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Geriatr Gerontol Int 2016; 16: 670–678
ORIGINAL ARTICLE: EPIDEMIOLOGY, CLINICAL PRACTICE AND HEALTH
Age and sex differences of risk factors of activity limitations in Japanese older adults Takafumi Monma,1 Fumi Takeda,1 Haruko Noguchi2 and Nanako Tamiya3 1
Faculty of Health and Sport Sciences, 3Faculty of Medicine, University of Tsukuba, Ibaraki, and 2Faculty of Political Science and Economics, Waseda University, Tokyo, Japan
Aim: The objective of the present study was to verify how socioeconomic and physical/mental health status would be associated with activity limitations by age and sex among older adults, using nationally representative crosssectional data in Japan. Methods: The present study focused on 8373 older adults aged 65 years or older extracted from the Comprehensive Survey of Living Conditions conducted in 2007 by the Japanese Ministry of Health, Labor and Welfare. Univariate and multiple logistic regression analyses and population-attributable risk were applied to validate the relationships of socioeconomic and physical/mental health status with activity limitations among the total population, and by age groups (young-old or old-old) and sex. Results: Mental health showed the highest odds ratio and population-attributable risk in the total population. In addition, low back pain was associated with activity limitations regardless of age and sex. Other musculoskeletal diseases, such as arthropathy and osteoporosis, were related to activity limitations for women, regardless of age, whereas cardiovascular diseases, including angina pectoris/myocardial infarction and cerebral stroke, were associated with activity limitations for men in any age group. There were no statistically significant correlations between socioeconomic status and activity limitations in any groups. Conclusion: Mental health was the most important factor of activity limitations in Japanese older adults. Furthermore, low back pain regardless of age and sex, other musculoskeletal diseases only for women and cardiovascular diseases mainly for men could also be significant risk factors to activity limitations. Therefore, preventive approaches of activity limitations considering sex differences are important for older adults in Japan. Geriatr Gerontol Int 2016; 16: 670–678. Keywords: activity limitations, aged, diseases, gender difference, mental health.
Introduction Although the longevity of Japanese older adults is well known, the gap between mean life expectancy and healthy life expectancy has been increasing: 9.13 years for men and 12.68 years for women.1 Expanding the gap would cause a decrease of quality of life among individuals, and an increase in financial burden to social security. Therefore, extending healthy life expectancy, and reducing the gap between mean life expectancy and
Accepted for publication 12 April 2015. Correspondence: Professor Nanako Tamiya Ph.D., Faculty of Medicine, University of Tsukuba, Laboratory of Advanced Research D, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8575 Japan. Email: [email protected]
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doi: 10.1111/ggi.12533
healthy life expectancy is important both for improving public health and keeping social security sustainable.1 To extend healthy life expectancy, a number of longitudinal studies have found various risk factors of disability or demands for long-term care in Japan. In particular, mental health status was a reliable predictor of disability and long-term care need.2–5 In addition, diseases under treatment3,6 and history of chronic diseases4,5 were important risk factors. Furthermore, recently some researchers reported the associations of socioeconomic status with demand for long-term care.7,8 However, these studies were investigated in specific regions. No study had ever investigated risk factors of activity limitations among a nationally representative Japanese population. Furthermore, although the Japanese Ministry of Health, Labor and Welfare (MHLW) © 2015 Japan Geriatrics Society
Activity limitations factors in elderly
suggested the necessity of adequate understanding about characteristics, needs, and health problems by life stages and sex to extend healthy life expectancy, age and sex differences of risk factors of activity limitations are still unclear.1 As there are differences of prevalence and incidence of physical and mental diseases by age and sex in older adults, the risk factors for activity limitations would also differ. Therefore, the major objective of the present study was to verify how socioeconomic and physical/mental health status would be associated with activity limitations by age and sex among older adults, using nationally representative cross-section data in Japan. In Japan, Hashimoto et al. calculated healthy life expectancy among Japanese people based on the question of activity limitations in the Comprehensive Survey of Living Conditions (CSLC), a nationally representative data carried out by the Japanese MHLW.9 The CSLC also surveys a wide range of individual and household characteristics, such as demographic, socioeconomic, physical health and mental health status; therefore, it would be one of the most proper data sources to achieve the purpose of the present study.
Methods Study population The present study used cross-sectional data from the CSLC in 2007.10 We were permitted to use the raw data from this survey by the Japanese MHLW. The CSLC was designed to obtain quantitative evidence for the planning and management for the health, labor and welfare policies. The survey was composed of five questionnaires for household, health, income, saving and long-term care. This study used data on three questionnaires for household, health and income. Participants of this survey were randomly chosen in 5440 districts from the census held in 2005. The household questionnaire and the health questionnaire covered approximately 760 000 individuals living in approximately 290 000 households among these districts, whereas the income questionnaire covered approximately 100 000 persons and approximately 40 000 households among these districts. Each participant completed questionnaires distributed by an enumerator in advance by mail, and the enumerator visited each participant’s house and collected them within a couple of days. We merged data from three questionnaires, and identified 16 850 respondents who were aged 65 years or older. Out of these, 8477 were excluded because of missing observations on variables indispensable for this study. The number of missing values of each variable was as follows: 2694 in equivalized disposable household © 2015 Japan Geriatrics Society
income, 3546 in activity limitations, 1597 in some sort of disease and 6207 in mental health. This study included 8373 older adults (valid response rate was 49.7%). We determined that an ethical review of the obtained data was not required based on the “Ethical Guidelines for Epidemiological Research” of the Japanese government.11
Measurements The activity limitations of respondents were evaluated using responses to the questions: “Is your daily life now affected by health problems?” Respondents who answered “yes” were categorized as the “activity limitations” group, and those who answered “no” were classified as the “no activity limitations” group. Socioeconomic status included age (calculated on the basis of year and month of birth), sex, living arrangement (living alone or with others) and equivalized disposable household income. Equivalized disposable household income is disposable household income adjusted for household size. This is calculated by dividing household income by equivalent household members, which is the square root of household members,12 and respondents in the present study were categorized into the high or low income group by the median. Diseases were evaluated using responses to the questions: “Do you now go to a hospital, clinic or facility of Japanese traditional massage, acupuncture, moxibustion, or judo-orthopedics for diseases or injuries?” and “What are your diseases or injuries?” The second question was for persons replying “Yes” to the first question. The responses to the second question were 39 diseases and injuries, “other disease or injury” and “unknown.” For the analyses, the “No” group in each item for the second question included respondents who answered “No” to the first question. In the present study, the top 10 responses were chosen by each group (Fig. 1). Mental health was assessed by the Japanese version of the K6 scale,13 which has been included in the CLSC since 2007. The K6 scale, a screening scale for psychological distress, is a powerful measurement to discriminate between community cases and non-cases of Diagnostic and Statistical Manual 4th edition disorders.14 Respondents answered six items rated on fivepoint Likert scale, and responses on each item were transformed to scores ranging from 0 to 4 points. A higher total score corresponds to a worse mental health condition. All respondents were split into two groups, “good mental health (below 5 points)” or “bad mental health (5 points or above),” with reference to 5 points identified as the optimal cut-off point for screening mood and anxiety disorders in Japan (100% sensitivity and 68.7% specificity), and this cut-off point was used in previous studies in Japan.15,16 The Japanese version of | 671
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IBM SPSS 21.0 Japanese version (IBM Corporation, Armonk, NY, USA). These analyses were based on the analyses we previously reported in the report for the Japanese MHLW.18
Results
Figure 1 Flowchart of categorization of answers to diseases. Diseases were evaluated using responses to the questions. The second question was for persons replying “Yes” to the first question. For the analyses, the “No” group in each item for the second question included respondents who answered “No” to the first question.
the K6 has been validated,13 and the internal consistency reliability (Cronbach’s alpha) of this scale in the present study was 0.89.
Statistical analysis The associations of socioeconomic status, disease, mental health and activity limitations were analyzed in the following manner. First, the associations between socioeconomic status, disease, mental health and activity limitations among total population were assessed using a univariate logistic regression analysis. Next, a multiple logistic regression analysis was applied to all the factors found to be related to the outcome at the significant level in the univariate logistic regression analysis. Then, population-attributable risk (PAR) was calculated by using adjusted odds ratios from the multiple logistic regression analysis for each variable that was significantly associated with activity limitations. PAR is most commonly defined as the proportional reduction in average disease risk over a specified time interval that would be achieved by eliminating the exposure of interest from the population while distributions of other risk factors in the population remain unchanged.17 After that, participants were divided into four groups according to sex and the following age groups: 65–74 years (young-old) and 75 years or older (old-old), and univariate and multiple logistic regression analysis were carried out to identify relationships between socioeconomic status except for age and sex, disease, mental health and activity limitations by these four groups. Finally, PAR was calculated. The level of significance for all analyses was set at P < 0.05. All statistical analyses were carried out using 672 |
The socioeconomic status, mental health and activity limitations of the respondents are shown in Table 1. In the present study, 2217 of total respondents had activity limitations, and the breakdown was as follows: 435 (18.5%) in young-old men, 431 (32.2%) in young-old women, 467 (19.1%) in old-old men and 884 (39.6%) in old-old women. The proportion of people who had activity limitations in old-old women was larger than that in other groups, and that in old-old men was larger than that in young-old men and women. Table 2 shows the results of the logistic regression analysis and PAR among all respondents. Age (OR 2.32, PAR 20.9%), eye diseases (OR 1.45, PAR 12.2%), low back pain (OR 2.19, PAR 26.8%), diabetes (OR 1.63, PAR 14.5%), arthropathy (OR 3.19, PAR 38.9%), angina pectoris/myocardial infarction (OR 2.22, PAR 27.1%), osteoporosis (OR 2.05, PAR 24.4%) and mental health (OR 4.40, PAR 39.3%) were significantly related to activity limitations. Tables 3 and 4 show the results of logistic regression analyses and PAR by age and sex groups. For young-old men, eye diseases (OR 2.05, PAR 18.0%), low back pain (OR 3.64, PAR 32.8%), angina pectoris/myocardial infarction (OR 2.72, PAR 27.3%), cerebral stroke (OR 7.44, PAR 51.0%), gastric and duodenal disease (OR 1.64, PAR 12.9%), and mental health (OR 4.04, PAR 30.2%) had statistically significant impacts on activity limitations (Table 3). In regard to old-old men, low back pain (OR 2.72, PAR 33.7%), diabetes (OR 1.89, PAR 23.2%), angina pectoris/ myocardial infarction (OR 1.97, PAR 25.4%), cerebral stroke (OR 4.20, PAR 49.6%), other cardiovascular disease (OR 1.85, PAR 23.0%) and mental health (OR 4.87, PAR 49.1%) were statistically significantly related to activity limitations (Table 3). For young-old women, eye diseases (OR 1.58, PAR 11.3%), low back pain (OR 2.54, PAR 26.4%), diabetes (OR 1.54, PAR 10.3%), arthropathy (OR 4.90, PAR 41.9%), osteoporosis (OR 2.43, PAR 24.6%) and mental health (OR 4.51, PAR 31.0%) were statistically significantly correlated with activity limitations (Table 4). Finally, regarding old-old women, low back pain (OR 1.48, PAR 17.5%), arthropathy (OR 2.45, PAR 35.6%), osteoporosis (OR 1.83, PAR 26.7%), diabetes (OR 1.62, PAR 20.1%), angina pectoris/myocardial infarction (OR 1.78, PAR 24.8%) and mental health (OR 4.15, PAR 48.2%) were statistically significantly associated with activity limitations (Table 4). © 2015 Japan Geriatrics Society
© 2015 Japan Geriatrics Society
(5.9)
(6.1) (4.8) (4.4)
139
144 112 103 3.0 ± 4.1 2179 (26.0) 2217 (26.5)
2.6 ± 3.8 511 (21.7) 435 (18.5)
(26.5) (10.2) (8.5) (8.0) (11.0) (9.0)
623 241 199 188 260 212
2411 1251 983 770 714 610 572 466 459 411
(28.8) (14.9) (11.7) (9.2) (8.5) (4.8) (6.8) (5.6) (5.5) (4.9)
163 (6.9) 2745 ± 1907
Young-old men (n = 2354)
1263 (15.1) 2593 ± 1907
Total (n = 8373)
The top 10 responses of diseases are shown in each group.
Socioeconomic status Living arrangement (living alone), n (%) Mean equivalized disposable household income (thousand yen) Diseases, n (%) High blood pressure Eye diseases Low back pain Hyperlipidemia (hypercholesterolemia) Diabetes Dental diseases Arthropathy Angina pectoris/myocardial infarction Stiff shoulder Osteoporosis Benign prostatic hyperplasia Cerebral stroke Gastric and duodenal disease Other cardiovascular disease Mean mental health Poor mental health (5 points or above), n (%) Activity limitations, n (%)
Table 1 Characteristics of participants
174 (13.0) 89 (6.6) 100 (7.5) 84 (6.3) 2.6 ± 3.9 296 (22.1) 431 (32.2)
(8.7)
(8.7) (6.3)
116 84 116
(30.5) (15.7) (12.8)
408 210 171
116 (8.7) 2677 ± 1915
Old-old men (n = 1339)
635 467
88
175 146
608 352 262 317 167 204 159
414
3.0 ± 4.0 (26.0) (19.1)
(3.6)
(7.2) (6.0)
(24.9) (14.4) (10.7) (13.0) (6.8) (8.3) (6.5)
(16.9) 2486 ± 1853
Young-old women (n = 2446)
(6.4) 3.7 ± 4.6 737 (33.0) 884 (39.6)
(11.2) (6.7) (6.7) (10.8)
251 150 149 242
142
(34.6) (20.1) (15.7) (8.7) (7.7)
772 448 351 195 171
570 (25.5) 2498 ± 1949
Old-old women (n = 2234)
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Table 2 Logistic regression analyses for activity limitations in the total population
Socioeconomic status Age Sex Living arrangements Equivalized disposable household income Diseases High blood pressure Eye diseases Low back pain Hyperlipidemia (hypercholesterolemia) Diabetes Dental diseases Arthropathy Angina pectoris/myocardial infarction Stiff shoulder Osteoporosis Mental health
Unadjusted analysis OR (95% CI)
Adjusted analysis OR (95% CI)
PAR %
Old-old/young-old Women/men Living alone/with others Low/high
2.52 1.32 0.92 1.12
(2.28–2.78)*** (1.20–1.46)*** (0.80–1.05) (1.01–1.23)*
2.32 0.97
(2.07–2.59)*** (0.86–1.09)
20.9
1.02
(0.91–1.14)
Presence/absence Presence/absence Presence/absence Presence/absence
1.22 2.04 3.20 1.11
(1.10–1.36)*** (1.80–2.32)*** (2.79–3.66)*** (0.94–1.31)
0.96 1.45 2.19
(0.85–1.08) (1.25–1.67)*** (1.86–2.57)***
12.2 26.8
Presence/absence Presence/absence Presence/absence Presence/absence
1.76 1.17 4.08 2.88
(1.50–2.07)*** (0.97–1.40) (3.43–4.85)*** (2.38–3.47)***
1.63
(1.36–1.96)***
14.5
3.19 2.22
(2.62–3.88)*** (1.80–2.75)***
38.9 27.1
Presence/absence Presence/absence Bad/good
2.11 3.33 4.76
(1.74–2.56)*** (2.73–4.07)*** (4.28–5.29)***
0.93 2.05 4.40
(0.73–1.17) (1.62–2.59)*** (3.93–4.93)***
24.4 39.3
*P < 0.05, ***P < 0.001. CI, confidence interval; OR, odds ratio; PAR, population attributable risk.
Discussion The major objective of the present study was to verify relationships between socioeconomic and physical/ mental health status, and activity limitations by age and sex among older adults, using nationally representative cross-sectional data in Japan. The result of a multiple logistic regression analysis in the total population showed that activity limitations were related to various physical/mental health status: eye diseases, low back pain, diabetes, arthropathy, angina pectoris/myocardial infarction, osteoporosis and mental health. In particular, mental health showed the highest odds ratio and PAR. Therefore, mental health would be the most important risk factor of activity limitations. This finding was consistent with previous studies, which reported that mental health was an appropriate factor to predict disability2,5 and demands for long-term care.3,4 One of the mechanisms underlying relationships between deterioration in mental health and activity limitations in older adults would be related to homebound states. It has been known that deterioration in mental health is one of the important risk factors of the homebound.19,20 They tend not to go outside and not to seek social integration. Older adults with bad mental health are also more likely to develop comorbidity and cognitive impairment,20 which are risk factors for dis674 |
ability.21 Thus, older adults with bad mental health might have activity limitations by daily inactivity. However, other research reported reverse causality between disability and mental health.22,23 Further research to identify causal associations between mental health and activity limitations should be carried out. In contrast, analyses by age and sex showed that both common and different risk factors to activity limitations among four groups were revealed. In diseases, low back pain was a common factor of activity limitations in all groups. Several studies showed the relationship between low back pain and disability in older adults.24–26 More recently, Hashimoto et al. reported that improving prevention of low back pain increased disability-free life expectancy in the Japanese population.27 Low back pain is one of the most frequent disorders among Japanese older adults, and would cause growth in medical bills. Prevention of disabilities in non-fatal conditions, such as low back pain, is the most cost-effective preventative strategy.28 Thus, interventions for prevention of low back pain are also important. For women regardless of age, not only low back pain but also other musculoskeletal diseases, such as arthropathy and osteoporosis, were statistically significantly related to activity limitations. Especially, arthropathy showed a high odds ratio and PAR. In the previous report, musculoskeletal diseases were the most © 2015 Japan Geriatrics Society
Activity limitations factors in elderly
Table 3 Logistic regression analyses for activity limitations in young-old and old-old men Young-old men Socioeconomic status Living arrangements Equivalized disposable household income Diseases High blood pressure Diabetes Eye diseases Dental diseases Low back pain Hyperlipidemia (hypercholesterolemia) Benign prostatic hyperplasia Angina pectoris/myocardial infarction Cerebral stroke Gastric and duodenal disease Mental health
Unadjusted analysis OR (95% CI)
PAR %
18.0
Living alone/with others Low/high
0.99 1.14
(0.66–1.50) (0.92–1.40)
Presence/absence Presence/absence Presence/absence Presence/absence Presence/absence Presence/absence
1.13 1.83 2.74 1.33 4.33 1.89
(0.90–1.43) (1.36–2.45)*** (2.06–3.66)*** (0.94–1.86) (3.20–5.86)*** (1.35–2.64)***
1.34 2.05
(0.95–1.89) (1.47–2.85)***
3.64 1.45
(2.59–5.12)*** (0.98–2.14)
Presence/absence Presence/absence
2.12 3.73
(1.47–3.07)*** (2.62–5.31)***
1.47 2.72
(0.96–2.27) (1.81–4.09)***
27.3
Presence/absence Presence/absence
7.28 2.27
(4.92–10.79)*** (1.49–3.48)***
7.44 1.64
(4.82–11.48)*** (1.01–2.66)*
51.0 12.9
Bad/good
4.70
(3.75–5.88)***
4.04
(3.17–5.15)***
30.2
Old-old men Socioeconomic status Living arrangement Equivalized disposable household income Diseases High blood pressure Eye diseases Benign prostatic hyperplasia Low back pain Diabetes Angina pectoris/myocardial infarction Gastric and duodenal disease Cerebral stroke Other cardiovascular disease Dental diseases Mental health
Adjusted analysis OR (95% CI)
Unadjusted analysis OR (95% CI) Living alone/with others Low/high
0.79 1.10
(0.51–1.20) (0.87–1.38)
Presence/absence Presence/absence Presence/absence Presence/absence Presence/absence Presence/absence
1.01 1.54 1.38 2.77 2.19 2.46
(0.79–1.30) (1.14–2.08)** (0.99–1.92) (2.00–3.84)*** (1.49–3.22)*** (1.68–3.61)***
Presence/Absence
1.51
(1.00–2.29)
Presence/absence Presence/absence Presence/absence Bad/good
4.40 2.23 0.83 5.19
(2.80–6.92)*** (1.43–3.47)*** (0.51–1.36) (3.95–6.83)***
Adjusted analysis OR (95% CI)
32.8
PAR %
1.30
(0.92–1.83)
2.72 1.89 1.97
(1.90–3.90)*** (1.23–2.92)** (1.27–3.04)**
33.7 23.2 25.4
4.20 1.85
(2.58–6.84)*** (1.12–3.07)*
49.6 23.0
4.87
(3.65–6.50)***
49.1
*P < 0.05, **P < 0.01, ***P < 0.001. CI, confidence interval; OR, odds ratio; PAR, population attributable risk.
important diseases causing demands for long-term care for Japanese older women.10 Several previous studies also reported that arthropathy predicted disability for women, but not for men.6,29 This sex difference might be a result of sociocultural and historical background.29 Women in this generation were probably raising children, having less physical © 2015 Japan Geriatrics Society
exercise, gaining weight and suffering more locomotor conditions.29 Furthermore, recently, the proportion of women with low body mass index of below 18.5 in their 20s to 40s has been increasing, and the proportion of women who have fitness habits has been decreasing.30 As the problem of musculoskeletal diseases would further increase for elderly women, the improvement of | 675
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Table 4 Logistic regression analyses for activity limitations in young-old and old-old women Young-old women Socioeconomic status Living arrangement Equivalized disposable household income Diseases High blood pressure Eye diseases Hyperlipidemia (hypercholesterolemia) Low back pain Dental diseases Stiff shoulder Diabetes Arthropathy Osteoporosis Gastric and duodenal disease Mental health
Unadjusted analysis OR (95% CI)
Adjusted analysis OR (95% CI)
Living alone/with others Low/high
1.24 1.23
(0.96–1.61) (1.00–1.50)*
1.08
(0.86–1.36)
Presence/absence Presence/absence Presence/absence
1.20 2.18 0.87
(0.95–1.50) (1.69–2.80)*** (0.64–1.19)
1.58
(1.18–2.12)**
11.3
Presence/absence Presence/absence Presence/absence Presence/absence Presence/absence Presence/absence Presence/absence
4.00 1.55 2.82 1.85 5.57 3.35 2.15
(3.05–5.23)*** (1.11–2.16)** (2.04–3.09)*** (1.30–2.62)*** (4.00–7.75)*** (2.37–4.73)*** (1.37–3.40)***
2.55 1.08 0.95 1.54 4.85 2.43 1.18
(1.83–3.54)*** (0.73–1.60) (0.63–1.43) (1.04–2.29)* (3.34–7.05)*** (1.63–3.61)*** (0.70–1.98)
26.4
Bad/good
4.94
(3.99–6.12)***
4.49
(3.57–5.65)***
31.0
Old-old women Socioeconomic status Living arrangement Equivalised disposable household income Diseases High blood pressure Eye diseases Low back pain Arthropathy Osteoporosis Hyperlipidemia (hypercholesterolemia) Diabetes Angina pectoris/myocardial infarction Stiff shoulder Other cardiovascular disease Mental health
PAR %
10.3 41.9 24.6
Unadjusted analysis OR (95% CI)
Adjusted analysis OR (95% CI)
PAR %
Living alone/with others Low/high
0.77 0.97
(0.64–0.94)* (0.82–1.15)
0.81
(0.66–1.01)
Presence/absence Presence/absence Presence/Absence Presence/absence Presence/absence Presence/absence
1.15 1.54 2.05 2.58 2.39 1.23
(0.96–1.37) (1.25–1.90)*** (1.63–2.58)*** (1.97–3.37)*** (1.82–3.14)*** (0.91–1.65)
1.22 1.48 2.45 1.83
(0.96–1.53) (1.13–1.92)** (1.82–3.29)*** (1.36–2.48)***
17.5 35.6 26.7
Presence/absence Presence/absence
1.78 2.10
(1.30–2.43)*** (1.50–2.94)***
1.62 1.78
(1.15–2.28)** (1.23–2.57)**
20.1 24.8
Presence/absence Presence/absence Bad/good
1.60 1.78 4.52
(1.15–2.23)** (1.26–2.50)*** (3.75–5.46)***
0.90 1.43 4.15
(0.61–1.33) (0.98–2.09) (3.42–5.04)***
48.2
*P < 0.05, **P < 0.01, ***P < 0.001. CI, confidence interval; OR, odds ratio; PAR, population attributable risk.
musculoskeletal diseases will be becoming increasingly important for prevention of activity limitations for older women. For men in all age groups, cardiovascular diseases, including angina pectoris/myocardial infarction and cerebral stroke, were statistically significantly associated with activity limitations. In particular, cerebral stroke showed a high odds ratio and PAR. In the previous report, cerebral stroke was the highest risk for demand 676 |
for long-term care in Japanese older men.10 The Japanese MHLW suggests that it is important for cardiovascular diseases to control high blood pressure, hyperlipidemia (hypercholesterolemia) and metabolic syndrome.1 Lifestyle habit approaches, such as smoking and alcohol, would be important to prevent cardiovascular diseases, especially for men. In the present study, there were no significant correlations between socioeconomic status and activity © 2015 Japan Geriatrics Society
Activity limitations factors in elderly
limitations. Although some previous studies reported that living arrangements7 and equivalized disposable household income8 predicted demands for long-term care, others showed that these socioeconomic status factors had no significant associations with disability2 and demands for long-term care.3 As the association between socioeconomic status and activity limitations still remains uncertain, further research is required to investigate this topic. As stated here, important risk factors of activity limitations depend on sex, but not age. Although the proportion of activity limitations increases with age, these findings suggest that important risk factors of activity limitations are influenced by physiological differences between sex rather than aging. One of the major strengths of the present study was the use of good nationally representative data. Furthermore, as the study population of the CLSC potentially included slightly higher ratios of healthy people compared with the general population of older adults as a result of excluding inpatients in hospitals and clinics, or residents of long-term aged care facilities, these findings would be useful for primary and secondary prevention of activity limitations in older adults. There were several limitations to the present study. First, the cross-sectional design of the study meant that we could not confirm causal relationships between activity limitations and risk factors. Longitudinal investigations are required to clarify the causality issue. Second, we did not investigate other potential risk factors, such as long-term care use. Future studies should include more various factors. Third, our study would have some sampling bias and attrition bias. The CSLC excluded inpatients in hospitals and clinics, or residents of long-term aged care facilities. Furthermore, approximately three-quarters of the excluded respondents did not respond to mental health, and approximately 40% of them did not respond to a question about activity limitations, and the excluded respondents was significantly older and had a higher proportion of activity limitations than the eligible respondents (data are not shown). Thus, the proportion of individuals who had severe diseases, bad mental health and activity limitations might be underestimated, especially in oldold adults. Fourth, diseases were self-reported and not verified by chart-review or an interview by medical professionals. Finally, activity limitations and diseases were rated on a dichotomized scale, and thus the severity of them was not assessed. In conclusion, mental health was the most important factor of activity limitations in Japanese older adults. Furthermore, the following diseases could be significant risk factors to activity limitations: low back pain regardless of age and sex, musculoskeletal diseases only for women and cardiovascular diseases mainly for men. These findings would be useful for primary and © 2015 Japan Geriatrics Society
secondary prevention of activity limitations in older adults in Japan.
Acknowledgments The use of governmental microdata was officially approved for the funded project. We thank Dr Kenji Shibuya and Dr Hideki Hashimoto for their academic support. This work was supported by the Ministry of Health, Labor and Welfare (H22-seisaku-shitei-033), and JSPS KAKENHI No. 24249031 (Grant-in-Aid for Scientific Research A).
Disclosure statement No potential conflicts of interest were disclosed.
References 1 Ministry of Health, Labour and Welfare, Japan. Healthy Japan 21 (2nd edition), 2013. [Cited 3 Oct 2014.] Available from URL: http://www.mhlw.go.jp/stf/seisakunitsuite/ bunya/kenkou_iryou/kenkou/kenkounippon21.html (In Japanese). 2 Yamazaki S, Nakano K, Saito E, Yasumura S. Prediction of functional disability by depressive state among community-dwelling elderly in Japan: a prospective cohort study. Geriatr Gerontol Int 2012; 12: 680–687. 3 Hirai H, Kondo K, Ojima T, Murata C. Examination of risk factors for onset of certification of long-term care insurance in community-dwelling older people: AGES project 3-year follow-up study. Jpn J Public Health 2009; 56: 501– 512. (In Japanese). 4 Ohmori-Matsuda K, Hozawa A, Sone T et al. Depression and the risk of long-term care insurance certification: the Tsurugaya project. Jpn J Public Health 2010; 57: 538–549. (In Japanese). 5 Iwasa H, Yoshida Y, Kumagai S, Ihara K, Yoshida H, Suzuki T. Depression status as a reliable predictor of functional decline among Japanese community-dwelling older adults: a 12-year population-based prospective cohort study. Int J Geriatr Psychiatry 2009; 24: 1192–1200. 6 Okochi J. Increase of mild disability in Japanese elders: a seven year follow-up cohort study. BMC Public Health 2005; 5: 55. 7 Moriya S, Murata A, Kimura S, Inoue N, Miura H. Predictors of eligibility for long-term care funding for older people in Japan. Australas J Ageing 2013; 32: 79–85. 8 Kondo K, Ashida T, Hrai H, Misawa J, Suzuki K. The relationship between socio-economic status and the loss of healthy aging, and relevant gender differences in the Japanese older population: AGES project longitudinal study. Journal of Health Care and Society 2012; 22: 19–30. (In Japanese). 9 Hashimoto S, Kawado M, Seko R et al. Trends in disabilityfree life expectancy in Japan, 1995–2004. J Epidemiol 2010; 20: 308–312. 10 Ministry of Health, Labour and Welfare, Japan. Comprehensive survey of living conditions in 2007, 2008 [Cited 3 Oct 2014.] Available from URL: http://www.mhlw.go.jp/ toukei/list/20-19-1.html (In Japanese).
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T Monma et al. 11 National Institute of Public Health. Ethical guidelines for epidemiological research, 2002 [Cited 3 Oct 2014.] Available from URL: http://www.niph.go.jp/wadai/ekigakurinri/ ethical-gl/guidelines.htm 12 Ministry of Internal, Affairs and Communications, Japan. National survey of family income and expenditure in 2009, 2010 [Cited 3 Oct 2014.] Available from URL: http://www .stat.go.jp/data/zensho/2009/02index.htm (In Japanese). 13 Furukawa TA, Kawakami N, Saitoh M et al. The performance of the Japanese version of the K6 and K10 in the World Mental Health Survey Japan. Int J Methods Psychiatr Res 2008; 17: 152–158. 14 Kessler RC, Andrews G, Colpe LJ et al. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med 2002; 32: 959–976. 15 Inoue A, Kawakami N, Tsuchiya M, Sakurai K, Hashimoto H. Association of occupation, employment contract, and company size with mental health in a national representative sample of employees in Japan. J Occup Health 2010; 52: 227–240. 16 Sakurai K, Kawakami N, Yamaoka K, Ishikawa H, Hashimoto H. The impact of subjective and objective social status on psychological distress among men and women in Japan. Soc Sci Med 2010; 70: 1832–1839. 17 Noguchi H, Tamiya N, Takeda F, Monma T. The relationships between mental and physical health, socioeconomic factors, and activity limitations in older adults. In: Shibuya K, ed. Comprehensive assessment of the health system in Japan. Tokyo, Japan: The Ministry of Health, Labour and Welfare, 2013; 127–139. (In Japanese). 18 Shinkai S, Fujita K, Fujiwara Y et al. Predictors for the onset of different types of homeboundness among community-living older adults: two-year prospective study. Jpn J Public Health 2005; 52: 874–885. (In Japanese). 19 Shinkai S. Homeboundness in the elderly. Jpn J Geriatr 2008; 45: 117–125. (In Japanese). 20 Stuck AE, Walthert JM, Nikolaus T, Büla CJ, Hohmann C, Beck JC. Risk factors for functional status decline in
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23
24 25
26 27
28 29
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community-living elderly people: a systematic literature review. Soc Sci Med 1999; 48: 445–469. Chen CM, Mullan J, Su YY, Griffiths D, Kreis IA, Chiu HC. The longitudinal relationship between depressive symptoms and disability for older adults: a populationbased study. J Gerontol A Biol Sci Med Sci 2012; 67: 1059– 1067. Gayman MD, Turner RJ, Cui M. Physical limitations and depressive symptoms: exploring the nature of the association. J Gerontol B Psychol Sci Soc Sci 2008; 63: S219– S228. Rudy TE, Weiner DK, Lieber SJ, Slaboda J, Boston JR. The impact of chronic low back pain on older adults: a comparative study of patients and controls. Pain 2007; 131: 293–301. Edmond SL, Felson DT. Function and back symptoms in older adults. J Am Geriatr Soc 2003; 51: 1702–1709. Weiner DK, Haggerty CL, Kritchevsky SB et al. How does low back pain impact physical function in independent, well-functioning older adults? Evidence from the Health ABC Cohort and implications for the future. Pain Med 2003; 4: 311–320. Hashimoto S, Kawado M, Yamada H et al. Gains in disability-free life expectancy from elimination of diseases and injuries in Japan. J Epidemiol 2012; 22: 199–204. Bonneux L, Barendregt JJ, Nusselder WJ, der Maas PJ. Preventing fatal diseases increases healthcare costs: cause elimination life table approach. BMJ 1998; 316: 26–29. Tas¸ U, Verhagen AP, Bierma-Zeinstra SM et al. Incidence and risk factors of disability in the elderly: the rotterdam study. Prev Med 2007; 44: 272–278. Ministry of Health, Labour and Welfare, Japan. National health and nutrition survey, 2007 [Cited 3 Oct 2014.] Available from URL: http://www0.nih.go.jp/eiken/english/ research/project_nhns.html Rockhill B, Newman B, Weinberg C. Use and misuse of population attributable fractions. Am J Public Health 1998; 88: 15–19.
© 2015 Japan Geriatrics Society
Geriatr Gerontol Int 2016; 16: 670–678
ORIGINAL ARTICLE: EPIDEMIOLOGY, CLINICAL PRACTICE AND HEALTH
Age and sex differences of risk factors of activity limitations in Japanese older adults Takafumi Monma,1 Fumi Takeda,1 Haruko Noguchi2 and Nanako Tamiya3 1
Faculty of Health and Sport Sciences, 3Faculty of Medicine, University of Tsukuba, Ibaraki, and 2Faculty of Political Science and Economics, Waseda University, Tokyo, Japan
Aim: The objective of the present study was to verify how socioeconomic and physical/mental health status would be associated with activity limitations by age and sex among older adults, using nationally representative crosssectional data in Japan. Methods: The present study focused on 8373 older adults aged 65 years or older extracted from the Comprehensive Survey of Living Conditions conducted in 2007 by the Japanese Ministry of Health, Labor and Welfare. Univariate and multiple logistic regression analyses and population-attributable risk were applied to validate the relationships of socioeconomic and physical/mental health status with activity limitations among the total population, and by age groups (young-old or old-old) and sex. Results: Mental health showed the highest odds ratio and population-attributable risk in the total population. In addition, low back pain was associated with activity limitations regardless of age and sex. Other musculoskeletal diseases, such as arthropathy and osteoporosis, were related to activity limitations for women, regardless of age, whereas cardiovascular diseases, including angina pectoris/myocardial infarction and cerebral stroke, were associated with activity limitations for men in any age group. There were no statistically significant correlations between socioeconomic status and activity limitations in any groups. Conclusion: Mental health was the most important factor of activity limitations in Japanese older adults. Furthermore, low back pain regardless of age and sex, other musculoskeletal diseases only for women and cardiovascular diseases mainly for men could also be significant risk factors to activity limitations. Therefore, preventive approaches of activity limitations considering sex differences are important for older adults in Japan. Geriatr Gerontol Int 2016; 16: 670–678. Keywords: activity limitations, aged, diseases, gender difference, mental health.
Introduction Although the longevity of Japanese older adults is well known, the gap between mean life expectancy and healthy life expectancy has been increasing: 9.13 years for men and 12.68 years for women.1 Expanding the gap would cause a decrease of quality of life among individuals, and an increase in financial burden to social security. Therefore, extending healthy life expectancy, and reducing the gap between mean life expectancy and
Accepted for publication 12 April 2015. Correspondence: Professor Nanako Tamiya Ph.D., Faculty of Medicine, University of Tsukuba, Laboratory of Advanced Research D, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8575 Japan. Email: [email protected]
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doi: 10.1111/ggi.12533
healthy life expectancy is important both for improving public health and keeping social security sustainable.1 To extend healthy life expectancy, a number of longitudinal studies have found various risk factors of disability or demands for long-term care in Japan. In particular, mental health status was a reliable predictor of disability and long-term care need.2–5 In addition, diseases under treatment3,6 and history of chronic diseases4,5 were important risk factors. Furthermore, recently some researchers reported the associations of socioeconomic status with demand for long-term care.7,8 However, these studies were investigated in specific regions. No study had ever investigated risk factors of activity limitations among a nationally representative Japanese population. Furthermore, although the Japanese Ministry of Health, Labor and Welfare (MHLW) © 2015 Japan Geriatrics Society
Activity limitations factors in elderly
suggested the necessity of adequate understanding about characteristics, needs, and health problems by life stages and sex to extend healthy life expectancy, age and sex differences of risk factors of activity limitations are still unclear.1 As there are differences of prevalence and incidence of physical and mental diseases by age and sex in older adults, the risk factors for activity limitations would also differ. Therefore, the major objective of the present study was to verify how socioeconomic and physical/mental health status would be associated with activity limitations by age and sex among older adults, using nationally representative cross-section data in Japan. In Japan, Hashimoto et al. calculated healthy life expectancy among Japanese people based on the question of activity limitations in the Comprehensive Survey of Living Conditions (CSLC), a nationally representative data carried out by the Japanese MHLW.9 The CSLC also surveys a wide range of individual and household characteristics, such as demographic, socioeconomic, physical health and mental health status; therefore, it would be one of the most proper data sources to achieve the purpose of the present study.
Methods Study population The present study used cross-sectional data from the CSLC in 2007.10 We were permitted to use the raw data from this survey by the Japanese MHLW. The CSLC was designed to obtain quantitative evidence for the planning and management for the health, labor and welfare policies. The survey was composed of five questionnaires for household, health, income, saving and long-term care. This study used data on three questionnaires for household, health and income. Participants of this survey were randomly chosen in 5440 districts from the census held in 2005. The household questionnaire and the health questionnaire covered approximately 760 000 individuals living in approximately 290 000 households among these districts, whereas the income questionnaire covered approximately 100 000 persons and approximately 40 000 households among these districts. Each participant completed questionnaires distributed by an enumerator in advance by mail, and the enumerator visited each participant’s house and collected them within a couple of days. We merged data from three questionnaires, and identified 16 850 respondents who were aged 65 years or older. Out of these, 8477 were excluded because of missing observations on variables indispensable for this study. The number of missing values of each variable was as follows: 2694 in equivalized disposable household © 2015 Japan Geriatrics Society
income, 3546 in activity limitations, 1597 in some sort of disease and 6207 in mental health. This study included 8373 older adults (valid response rate was 49.7%). We determined that an ethical review of the obtained data was not required based on the “Ethical Guidelines for Epidemiological Research” of the Japanese government.11
Measurements The activity limitations of respondents were evaluated using responses to the questions: “Is your daily life now affected by health problems?” Respondents who answered “yes” were categorized as the “activity limitations” group, and those who answered “no” were classified as the “no activity limitations” group. Socioeconomic status included age (calculated on the basis of year and month of birth), sex, living arrangement (living alone or with others) and equivalized disposable household income. Equivalized disposable household income is disposable household income adjusted for household size. This is calculated by dividing household income by equivalent household members, which is the square root of household members,12 and respondents in the present study were categorized into the high or low income group by the median. Diseases were evaluated using responses to the questions: “Do you now go to a hospital, clinic or facility of Japanese traditional massage, acupuncture, moxibustion, or judo-orthopedics for diseases or injuries?” and “What are your diseases or injuries?” The second question was for persons replying “Yes” to the first question. The responses to the second question were 39 diseases and injuries, “other disease or injury” and “unknown.” For the analyses, the “No” group in each item for the second question included respondents who answered “No” to the first question. In the present study, the top 10 responses were chosen by each group (Fig. 1). Mental health was assessed by the Japanese version of the K6 scale,13 which has been included in the CLSC since 2007. The K6 scale, a screening scale for psychological distress, is a powerful measurement to discriminate between community cases and non-cases of Diagnostic and Statistical Manual 4th edition disorders.14 Respondents answered six items rated on fivepoint Likert scale, and responses on each item were transformed to scores ranging from 0 to 4 points. A higher total score corresponds to a worse mental health condition. All respondents were split into two groups, “good mental health (below 5 points)” or “bad mental health (5 points or above),” with reference to 5 points identified as the optimal cut-off point for screening mood and anxiety disorders in Japan (100% sensitivity and 68.7% specificity), and this cut-off point was used in previous studies in Japan.15,16 The Japanese version of | 671
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IBM SPSS 21.0 Japanese version (IBM Corporation, Armonk, NY, USA). These analyses were based on the analyses we previously reported in the report for the Japanese MHLW.18
Results
Figure 1 Flowchart of categorization of answers to diseases. Diseases were evaluated using responses to the questions. The second question was for persons replying “Yes” to the first question. For the analyses, the “No” group in each item for the second question included respondents who answered “No” to the first question.
the K6 has been validated,13 and the internal consistency reliability (Cronbach’s alpha) of this scale in the present study was 0.89.
Statistical analysis The associations of socioeconomic status, disease, mental health and activity limitations were analyzed in the following manner. First, the associations between socioeconomic status, disease, mental health and activity limitations among total population were assessed using a univariate logistic regression analysis. Next, a multiple logistic regression analysis was applied to all the factors found to be related to the outcome at the significant level in the univariate logistic regression analysis. Then, population-attributable risk (PAR) was calculated by using adjusted odds ratios from the multiple logistic regression analysis for each variable that was significantly associated with activity limitations. PAR is most commonly defined as the proportional reduction in average disease risk over a specified time interval that would be achieved by eliminating the exposure of interest from the population while distributions of other risk factors in the population remain unchanged.17 After that, participants were divided into four groups according to sex and the following age groups: 65–74 years (young-old) and 75 years or older (old-old), and univariate and multiple logistic regression analysis were carried out to identify relationships between socioeconomic status except for age and sex, disease, mental health and activity limitations by these four groups. Finally, PAR was calculated. The level of significance for all analyses was set at P < 0.05. All statistical analyses were carried out using 672 |
The socioeconomic status, mental health and activity limitations of the respondents are shown in Table 1. In the present study, 2217 of total respondents had activity limitations, and the breakdown was as follows: 435 (18.5%) in young-old men, 431 (32.2%) in young-old women, 467 (19.1%) in old-old men and 884 (39.6%) in old-old women. The proportion of people who had activity limitations in old-old women was larger than that in other groups, and that in old-old men was larger than that in young-old men and women. Table 2 shows the results of the logistic regression analysis and PAR among all respondents. Age (OR 2.32, PAR 20.9%), eye diseases (OR 1.45, PAR 12.2%), low back pain (OR 2.19, PAR 26.8%), diabetes (OR 1.63, PAR 14.5%), arthropathy (OR 3.19, PAR 38.9%), angina pectoris/myocardial infarction (OR 2.22, PAR 27.1%), osteoporosis (OR 2.05, PAR 24.4%) and mental health (OR 4.40, PAR 39.3%) were significantly related to activity limitations. Tables 3 and 4 show the results of logistic regression analyses and PAR by age and sex groups. For young-old men, eye diseases (OR 2.05, PAR 18.0%), low back pain (OR 3.64, PAR 32.8%), angina pectoris/myocardial infarction (OR 2.72, PAR 27.3%), cerebral stroke (OR 7.44, PAR 51.0%), gastric and duodenal disease (OR 1.64, PAR 12.9%), and mental health (OR 4.04, PAR 30.2%) had statistically significant impacts on activity limitations (Table 3). In regard to old-old men, low back pain (OR 2.72, PAR 33.7%), diabetes (OR 1.89, PAR 23.2%), angina pectoris/ myocardial infarction (OR 1.97, PAR 25.4%), cerebral stroke (OR 4.20, PAR 49.6%), other cardiovascular disease (OR 1.85, PAR 23.0%) and mental health (OR 4.87, PAR 49.1%) were statistically significantly related to activity limitations (Table 3). For young-old women, eye diseases (OR 1.58, PAR 11.3%), low back pain (OR 2.54, PAR 26.4%), diabetes (OR 1.54, PAR 10.3%), arthropathy (OR 4.90, PAR 41.9%), osteoporosis (OR 2.43, PAR 24.6%) and mental health (OR 4.51, PAR 31.0%) were statistically significantly correlated with activity limitations (Table 4). Finally, regarding old-old women, low back pain (OR 1.48, PAR 17.5%), arthropathy (OR 2.45, PAR 35.6%), osteoporosis (OR 1.83, PAR 26.7%), diabetes (OR 1.62, PAR 20.1%), angina pectoris/myocardial infarction (OR 1.78, PAR 24.8%) and mental health (OR 4.15, PAR 48.2%) were statistically significantly associated with activity limitations (Table 4). © 2015 Japan Geriatrics Society
© 2015 Japan Geriatrics Society
(5.9)
(6.1) (4.8) (4.4)
139
144 112 103 3.0 ± 4.1 2179 (26.0) 2217 (26.5)
2.6 ± 3.8 511 (21.7) 435 (18.5)
(26.5) (10.2) (8.5) (8.0) (11.0) (9.0)
623 241 199 188 260 212
2411 1251 983 770 714 610 572 466 459 411
(28.8) (14.9) (11.7) (9.2) (8.5) (4.8) (6.8) (5.6) (5.5) (4.9)
163 (6.9) 2745 ± 1907
Young-old men (n = 2354)
1263 (15.1) 2593 ± 1907
Total (n = 8373)
The top 10 responses of diseases are shown in each group.
Socioeconomic status Living arrangement (living alone), n (%) Mean equivalized disposable household income (thousand yen) Diseases, n (%) High blood pressure Eye diseases Low back pain Hyperlipidemia (hypercholesterolemia) Diabetes Dental diseases Arthropathy Angina pectoris/myocardial infarction Stiff shoulder Osteoporosis Benign prostatic hyperplasia Cerebral stroke Gastric and duodenal disease Other cardiovascular disease Mean mental health Poor mental health (5 points or above), n (%) Activity limitations, n (%)
Table 1 Characteristics of participants
174 (13.0) 89 (6.6) 100 (7.5) 84 (6.3) 2.6 ± 3.9 296 (22.1) 431 (32.2)
(8.7)
(8.7) (6.3)
116 84 116
(30.5) (15.7) (12.8)
408 210 171
116 (8.7) 2677 ± 1915
Old-old men (n = 1339)
635 467
88
175 146
608 352 262 317 167 204 159
414
3.0 ± 4.0 (26.0) (19.1)
(3.6)
(7.2) (6.0)
(24.9) (14.4) (10.7) (13.0) (6.8) (8.3) (6.5)
(16.9) 2486 ± 1853
Young-old women (n = 2446)
(6.4) 3.7 ± 4.6 737 (33.0) 884 (39.6)
(11.2) (6.7) (6.7) (10.8)
251 150 149 242
142
(34.6) (20.1) (15.7) (8.7) (7.7)
772 448 351 195 171
570 (25.5) 2498 ± 1949
Old-old women (n = 2234)
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Table 2 Logistic regression analyses for activity limitations in the total population
Socioeconomic status Age Sex Living arrangements Equivalized disposable household income Diseases High blood pressure Eye diseases Low back pain Hyperlipidemia (hypercholesterolemia) Diabetes Dental diseases Arthropathy Angina pectoris/myocardial infarction Stiff shoulder Osteoporosis Mental health
Unadjusted analysis OR (95% CI)
Adjusted analysis OR (95% CI)
PAR %
Old-old/young-old Women/men Living alone/with others Low/high
2.52 1.32 0.92 1.12
(2.28–2.78)*** (1.20–1.46)*** (0.80–1.05) (1.01–1.23)*
2.32 0.97
(2.07–2.59)*** (0.86–1.09)
20.9
1.02
(0.91–1.14)
Presence/absence Presence/absence Presence/absence Presence/absence
1.22 2.04 3.20 1.11
(1.10–1.36)*** (1.80–2.32)*** (2.79–3.66)*** (0.94–1.31)
0.96 1.45 2.19
(0.85–1.08) (1.25–1.67)*** (1.86–2.57)***
12.2 26.8
Presence/absence Presence/absence Presence/absence Presence/absence
1.76 1.17 4.08 2.88
(1.50–2.07)*** (0.97–1.40) (3.43–4.85)*** (2.38–3.47)***
1.63
(1.36–1.96)***
14.5
3.19 2.22
(2.62–3.88)*** (1.80–2.75)***
38.9 27.1
Presence/absence Presence/absence Bad/good
2.11 3.33 4.76
(1.74–2.56)*** (2.73–4.07)*** (4.28–5.29)***
0.93 2.05 4.40
(0.73–1.17) (1.62–2.59)*** (3.93–4.93)***
24.4 39.3
*P < 0.05, ***P < 0.001. CI, confidence interval; OR, odds ratio; PAR, population attributable risk.
Discussion The major objective of the present study was to verify relationships between socioeconomic and physical/ mental health status, and activity limitations by age and sex among older adults, using nationally representative cross-sectional data in Japan. The result of a multiple logistic regression analysis in the total population showed that activity limitations were related to various physical/mental health status: eye diseases, low back pain, diabetes, arthropathy, angina pectoris/myocardial infarction, osteoporosis and mental health. In particular, mental health showed the highest odds ratio and PAR. Therefore, mental health would be the most important risk factor of activity limitations. This finding was consistent with previous studies, which reported that mental health was an appropriate factor to predict disability2,5 and demands for long-term care.3,4 One of the mechanisms underlying relationships between deterioration in mental health and activity limitations in older adults would be related to homebound states. It has been known that deterioration in mental health is one of the important risk factors of the homebound.19,20 They tend not to go outside and not to seek social integration. Older adults with bad mental health are also more likely to develop comorbidity and cognitive impairment,20 which are risk factors for dis674 |
ability.21 Thus, older adults with bad mental health might have activity limitations by daily inactivity. However, other research reported reverse causality between disability and mental health.22,23 Further research to identify causal associations between mental health and activity limitations should be carried out. In contrast, analyses by age and sex showed that both common and different risk factors to activity limitations among four groups were revealed. In diseases, low back pain was a common factor of activity limitations in all groups. Several studies showed the relationship between low back pain and disability in older adults.24–26 More recently, Hashimoto et al. reported that improving prevention of low back pain increased disability-free life expectancy in the Japanese population.27 Low back pain is one of the most frequent disorders among Japanese older adults, and would cause growth in medical bills. Prevention of disabilities in non-fatal conditions, such as low back pain, is the most cost-effective preventative strategy.28 Thus, interventions for prevention of low back pain are also important. For women regardless of age, not only low back pain but also other musculoskeletal diseases, such as arthropathy and osteoporosis, were statistically significantly related to activity limitations. Especially, arthropathy showed a high odds ratio and PAR. In the previous report, musculoskeletal diseases were the most © 2015 Japan Geriatrics Society
Activity limitations factors in elderly
Table 3 Logistic regression analyses for activity limitations in young-old and old-old men Young-old men Socioeconomic status Living arrangements Equivalized disposable household income Diseases High blood pressure Diabetes Eye diseases Dental diseases Low back pain Hyperlipidemia (hypercholesterolemia) Benign prostatic hyperplasia Angina pectoris/myocardial infarction Cerebral stroke Gastric and duodenal disease Mental health
Unadjusted analysis OR (95% CI)
PAR %
18.0
Living alone/with others Low/high
0.99 1.14
(0.66–1.50) (0.92–1.40)
Presence/absence Presence/absence Presence/absence Presence/absence Presence/absence Presence/absence
1.13 1.83 2.74 1.33 4.33 1.89
(0.90–1.43) (1.36–2.45)*** (2.06–3.66)*** (0.94–1.86) (3.20–5.86)*** (1.35–2.64)***
1.34 2.05
(0.95–1.89) (1.47–2.85)***
3.64 1.45
(2.59–5.12)*** (0.98–2.14)
Presence/absence Presence/absence
2.12 3.73
(1.47–3.07)*** (2.62–5.31)***
1.47 2.72
(0.96–2.27) (1.81–4.09)***
27.3
Presence/absence Presence/absence
7.28 2.27
(4.92–10.79)*** (1.49–3.48)***
7.44 1.64
(4.82–11.48)*** (1.01–2.66)*
51.0 12.9
Bad/good
4.70
(3.75–5.88)***
4.04
(3.17–5.15)***
30.2
Old-old men Socioeconomic status Living arrangement Equivalized disposable household income Diseases High blood pressure Eye diseases Benign prostatic hyperplasia Low back pain Diabetes Angina pectoris/myocardial infarction Gastric and duodenal disease Cerebral stroke Other cardiovascular disease Dental diseases Mental health
Adjusted analysis OR (95% CI)
Unadjusted analysis OR (95% CI) Living alone/with others Low/high
0.79 1.10
(0.51–1.20) (0.87–1.38)
Presence/absence Presence/absence Presence/absence Presence/absence Presence/absence Presence/absence
1.01 1.54 1.38 2.77 2.19 2.46
(0.79–1.30) (1.14–2.08)** (0.99–1.92) (2.00–3.84)*** (1.49–3.22)*** (1.68–3.61)***
Presence/Absence
1.51
(1.00–2.29)
Presence/absence Presence/absence Presence/absence Bad/good
4.40 2.23 0.83 5.19
(2.80–6.92)*** (1.43–3.47)*** (0.51–1.36) (3.95–6.83)***
Adjusted analysis OR (95% CI)
32.8
PAR %
1.30
(0.92–1.83)
2.72 1.89 1.97
(1.90–3.90)*** (1.23–2.92)** (1.27–3.04)**
33.7 23.2 25.4
4.20 1.85
(2.58–6.84)*** (1.12–3.07)*
49.6 23.0
4.87
(3.65–6.50)***
49.1
*P < 0.05, **P < 0.01, ***P < 0.001. CI, confidence interval; OR, odds ratio; PAR, population attributable risk.
important diseases causing demands for long-term care for Japanese older women.10 Several previous studies also reported that arthropathy predicted disability for women, but not for men.6,29 This sex difference might be a result of sociocultural and historical background.29 Women in this generation were probably raising children, having less physical © 2015 Japan Geriatrics Society
exercise, gaining weight and suffering more locomotor conditions.29 Furthermore, recently, the proportion of women with low body mass index of below 18.5 in their 20s to 40s has been increasing, and the proportion of women who have fitness habits has been decreasing.30 As the problem of musculoskeletal diseases would further increase for elderly women, the improvement of | 675
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Table 4 Logistic regression analyses for activity limitations in young-old and old-old women Young-old women Socioeconomic status Living arrangement Equivalized disposable household income Diseases High blood pressure Eye diseases Hyperlipidemia (hypercholesterolemia) Low back pain Dental diseases Stiff shoulder Diabetes Arthropathy Osteoporosis Gastric and duodenal disease Mental health
Unadjusted analysis OR (95% CI)
Adjusted analysis OR (95% CI)
Living alone/with others Low/high
1.24 1.23
(0.96–1.61) (1.00–1.50)*
1.08
(0.86–1.36)
Presence/absence Presence/absence Presence/absence
1.20 2.18 0.87
(0.95–1.50) (1.69–2.80)*** (0.64–1.19)
1.58
(1.18–2.12)**
11.3
Presence/absence Presence/absence Presence/absence Presence/absence Presence/absence Presence/absence Presence/absence
4.00 1.55 2.82 1.85 5.57 3.35 2.15
(3.05–5.23)*** (1.11–2.16)** (2.04–3.09)*** (1.30–2.62)*** (4.00–7.75)*** (2.37–4.73)*** (1.37–3.40)***
2.55 1.08 0.95 1.54 4.85 2.43 1.18
(1.83–3.54)*** (0.73–1.60) (0.63–1.43) (1.04–2.29)* (3.34–7.05)*** (1.63–3.61)*** (0.70–1.98)
26.4
Bad/good
4.94
(3.99–6.12)***
4.49
(3.57–5.65)***
31.0
Old-old women Socioeconomic status Living arrangement Equivalised disposable household income Diseases High blood pressure Eye diseases Low back pain Arthropathy Osteoporosis Hyperlipidemia (hypercholesterolemia) Diabetes Angina pectoris/myocardial infarction Stiff shoulder Other cardiovascular disease Mental health
PAR %
10.3 41.9 24.6
Unadjusted analysis OR (95% CI)
Adjusted analysis OR (95% CI)
PAR %
Living alone/with others Low/high
0.77 0.97
(0.64–0.94)* (0.82–1.15)
0.81
(0.66–1.01)
Presence/absence Presence/absence Presence/Absence Presence/absence Presence/absence Presence/absence
1.15 1.54 2.05 2.58 2.39 1.23
(0.96–1.37) (1.25–1.90)*** (1.63–2.58)*** (1.97–3.37)*** (1.82–3.14)*** (0.91–1.65)
1.22 1.48 2.45 1.83
(0.96–1.53) (1.13–1.92)** (1.82–3.29)*** (1.36–2.48)***
17.5 35.6 26.7
Presence/absence Presence/absence
1.78 2.10
(1.30–2.43)*** (1.50–2.94)***
1.62 1.78
(1.15–2.28)** (1.23–2.57)**
20.1 24.8
Presence/absence Presence/absence Bad/good
1.60 1.78 4.52
(1.15–2.23)** (1.26–2.50)*** (3.75–5.46)***
0.90 1.43 4.15
(0.61–1.33) (0.98–2.09) (3.42–5.04)***
48.2
*P < 0.05, **P < 0.01, ***P < 0.001. CI, confidence interval; OR, odds ratio; PAR, population attributable risk.
musculoskeletal diseases will be becoming increasingly important for prevention of activity limitations for older women. For men in all age groups, cardiovascular diseases, including angina pectoris/myocardial infarction and cerebral stroke, were statistically significantly associated with activity limitations. In particular, cerebral stroke showed a high odds ratio and PAR. In the previous report, cerebral stroke was the highest risk for demand 676 |
for long-term care in Japanese older men.10 The Japanese MHLW suggests that it is important for cardiovascular diseases to control high blood pressure, hyperlipidemia (hypercholesterolemia) and metabolic syndrome.1 Lifestyle habit approaches, such as smoking and alcohol, would be important to prevent cardiovascular diseases, especially for men. In the present study, there were no significant correlations between socioeconomic status and activity © 2015 Japan Geriatrics Society
Activity limitations factors in elderly
limitations. Although some previous studies reported that living arrangements7 and equivalized disposable household income8 predicted demands for long-term care, others showed that these socioeconomic status factors had no significant associations with disability2 and demands for long-term care.3 As the association between socioeconomic status and activity limitations still remains uncertain, further research is required to investigate this topic. As stated here, important risk factors of activity limitations depend on sex, but not age. Although the proportion of activity limitations increases with age, these findings suggest that important risk factors of activity limitations are influenced by physiological differences between sex rather than aging. One of the major strengths of the present study was the use of good nationally representative data. Furthermore, as the study population of the CLSC potentially included slightly higher ratios of healthy people compared with the general population of older adults as a result of excluding inpatients in hospitals and clinics, or residents of long-term aged care facilities, these findings would be useful for primary and secondary prevention of activity limitations in older adults. There were several limitations to the present study. First, the cross-sectional design of the study meant that we could not confirm causal relationships between activity limitations and risk factors. Longitudinal investigations are required to clarify the causality issue. Second, we did not investigate other potential risk factors, such as long-term care use. Future studies should include more various factors. Third, our study would have some sampling bias and attrition bias. The CSLC excluded inpatients in hospitals and clinics, or residents of long-term aged care facilities. Furthermore, approximately three-quarters of the excluded respondents did not respond to mental health, and approximately 40% of them did not respond to a question about activity limitations, and the excluded respondents was significantly older and had a higher proportion of activity limitations than the eligible respondents (data are not shown). Thus, the proportion of individuals who had severe diseases, bad mental health and activity limitations might be underestimated, especially in oldold adults. Fourth, diseases were self-reported and not verified by chart-review or an interview by medical professionals. Finally, activity limitations and diseases were rated on a dichotomized scale, and thus the severity of them was not assessed. In conclusion, mental health was the most important factor of activity limitations in Japanese older adults. Furthermore, the following diseases could be significant risk factors to activity limitations: low back pain regardless of age and sex, musculoskeletal diseases only for women and cardiovascular diseases mainly for men. These findings would be useful for primary and © 2015 Japan Geriatrics Society
secondary prevention of activity limitations in older adults in Japan.
Acknowledgments The use of governmental microdata was officially approved for the funded project. We thank Dr Kenji Shibuya and Dr Hideki Hashimoto for their academic support. This work was supported by the Ministry of Health, Labor and Welfare (H22-seisaku-shitei-033), and JSPS KAKENHI No. 24249031 (Grant-in-Aid for Scientific Research A).
Disclosure statement No potential conflicts of interest were disclosed.
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