Life-space mobility and social support in elderly adults with orthopaedic disorders
The purpose of this cross-sectional survey was to explore relationships between life-space mobility and the related factors in elderly Japanese people who attend orthopaedic clinics. The study measures included surveys of life-space mobility (Life-space Assessment (LSA) score), social support (social network diversity and social ties), physical ability (instrumental self-maintenance, intellectual activity, social role), orthopaedic factors (diseases and symptoms) and demographic information. The questionnaire was distributed to 156 subjects; 152 persons responded, yielding 140 valid responses. Mean age of the sample was 76.0 ± 6.4 (range, 65–96 years), with 57.9% women (n = 81). In a multiple regression analysis, the six factors were significantly associated with LSA. Standardized partial regression coefficients (β) were gender (0.342), instrumental self-maintenance (0.297), social network diversity (0.217), age (−0.170), difficulty of motion (−0.156) and intellectual activity (0.150), with an adjusted R2 = 0.488. These results suggest that outpatient health-care providers need to intervene in not only addressing orthopaedic factors but also promoting social support among elderly Japanese.
Japan is facing large demographic changes with an increasing elderly adult rate and a declining birth rate. As a result, the challenge to extend healthy life expectancy is very important. According to the Comprehensive Survey of Living Conditions in 2010, many elderly people have orthopaedic disorders that affect the back and major joints such as the hips and shoulders. Characteristics of orthopaedic problems are pain, deformity and limited range of motion that negatively affect self-care and activity. When activity is reduced, the results are muscle atrophy or cardiopulmonary function decline. In addition, the individual has an increased risk of entering a nursing home. Reduced activity status also affects mental status and can lead to cognitive decline. Therefore, nurses must consider orthopaedic diseases and symptoms and rehabilitation of physical ability as well as daily activity. However, activity status might not be the same for every orthopaedic patient even if they had the same disease or symptoms.
There are many factors other than orthopaedic function that affect daily activity, such as age, gender and marital status. Social support is also considered a significant predictor of activity status.[4, 5] Although there are many aspects of social support, in this study we focused especially on social network and social integration. Broman showed that fewer social relationships lead to poorer health behaviour, and conversely, more social relationships lead to better health behaviour. Cohen and Janicki-Deverts also showed that researchers found the most consistent and provocative results in a group of studies focused on social integration (one's membership to a diverse social network). The Alameda Country study[8, 9] was pioneering research on social networks. This study indicated that people who have more types of relationships (i.e. being married, having close relatives, friends, and belonging to some groups) have lower mortality rates and carry out proper health behaviour. Subsequent studies suggest that social support has favourable effects on health.[4, 10-12] Likewise in Japan, Arai et al. showed that elders who exercise habitually contact their neighbours more frequently and join more social activities.
This aim of this study was to explore the relationships between life-space mobility, related factors and social support in elderly Japanese people with orthopaedic disorders.
This paper describes a cross-sectional study using a convenience sample of elderly Japanese. Subjects were 156 elderly (> 65 years of age) outpatients of two orthopaedic clinics from a city of approximately 964 000 people in Japan.
The internal review committee of the School of Nursing at Chiba University, Japan, approved the research protocol. The researcher explained that participants were free to cooperate or decline, their care in the clinic will not be affected even if they declined taking part in the study and that they could refuse to participate anytime. Verbal consent was given by responding to the questionnaire. Furthermore, collected data were maintained on password-protected computers and participant's data were de-identified.
The investigator asked elderly patients to cooperate in the study at waiting rooms of orthopaedic clinics. After participants' consent, a paper-and-pencil questionnaire was distributed to them. If participants needed support for answering the survey, the investigator helped them by reading the questions or marking the survey. The survey took approximately 20 min to complete. Approximately 20% of participants required assistance with reading due to vision problems or marking the answers due to problems with manual dexterity. Participants answered the questionnaire immediately or after returning home. The data were collected over one month during 2012.
This study used a five-page paper-and-pencil survey. The measures included scales to capture demographic data (age, gender, marital status and family structure), orthopaedic factors, physical ability, social support and life-space mobility.
Orthopaedic factors refer to orthopaedic diseases and their symptoms. Disorders that comprise orthopaedic diseases are spine disease, knee joint disease, lower back pain, shoulder disease, osteoporosis, rheumatoid arthritis, fractures, sprains and others. Items for symptoms are pain, difficulty of motion and not feeling power. Whereas in a clinical orthopaedic setting, ROM (range of motion) and MMT (manual muscle testing) are used for assessment, we used ‘difficulty of motion’ instead of ROM, and ‘not feeling power’ for MMT.
We used the Tokyo Metropolitan Institute of Gerontology Index of Competence (TMIG) for physical assessment. The TMIG refers to Lawton's hierarchy of activity competence, and it measures Instrumental Activities of Daily Living (IADL) and higher physical abilities than IADL. The TMIG is composed of three subscales: Instrumental Self-Maintenance (five items), Intellectual Activity (four items) and Social Role (four items). Each item is assessed on a dichotomous scale (yes or no). In the factor analysis to determine the question items, factor structure was clear and analysis results were similar to the pilot study. This scale's reliability coefficient (α) was 0.913 and also all subscales had high α. The higher the score, the higher the physical ability.
Social support refers to social network diversity and social ties. The Cohen's Social Network Index (SNI) was used to measure social network diversity and social ties.[10, 16, 17] Social network diversity refers to the number of high-contact roles. This is the number of social roles in which the respondent has regular contact (at least once every 2 weeks) with at least one person. The maximum number of high-contact roles is 11. They are: spouse, parent, parent-in-law, child, close relative, close friend, church/temple member, employee, neighbour, volunteer and group member. For each of the 11 possible high-contact roles, we assigned a zero if the respondent did not have the role and a one if he/she does. Social ties are the total number of people with whom the respondent has regular contact (at least once every 2 weeks) for each of the 11 possible roles. The number determines the strength of social ties. The total number of people in the social network was computed by summing across the 11 roles.
We used the Life-space Assessment (LSA), developed by Patricia S. Baker et al., to assess life-space mobility.[18-20] The test–retest reliability over the short term were greater than 0.86. Harada et al. developed the Japanese version of LSA, and then they demonstrated its validity. The LSA was used to derive a score based on reported movement distance for 4 weeks preceding the assessment. The five life-space levels ranged from the bedroom to out of town: (i) rooms of the home other than the bedroom; (ii) an area outside your home, such as your porch deck, patio, hallway (of an apartment building), garage, your own yard or driveway; (iii) places in your neighbourhood other than your own yard or apartment building; (iv) places outside your neighbourhood, but within your town; and (v) places outside your town. Participants were asked how often they spent in each area (less than once a week, 1–3 times each week, 4–6 times each week,or daily) and whether they required assistance from another person or from an assistive device (yes or no). The LSA scores ranged from 0 (totally room bound) to 120 (travelled out of town every day without assistance), with lower scores reflecting lower life-space mobility.
The relationships between LSA and other measurements were examined using t-test and correlation analysis. We conducted multiple regression (stepwise) analysis assigning LSA score as dependent variables and variables that were significantly different in former bivariate analysis as independent variables. SPSS Statistics18.0 (IBM Corporation, Armonk, NY, USA) was used for all statistical analysis.
Questionnaires were distributed to 156 subjects; 152 (97.4%) participants responded and data from the 140 (92.1%) who completed the surveys were analysed.
Characteristics of participants are displayed in Table 1. Eighty-one participants (57.9%) were women, and mean age was 76.0 ± 6.4 years (range, 65–96 years). Ninety-five participants (67.9%) were married and 28 (20.0%) were living alone.
Table 1. Characteristics of participants in elderly people who have orthopaedic disease
|Demographic data|| || || |
| Age||76.0 ± 6.4||74.7 ± 5.3||77.0 ± 7.0*|
| Spouse (yes)||95 (67.9)||53 (89.8)||42 (51.9)**|
| Living alone||28 (20.0)||4 (6.8)||24 (29.6)**|
|Orthopaedic factors|| || || |
| Lower back pain||78 (55.7)||33 (55.9)||45 (55.6)|
| Knee joint disease||46 (32.9)||12 (12.3)||34 (42.0)**|
| Spine disease||20 (14.3)||10 (16.9)||10 (12.3)|
| Osteoporosis||15 (10.7)||1 (1.7)||14 (17.3)**|
| Rheumatoid arthritis||3 (2.1)||0 (0.0)||3 (3.7)|
| Pain||113 (80.7)||46 (78.0)||67 (82.7)|
| Difficulty of motion||94 (67.1)||43 (72.9)||51 (63.0)|
| Not feeling power||68 (48.6)||32 (54.2)||36 (44.4)|
|Physical ability|| || || |
| TMIG||11.0 ± 2.1||11.0 ± 2.1||10.9 ± 2.1|
| Instrumental self-maintenance||4.5 ± 1.0||4.5 ± 1.0||4.5 ± 1.0|
| Intellectual activity||3.5 ± 0.8||3.5 ± 0.8||3.5 ± 0.8|
| Social role||3.0 ± 1.1||3.0 ± 1.1||2.9 ± 1.1|
|Social support|| || || |
| Social diversity||4.5 ± 1.6||4.4 ± 1.8||4.5 ± 1.5|
| Social ties||11.1 ± 7.6||10.1 ± 8.0||11.9 ± 7.3|
|Life-space mobility|| || || |
| LSA||76.9 ± 26.5||88.0 ± 24.2||68.8 ± 25.3|
The largest orthopaedic disease was lower back pain in 78 people (55.7%). Forty-six (32.9%) had knee joint disease. There were no age differences to each disease; however, there were significantly more women who had knee joint disease and osteoporosis than men. As for orthopaedic symptoms, 113 participants (80.7%) had pain, 94 (67.1%) had difficulty of motion and 68 (48.6%) had no feeling power.
Mean TMIG was 11.0 ± 2.1 (range, 4–13 points). In subscales, the mean of instrumental self-maintenance was 4.5 ± 1.0 (range, 0–5 points), intellectual activity was 3.5 ± 0.8 (range, 0–4 points) and social role was 3.0 ± 1.1 (range, 0–4 points).
The mean of social network diversity was 4.5 ± 1.6 (range, 1–8); there were no significant differences in gender and age. The mean of social ties was 11.1 ± 7.6 (range, 0–44). There was no difference between genders; however, the score lowered as age rose.
Mean LSA was 76.9 ± 26.5 (range, 12–120); 88.0 ± 24.2 for men and 68.8 ± 25.3 for women. Figures were significantly different between men and women regarding LSA. On the other hand, LSA score lowered as age rose.
Association between LSA score and each variable
Tables 2-4 show results of bivariate analysis. As for the t-test between LSA and measures of orthopaedic factor, the LSA score was significantly lower in people who had knee joint disease and difficulty of motion. As for not feeling power, the LSA score was significantly lower in women. For Pearson correlation between LSA and physical ability and social support, all variables showed significantly high correlation.
Table 2. Bivariate analyses: LSA and physical factor
|Gender||Men||88.0 ± 24.2|
|Women||68.8 ± 25.3**|
|Age|| ||r = −0.403**|
|Knee joint disease||Yes(32.9)||70.0 ± 28.0|
|No (67.1)||80.3 ± 25.3*|
|Back pain||Yes(55.7)||75.5 ± 25.5|
|No (44.3)||78.7 ± 27.9|
|Pain||Yes(80.7)||77.0 ± 27.0|
|No (19.3)||76.4 ± 25.0|
|Difficulty of motion||Yes(67.1)||73.5 ± 27.2|
|No (32.9)||83.8 ± 24.0*|
|Not feeling power||Yes(48.6)||73.8 ± 29.2|
|No (51.4)||79.8 ± 23.5|
Table 3. Bivariate analyses: LSA and physical ability
|TMIG||r = 0.548**|
|Instrumental self-maintenance||r = 0.487**|
|Intellectual activity||r = 0.357**|
|Social role||r = 0.348**|
Table 4. Bivariate analyses: LSA and social support
|Social diversity||r = 0.425**|
|Social tie||r = 0.332**|
Multiple regression analysis
Table 5 shows factors significantly related to LSA scores in the stepwise multiple regression. The stepwise method was used to determine the best combination of demographic, orthopaedic, TMIG and social support factors to account for LSA score. The multiple correlation coefficient was 0.714, R2 was 0.510 and adjusted R2 was 0.488. The model explains 48.8% of the LSA score variance. Factors retained in the final model were gender (β = 0.342, P < 0.01), instrumental self-maintenance (β = 0.297, P < 0.01), social network diversity (β = 0.217, P < 0.01), age (β = −0.170, P < 0.05), difficulty of motion (β = −0.156, P < 0.05) and intellectual activity (β = 0.150, P < 0.05).
Table 5. Multiple regression analysis
|Gender (1 = men, 0 = women)||0.342**|
|Instrumental self-maintenance (range, 0–5)||0.297**|
|Social network diversity (range, 0–11)||0.217**|
|Age (5-year age group)||−0.170*|
|Difficulty of motion (1 = yes, 0 = no)||−0.156*|
|Intellectual activity (range, 0–4)||0.150*|
In this sample of elderly adults with orthopaedic disorders, 10 variables had significant association with the LSA score in the bivariate analysis. Those were gender, age, knee joint diseases, difficulty of motion, not feeling power, all subscales of TMIG (instrumental self-maintenance, intellectual activity and social role), social network diversity and social ties. As a result, six variables were selected for regression analysis (stepwise analysis). The independent variables were the 10 variables above and the dependent variable was LSA. The LSA items were gender, instrumental self-maintenance, social network diversity, age, difficulty of motion and intellectual activity.
The factor that had the strongest effect predictor of activity level was gender. Women had less LSA score than men. It is often considered that cross-sectional surveys of elderly people indicate that disabilities increase with age, and women have more disabilities than men.[22-24] Women's activities are limited because they are more prone to knee joint disease or other disabilities. They often live longer than men. In addition, in Japan, Seiza (sitting on the knees) is a common posture associated with tatami mats and remains the traditional sitting position when practising the art of flower arranging, taking part in a tea ceremony or engaging in martial arts. Especially, when women wear kimonos (traditional clothes), they have to do Seiza. However, Seiza puts a strain on the knee and can trigger a knee joint disease. We have to teach the patients to change their lifestyle if necessary. We have to note, though, that the reason for low LSA is not gender (women), but rather depends on the lifestyle practices of the person.
Instrumental self-maintenance showed the second strongest effect on LSA. According to a previous study, LSA has relationship to Activities of Daily Living (ADL) or IADL.[18, 20, 21] Our study also showed high correlation with LSA and does not differ from the aforementioned study. Koyano et al., who developed the TMIG, showed that TMIG scores decreased with older age.
In a clinical setting, we are encouraged to take full advantage of remaining physical functions and use strategies to regain physical ability in elderly adults, because orthopaedic disease might promote decline in physical ability. In the realm of social support, social network diversity has effect on LSA. As previously mentioned, social support promotes health-promoting behaviours. People who have high social network diversity particularly have many ‘roles’ and social environments. Even if they lose one role, they can feel self-worth from another role. However, in the case of those who have only one role, if he/she loses the role, he/she will lose the place of self-realization, even with a strong network tie. It might be the rationale why social network diversity remained in the stepwise analysis rather than social ties.
Thoits suggested that role identities provide people information about who they are in an existential sense. Social roles provide a purpose to life. Thus, as people accumulate role-identities, the sense that they possess a meaningful, guided existence strengthens. Cohen suggested that the ability to meet role expectations might result in cognitive benefits. An example of a benefit includes increased feelings of self-worth and control over one's environment, which could influence health through a variety of pathways. These positive impacts of social roles might promote the activity of the elderly. Social network diversity affects LSA independent of physical factors. This suggests that promoting social network diversity to promote life-space mobility is worth the challenge for elderly adults with orthopaedic health problems whose symptoms do not improve even if they have been treated at a clinic.
This study measured social support using SNI. However, social networks are different for each country, region or person. Clinic settings used in this study were located in a metropolitan city that has 964 000 people. In comparison with rural towns of the same prefecture, the city has a larger population and younger age structure than rural areas. Also, the population of the city has more adults over 65 living alone than rural areas. This suggests that important social networks are different for each generation. We need to think more about what social supports are important for senior citizens and design effective care to improve life-space mobility.
Subjects of this study were outpatients of two orthopaedic clinics in a large metropolitan city of Japan. Additional research is needed in rural towns and areas with a higher population of elders to consider this theme in more depth. On the other hand, many Japanese elders cannot move to be closer to their children and must stay where there are fewer young people. This reduces opportunities for interacting in the community. We were unable to assess the population's actual amount of activity. Therefore, further study of the population is needed.
Although we only noted the good positive aspects of social support in this study, in the future research needs to examine the negative effects of social support, such as role strain, caregiving responsibilities and negative aspects of social circles support.
This study explored the relationships between life-space mobility, orthopaedic factors, physical ability and social support in elderly Japanese people who have orthopaedic health issues. The results showed that: (i) people who have knee joint disease and difficulty of motion have low life-space mobility; (ii) there is a correlation association between physical ability and life-space mobility; and (iii) there is a correlation association between social support and life-space mobility. Results of multiple regression analysis showed that variables of LSA relates to gender, instrumental self-maintenance, social network diversity, age, difficulty of motion and intellectual activity. These results suggest that we need to intervene not only in the caring for orthopaedic disorders but also in promoting social support for elderly adults.
The authors are grateful to the participants, the elders, who cooperated and participated in this study. And we would like to express our deepest gratitude to the clinic staff who cooperated with us in doing this study.
The authors declare no conflict of interest.