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Cohort study on living arrangements of older men and women and risk for basic activities of daily living disability: findings from the AGES project

BMC GeriatricsBMC series – open, inclusive and trusted201717:183

https://doi.org/10.1186/s12877-017-0580-7

Received: 10 October 2016

Accepted: 7 August 2017

Published: 16 August 2017

Abstract

Background

Living arrangements of older adults have changed worldwide with increasing solitary and non-spouse households, which could affect social care systems. However, the relationship between these households and disability onset has remained unclear. We examined the relationship between living arrangements and the onset of basic activities of daily living disability in older adults, with a focus on gender differences and cohabitation status of those without a spouse.

Methods

Data from 6600 men and 6868 women aged 65 years or older without disability were obtained from the Aichi Gerontological Evaluation Study Project in Japan. Onset of disability was followed for 9.4 years. Disability was assessed based on Long-term Care Insurance System registration. A hierarchical Cox proportional hazards model was conducted to examine the risk of living alone and living only with non-spousal cohabitants compared to those living with spouses.

Results

Men living only with non-spousal cohabitants and those living alone were significantly more likely to develop disability after controlling for health and other covariates (hazard ratio = 1.38 and 1.45, respectively), while a significant difference was found only for women living alone (hazard ratio = 1.19). The risk of living with non-spousal cohabitants was marginally stronger in men, indicated by the interaction effect model (p = .08). A series of hierarchical analyses showed that social support exchange explained 24.4% and 15.8% of the excess risk of disability onset in men living alone and those living only with non-spousal cohabitants, respectively. A subsequent analysis also showed that support provision by older adults more greatly explained such excess risk than receiving support from others.

Conclusions

Older men without spouses were more likely to develop disability onset regardless of cohabitants. Health professionals should consider programs that enhance social support exchange, particularly support provision by older adults who are at risk of disability.

Keywords

Basic activities of daily living Living arrangements Longitudinal study Japanese

Background

Prevention of functional disability among older individuals and related costs to the healthcare system are a pressing issue in aging societies [1, 2]. In countries with the most progressed aging populations, such as Japan, the proportion of older people is expected to reach 40% in 2050 [3].

Living arrangements of older adults have changed dramatically over time [4]. The proportion of older adults living alone is increasing worldwide [5], which could affect care provision by the community [6] and necessitates more detailed focus on their health problems and needs. In addition, the proportion of older adults without spouses living in the household could increase in the future. For instance, in the United States, about one third of baby boomers were unmarried [7]. Such changes in living arrangements imply the growing importance of examining the role of non-spousal networks in older adults’ health.

Many longitudinal studies have reported marital advantage regarding mortality and morbidity [812]; in contrast, relatively few studies have examined the relationship between functional disability and living with non-spousal cohabitants [1117]. The presence of non-spousal family members of the unmarried could compensate for the lack of marital protection for older adults [18], while solitary living could promote independence among older adults [19]. Previous longitudinal studies have shown that older adults who lived only with non-spousal family members were more likely to develop functional decline compared to those who lived with spouses [12, 14, 15] or those who lived alone [11, 13, 16, 17]. Regarding those living alone, there have been inconsistent findings of comparable risk [11, 15, 16], excess risk [20], or less risk [14] compared to older adults living with a spouse.

Based on these findings, several points are worth further consideration. First, gender differences could exist in the association between living arrangements and onset of disability. Studies have shown more benefits for men living with a spouse compared to women for mortality [8, 21] and morbidity [10]. The association between living with non-spousal cohabitants and health could also differ by gender, since intimate relationships were more likely to be limited to a wife in older men, while older women relied on more diverse individuals such as their children [22]. However, few longitudinal studies have examined gender differences in the relationship between living arrangements and disability [11, 20].

Second, several factors could mediate the association between living arrangements and onset of disability. In studies on marital status and health, “marital protection [8],” referring to benefits obtained because of marriage, such as economic resources, social resources such as social support networks [7, 8, 10], and control over health-related behaviors [10], affects health in older adults [8, 13]. This has been observed even when considering the association of “marital selection,” a precursor to marital status [8]. Also, mental disorders in middle-aged adults differed by types of living arrangement, partially due to differential social support and unhealthy behaviors [10]. However, it remains unclear which factors mediate the association between living arrangements and onset of disability.

Third, needs-driven cohabitation among older adults, meaning those needing support tend to live with family members, particularly with their adult children [23], could confound the findings [17]. In Japan, living arrangements of older adults are relatively stable [24] because of low rates of needs-driven cohabitation [25] and remarriage [26]. Takagi and colleagues examined types of cohabitation with children and indicated that among older adults residing with their children, nearly 80% resided with their children their entire life [25]. This suggests that most older adults who reside with their children started living with them before the onset of health decline. Thus, reverse causation is less likely to be an issue as compared to Western countries, where needs-driven cohabitation is dominant [23].

The aim of this study was to examine the relationship between living arrangements and the onset of BADL disability among older adults with a focus on gender differences and cohabitation status in those living without a spouse. Following this, we also examined how social support and health-related behaviors mediated these associations.

Methods

Participants

Data were obtained from the Aichi Gerontological Evaluation Study (AGES) cohort dataset, which was part of the Japan Gerontological Evaluation Study (JAGES) project. A self-administered questionnaire survey was conducted in October 2003 with 33,152 people aged 65 years or older who were not eligible to utilize Long-term Care Insurance (LTCI) system services and who were selected through simple randomization (6 municipalities) or complete enumeration (4 small-scale municipalities) in Aichi Prefecture, Central Japan (response rate = 52.1%). The details of the survey were shown elsewhere [1, 27].

Survey data from 15,313 respondents who provided information for identification by the LTCI system were linked to the LTCI records dataset for a follow-up period of 3436 days (9.4 years) from November 1, 2003. We excluded data from 401 respondents who had qualified for LTCI benefits with a level 2 or higher rating by October 31, 2004, 332 who did not apply for LTCI benefits despite having BADL limitations, and 806 who did not provide information on the BADL items, to avoid the problem of reverse causation. We also excluded data for 306 cases for which information on living arrangements was not provided. Data for a total of 13,468 respondents (6600 men and 6868 women) were finally included in the analysis.

Measurements

Outcome

We collected information on the onset of BADL decline from the LTCI records administrated by municipalities. The LTCI system classifies frail older adults into seven levels (Support need levels 1 and 2 and Care need levels 1 to 5; a larger number indicates a more severe level) using a nationally standardized and validated algorithm. The levels are solely determined according to older adults’ physical and mental care needs, regardless of informal care provided to the recipients [28] and assessed by both computer-based and home-visit interviews by a trained healthcare professional and examination by a primary physician [29]. In the computer-based assessment, time required for care is calculated according to nine categories of care needs such as five domains of BADL care (bathing, eating, toileting, dressing, and transferring), assistance with instrumental activities of daily living (IADL), behavioral problems, rehabilitation, and medical services [28]. In our study, BADL decline was defined as a new registration within the LTCI records with a care-needs level of 2 or above, which requires 50 min of care or longer per day and nearly corresponds to the need for any type of BADL care [29]. More detailed information was shown in another study [28].

Living Arrangements

Japanese families have been traditionally based on the “stem family” system, indicating cohabitation of parent(s) and one of their children (typically, the eldest son and his wife) [30]. Although a recent trend shows an increase in solitary households, the majority of older adults live with their spouse and/or children [31]. Since our focus was on examining the risk of cohabitation status of older adults without spouses, we created a living arrangement variable with three categories: living with a spouse, living without a spouse but with at least one non-spousal cohabitant, and living alone. Previous studies in Asian countries [11, 15] showed no significant differences based on the presence of children among those who lived with a spouse, suggesting that living with a spouse could comprise one category regardless of the presence of other family members. Regarding older adults living only with non-spousal cohabitants, about 90% lived with their children, grandchildren, or other blood relatives in this study. Although it is possible that older adults living only with in-law families differ psychosocially from those living with blood relatives, our preparatory analysis showed almost no significant differences between these groups, except for education and income. Therefore, we regarded them as a group. Additionally, a total of 20 cases among 13,468 respondents lived only with non-relatives. Those people were included in the category of older adults living only with non-spousal cohabitants.

Mediators

We regarded health-related behaviors and social support as possible mediators in the relationship between living arrangements and onset of BADL decline according to the context of marital protection [7, 8, 10]. In terms of health-related behaviors, we assessed smoking habits (none vs. past/current), alcohol consumption (none vs. yes), and body mass index, which was calculated using the respondent’s self-rated height and weight, and categorized into “less than 18.5 kg/m2,” “18.5–24.9 kg/m2,” and “25.0 kg/m2 or over.” In addition, daily walking time (less than 30 min vs. 30 min or longer) was assessed as a potential physical activity mediator, since walking was one of the most popular physical activities in Japanese older adults [32] and known as a predictor of physical function [33]. Regarding social support, we assessed emotional support received (“Do you have someone to listen to your concerns or complaints?”), emotional support provided (“Do you listen to someone’s concerns and complaints?”), instrumental support received (“Do you have someone who looks after you when you are sick and confined to a bed for a few days?”), and instrumental support provided (“Do you look after someone when he/she is sick and confined to a bed for a few days?”). Each support variable had “yes” or “no” response options.

Covariates

Covariates in this study were selected according to previous studies on risk factors for functional decline [34]: age, education, income, and baseline health status as potential precursors of living arrangements of older adults [23]. In terms of health variables, we assessed self-rated health, presence of illness, depression, IADL, and subjective cognitive complaints (SCC). Self-rated health was assessed using one question: “How do you rate your health?” Response options ranged from excellent to poor, and were dichotomized into two categories (excellent/good vs. fair/poor). Presence of illness was assessed in terms of whether participants had at least one illness such as cancer, heart disease, stroke, hypertension, diabetes, obesity, hyperlipidemia, osteoporosis, arthritis, trauma, respiratory illness, gastrointestinal illness, liver illness, mental illness, dysphagia, visual/hearing impairment, or incontinence. Depression was assessed with a 15-item Japanese version of the Geriatric Depression Scale [35]. Scores on the scale were categorized into three groups: “no depression (0–4 points),” “depressive tendency (5–9),” and “depression (10 and above).” We assessed IADL using a five-item subscale from the Tokyo Metropolitan Institute of Gerontology Higher Competence Scale. The scale was developed based on Lawton’s model of competence [36] and its validity and reliability were confirmed [37]. We dichotomized respondents based on their having difficulty with at least one item, for instance, shopping for daily necessities. We assessed SCC using one item asking respondents if they often perceived themselves to be disoriented. Equivalized household income (low, middle, or high), years of education (less than 10 years, or 10 years or more), age in years, and gender (male or female) were also assessed. All mediators and covariates included a missing category, except for age and gender.

Analysis

All analyses were conducted by gender because we hypothesized that the relationships between living arrangements and BADL disability would differ by gender. After presenting descriptive statistics and differences for each variable among the three living arrangement categories, we examined the relationship between living arrangements and the onset of BADL disability using a Cox proportional hazards model by entering the group of covariates and mediators hierarchically. First, only age was controlled (Model 1). Second, household income, education, and health variables were added to Model 1 (Model 2) to examine the relationship of living arrangements, excluding differences based on the precursors. Additionally, we conducted a series of sub-analyses that examined the differences between the two non-spouse household groups in men and women. Further, to examine gender differences in the relationship between living arrangements and onset of BADL disability, we entered the cross-product terms of living with cohabitants or living alone by gender using the whole sample.

The next three models were employed to examine the influence of mediators on the relationship between living arrangements and BADL disability onset. We added each group of health-related behavior variables and social support variables to Model 2 (Models 3 and 4). Finally, all covariates were entered with living arrangements in the analytical model (Model 5). As a sensitivity analysis, we conducted mediation analysis for Models 3 and 4 to estimate mediation effects of health-related behavior variables (Model 3) and social support variables (Model 4). For this analysis, we applied logistic regression models instead of Cox proportional hazards models due to the limitation of the software program. Stata command “ldecomp” was used for the mediation analysis [38].

Although missing cases for each covariate were modest (24.8% at the most), 41.1% of the analyzed respondent data had a missing score for at least one covariate. Therefore, in those multivariate models, we performed a multiple imputation by chained equations under the assumption of missing at random. We generated 20 datasets, analyzed them separately, and pooled the estimates and standardized errors applying Rubin’s rules [39]. For mediation analysis, complete case analysis was applied. We regarded respondents who died or who were lost to follow-up due to relocation before the onset of BADL disability as censored cases. All analyses were conducted using IBM SPSS 22.0 J for Windows (IBM Japan Ltd., Tokyo, Japan) and STATA SE version 14.1 (Stata Corp., College Station, TX, USA). Statistical significance was set at p < .05.

Results

Tables 1 and 2 show the respondents’ characteristics by living arrangement status for men and women. For men, 85.5% lived with a spouse, 10.3% lived only with non-spousal cohabitants, and 4.2% lived alone; fewer women lived with a spouse (54.1%). Those living only with non-spousal cohabitants were older than those living with spouses for both men and women. Men living alone were more likely to have a depressive tendency or depression than those living only with non-spousal cohabitants or those living with a spouse. In contrast, IADL difficulty was less likely among men living alone compared to those living with non-spousal cohabitants or those living with a spouse. Men living alone were less likely to receive and provide emotional and instrumental support than those living with a spouse. For women, those living alone were less likely to receive or provide instrumental support than those with a spouse.
Table 1

Respondent characteristics by living arrangements for men (N = 6600)

Variables and categories

Total

With spouse

With non-spousal cohabitants

Living alone

 

n (%)

n (%)

n (%)

n (%)

p a

Living arrangements

 Living with spouse

5645 (85.5)

 Living with non-spousal cohabitants

677 (10.3)

 Living alone

278 (4.2)

Age

 65–69

2567 (38.9)

2308 (40.9)

173 (25.6)

86 (30.9)

p < .001

 70–74

2044 (31.0)

1767 (31.3)

191 (28.2)

86 (30.9)

 

 75–79

1275 (19.3)

1048 (18.6)

159 (23.5)

68 (24.5)

 

 80–84

526 (8.0)

409 (7.2)

94 (13.9)

23 (8.3)

 

 85 and older

188 (2.8)

113 (2.0)

60 (8.9)

15 (5.4)

 

Years of education

  < 10

3603 (54.6)

2991 (53.0)

458 (67.7)

154 (55.4)

p < .001

  ≥ 10

2950 (44.7)

2618 (46.4)

211 (31.2)

121 (43.5)

 

 Missing

47 (0.7)

36 (0.6)

8 (1.2)

3 (1.1)

 

Household income

 Low

2263 (34.3)

1981 (35.1)

204 (30.1)

78 (28.1)

p < .001

 Middle

3022 (45.8)

2633 (46.6)

267 (39.4)

122 (43.9)

 

 High

731 (11.1)

616 (10.9)

95 (14.0)

20 (7.2)

 

 Missing

54 (8.8)

415 (7.4)

111 (16.4)

58 (20.9)

 

Self-rated health

 Excellent/good

4879 (73.9)

4229 (74.9)

453 (66.9)

197 (70.9)

p < .001

 Fair/poor

1659 (25.1)

1370 (24.3)

211 (31.2)

78 (28.1)

 

 Missing

62 (0.9)

46 (0.8)

13 (1.9)

3 (1.1)

 

Presence of illness

 No

1204 (18.2)

1036 (18.4)

115 (17.0)

53 (19.1)

p = .239

 Yes

5181 (78.5)

4436 (78.6)

531 (78.4)

214 (77.0)

 

 Missing

215 (3.3)

173 (3.1)

31 (4.6)

11 (4.0)

 

Geriatric Depression Scale

 No depression

4304 (65.2)

3784 (67.0)

398 (58.8)

122 (43.9)

p < .001

 Depressive tendency

1264 (19.2)

1037 (18.4)

153 (22.6)

74 (26.6)

 

 Depression

364 (5.5)

273 (4.8)

51 (7.5)

40 (14.4)

 

 Missing

668 (10.1)

551 (9.8)

75 (11.1)

42 (15.1)

 

Instrumental activities of daily living

 Without difficulty

4935(74.8)

4212 (74.7)

483 (71.3)

238 (85.6)

p < .001

 With difficulty

1455 (22.0)

1256 (22.2)

165 (23.8)

34 (12.2)

 

 Missing

210 (3.2)

175 (3.0)

29 (4.3)

6 (2.2)

 

Subjective cognitive complaints

 No

5597 (84.8)

4811 (85.2)

549 (81.1)

237 (85.3)

p = .023

 Yes

891 (13.5)

737 (13.1)

114 (16.8)

40 (14.4)

 

 Missing

112 (1.7)

97 (1.7)

14 (2.1)

1 (0.4)

 

Body mass index

  < 18.5

435 (6.6)

337 (6.0)

71 (10.5)

27 (9.7)

p < .001

 18.5–24.9

4685 (71.0)

4036 (71.5)

454 (67.1)

195 (70.1)

 

  ≥ 25

1320 (20.0)

1147 (20.3)

125 (18.5)

48 (17.3)

 

 Missing

160 (2.4)

125 (2.2)

27 (4.0)

8 (2.9)

 

Alcohol consumption

 No

2700 (40.9)

2258 (40.0)

317 (46.8)

125 (45.0)

p = .007

 Yes

3812 (57.8)

3312 (58.7)

350 (51.7)

150 (54.0)

 

 Missing

88 (1.3)

75 (1.3)

10 (1.5)

3 (1.1)

 

Smoking habit

 None

1737 (26.3)

1494 (26.5)

174 (25.7)

69 (24.8)

p = .073

 Past/current

4657 (70.6)

3989 (70.7)

473 (69.9)

195 (70.1)

 

 Missing

206 (3.1)

162 (2.9)

30 (4.4)

14 (5.0)

 

Daily walking time

  ≥ 30 min

4105 (62.2)

3556 (630)

383 (56.6)

166 (59.7)

p = .015

  < 30 min

2069 (31.3)

1735 (30.7)

239 (35.3)

95 (34.2)

 

 Missing

426 (6.5)

354 (6.3)

55 (8.1)

17 (6.1)

 

Emotional support received

 Yes

5471 (82.9)

4776 (84.6)

505 (74.6)

190 (68.3)

p < .001

 No

858 (13.0)

657 (11.6)

126 (18.6)

75 (27.0)

 

 Missing

271 (4.1)

212 (3.8)

46 (6.8)

13 (4.7)

 

Emotional support provided

 Yes

5179 (78.5)

4532 (80.3)

469 (69.3)

178 (64.0)

p < .001

 No

1113 (16.9)

866 (15.3)

163 (24.1)

84 (30.2)

 

 Missing

308 (4.7)

247 (4.4)

45 (6.6)

16 (5.8)

 

Instrumental support received

 Yes

6157 (933)

5369 (95.1)

610 (90.1)

178 (64.0)

p < .001

 No

239 (3.6)

110 (1.9)

41 (6.1)

88 (31.7)

 

 Missing

204 (3.1)

166 (2.9)

26 (3.8)

12 (4.3)

 

Instrumental support provided

 Yes

5904 (89.5)

5221 (92.5)

518 (76.5)

165 (59.4)

p < .001

 No

435 (6.6)

223 (4.0)

116 (17.1)

96 (34.5)

 

 Missing

261 (4.0)

201 (3.6)

43 (6.4)

17 (6.1)

 

aA chi-square test was used to examine differences among living arrangement categories

Table 2

Respondent characteristics by living arrangements for women (N = 6868)

Variables and categories

Total

With spouse

With non-spousal cohabitants

Living alone

 

n (%)

n (%)

n (%)

n (%)

p a

Living arrangements

 Living with spouse

3716 (54.1)

 Living with non-spousal cohabitants

2076 (30.2)

 Living alone

1076 (15.7)

Age

 65–69

2417 (35.2)

1724 (46.4)

426 (20.5)

267 (24.8)

p < .001

 70–74

1993 (29.0)

1171 (31.5)

480 (23.1)

342 (31.8)

 

 75–79

1433 (20.9)

632 (17.0)

536 (25.8)

265 (24.6)

 

 80–84

701 (10.2)

166 (4.5)

388 (18.7)

147 (13.7)

 

 85 and older

324 (4.7)

23 (0.6)

246 (11.8)

55 (5.1)

 

Years of education

  < 10

4294 (62.5)

2227 (59.9)

1430 (68.9)

637 (59.2)

p < .001

  ≥ 10

2495 (36.3)

1460 (39.3)

614 (29.6)

421 (39.1)

 

 Missing

79 (1.2)

29 (0.8)

32 (1.5)

18 (1.7)

 

Household income

 Low

2257 (32.9)

1276 (34.3)

539 (26.0)

442 (41.1)

p < .001

 Middle

2269 (33.0)

1498 (40.3)

545 (26.3)

226 (21.0)

 

 High

637 (9.3)

330 (8.9)

279 (13.4)

28 (2.6)

 

 Missing

1705 (24.8)

612 (16.5)

713 (34.3)

380 (35.3)

 

Self-rated health

 Excellent/good

4994 (72.7)

2721 (73.2)

1493 (71.9)

780 (72.5)

p = .118

 Fair/poor

1752 (25.5)

941 (25.3)

533 (25.7)

278 (25.8)

 

 Missing

122 (1.8)

54 (1.5)

50 (2.4)

18 (1.7)

 

Presence of illness

 No

1124 (16.4)

649 (17.5)

326 (15.7)

149 (13.8)

p = .013

 Yes

5393 (78.5)

2896 (77.9)

1628 (78.4)

869 (80.8)

 

 Missing

351 (5.1)

171 (4.6)

122 (5.9)

58 (5.4)

 

Geriatric Depression Scale

 No depression

3961 (57.7)

2243 (60.4)

1180 (56.8)

538 (50.0)

p < .001

 Depressive tendency

1319 (19.2)

699 (18.8)

376 (18.1)

244 (22.7)

 

 Depression

384 (5.6)

187 (5.0)

128 (6.2)

69 (6.4)

 

 Missing

1204 (17.5)

587 (15.8)

392 (18.9)

225 (20.9)

 

Instrumental activities of daily living

 Without difficulty

5630 (82.0)

3229 (86.9)

1474 (71.0)

927 (86.2)

p < .001

 With difficulty

1010 (14.7)

386 (10.3)

506 (24.4)

118 (11.0)

 

 Missing

228 (3.3)

101 (2.5)

96 (4.6)

31 (2.9)

 

Subjective cognitive complaints

 No

5673 (82.6)

3179 (85.5)

1601 (77.1)

893 (83.0)

p < .001

 Yes

1035 (15.1)

464 (12.5)

414 (19.9)

157 (14.6)

 

 Missing

160 (2.3)

73 (1.9)

61 (2.9)

26 (2.4)

 

Body mass index

  < 18.5

531 (7.7)

245 (6.6)

190 (9.2)

96 (8.9)

p < .001

 18.5–24.9

4497 (65.5)

2498 (67.2)

1289 (62.1)

710 (66.0)

 

  ≥ 25

1523 (22.2)

860 (23.1)

452 (21.8)

211 (19.6)

 

 Missing

317 (4.6)

113 (3.0)

145 (7.0)

59 (5.5)

 

Alcohol consumption

 No

5882 (85.6)

3157 (85.0)

1818 (87.6)

907 (84.3)

p < .001

 Yes

848 (12.3)

508 (13.7)

202 (9.7)

138 (12.8)

 

 Missing

138 (2.0)

51 (1.4)

56 (2.7)

31 (2.9)

 

Smoking habit

 None

6176 (89.9)

3387 (91.13)

1845 (88.9)

944 (87.7)

p < .001

 Past/current

411 (6.0)

206 (5.5)

122 (5.9)

83 (7.7)

 

 Missing

281 (4.1)

123 (3.3)

109 (5.3)

49 (4.6)

 

Daily walking time

  ≥ 30 min

3768 (54.9)

2078 (55.9)

1133 (54.6)

557 (51.8)

p = .015

  < 30 min

2187 (31.8)

1147 (30.9)

651 (31.4)

389 (36.2)

 

 Missing

913 (13.3)

491 (13.2)

292 (14.1)

130 (12.1)

 

Emotional support received

 Yes

6189 (90.1)

3402 (91.6)

1856 (89.4)

931 (86.5)

p < .001

 No

402 (5.9)

183 (4.9)

119 (5.7)

100 (9.3)

 

 Missing

277 (4.0)

131 (3.5)

101 (4.9)

45 (4.2)

 

Emotional support provided

 Yes

5587 (81.3)

3155 (84.9)

1566 (75.4)

866 (80.5)

p < .001

 No

887 (12.9)

385 (10.4)

363 (17.5)

139 (12.9)

 

 Missing

394 (5.7)

176 (4.7)

147 (7.1)

71 (6.6)

 

Instrumental support received

 Yes

6119 (89.1)

3415 (91.9)

1868 (90.0)

836 (77.7)

p < .001

 No

502 (7.3)

180 (4.8)

125 (6.0)

197 (18.3)

 

 Missing

247 (3.6)

121 (3.3)

83 (4.0)

43 (4.0)

 

Instrumental support provided

 Yes

5996 (87.3)

3440 (92.6)

1732 (83.4)

824 (76.6)

p < .001

 No

496 (7.2)

120 (3.2)

205 (9.9)

171 (15.9)

 

 Missing

376 (5.5)

156 (4.2)

139 (6.7)

81 (7.5)

 

aA chi-square test was used to examine differences among living arrangement categories

Table 3 shows the incidence rate of the onset of BADL disability during the 9.4-year follow-up period in each category of the explanatory variables. A total of 1108 men and 1248 women showed new onset of disability, with incidence rates per 1000 person-years being 21.4 and 22.3, respectively, for men and women. In men, the incidence rates were 19.4, 35.6, and 32.4, in those with a spouse, living only with non-spousal cohabitants, and living alone, respectively. In women, the rates were 15.0, 34.0, and 27.8, in those who lived with a spouse, those without a spouse and with non-spousal cohabitants, and those living alone, respectively. The incidence rate of onset of BADL disability in those aged 85 and older was more than 10 times higher than those aged 65 to 69 in both men and women.
Table 3

Incidence rate of basic activities of daily living disability onset during the follow-up period

Variables

Categories

Men

Women

Incidence/person-year

Incidence rate per 1000

p a

Incidence/person-year

Incidence rate per 1000

p a

Total

1108/51734

21.4

1248/55850

22.3

Living arrangement

Living with spouse

871/44890

19.4

p < .001

473/31543

15.0

p < .001

Living with non-spousal cohabitants

171/4806

35.6

 

541/15897

34.0

 

Living alone

66/2039

32.4

 

234/8410

27.8

 

Age

65–69

184/21906

8.4

p < .001

148/21341

6.9

p < .001

70–74

309/16272

19.0

 

244/16573

14.7

 

75–79

322/9216

34.9

 

357/11301

31.6

 

80–84

199/3384

58.8

 

307/4955

62.0

 

85 and over

94/955

98.4

 

192/1680

114.3

 

Years of education

<10

656/27872

23.5

p < .001

837/34714

24.1

p < .001

≥10

441/23498

18.8

 

387/20572

18.8

 

Missing

11/364

30.2

 

24/565

42.5

 

Equivalent income

Low

376/17,492

21.5

p < .001

407/18,495

22.0

p < .001

Middle

473/23995

19.7

 

310/18910

16.4

 

High

113/5910

19.1

 

119/5051

23.6

 

Missing

146/4336

33.7

 

412/13393

30.8

 

Self-rated health

Excellent/good

704/39459

17.8

p < .001

749/41359

18.1

p < .001

Fair/poor

387/11844

32.7

 

469/13540

34.6

 

Missing

17/431

39.4

 

30/951

31.6

 

Presence of illness

No

131/10138

12.9

p < .001

120/9535

12.6

p < .001

Yes

941/39942

23.6

 

1060/43543

24.3

 

Missing

36/1655

21.8

 

68/2771

24.5

 

Geriatric Depression Scale

No depression

619/34677

17.9

p < .001

583/32958

17.7

p < .001

Depressive tendency

250/9493

26.3

 

289/10422

27.7

 

Depression

89/2548

34.9

 

101/2941

34.3

 

Missing

150/5016

29.9

 

275/9529

28.9

 

Instrumental activities of daily living

Without difficulty

724/39518

18.3

p < .001

778/47101

16.5

p < .001

With difficulty

324/10675

30.4

 

408/6996

58.3

 

Missing

60/1541

38.9

 

62/1753

35.4

 

Subjective cognitive complaints

No

850/44512

19.1

p < .001

893/46860

19.1

p < .001

Yes

226/6428

35.2

 

307/7807

39.3

 

Missing

32/794

40.3

 

48/1183

40.6

 

Body mass index

<18.5

122/2938

41.5

p < .001

151/3920

38.5

p < .001

18.5–24.9

767/37038

20.7

 

732/36996

19.8

 

≥25

177/10653

16.6

 

240/12722

18.9

 

Missing

42/1105

38.0

 

125/2212

56.5

 

Alcohol consumption

No

512/20451

25.0

p < .001

1105/47731

23.2

p < .001

Yes

577/30608

18.9

 

97/7109

13.6

 

Missing

19/675

28.1

 

46/1010

45.5

 

Smoking habit

None

299/13849

21.6

p = .887

1083/50509

21.4

p < .001

Past/current

774/36350

21.3

 

82/3186

25.7

 

Missing

35/1535

22.8

 

83/2155

38.5

 

Daily walking time

≥30 min

632/32851

19.2

p < .001

637/30997

20.6

p < .001

<30 min

411/15574

26.4

 

451/17498

25.8

 

Missing

65/3309

19.6

 

160/7355

21.8

 

Emotional support received

Yes

851/43165

19.7

p < .001

1085/50517

21.5

p < .001

No

183/6589

27.8

 

92/3151

29.2

 

Missing

74/1980

37.4

 

71/2182

32.5

 

Emotional support provided

Yes

781/41271

18.9

p < .001

916/46023

19.9

p < .001

No

240/8182

29.3

 

236/6740

35.0

 

Missing

87/2280

38.2

 

96/3086

31.1

 

Instrumental support received

Yes

997/48425

20.6

p < .001

1090/49835

21.9

p = .031

No

51/1812

28.2

 

100/4077

24.5

 

Missing

60/1498

40.1

 

58/1938

29.9

 

Instrumental support provided

Yes

927/46692

19.9

p < .001

972/49306

19.7

p < .001

No

113/3101

36.4

 

164/3654

44.9

 

Missing

68/1940

35.0

 

112/2890

38.8

 

a A log-rank test was used to examine differences among categories for each study variable

Table 4 shows the relationship of living without a spouse (with non-spousal cohabitants or without any cohabitants) for men and women. In Model 1, adjusting for age, both non-spouse household groups were significantly related to the onset of BADL disability in men (hazard ratio [HR] = 1.39 for men only with non-spousal cohabitants; HR = 1.42 for men living alone). When controlling for age, socioeconomic variables, and health variables, HR was 1.38 for men with non-spousal cohabitants, and was slightly increased (HR = 1.45) for those living alone (Model 2). In women, both non-spouse household groups showed no significant relationship with BADL disability in Model 1, and living alone showed a significant relationship in Model 2 (HR =1.19). Among such differences in the relationship between living arrangements and the onset of BADL disability by gender, the interaction effect of living only with non-spousal cohabitants by gender was marginally significant (p = .080), indicating a tendency toward a stronger association in men. A sub-analysis to examine differences between the two non-spouse household groups showed no significant difference for men or women in any models. For instance, compared to those who lived only with non-spousal cohabitants, the HR of those living alone was 1.12 (95% confidence interval: 0.82–1.51) and 1.06 (95% confidence interval: 0.90–1.25) in men and women, respectively, controlling for age, socioeconomic status, and health variables.
Table 4

Risk of living arrangements on the onset of basic activities of daily living disability

 

Men

Women

HR (95% CI)a

HR (95% CI)a

Model 1b

Living arrangements

 Living with spouse (Reference)

1.00

1.00

 Living with non-spousal cohabitants

1.39 (1.18–1.64)

1.09 (0.95–1.26)

 Living alone

1.42 (1.11–1.83)

1.14 (0.97–1.35)

Model 2c

Living arrangements

 Living with spouse (Reference)

1.00

1.00

 Living with non-spousal cohabitants

1.38 (1.16–1.63)

1.08 (0.94–1.24)

 Living alone

1.45 (1.12–1.87)

1.19 (1.01–1.40)

Model 3d

Living arrangements

 Living with spouse (Reference)

1.00

1.00

 Living with non-spousal cohabitants

1.37 (1.16–1.62)

1.09 (0.95–1.25)

 Living alone

1.45 (1.12–1.87)

1.19 (1.01–1.40)

Model 4e

Living arrangements

 Living with spouse (Reference)

1.00

1.00

 Living with non-spousal cohabitants

1.32 (1.11–1.57)

1.07 (0.93–1.23)

 Living alone

1.34 (1.02–1.76)

1.17 (0.98–1.38)

Model 5f

Living arrangements

 Living with spouse (Reference)

1.00

1.00

 Living with non-spousal cohabitants

1.31 (1.10–1.56)

1.08 (0.94–1.24)

 Living alone

1.35 (1.03–1.77)

1.16 (0.98–1.38)

a HR hazard ratio, CI confidence interval

bModel 1: The effect of living arrangements on the outcome variable controlling for age

cModel 2: Model 1 + education + household income + health variables (self-rated health, presence of illness, depression, instrumental activities of daily living, and subjective cognitive complaints)

dModel 3: Model 2 + heath-related behavior variables (body mass index, alcohol consumption, smoking habits, and daily walking time) were controlled

eModel 4: Model 2 + social support variables (emotional support received, emotional support provided, instrumental support received, and instrumental support provided) were controlled

fModel 5: All covariates were controlled

The next three models revealed a substantial excess risk reduction for both non-spouse household groups in men in Model 4, which controlled for social support variables within Model 2. The HR decreased from 1.45 (Model 2) to 1.34 (Model 4) in men living alone, indicating 24.4% excess risk reduction. For men living only with non-spousal cohabitants, a 15.8% excess risk reduction was found in Model 4 compared to Model 2. Additionally, to examine the relative importance of received or provided supports, we conducted an analysis entering the two support-received and two support-provided variables separately in Model 4, and found that the HR of men living alone was 1.40 in the model using only support-received variables, and 1.33 when controlling only for support provided variables. The same tendency was found in men who lived only with non-spousal cohabitants (HR = 1.36 and 1.32, respectively). As for women living alone, Model 4 showed a similar reduction in excess risk of BADL disability of 10.5% compared to Model 2, and social support provision variables almost explained the reduction. The mediation analysis revealed a significant mediating effect of social support in men, which represented 18% and 49% of the total effect in those living with non-spousal cohabitants (p = .004) and those living alone (p = .036), respectively. On the other hand, mediation effects of health-related variables and those of social support variables in women were non-significant [see Additional file 1: Table S1].

Finally, we conducted a series of sensitivity analyses. First, we limited respondents to those whose IADL were independent at baseline (n = 10,892) to avoid reverse causation in which mild disability affected living arrangements. The findings showed that HR for men living with non-spousal cohabitants and those living alone decreased from 1.38 and 1.45 to 1.28 and 1.36, respectively, while HR for women living alone slightly increased to 1.28. Second, we excluded respondents who experienced spousal bereavement within a year (n = 537) to avoid the influence of this type of recent stressful life event on BADL disability. The findings showed that HR for men living with non-spousal cohabitants and those living alone were 1.33 and 1.41, respectively, while HR in women living alone decreased from 1.19 to 1.12.

Discussion

Under the premise of a relatively low rate of needs-driven cohabitation, this study showed a relationship between living arrangements and BADL disability onset, taking into consideration gender differences and cohabitation status of those living without a spouse. Indeed, in our data, only 429 among 13,468 cases (3.2%) moved out during the 9.4 years of the follow-up period. The findings of this study showed that men living without a spouse, regardless of the presence of cohabitants, were more likely to develop BADL disability than those who lived with a spouse, while for women, a significant relationship was found only when they lived alone. Although the interaction effect of living only with non-spousal cohabitants by gender was only marginally significant, this study suggests higher risk in older men compared to women when they live only with non-spousal cohabitants. Several studies have also shown higher risk for BADL disability in older adults living only with non-spousal cohabitants compared to those living with a spouse [12, 15]. However, our study provided new findings that excess risk of living with non-spousal cohabitants in older adults could depend on gender. Our findings suggest that men rely on spousal relationships for protecting their functional health, and that non-spousal cohabitants such as adult children do not compensate sufficiently for the role of the spouse. On the other hand, women may gain health protection from cohabitants, regardless of spousal relationships. Thus, the findings of this study confirmed the need to examine gender-specific risk assessments in the association between social relationships and functional health.

Contrary to previous studies [11, 13, 16, 17] showing a health advantage in older adults living alone compared to those living only with non-spousal cohabitants, the sub-group analysis in this study showed no significant differences in men and women despite using a larger or comparable sample size. This discrepancy might reflect a lower level of reverse causation in this study compared to previous studies, in which decreasing functional ability among older adults living alone leads to cohabitation with non-spousal family members such as adult children.

Our findings also showed a potential pathway between living arrangements and BADL disability. A series of hierarchical analyses (Table 4) showed that social support exchange variables explained more excess risk than did health-related behaviors in men living alone and those living only with non-spousal cohabitants, with reduction rates of 24.4% and 15.8%, respectively. In addition, a subsequent analysis showed the relative importance of support provision rather than support receipt by older adults in decreasing excess risk of BADL disability, even when controlling for predictors such as health. Social support provision is known to improve health in older adults [40, 41]. Older men provide support mostly to their wife, while women provide support to more extended network members such as a spouse, children, or others [22]. Therefore, our findings suggest that living without a spouse could affect disability onset, partially due to lack of opportunities for support provision particularly in men. However, further research is necessary to examine the effect of social support provision and its pathways to functional disability, as the studies in this area are few [42].

Although the lack of social support exchange could explain part of the excess risk for BADL disability, men without spouses still had a significantly higher BADL disability risk than those living with a spouse after controlling for all covariates including mediator variables. This implies that the excess risk of BADL disability in men could be explained by unmeasured factors such as a decrease in social roles or self-efficacy [43].

Limitations

There were several limitations to this study. First, the onset of BADL was assessed based on the LTCI system; therefore, older adults with functional difficulty who had not applied for the LTCI benefit could have been misclassified as having no functional disabilities. However, such misclassification is less likely for the more severe levels of disability examined in this study [44]. Furthermore, BADL disability in this study was assessed using uniform nationwide criteria based on both a home-visit interview by a trained healthcare professional and a primary physician’s opinion, suggesting that the outcome was less likely to suffer from self-report bias. However, further studies should replicate the findings of this study, using cut-off points reflecting more severe disability for LTCI care-needs or other BADL assessments.

Second, we measured living arrangements as well as covariates (for instance, IADL) only at baseline, which could have changed during the follow-up period of almost 10 years. Although the residential mobility rate in the data we used was very low during the follow-up period, implying less residential moves for support needs, it is still possible that respondents who had lived alone and then started to live with others during the follow-up period may have confounded the findings. In addition, more respondents could have experienced widowhood in the follow-up period, which may have led to an underestimation of the difference between those living with and without spouses in this study. Although we confirmed the excess risk of men living with non-spousal cohabitants and men living alone, even excluding those having a recent spousal bereavement from the analysis, we should further consider the effect of change in living arrangements in older adults to better understand the relationships between living arrangements and health.

Third, generalizability of this study is limited due to a moderate response rate (52.1%); however, the respondents were selected randomly or completely enumerated from 10 municipalities in Japan.

Implications

Despite these limitations, the findings of our study could provide effective suggestions for the prevention of functional disability in community-dwelling older adults. Focusing on gender differences is important with respect to the role of living arrangements in the prevention of functional disability. Furthermore, more focus should be placed on support needs of older men living without spouses but with non-spousal cohabitants, in addition to those living alone, since older people with any cohabitants tend to be overlooked within the formal support system despite being at risk of BADL decline.

Policy makers and professionals should enhance opportunities for support exchange, particularly support provision by older adults. Social participation is known to be effective for disability prevention [27], and provides opportunities for social support exchange among participants [43]. Therefore, encouraging social participation for older adults at risk for BADL disability due to lack of social support exchange could be helpful. However, since Japanese older men are less likely to participate in these community groups than women [32], it is important to explore the needs and preferences of older men. For instance, a group for walking [32] or manufacturing products [45] might be relatively more acceptable to older men.

Future studies should consider the effect of change in marital status or cohabitation in the analytical model, since studies have shown that these changes could have a negative impact on health [46]. Furthermore, more detailed attention needs to be paid to the role of social support exchanges with spouses in preventing functional disabilities. This may provide practical suggestions regarding possible preventive services for the increasing population of individuals without spouses in aging societies.

Conclusions

This study examined the relationship between living arrangements and BADL disability onset in community-dwelling older adults, taking into consideration gender differences and cohabitation status of those living without a spouse. The findings showed that older men without spouses were more likely to develop disability onset regardless of cohabitants, while a marginal difference was found only for women living alone, confirming the necessity for gender-specific risk assessments of the effect of social relationships on functional health. Our study also revealed a potential pathway of social support exchange between living arrangements and BADL disability onset, and particularly the role of support giving by older adults. Policy makers and professionals should enhance opportunities for support exchange, and in particular, support giving by older adults who are at risk of disability.

Abbreviations

AGES: 

Aichi Gerontological Evaluation Study

BADL: 

Basic activities of daily living

HR: 

Hazard ratio

JAGES: 

Japan Gerontological Evaluation Study

LTCI: 

Long-Term Care Insurance system

Declarations

Acknowledgements

We thank all JAGES project members for collaborating in our work. We also appreciate the work of Drs. H. Hirai, Y. Inoue, and S. Jeong in preparing the longitudinal dataset. This study used data from the Aichi Gerontological Evaluation Study (AGES) conducted by the Center for Well-being and Society, Nihon Fukushi University, as one of their research projects.

Funding

This study was supported by MEXT-Supported Program for the Strategic Research Foundation at Private Universities (2009–2013); Grant-in-Aid for Scientific Research (KAKENHI) (23,243,070, 18,390,200, and 25,713,027); and Grant (24–17 and 27–18) from the National Center for Gerontology and Geriatrics (NCGG).

Availability of data and materials

Data are from the AGES study, a part of the JAGES project. All enquiries are to be addressed to the data management committee via e-mail: dataadmin.ml@jages.net. All JAGES datasets have ethical or legal restrictions for public deposition due to inclusion of sensitive information from the human participants.

Authors’ contributions

All authors contributed to the conception and design of this study. Data collection was primarily conducted by KK. Analyses were performed by TS and JA, and supported by CM. TS prepared the initial manuscript and CM, JA, and KK significantly contributed to revising it. All authors read and approved the final manuscript.

Ethics approval and consent to participate

This survey project was conducted under a comprehensive agreement between each insurer and our research project team. The insurers took charge of conducting the survey and researchers analyzed anonymous data provided by the insurers. The study protocol and informed consent procedure were approved by the Nihon Fukushi University Ethics Committee.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

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Authors’ Affiliations

(1)
Department of Social Science, National Center for Geriatrics and Gerontology
(2)
Department of International and Community Oral Health, Tohoku University Graduate School of Dentistry
(3)
Center for Preventive Medical Science, Chiba University
(4)
Department of Gerontological Evaluation, National Center for Geriatrics and Gerontology

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