity (MVPA).
Table 4.
The relationship between exercise and physical frailty or pre-frailty and its components after adjusting for sedentary time (ST) and moderate-to-vigorous physical activity (MVPA).
| N Group | W Group | W + O Group | O Group | |
|---|---|---|---|---|
| Physical frailty or pre-frailty, n (%): | 114 (53.8) | 33 (44.0) | 71 (34.8) | 146 (41.1) |
| OR | 1.00 | 0.85 | 0.54 | 0.67 |
| 95%CI | Ref. | 0.48–1.49 | 0.36–0.83 | 0.47–0.97 |
| p-value | – | 0.57 | 0.005 | 0.03 |
| Components of physical frailty: | ||||
| Shrinking, n (%): | 31 (14.6) | 7 (9.3) | 23 (11.3) | 35 (9.9) |
| OR | 1.00 | 0.58 | 0.81 | 0.66 |
| 95%CI | Ref. | 0.24–1.44 | 0.44–1.48 | 0.39–1.13 |
| p-value | – | 0.24 | 0.48 | 0.13 |
| Exhaustion, n (%): | 45 (21.2) | 8 (10.7) | 13 (6.4) | 40 (11.3) |
| OR | 1.00 | 0.52 | 0.30 | 0.51 |
| 95%CI | Ref. | 0.22–1.23 | 0.15–0.59 | 0.31–0.85 |
| p-value | – | 0.14 | 0.0006 | 0.009 |
| Weakness, n (%): | 40 (18.9) | 14 (18.7) | 31 (15.2) | 62 (17.5) |
| OR | 1.00 | 1.25 | 0.92 | 0.99 |
| 95%CI | Ref. | 0.60–2.58 | 0.52–1.61 | 0.62–1.59 |
| p-value | – | 0.55 | 0.76 | 0.97 |
| Slowness, n (%): | 18 (8.6) | 2 (2.7) | 3 (1.5) | 15 (4.3) |
| OR | 1.00 | 0.55 | 0.28 | 0.54 |
| 95%CI | Ref. | 0.12–2.61 | 0.07–1.02 | 0.25–1.18 |
| p-value | – | 0.45 | 0.053 | 0.12 |
| Low physical activity, n (%): | 29 (13.6) | 6 (8.0) | 16 (7.8) | 41 (11.6) |
| OR | 1.00 | 2.91 | 2.22 | 1.83 |
| 95%CI | Ref. | 0.86–9.90 | 0.86–5.69 | 0.89–3.75 |
| p-value | – | 0.09 | 0.10 | 0.10 |
N group, no exercise group; W group, walking only group; W + O group, walking plus other exercise group; O group, exercise other than walking group. Adjusted for age, sex, BMI, number of diseases, number of pain locations, years of education, the total ADL score, the total Mini-Mental State Examination score, residential district, smoking habit, alcohol consumption, sedentary time, and moderate-to-high-intensity physical activity.
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Yokote, T.; Yatsugi, H.; Chu, T.; Liu, X.; Kishimoto, H. Association between Walking Habit and Physical Frailty among Community-Dwelling Older Adults. Healthcare 2022, 10, 1396. https://doi.org/10.3390/healthcare10081396
AMA Style
Yokote T, Yatsugi H, Chu T, Liu X, Kishimoto H. Association between Walking Habit and Physical Frailty among Community-Dwelling Older Adults. Healthcare. 2022; 10(8):1396. https://doi.org/10.3390/healthcare10081396
Chicago/Turabian StyleYokote, Tsubasa, Harukaze Yatsugi, Tianshu Chu, Xin Liu, and Hiro Kishimoto. 2022. "Association between Walking Habit and Physical Frailty among Community-Dwelling Older Adults" Healthcare 10, no. 8: 1396. https://doi.org/10.3390/healthcare10081396
APA StyleYokote, T., Yatsugi, H., Chu, T., Liu, X., & Kishimoto, H. (2022). Association between Walking Habit and Physical Frailty among Community-Dwelling Older Adults. Healthcare, 10(8), 1396. https://doi.org/10.3390/healthcare10081396
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