Scholarly article on topic 'Factors Affecting Mobility in Community-dwelling Older Koreans with Chronic Illnesses'

Factors Affecting Mobility in Community-dwelling Older Koreans with Chronic Illnesses Academic research paper on "Clinical medicine"

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{aged / "chronic disease" / Koreans / "mobility limitation" / walking}

Abstract of research paper on Clinical medicine, author of scientific article — Hye-A Yeom, Carol M. Baldwin, Myung-Ah Lee, Su-Jeong Kim

Summary Purpose This descriptive study aims to describe the levels of mobility in community-dwelling older Koreans with chronic illnesses, and to examine the associations of their mobility with sleep patterns, physical activity and physical symptoms including fatigue and pain. Methods The participants were a total of 384 community-dwelling older adults recruited from three senior centers in Seoul, Korea. Measures included mobility assessed using 6-minute walk test (6MWT), physical activity behavior, sleep profiles, fatigue and pain. Data were collected from July to December 2012. Results The mean 6MWT distance was 212.68 meters. Over 90% of the study participants (n = 373) were classified as having impaired mobility using 400 meters as the cutoff point diagnostic criteria of normal mobility in 6MWT. The 6MWT distance was 246.68 meters for participants in their 60s, 212.32 meters for those in their 70s, and 175.54 meters for those in their 80s. Significant predictors of mobility included younger age, taking mediation, regular physical activity, female gender, higher income, higher fatigue and better perception on sleep duration, which explained 18% of the total variance of mobility. Conclusions A high-risk group for mobility limitation includes low income, sedentary older men who are at risk for increased fatigue and sleep deficit. Further research should incorporate other psychological and lifestyle factors such as depression, smoking, drinking behavior, and/or obesity into the prediction model of mobility to generate specific intervention strategies for mobility enhancement recommendations for older adults.

Academic research paper on topic "Factors Affecting Mobility in Community-dwelling Older Koreans with Chronic Illnesses"

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Asian Nursing Research

journal homepage: www.asian-nursingresearch.com

Factors Affecting Mobility in Community-dwelling Older Koreans with Chronic Illnesses

Hye-A Yeom, PhD, RN, ANP-C,1'2' * Carol M. Baldwin, PhD, RN, AHN-BC, FAAN, 2 Myung-Ah Lee, MD, PhD, 3 Su-Jeong Kim, RN, MS 4

1 The Catholic University of Korea College of Nursing, South Korea

2 Arizona State University College of Nursing and Health Innovation, Phoenix, AZ, USA

3 The Catholic University of Korea College of Medicine, Seoul, South Korea

4 University of Illinois, College of Nursing, Chicago, IL, USA

CrossMark

ARTICLE INFO

Article history: Received 27 February 2014 Received in revised form 21 April 2014

Accepted 23 September 2014

Keywords: aged

chronic disease Koreans

mobility limitation walking

SUMMARY

Purpose: This descriptive study aims to describe the levels of mobility in community-dwelling older Koreans with chronic illnesses, and to examine the associations of their mobility with sleep patterns, physical activity and physical symptoms including fatigue and pain.

Methods: The participants were a total of 384 community-dwelling older adults recruited from three senior centers in Seoul, Korea. Measures included mobility assessed using 6-minute walk test (6MWT), physical activity behavior, sleep profiles, fatigue and pain. Data were collected from July to December 2012.

Results: The mean 6MWT distance was 212.68 meters. Over 90% of the study participants (n = 373) were classified as having impaired mobility using 400 meters as the cutoff point diagnostic criteria of normal mobility in 6MWT. The 6MWT distance was 246.68 meters for participants in their 60s, 212.32 meters for those in their 70s, and 175.54 meters for those in their 80s. Significant predictors of mobility included younger age, taking mediation, regular physical activity, female gender, higher income, higher fatigue and better perception on sleep duration, which explained 18% of the total variance of mobility. Conclusions: A high-risk group for mobility limitation includes low income, sedentary older men who are at risk for increased fatigue and sleep deficit. Further research should incorporate other psychological and lifestyle factors such as depression, smoking, drinking behavior, and/or obesity into the prediction model of mobility to generate specific intervention strategies for mobility enhancement recommendations for older adults.

Copyright © 2015, Korean Society of Nursing Science. Published by Elsevier. All rights reserved.

Introduction

Mobility, defined as the ability to make a physical movement, is an important indicator of functional independence in older adults. Impaired mobility is experienced by 46% of community-dwelling older adults [1] and is associated with depression, institutionalization, and mortality in older adults [2—4]. Limited mobility is also an essential component of diagnostic criteria for sarcopenia and a major risk factor for functional disability in older adults [5]. Thus,

* Correspondence to: Hye-A Yeom, PhD, RN, ANP-C, The Catholic University of Korea College of Nursing, 222 Banpo-daero, Seocho-gu, Seoul, 137-701, South Korea. E-mail address: yha@catholic.ac.kr

maintaining an optimal level of mobility is important for preventing disability and improving quality of life in older adults.

Of the types of mobility, walking indicates sound exercise capacity and significantly impacts the functional independence of older adults [3,6]. The validity of walking capacity as an indicator for basic mobility function has been well established [7—8]. Due to the negative influence of impaired mobility on functional ability, the prevalence and risk factors for limited mobility in various populations have been addressed, although little research focused on reporting the levels of mobility in Asian groups, including older Koreans. For example, a cutoff of 400 meters has been established as an international consensus in 6-minute walk test (6MWT) [5]. However, its validity as a cutoff-point for screening limited mobility among Asian elderly who may have different step length and gait speed from their Western cohorts still needs to be examined for the

http://dx.doi.org/10.1016/j.anr.2014.09.005

p1976-1317 e2093-7482/Copyright © 2015, Korean Society of Nursing Science. Published by Elsevier. All rights reserved.

development of a more valid international standard in mobility function of older adults.

Major theories on mobility propose that disablement process from limited mobility is affected by extra-individual and intra-individual factors [9—10]. Extra-individual factors include environmental context, including access to medical care and social resources for maintaining mobility. Intra-individual factors consist of comorbidity, physical symptoms, psychosocial factors like coping skills and motivation to move, and lifestyle factors [11]. While older age and co-morbid illnesses are well known risk factors for impaired mobility, lifestyles and individual characteristics of racially diverse geriatric groups have not been widely examined of their roles in preserving mobility [11].

It has been proposed that physical symptoms, such as chronic pain and fatigue, decrease physical performance in community-dwelling older adults [12]. Significance levels of fatigue limit an older adult's physical capacity and the energy needed to maintain optimal daily function [13]. While their impacts on the overall health of older adults are substantial [14], their specific link with mobility has not been clarified, with mixed research findings. For example, increased levels of fatigue have been found to relate to slower walking speed [15], but fatigue has also been reported to be not associated with ambulatory mobility [16]. Research on the role of physical symptoms in mobility is still limited, and therefore, a specific relationship has not been identified.

Of the lifestyle factors, sleep disturbance is one of the most common complaints of older adults, and is negatively associated with their physical and mental health. The prevalence of sleep disturbance is about 30% in the general public [17] and 40% in older adults [18]. Sleep disturbance is a multidimensional geriatric syndrome that is closely related to health-related quality of life, activities of daily living, and frailty in older adults [19—21]. It is generally known that chronic illnesses and daytime inactivity may trigger chronic sleep disturbance [18,21]. However, in the field of mobility, the relationship between sleep duration and mobility is still controversial. For example, shorter night sleep duration in older adults has been associated with both increased and decreased gait speed, suggesting an incomplete conclusion on their link [22—23]. Underlying mechanisms for the interplay between sleep profiles and mobility function still need to be further identified [22]. Particularly, further research on the sleep of frail older adults remains to be conducted [24].

A gap in the literature is ways in which older adults' perceived sleep patterns are associated with their physical activity behavior and mobility function, and which aspects of sleep disturbances are linked to declines in their mobility. Known correlation between symptoms and function [25] also leads to the belief that physical symptoms such as pain and fatigue could be associated with daytime frailty, possibly resulting in reduced mobility in older adults. An understanding of the symptom and lifestyle correlates of mobility in older adults, which are modifiable factors, is necessary to develop effective intervention strategies that would improve the mobility of this cohort group. Thus, this study aims to describe the levels of mobility in community-dwelling older Koreans with chronic illnesses, and to examine the associations of their mobility with lifestyle factors (sleep patterns, physical activity) and physical symptoms (fatigue, pain).

Methods

Study design

This study used a cross-sectional descriptive study design.

Setting and sample

The participants were a total of 387 community-dwelling older adults recruited from three senior centers in Seoul, Korea. This sample size was estimated based on a significance level of .05, a power of .80, and effect size of 0.15 [26]. This sample size also meets the minimum requirement of the ratio of 15:1, the ratio of valid cases to a predictor variable for multiple regressions [27]. The total number of predictors used in this study was 11. For inclusion in the study, a participant had to be aged 65 years or over, community-dwelling, diagnosed with one or more chronic illnesses, and have the ability to understand oral instructions. Persons who met the eligibility criteria reviewed and signed the informed consent form. The final data analyzed included a total of 384 participants after excluding three incomplete surveys with missing values over one third of the total number of variables.

Ethical consideration

This study was approved by the Institutional Review Board of the Catholic University of Korea (IRB approval no. MC12QISI0105). All participants voluntarily agreed to participate in the study. Data confidentiality and survey procedures were reviewed with each participant before the interview. Researchers assured participants that the contents of the interview would be used solely for research purposes. The data were collected after the approval from the Institutional Review Board.

Measurements

General characteristics included gender, age, religion, education, monthly income, and number of family members. Number of medication was not included as a variable. Disease-related variables included prevalence of heart and lung diseases, type and number of chronic illnesses, and medication status. Specifically, participants' medical problems or chronic illnesses were assessed using a self-reported single question: "Please tell us all types of chronic disease that you have been diagnosed with at hospitals or clinics."

Mobility was measured using the 6MWT [28]. It is a performance-based assessment that measures the maximum distance one can walk within 6 minutes at a usual gait speed. The 6MWT incorporates both gait speed and step length into the result and is a reliable and valid measure for assessing the level of mobility in community-dwelling older adults [5,8,29]. A participant's 6MWT was assessed by multiplying the person's stride length and number of walking steps. A walking step was counted using a pedometer. Each participant was instructed to perform the 6MWT in the flat hallway of the senior centers. The participants were allowed to rest or stop the test at any time.

Physical activity behavior was measured with a binary category (regular physical activity vs. sedentary). Participants were classified as engaged in regular physical activity using the classification of American College of Sports Medicine that defined a regular physical activity as engagement in a moderately intense walking or aerobic exercise at least three times a week for 20 minute at a time [30].

Sleep profiles, assessed with four categories including main sleep period, sleep hours, and perception on sleep quality in depth and duration, were measured using components of the English/ Spanish translated and validated Sleep Heart Health Study Sleep Habits Questionnaire [17,31]. Main sleep period was assessed by asking a single question "When is your main sleep period?" with possible responses of "night", "day", or "sometimes in the day and sometimes at night". Sleep hours were assessed by hours of sleep per night during the week. Perception of depth of sleep as a component of sleep quality was measured by the question "In

Table 1 Mobility in Relation to General Characteristics (N = 384).

Characteristics n (%) or M ± SD M ± SD Mobility t/F p

Male 94 (24.5) 192.66 ± 98.35 2.29 .023*

Female 290 (75.5) 217.85 ± 90.96

Age (yr) 72.0 ± 5.82 246.68 ± 97.51ab

65-69 85 (22.2) 13.28 <.001*

70-79 211 (55.1) 212.32 ± 89.04ac

> 80 87 (22.7) 175.54 ± 87.13bc

Religion

Protestant 100 (26.0) 210.35 ± 84.79 2.47 .062

Roman Catholic 84 (21.9) 203.60 ± 90.81

Buddhism 88 (22.9) 234.62 ± 102.96

Other 112 (29.2) 201.88 ± 91.85

Education

Primary school 183 (48.0) 200.42 ± 87.94 2.21 .087

Middle school 85 (22.3) 226.04 ± 96.27

High school 91 (23.9) 223.35 ± 97.90

College 22 (5.8) 197.60 ± 103.14

Monthly income

< $900 332 (86.5) 205.17 ± 92.74 3.51 .001*

> $900 52 (13.5) 253.29 ± 86.85

No. of family members 2.39 ± 1.44

1 117 (30.5) 207.45 ± 87.57 1.21 .300

2 142 (37.1) 221.27 ± 99.88

> 3 124 (32.4) 204.76 ± 91.00

Cardiovascular problem (heart failure, CHD, etc. )

Yes 49(12.8) 183.53 ± 98.30 2.27 .024*

No 335 (87.2) 215.80 ± 92.01

Respiratory problem (bronchitis, asthma, etc.)

Yes 18 (4.7) 167.63 ± 71.51 2.06 .040*

No 366 (95.3) 213.85 ± 93.81

Hypertension

Yes 260 (67.7) 206.02 ± 92.25 2.63 .106

No 124 (32.3) 259.05 ± 89.80

Arthritis

Yes 196 (51.0) 211.15 ± 92.84 0.02 .898

No 188 (49.0) 212.24 ± 94.08

Diabetes mellitus

Yes 104(27.1) 202.52 ± 92.90 0.04 .833

No 280 (72.9) 215.08 ± 93.42

No. of chronic diseases 3.12 ± 1.16

Medication status 2.30 ± 1.17

Yes 343 (89.3) 206.02 ± 92.25 3.49 .001*

No 41 (10.7) 259.05 ± 89.80

Note. CHD = coronary heart disease.

a,b,c Scheffe test: means with the same letter are significantly different. *p < .05.

general, how would you rate the depth of your sleep?" Possible responses include "light — I wake up too easily," "somewhat light — I wake up easily," "moderate — I sometimes wake up, but not easily," "somewhat deep — I sleep well," and "deep — I sleep very well." The first three responses (light to moderate) were categorized as light sleep and the last two responses (somewhat deep and deep) were categorized as deep sleep. Perception on sleep duration as a component of sleep quality was ascertained by the question "In general, how would you rate the duration of your sleep time?" Possible responses include "short", "somewhat short", "moderate", "somewhat restful", and "restful". The first three responses (short to moderate) were categorized as short sleep duration and the last two responses (somewhat restful and restful) were categorized as long sleep duration.

Fatigue was measured using a visual analogue scale (VAS) [32]. The zero point at the left end of the line was scored as 0, indicating no fatigue at all, and the 10 at the right end of the line was scored as 10, indicating a maximum level of fatigue one can experience. The higher the score, the more fatigue the person reported.

Pain was measured using VAS [32] with a range from 0 (no pain) to 10 (maximal level of pain one can experience). The higher the score, the more pain the person reported.

Data collection

Participants were recruited from three senior centers located in Seoul metropolitan areas. Upon the agreement by the directors of the senior centers on data collection, a verbal announcement was made by the investigators to elders at the senior centers regarding the research purpose and overall study procedure. Individual interview schedules were arranged for persons who were interested in participating in the study and signed informed consents. Then face-to-face interviews were conducted in a private room at the senior centers. Upon the completion of the interview, each participant was instructed to perform the 6MWT in the flat hallway of the senior center. There were no seasonal variations in the participants' responses and performance as the entire data collection was conducted in an indoor setting. The data were collected from July to December 2012 by a research assistant. The average time

Table 2 Mobility in Relation to Lifestyle Profiles (N = 384).

Variables

Mobility

n (%) or M ± SD

M ± SD

6MWT (m)

Fatigue

Regular physical activity Yes No

Main sleep period Night Day

Mixture of day & night Sleep depth

Deep Sleep duration Short Long

212.68 ± 93.33 4.47 ± 1.97 4.64 ± 2.14

302 (78.6) 82 (21.4)

372 (97.4) 4(1.0) 6(1.6)

245 (64.1) 137 (35.9)

124 (32.5)

218.68 ± 91.24 185.91 ± 96.90

212.20 ± 94.04 165.85 ± 64.43 204.19 ± 93.35

202.93 ± 87.26 227.08 ± 101.85

192.91 ± 89.16 221.08 ± 93.98

Note. 6MWT = 6-minute walk test. *p < .05.

spent on the completion of a survey was about 20-30 minutes per participant. Each participant was compensated the equivalent of US$5 in Korean won for their participation in the study.

Data analysis

Data were analyzed using IBM PASW Statistics 18.0, Chicago, IL, USA. Descriptive statistics were calculated for all study variables. Associations of walking mobility with demographic and clinical characteristics were tested using t test and analysis of variance with the Scheffe post hoc test. The correlations of walking mobility with sleep disturbance, fatigue, and pain were tested using Pearson's correlation coefficients. Predictors of walking mobility were examined using hierarchical regression techniques. Nominal variables with dichotomous responses were dummy-coded to be included in the multiple regression analysis.

Results

The mean age of the participants was 74 years (SD = 5.82), ranging from 65 to 91 years. The majority of the participants were women (n = 290; 75.5%), primary school graduates (n = 183, 48.0%), and had a monthly income below $900 in Korean won converted to US dollars (n = 332, 86.5%). Twenty-six percent of the participants were Protestant (n = 100, 26.0%) and 30% of the participants (n = 117) were living alone. The average number of family members was 2.39, ranging from 1 to 7. Hypertension was the most prevalent chronic illness (n = 260, 67.6%) followed by arthritis (n = 196, 51.0%), spinal stenosis/herniated disc (n = 113,29.4%), and diabetes mellitus (n = 104; 27.1%). The average number of chronic illnesses in the participants was 3.12 with a range from 1 to 7. About 89% of the participants (n = 343, 89.3%) reported they were currently taking medications for managing their chronic illnesses, with the average number of medications at 2.3, ranging from 1 to 7 (Table 1).

The mean 6MWT distance was 212.68 meters (SD = 93.33), with a range from 23.43 to 517.12 meters. The mean 6MWT distance was 217.85 meters in women and 192.66 meters in men, indicating that women showed a significantly higher walking mobility than did men (t = 2.29, p = .023). During a 6-minute walk, 97% of participants (n = 373) walked less than 400 meters. By age groups, the 6MWT distance were 246.68 meters for persons in their 60s, 212.32 meters for persons in their 70s, and 175.54 meters for persons in

their 80s, showing a gradual decrease with advance in age (F = 13.28, p < .001). Respondents who had more monthly income ($900 or more) showed significantly higher scores in 6MWT than did participants in the lower income bracket (below $900) (t = 3.51, p = .001). The 6MWT distances were significantly lower among participants with cardiovascular problems (t = 2.27, p = .024), respiratory problems (t = 2.06, p = .04), or were taking medications (t = 3.49, p = .001) compared with their counterparts without cardiorespiratory diseases or medication intake (Table 1).

Approximately 78.6% (n = 302) of the participants reported they engaged in regular physical activity at least three times a week. A total of eight types of physical activity were reported by the participants, including walking, dance, stretching, yoga, ping pong, swimming, climbing, and playing musical instruments. The most prevalent type of physical activity was walking (n = 183, 47.7%), followed by dance (n = 52, 13.5%) and ping ping (n = 50, 13.0%). There was an association between level of mobility and regular physical activity behavior. Participants who engaged in regular physical activity showed a higher level of mobility than did participants who did not engage in regular physical activity (t = 2.85, p = .005) (Table 2).

The majority of the participants reported night as the main sleep period (n = 372, 97.4%). For those reported night as their main sleep period, the mean hours of sleep per night during the week was 5.93 hours (SD = 1.74) with a range from 1 to 11 hours. Mobility was significantly associated with participants' perceptions of the quality of their sleep depth and duration. Participants who rated the quality of their sleep as deep showed a higher level of mobility than those reporting their depth of sleep as light (t = -2.44, p = .015). Participants who perceived their sleep duration as long also reported a higher level of mobility than persons who perceived their sleep duration as short (t = -2.79, p = .006) (Table 2).

The mean VAS score was 4.47 for fatigue (SD = 1.97) and 4.64 for pain (SD = 2.14), with a range from 0 to 10, suggesting a moderate

Table 3 Correlations between Mobility and Fatigue, Pain, and Sleep Disturbance (N = 384).

Variables Fatigue Pain Sleep disturbance

Mobility -.18** -.17** -.10*

Fatigue .51** .41**

Pain .32**

Note. *p < .05. **p < .01.

Table 4 Factors Affecting Mobility in Older Adults with Chronic Illnesses.

Variables

Adjusted R2

Step 1 Age

Gendera (1 = men) Monthly incomea (1 = over $900) Cardiovascular diseasea (1 = yes) Respiratory diseasea (1 = yes) Step 2 Age

Gendera (1 = men)

Monthly incomea (1 = over $900)

Cardiovascular diseasea (1 = yes)

Respiratory diseasea (1 = yes)

Taking medicationa (1 = yes)

Fatigue

Regular physical activitya (1 = yes) Sleep depth Sleep duration

-4.28 -14.82 32.23 -29.59 -41.43

-3.92 -19.82 27.67 -19.62 -39.01 -38.34 -0.81 -3.37 22.67 0.05 7.66

0.81 10.55 13.81 13.43 21.33

0.82 10.69 13.95 13.38 21.08 14.72 2.57 2.79 10.99 4.28 4.05

.27 .07 .12 .11 .09

- 1.40 2.33

-2.20 -1.94

-4.80 -1.85 1.98

- 1.47 -1.85 -2.60 -0.31 -1.21

2.06 0.01 1.89

.000 .161 .020 .028 .053

.000 .065 .048 .143 .065 .010 .754 .228 .040 .990 .060

11.72*

Note**p < .01. a Dummy coded.

level of fatigue as well as pain for respondents (Table 2). A higher level of mobility was correlated with lower levels of fatigue (r = -.14, p = .006) and pain (r = -.14, p = .005) (Table 3).

Hierarchical regression analyses were conducted to explore the influence of physical symptoms and lifestyle variables on mobility. Independent variables found to be significantly associated with mobility in primary analysis using t test and analysis of variance, and Pearson's correlation were entered as predictors in the regression model. Examination of the assumptions of multiple regressions showed that the variance inflation factors was not larger than 10, ascertaining multicollinearity of all variables. Linearity, normality, and equal variance of the equation model were confirmed by residual analysis. Two-step hierarchical regressions were conducted. The order of entry of the independent variables included nonmodifiable correlates (i.e. age, gender, monthly income, and comorbidity) for Step 1, and physical symptoms (i.e., pain, fatigue) and lifestyle factors (i.e., regular physical activity, sleep patterns, medication status) for Step 2. The first hierarchical regression equation resulted in 12% of the explained variance in mobility. Addition of physical symptoms and lifestyle factors into the equation increased only 4% of the variance, resulting in 16% of the explained variance in mobility. Significant predictors of mobility included younger age (b = -.24), higher income (b = .10), taking no mediation (b = -.13), and regular physical activity (b = .10) (Table 4).

Discussion

This study aims to report the level of mobility in community-dwelling older Koreans and to examine its demographic, lifestyle, and symptom predictors in this population. The overall level of their mobility was poor, with an average 6MWT distance of 211 meters. This level of mobility in Koreans is lower than the 359 meters in the Finnish population and the 440 and/or 480 meters in the US sample [8,29]. The participants of these studies were homogeneous and comparable to those of the present study in that they included community-dwelling, independently functioning older adults as participants. Over 90% of community-dwelling older Koreans in this study were classified as having impaired mobility (n = 373) using 400 meters as the cutoff point diagnostic criterion of normal mobility in 6MWT [7]. A question may be raised as to whether this lower level of mobility in older Koreans compared with Western samples results from congenital differences in gait

speed and stride length among the racial groups or from a possible problem of limited sample generalizability in this study. The next step of exploration should include a cross-cultural comparison of mobility in different cohort groups and/or repeated multicenter trials for older Koreans with a larger community sample in order to provide clearer evidence on the "norm" value of mobility in older Koreans.

In this study, advanced age was associated with decreased mobility; 6MWT distance was the lowest among those aged over 80 years. This role of older age in decreasing mobility function has also been reported by previous studies [1,8], suggesting that older old group is a vulnerable population who needs mobility intervention primarily. By gender, older women showed a significantly higher mobility than did men, which is not consistent with the findings of previous research reporting higher levels of mobility in men than women [1,8]. Longer 6MWT distances are usually observed in men who may have a longer stride length and therefore longer 6MWT distances than women but are also found in those who are highly motivated to move [7]. The significance role of motivational factors in mobility limitation has been supported by previous research [11], proposing a possibility of older Korean women as a physically frail but highly motivated and physically active group. To date, data examining the role of motivational factors in maintaining mobility function in older adults have been limited. Further exploration on the role of gender and internal motivation for walking in mobility function of older adults needs to be conducted in the future studies.

The findings of this study showed that mobility is significantly associated with regular physical activity behaviors, suggesting that engagement in regular physical activity at least three times a week for 20 minutes at a time may help increase the walking capacity of older adults. This finding appears consistent with the view that regular physical activity has a positive impact on mobility function in older adults [33]. This study also has significant implications related to the linkage of sleep patterns and mobility in older adults. The findings of this study showed that those perceiving their sleep quality as good and their sleep duration as long reported higher levels of mobility, suggesting that improving perception of sleep quality in older adults may increase the daytime walking capacity of older adults. This finding is consistent with the previous view that self-reported poor sleep quality is associated with lower levels of physical performance and greater levels of frailty in community-dwelling older adults [19,22]. It should be emphasized that when educating older adults with chronic illnesses that they need to

engage in regular physical activity, minimize daytime fatigue as much as possible, and make efforts to have sufficient volume of sleep during the night in order to maintain their mobility function.

Although daytime physical activity is known to affect objective parameters sleep quality such as sleep-wave in the elderly [34], the complex mechanisms on the interplay among sleep patterns, daytime activities, and mobility function in older adults are not well understood. More research is needed on whether the link of mobility with perceived sleep quality and volume found in this study can be confirmed with objective measures of sleep quality (e.g., polysomnography) and how nighttime sleep quality impacts daytime physical performance, including walking capacity, while controlling for baseline comorbidity and age in older adults.

It is generally well recognized that fatigue and pain negatively impact the physical function of older adults [7,14,35]. In this study, increased fatigue and pain were significantly correlated with reduced mobility of older adults, which is consistent with the view that worsening of these physical symptoms is negatively associated with mobility function [12,15,23,25,35] but is not consistent with the findings of a previous study where fatigue and mobility were not associated with each other [16]. These mixed findings reflect the need for additional attention to the role of physical symptoms in the mobility level of older adults in the community in the future. As pain and fatigue are modifiable factors, researchers may also focus on examining the effects of the management of these symptoms on improving mobility function in older adults in future studies.

Based on the prediction model, a high-risk group for mobility limitation identified in this study includes low-income, sedentary elderly who take multiple prescribed medications on a daily basis. As expected, age was the most powerful predictor of physical mobility in community-dwelling older adults with chronic illnesses. While pain is a known predictor of mobility function [25], it was not a significant factor with explanatory power in the prediction model of mobility in older Koreans in this study. Whereas a set of variables including older age, taking mediation, sedentary lifestyle, and monthly income below $900 contributed significantly to the prediction model, they account for only 16% of the variance in mobility, suggesting that there should be more efforts to find powerful, latent factors explaining more variance in mobility function of older Koreans. Use of a causal modeling approach, such as structural equation modeling, may help estimate relationships of mobility with a variety of its known correlates in the literature in a more precise way in future research.

This study has several limitations. The major ones are the lack of a causal-relationship among variables by the use of a cross-sectional design and limited generalizability of the findings due to the collection of the data from one group of older adults. Since the sample of this study was a group of ambulatory, community-dwelling older adults recruited from three senior centers in Seoul metropolitan areas, there could be a selection bias and the findings should not be generalized to the disabled, institutionalized, or Korean elderly residing in other regions of Korea. Additionally, emotional factors such as depression and anxiety were not included as variables in the current study. These psychological factors should be incorporated into the pool of independent variables in future research in order to describe more cohesive pictures of mobility in older adults. Other lifestyle markers such as obesity, measured using BMI, or smoking behaviors need to be considered as predictors of mobility in future studies. Nevertheless, the findings of this study add to the volume of knowledge on geriatric mobility by addressing prevalence of mobility limitation in older Koreans, an understudied geriatric group, and general and lifestyle correlates of their walking mobility.

Conclusion

In conclusion, the mean walking capacity of community-dwelling older Koreans with chronic illnesses measured with the 6MWT is approximately 212 meters. A high-risk group for mobility limitation includes low income, sedentary older men who are at risk for increased fatigue and sleep deficit. Older adults aged over 80 years are a vulnerable group who needs mobility intervention primarily. Regular physical activity, reduction of daytime fatigue, and improvement of sleep quality through better perception of sleep volume could be sound strategies for preserving mobility in older adults. Further research should focus on cross-cultural comparisons of the levels of mobility in community-dwelling older adults and incorporate other lifestyle factors such as smoking, drinking behavior, and/or obesity into the prediction model of mobility to generate specific intervention strategies for mobility enhancement recommendations for older adults.

Conflict of interest

The authors have no conflict of interest to declare.

Acknowledgment

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (grant no. 5-2013-A0154-00071) and the Catholic Medical Center Research Foundation made in the program year of 2011 (grant no. 5-2013-B0001-001; IRB approval no. MC12QISI0105). These sponsors had no involvement in the research process.

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