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01.12.2011 | Research article | Ausgabe 1/2011 Open Access

BMC Public Health 1/2011

Assessing the association between all-cause mortality and multiple aspects of individual social capital among the older Japanese

Zeitschrift:
BMC Public Health > Ausgabe 1/2011
Autoren:
Jun Aida, Katsunori Kondo, Hiroshi Hirai, S V Subramanian, Chiyoe Murata, Naoki Kondo, Yukinobu Ichida, Kokoro Shirai, Ken Osaka
Wichtige Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1186/​1471-2458-11-499) contains supplementary material, which is available to authorized users.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

JA had the idea for the study, participated in its design, performed the statistical analysis and drafted the manuscript as a principal author. KK helped develop the idea of the study, participated in acquiring the data and with design, and edited the manuscript. HH participated in acquiring the data and critically revising the manuscript. SVS participated in design of study, data analysis and critically revised the manuscript. CM, NK, YI, KS and KO participated in design of study and critically revised the manuscript. All authors read and approved the final manuscript.

Background

Few prospective cohort studies have assessed the association between social capital and mortality [15]. The studies did not use the same social capital indicators [15]. Some of these studies used proxy measures of social capital [6, 7], such as crime rate [1], electoral participation [1, 5] or volunteer activity [35]. There are several components of social capital, such as social network, participation, trust, reciprocity and volunteering [8]. Previous studies on social capital and mortality did not simultaneously use various components of social capital and their results were not fully consistent. In Finland, the association between mortality and individual social capital variables obtained by factor analysis (leisure participation, interpersonal trust and residential stability) was examined [2]. In men, leisure participation was associated with reduced all-cause mortality. In women, leisure participation and interpersonal trust were associated with reduced all-cause mortality. In a Swedish study, survival analyses showed that both neighbourhood social capital variables (election participation rate and crime rate) were significantly associated with mortality for males older than 65 years old but not for females [1]. Another study showed that living in a neighbourhood with the lowest level of social capital (volunteering, participation, political activities) was associated with significantly higher mortality than living in a neighbourhood with the highest level of social capital in England [5]. In contrast, among adults diagnosed and hospitalized with serious illnesses in the U.S, neighbourhood social capital (network density) was detrimental [4]. In addition, other neighbour social capital variables (social support, participation, volunteering, violence) did not significantly affect mortality [4]. In New Zealand, non-significant associations between neighbourhood social capital (volunteering) and mortality for both male and female were observed [3].
Studies on mortality and social capital have been conducted only in Western countries. However, social capital measurements developed in Western countries may not necessarily be equally applicable to Asian countries because of their different culture [9]. Although general trust has been broadly used as a measurement of social capital [10], it is known that intense ties within a family or group, often observed in collectivist cultures, prevent trust from developing beyond family or group boundaries [1113]. In Japan, a relatively collectivist society with intense group ties, human relationships are based on mutual assurance within group members rather than mutual trust between members from different groups [11, 13]. These cultural differences could potentially affect findings on the associations between social capital and health outcomes. In this respect, a social epidemiological study using various social capital indices in a non-Western cultural setting is important.
There is still debate about the precise definition and measurement of social capital [8, 14, 15]. Bourdieu defined social capital as "the aggregate of the actual or potential resources which are linked to possession of a durable network of more or less institutionalised relationships of mutual acquaintance and recognition"[16] and which focuses on the resources of individuals [8]. It is important to determine the association between individual social capital and health, because individual social capital indexes are components of aggregated measurements of community social capital [17]. Additionally, individual measures of social capital are not subject to the common problems arising from using area measurement in epidemiological studies, such as definition of a relevant areas [18, 19]. No study has used various measures of individual social capital as a predictor of mortality in a non-Western country. The aim of the present prospective cohort study was to assess the influence of individual social capital on all-cause mortality among older Japanese.

Methods

Study population and procedure

The present analysis is based on the Aichi Gerontological Evaluation Study (AGES) Project data, an on-going prospective cohort study [2024]. AGES investigates factors associated with the loss of health, including death and functional decline or cognitive impairment among older individuals. The study was undertaken in six municipalities covered the entire southern part of the Chita peninsula in Aichi Prefecture, Japan. During October one to 31 2003, a baseline mail questionnaire survey was administered. The follow-up started in November one 2003. Mortality data until May 2008 were obtained from 6 of the municipalities participating in AGES.
In 2003, there were 274,750 people living in the six municipalities, 17.9% of them being 65 years or older. The sample was restricted to people who did not already have physical or cognitive disabilities, defined as receiving public long-term care insurance benefits. From the municipalities, 29,374 community-dwelling, aged 65 years or over people were selected randomly. From this sample population, 14,804 people responded to the baseline survey. Of the 14,804 respondents, we could link the mortality data and baseline survey data on 14,668 subjects, because 91 were ineligible due to death, functional decline or cognitive impairment before November 1, 2003, and for a further 45 there was no information that would allow linking of the mortality data. Some subjects did not apply to certification of long-term care needs though they had limitations in basic activities of daily living including walking, bathing and toilet use. We excluded them from the analysis to avoid potential confounding (1,358 of the 14,668 respondents). Finally, 13,310 subjects (6,508 men and 6,802 women.) were included in the analysis for this cohort study. Figure 1 shows the study profile. Characteristics of participants at baseline have been reported elsewhere [23, 24]. The AGES protocol was reviewed and approved by the ethics committee in Research of Human Subjects at Nihon Fukushi University.

Social capital variables

Both cognitive and structural components [8, 10, 17, 25] of individual social capital were used. We basically followed Harpham's classification of social capital [17]. We used eight cognitive social capital variables, including general trust, social support and generalised reciprocity, and nine structural social capital variables, including social networks.

Cognitive social capital

General trust was measured by 3 questions: "Generally speaking, would you say that most people can be trusted?", "Do you think most people would try to take advantage of you if they got a chance?" and "Would you say that most of the time people try to be helpful?". For all these questions, response alternatives were "yes", "it depends" and "no".
Social support was measured by three questions, using a dichotomous answering choice (yes/no): "Do you have someone who listens to your concerns and complaints?", "Do you have someone who looks after you when you are sick and stay in bed for a few days?" and "Do you have someone who acknowledges your existence and value?".
Generalised reciprocity was measured by two questions, again with a dichotomous choice (yes/no): "Do you listen to someone's concerns and complaints?" and "Do you look after someone when he/she is sick and stays in bed for a few days?".

Structural social capital

Participation in community activities was used as an indication of social network. Respondents were asked whether they belonged to a (i) political organization or group, (ii) industrial or trade association, (iii) volunteer group, (iv) citizen or consumer group, (v) religious organization or group, (vi) sports group or club, (vii) neighbourhood association / senior citizen club / fire-fighting team and (viii) leisure activity group.
Social network was also measured by the question "How often do you meet your friends?" (response options: "almost everyday", "twice or three times a week", "once a week", "once or twice a month", "several times a year", "rarely" or "I have no friends"). For analyses purposes, the first four response options were integrated into one category, named "once or more/month".

Covariates

We also asked about socio-demographic characteristics, lifestyle and health condition and included the following in the analyses as covariates: age, sex, self-reported body mass index (BMI), self-rated health, present illness, smoking history, alcohol consumption, exercise, equivalent income and educational attainment [23]. Self-reported BMI was categorized into 4 groups (less than 18.5, 18.5-24.9, 25-29.9, 30 or more). Self-rated health was measured by a single question, "What is your current health status?: Excellent; Good; Fair; Poor". Present illnesses and present medical treatment were surveyed as follows: "Are you currently receiving any medical treatment?: I have no illnesses or disabilities; I have illness(es) or disability(ies) but need no treatment at the moment; I discontinued treatment of my own decision; I am currently receiving some treatment. Smoking history was recorded in 3 categories (never, quit or current) and alcohol consumption into 4 categories (non-drinker, do not drinking everyday, drinking 35 g of alcohol or less daily, or drink more than 35 g every day). Subjects were asked about how many minutes a day they walk - the exercise variable; less than 30 minutes, 30-60, 60-90 or more than 90 minutes or more. Years of educational attainment was grouped as less than 6 years, 6-9 years, 10-12 years and 13 years or more. Household income and number of household members were recorded and then equivalent income was calculated and categorized in Yen: less than 1,500,000; 1,500,000-1,999,999; 2,000,000-2,499,999; 2,500,000-2,999,999; 3,000,000-3,499,999; 3,500,000-3,999,999; 4,000,000-4,999,999; 500,000,000 or higher.

Mortality outcome

Mortality obtained from the municipality government registry was treated as all-causes.

Analysis

We used Cox proportional hazard models to calculate the hazard ratio (HR) and 95% confidential intervals (95%CI) for all-cause mortality during the follow-up period. At first, we calculated univariate hazard ratios for mortality for the categories of each social capital variable. In the covariate adjusted models, we assessed the effect of each social capital variable on mortality with adjustment for age, BMI, self-rated health, current illness, smoking history, alcohol consumption, exercise, equivalent income and educational attainment. All analyses were stratified by sex.
In terms of analysis of missing data (numbers of missing responses in each variable are described in Table 1,2), we used the missing at random assumption for the relevant procedures. Multiple imputation with the MICE (multivariate imputation by chained equations) method in STATA was used [26]. Cox proportional hazard models were independently applied for 10 copies of the data, each with missing values suitably imputed. Estimates of the variables were calculated to give a single mean estimate and adjusted standard errors according to Rubin's rules [27]. HRs and 95%CI of the Cox proportional hazard models were calculated from these estimates. We show results both from multiple imputation analyses and analyses with complete data for each model (non-imputation analyses). STATA SE version 11.1 (Stata Corp, College Station, TX) was used and sample weights were applied when estimating HR.
Table 1
Characteristics of the subjects by mortality rate: the Aichi Gerontological Evaluation Study (AGES), Aichi, Japan, 2003-2008
 
Man
Woman
 
N
Incidence/person-year
Incidence rate (95% CI) (1000 person-years)
N
Incidence/person-year
Incidence rate (95% CI) (1000 person-years)
Age
      
   65-69
2528
164/10978
14.9 (12.8-17.4)
2325
62/10285
6.0 (4.7-7.7)
   70-74
1982
181/8524
21.2 (18.4-24.6)
1908
76/8377
9.1 (7.2-11.4)
   75-79
1272
214/5288
40.5 (35.4-46.3)
1510
102/6533
15.6 (12.9-19.0)
   80-84
516
138/2035
67.8 (57.4-80.1)
715
82/3029
27.1 (21.8-33.6)
   85 or older
210
93/746
124.6 (101.7-152.7)
344
102/1336
76.3 (62.9-92.7)
Education (years)
      
   <6
154
31/628
49.3 (34.7-70.1)
407
60/1710
35.1 (27.2-45.2)
   6-9
3322
441/14046
31.4 (28.6-34.5)
3695
212/16108
13.2 (11.5-15.1)
   10-12
1755
179/7493
23.9 (20.6-27.7)
1959
109/8523
12.8 (10.6-15.4)
   ≥13
885
83/3764
22.1 (17.8-27.3)
343
15/1487
10.1 (6.1-16.7)
   Missing
392
56/1641
34.1 (26.3-44.3)
398
28/1733
16.2 (11.2-23.4)
Individual-level equivalent income ($)
      
   <15,000
1111
166/4634
35.8 (30.8-41.7)
1361
88/5889
14.9 (12.1-18.4)
   15,000-19,999
1132
116/4826
24.0 (20.0-28.8)
812
38/3563
10.7 (7.8-14.7)
   20,000-24,999
1364
171/5751
29.7 (25.6-34.5)
949
49/4155
11.8 (8.9-15.6)
   25,000-29,999
337
43/1415
30.4 (22.5-41.0)
295
19/1276
14.9 (9.5-23.3)
   30,000-39,999
1089
103/4695
21.9 (18.1-26.6)
804
42/3505
12.0 (8.9-16.2)
   40,000-49,999
382
28/1670
16.8 (11.6-24.3)
367
33/1573
21.0 (14.9-29.5)
   ≥50,000
278
25/1202
20.8 (14.1-30.8)
220
13/942
13.8 (8.0-23.8)
   Missing
815
138/3379
40.8 (34.6-48.3)
1994
142/8657
16.4 (13.9-19.3)
Self-rated health
      
   Very good
562
41/2440
16.8 (12.4-22.8)
489
22/2121
10.4 (6.8-15.8)
   Good
4161
377/17902
21.1 (19.0-23.3)
4367
224/19099
11.7 (10.3-13.4)
   Poor
1416
257/5842
44.0 (38.9-49.7)
1541
133/6633
20.0 (16.9-23.8)
   Very poor
300
99/1121
88.3 (72.5-107.6)
268
35/1112
31.5 (22.6-43.8)
   Missing
69
16/267
60.0 (36.8-98.0)
137
10/595
16.8 (9.0-31.2)
Self-reported BMI
      
   <18.5
464
116/1835
63.2 (52.7-75.9)
553
70/2333
30.0 (23.7-37.9)
   18.5-24.9
4527
511/19269
26.5 (24.3-28.9)
4378
240/19067
12.6 (11.1-14.3)
   25-29.9
1249
106/5388
19.7 (16.3-23.8)
1372
63/6028
10.5 (8.2-13.4)
   ≥30
74
8/317
25.2 (12.6-50.5)
142
5/631
7.9 (3.3-19.0)
   Missing
194
49/764
64.2 (48.5-84.9)
357
46/1503
30.6 (22.9-40.9)
Present illness
      
   No illness
1155
84/5015
16.7 (13.5-20.7)
1056
43/4632
9.3 (6.9-12.5)
   Having illness but need no treatment
743
82/3179
25.8 (20.8-32.0)
547
33/2378
13.9 (9.9-19.5)
   Having illness but discontinued treatment
404
51/1701
30.0 (22.8-39.4)
448
18/1965
9.2 (5.8-14.5)
   Receiving some treatment
3957
545/16599
32.8 (30.2-35.7)
4337
304/18780
16.2 (14.5-18.1)
   Missing
249
28/1076
26.0 (18.0-37.7)
414
26/1806
14.4 (9.8-21.1)
Alcohol consumption
      
   None
2787
433/11555
37.5 (34.1-41.2)
5791
369/25173
14.7 (13.2-16.2)
   Do not drink everyday
1156
110/4973
22.1 (18.3-26.7)
589
31/2563
12.1 (8.5-17.2)
   Drink every day (35 g of alcohol or less)
1885
175/8121
21.6 (18.6-25.0)
235
10/1018
9.8 (5.3-18.3)
   Drink every day (more than 35 g of alcohol)
572
51/2482
20.6 (15.6-27.0)
22
1/92
10.8 (1.5-76.8)
   Missing
108
21/442
47.5 (31.0-72.9)
165
13/714
18.2 (10.6-31.4)
Smoking status
      
   Non-smoker
1772
179/7584
23.6 (20.4-27.3)
6016
355/26191
13.6 (12.2-15.0)
   Quit
2991
339/12696
26.7 (24.0-29.7)
271
22/1157
19.0 (12.5-28.9)
   Current
1499
220/6297
34.9 (30.6-39.9)
172
20/729
27.4 (17.7-42.5)
   Missing
246
52/994
52.3 (39.9-68.6)
343
27/1483
18.2 (12.5-26.5)
Exercise
      
   Walking less than 30 minutes walk a day
2120
344/8789
39.1 (35.2-43.5)
2176
165/9414
17.5 (15.0-20.4)
   Walking 30-60 minutes walk a day
2222
246/9477
26.0 (22.9-29.4)
2101
136/9105
14.9 (12.6-17.7)
   Walking 60-90 minutes walk a day
906
74/3908
18.9 (15.1-23.8)
769
25/3378
7.4 (5.0-11.0)
   Walking 90 or more minutes walk a day
799
58/3472
16.7 (12.9-21.6)
788
38/3443
11.0 (8.0-15.2)
   Missing
461
68/1926
35.3 (27.8-44.8)
968
60/4221
14.2 (11.0-18.3)
Total
6508
790/27572
28.7 (26.7-30.7)
6802
424/29561
14.3 (13.0-15.8)
Table 2
Characteristics of the subjects according to social capital and mortality rate: the Aichi Gerontological Evaluation Study (AGES), Aichi, Japan, 2003-2008
  
Man
Woman
  
N
Incidence/person-year
Incidence rate (95% CI) (1000 person-years)
N
Incidence/person-year
Incidence rate (95% CI) (1000 person-years)
General trust
       
   Generally speaking, would you say that most people can be trusted or you cannot be too careful in dealing with people?
Yes (High SC)
2121
252/9007
28.0 (24.7-31.7)
1448
86/6290
13.7 (11.1-16.9)
 
Depends
3667
422/15577
27.1 (24.6-29.8)
4480
287/19452
14.8 (13.1-16.6)
 
No (Low SC)
545
80/2274
35.2 (28.3-43.8)
667
31/2937
10.6 (7.4-15.0)
 
Missing
175
36/713
50.5 (36.4-70.0)
207
20/882
22.7 (14.6-35.1)
   Would you say that most of the time people try to be helpful or that they are mostly looking out for themselves?
Yes (High SC)
1954
227/8291
27.4 (24.0-31.2)
1791
95/7817
12.2 (9.9-14.9)
 
Depends
3710
412/15796
26.1 (23.7-28.7)
4104
254/17826
14.2 (12.6-16.1)
 
No (Low SC)
645
106/2675
39.6 (32.8-47.9)
637
50/2760
18.1 (13.7-23.9)
 
Missing
199
45/810
55.5 (41.5-74.4)
270
25/1159
21.6 (14.6-31.9)
   Do you think that most people would try to take advantage of you if they got the chance, or would they try to be fair?
Yes (Low SC)
797
101/3377
29.9 (24.6-36.4)
616
40/2689
14.9 (10.9-20.3)
 
Depends
3418
378/14536
26.0 (23.5-28.8)
3558
210/15475
13.6 (11.9-15.5)
 
No (High SC)
2093
263/8847
29.7 (26.3-33.5)
2318
143/10073
14.2 (12.1-16.7)
 
Missing
200
48/812
59.1 (44.5-78.4)
310
31/1323
23.4 (16.5-33.3)
Social support
       
   Do you have someone who listens to your concerns and complaints?
Yes (High SC)
5267
605/22392
27.0 (24.9-29.3)
5995
360/26087
13.8 (12.4-15.3)
 
No (Low SC)
878
122/3671
33.2 (27.8-39.7)
424
34/1819
18.7 (13.4-26.2)
 
Missing
363
63/1508
41.8 (32.6-53.5)
383
30/1655
18.1 (12.7-25.9)
   Do you have someone who looks after you when you are sick and stay in bed for a few days?
Yes (High SC)
5967
713/25308
28.2 (26.2-30.3)
5988
372/26045
14.3 (12.9-15.8)
 
No (Low SC)
258
29/1081
26.8 (18.6-38.6)
485
23/2112
10.9 (7.2-16.4)
 
Missing
283
48/1182
40.6 (30.6-53.9)
329
29/1404
20.6 (14.3-29.7)
   Do you have someone who acknowledges your existence and value?
Yes (High SC)
5705
664/24243
27.4 (25.4-29.6)
5849
357/25440
14.0 (12.7-15.6)
 
No (Low SC)
433
65/1798
36.2 (28.4-46.1)
379
30/1628
18.4 (12.9-26.3)
 
Missing
370
61/1532
39.8 (31.0-51.2)
574
37/2492
14.8 (10.8-20.5)
Generalised reciprocity
       
   Do you listen to someone's concerns and complaints?
Yes (High SC)
4945
522/21122
24.7 (22.7-26.9)
5348
282/23326
12.1 (10.8-13.6)
 
No (Low SC)
1153
197/4748
41.5 (36.1-47.7)
941
107/4000
26.8 (22.1-32.3)
 
Missing
410
71/1701
41.7 (33.1-52.7)
513
35/2235
15.7 (11.2-21.8)
   Do you look after someone when he/she is sick and stays in bed for a few days?
Yes (High SC)
5690
651/24190
26.9 (24.9-29.1)
5785
324/25209
12.9 (11.5-14.3)
 
No (Low SC)
461
78/1901
41.0 (32.9-51.2)
526
53/2242
23.6 (18.1-30.9)
 
Missing
357
61/1481
41.2 (32.0-52.9)
491
47/2109
22.3 (16.7-29.7)
Social network
       
   Political group participation
Yes (High SC)
665
72/2848
25.3 (20.1-31.9)
287
13/1250
10.4 (6.0-17.9)
 
No (Low SC)
5230
605/22171
27.3 (25.2-29.6)
5622
347/24445
14.2 (12.8-15.8)
 
Missing
613
113/2553
44.3 (36.8-53.2)
893
64/3866
16.6 (13.0-21.2)
   Industry group participation
Yes (High SC)
952
108/4059
26.6 (22.0-32.1)
293
6/1304
4.6 (2.1-10.2)
 
No (Low SC)
4869
556/20653
26.9 (24.8-29.3)
5510
349/23929
14.6 (13.1-16.2)
 
Missing
687
126/2860
44.1 (37.0-52.5)
999
69/4327
15.9 (12.6-20.2)
   Volunteer group participation
Yes (High SC)
642
45/2796
16.1 (12.0-21.6)
574
22/2522
8.7 (5.7-13.2)
 
No (Low SC)
5122
613/21678
28.3 (26.1-30.6)
5255
331/22829
14.5 (13.0-16.1)
 
Missing
744
132/3097
42.6 (35.9-50.5)
973
71/4210
16.9 (13.4-21.3)
   Citizen group participation
Yes (High SC)
245
28/1044
26.8 (18.5-38.8)
309
10/1368
7.3 (3.9-13.6)
 
No (Low SC)
5465
622/23202
26.8 (24.8-29.0)
5470
346/23752
14.6 (13.1-16.2)
 
Missing
798
140/3326
42.1 (35.7-49.7)
1023
68/4441
15.3 (12.1-19.4)
   Religious group participation
Yes (High SC)
738
81/3152
25.7 (20.7-31.9)
698
38/3031
12.5 (9.1-17.2)
 
No (Low SC)
5021
580/21288
27.2 (25.1-29.6)
5151
319/22391
14.2 (12.8-15.9)
 
Missing
749
129/3131
41.2 (34.7-49.0)
953
67/4139
16.2 (12.7-20.6)
   Sports group participation
Yes (High SC)
1282
87/5602
15.5 (12.6-19.2)
1152
36/5074
7.1 (5.1-9.8)
 
No (Low SC)
4458
564/18776
30.0 (27.7-32.6)
4642
319/20118
15.9 (14.2-17.7)
 
Missing
768
139/3193
43.5 (36.9-51.4)
1008
69/4369
15.8 (12.5-20.0)
   Neighborhood group participation
Yes (High SC)
3445
384/14716
26.1 (23.6-28.8)
3583
199/15657
12.7 (11.1-14.6)
 
No (Low SC)
2531
308/10650
28.9 (25.9-32.3)
2557
170/11058
15.4 (13.2-17.9)
 
Missing
532
98/2206
44.4 (36.4-54.1)
662
55/2846
19.3 (14.8-25.2)
   Avocation group participation
Yes (High SC)
1592
126/6882
18.3 (15.4-21.8)
2054
75/9046
8.3 (6.6-10.4)
 
No (Low SC)
4192
533/17671
30.2 (27.7-32.8)
3819
285/16483
17.3 (15.4-19.4)
 
Missing
724
131/3019
43.4 (36.6-51.5)
929
64/4032
15.9 (12.4-20.3)
   How often do you meet your friend?
Once or more/month
4360
448/18691
24.0 (21.8-26.3)
5301
296/23134
12.8 (11.4-14.3)
 
Several times/year
1077
145/4513
32.1 (27.3-37.8)
610
31/2654
11.7 (8.2-16.6)
 
Rarely
752
141/3054
46.2 (39.1-54.5)
529
59/2231
26.4 (20.5-34.1)
 
Having no friends
151
24/620
38.7 (25.9-57.7)
125
22/508
43.3 (28.5-65.8)
 
Missing
168
32/694
46.1 (32.6-65.2)
237
16/1034
15.5 (9.5-25.3)
Total
 
6508
790/27572
28.7 (26.7-30.7)
6802
424/29561
14.3 (13.0-15.8)

Results

The average follow-up period was 4.29 years (SD = 0.75). During 27,571 person-years of follow-up for men and 29,561 person-years of follow-up for women, 790 all-cause deaths in men and 424 in women were observed. The incidence rate per 1000 person-years (IR) of death was 28.7 in men and 14.3 in women. Table 1 and 2 show the distribution of the number of deaths and IR according to covariates and social capital variables. Participants with low social capital in terms of generalised reciprocity and social network tended to have higher IR.
Table 3 shows the univariate and covariates adjusted mortality HRs for the different social capital variables among men. The results of multiple imputation models and non-imputation models were similar, particularly in the univariate models, but the 95%CIs were wider in most of the estimates obtained from the imputation models. In the univariate models using multiple imputation, lower social capital was significantly related to higher mortality in one general trust variable (people try to be helpful: HR = 1.42 (95%CI = 1.01-2.00)), all generalised reciprocity variables (listen to someone's concerns: HR = 1.59 (95%CI = 1.24-2.04); look after someone: HR = 1.49 (95%CI = 1.12-2.00)) and four social network variables (volunteer: HR = 1.78 (95%CI = 1.34-2.37); sports: HR = 1.89 (95%CI = 1.28-2.80); leisure: HR = 1.64 (95%CI = 1.21-2.20); meet friends rarely: HR = 1.99 (95%CI = 1.72-2.31)). When adjusting these models for covariates, only one low social network variable was found to be related to higher mortality (meet friends rarely: HR = 1.30 (95%CI = 1.10-1.53)), while the respective findings for two other social network variables (volunteering and leisure) were marginally not significant
Table 3
Univariate and covariate adjusted hazard ratios and 95% confidence intervals for all-cause mortality according to social capital
  
Univariate (imputation)
 
Univariate (non-imputation)
 
Covariate adjusted (imputation)
 
Covariate adjusted (non-imputation)
 
  
HR
95%CI
 
HR
95%CI
 
HR
95%CI
 
HR
95%CI
 
General trust
             
   Generally speaking, would you say that most people can be trusted? (Ref; Yes (High SC))
Depends
0.96
(0.77-1.20)
 
0.97
(0.80-1.17)
 
0.90
(0.69-1.16)
 
1.01
(0.77-1.33)
 
 
No (Low SC)
1.24
(0.91-1.70)
 
1.25
(0.96-1.63)
 
1.01
(0.74-1.36)
 
0.96
(0.65-1.42)
 
   Would you say that most of the time people try to be helpful? (Ref; Yes (High SC))
Depends
1.00
(0.84-1.20)
 
1.01
(0.87-1.16)
 
0.92
(0.78-1.08)
 
1.00
(0.86-1.16)
 
 
No (Low SC)
1.42
(1.01-2.00)
*
1.41
(1.06-1.87)
*
1.20
(0.83-1.74)
 
1.06
(0.69-1.63)
 
   Do you think most people would try to take advantage of you if they got a chance? (Ref; Yes (Low SC))
Depends
0.91
(0.63-1.33)
 
0.92
(0.65-1.30)
 
1.01
(0.61-1.68)
 
1.00
(0.57-1.73)
 
Social support
             
   Do you have someone who listens to your concerns and complaints? (Ref; Yes (High SC))
No (Low SC)
1.33
(0.79-2.23)
 
1.33
(0.80-2.20)
 
1.09
(0.61-1.95)
 
1.17
(0.63-2.15)
 
   Do you have someone who looks after you when you are sick and stay in bed for a few days? (Ref; Yes (High SC))
No (Low SC)
1.06
(0.70-1.61)
 
1.06
(0.71-1.58)
 
0.84
(0.58-1.22)
 
0.87
(0.50-1.52)
 
   Do you have someone who acknowledges your existence and value? (Ref; Yes (High SC))
No (Low SC)
1.49
(0.99-2.25)
 
1.48
(0.95-2.30)
 
1.18
(0.67-2.08)
 
1.33
(0.70-2.54)
 
General reciprocity
             
   Do you listen to someone's concerns and complaints? (Ref; Yes (High SC))
No (Low SC)
1.59
(1.24-2.04)
*
1.58
(1.31-1.91)
*
1.27
(0.95-1.70)
 
1.03
(0.70-1.51)
 
   Do you look after someone when he/she is sick and stays in bed for a few days? (Ref; Yes (High SC))
No (Low SC)
1.49
(1.12-2.00)
*
1.44
(1.13-1.83)
*
1.01
(0.78-1.32)
 
0.83
(0.70-0.98)
*
Social network
             
   Political organization or group (Ref; yes)
No (Low SC)
1.14
(0.83-1.56)
 
1.11
(0.85-1.46)
 
0.99
(0.71-1.39)
 
1.11
(0.83-1.49)
 
   Industrial or trade association (Ref; yes)
No (Low SC)
1.04
(0.72-1.51)
 
1.02
(0.80-1.29)
 
0.88
(0.59-1.30)
 
0.91
(0.62-1.35)
 
   Volunteer group (Ref; yes)
No (Low SC)
1.78
(1.34-2.37)
*
1.75
(1.39-2.21)
*
1.30
(0.95-1.77)
 
1.51
(1.19-1.91)
*
   Citizen or consumer group (Ref; yes)
No (Low SC)
1.05
(0.59-1.86)
 
0.98
(0.57-1.68)
 
0.79
(0.43-1.47)
 
0.95
(0.37-2.40)
 
   Religious organization or group (Ref; yes)
No (Low SC)
1.10
(0.77-1.56)
 
1.11
(0.79-1.56)
 
1.21
(0.86-1.70)
 
1.30
(1.06-1.58)
*
   Sports group or club (Ref; yes)
No (Low SC)
1.89
(1.28-2.80)
*
1.98
(1.52-2.58)
*
1.32
(0.78-2.21)
 
1.44
(1.10-1.88)
*
   Neighbourhood association / Senior citizen club / Fire-fighting team (Ref; yes)
No (Low SC)
1.16
(0.94-1.42)
 
1.15
(0.95-1.39)
 
1.12
(0.90-1.40)
 
1.20
(0.80-1.81)
 
   Leisure activity group (Ref; yes)
No (Low SC)
1.64
(1.21-2.20)
*
1.59
(1.40-1.81)
*
1.29
(0.94-1.77)
 
1.27
(1.04-1.55)
*
   How often do you meet your friends? (Ref; Once or more/month)
Several/year
1.26
(0.96-1.67)
 
1.26
(0.99-1.60)
 
1.09
(0.77-1.56)
 
1.06
(0.75-1.48)
 
 
Rarely
1.99
(1.72-2.31)
*
1.99
(1.75-2.25)
*
1.30
(1.10-1.53)
*
1.38
(1.28-1.49)
*
 
Having no friend
1.43
(0.79-2.56)
 
1.41
(0.90-2.20)
 
0.77
(0.47-1.26)
 
0.49
(0.19-1.26)
 
Multiple imputation Cox proportional hazard models: the Aichi Gerontological Evaluation Study (AGES), Aichi, Japan, 2003-2008, Men1.
1 Adjusted for age, BMI, self-rated health, current illness, smoking history, alcohol consumption, exercise, equivalent income and education.
* Statistically significant variable (p < 0.05).
Table 4 shows the univariate and covariates adjusted mortality HRs for the different social capital variables among women. The results of multiple imputation models and non-imputation models were also similar, particularly in the univariate models, but the 95%CIs were wider in most of the estimates obtained from the imputation models. In the univariate multiple imputation models, lower social capital was significantly related to higher mortality in all generalised reciprocity variables (listen to someone's concerns: HR = 2.31 (95%CI = 1.49-3.58) and look after someone: HR = 1.71 (95%CI = 1.18-2.47)) and four social network variables (sports: HR = 2.32 (95%CI = 1.41-3.82); leisure: HR = 2.24 (95%CI = 1.36-3.68); meet friends rarely: HR = 2.41 (95%CI = 1.31-4.45); having no friends: HR = 3.40 (95%CI = 2.10-5.52)). In the covariate adjusted multiple imputation analysis, only one lower social network response related to higher mortality (having no friends: HR = 1.81 (95%CI = 1.02-3.23)), while findings for one generalised reciprocity variable (listen to someone's concerns) and one social network variable (leisure) were marginally not significant. Interestingly, the response indicating lower social capital in one general trust variable was significantly related to lower mortality (most people cannot be trusted; HR = 0.65 (95%CI = 0.45-0.96)).
Table 4
Univariate and covariate adjusted hazard ratios and 95% confidence intervals for all-cause mortality according to social capital
  
Univariate (imputation)
 
Univariate (non-imputation)
 
Covariate adjusted (imputation)
 
Covariate adjusted (non-imputation)
 
  
HR
95%CI
 
HR
95%CI
 
HR
95%CI
 
HR
95%CI
 
General trust
             
   Generally speaking, would you say that most people can be trusted? (Ref; Yes (High SC))
Depends
0.98
(0.67-1.43)
 
0.99
(0.70-1.42)
 
0.98
(0.65-1.50)
 
0.97
(0.79-1.18)
 
 
No (Low SC)
0.80
(0.55-1.16)
 
0.80
(0.60-1.05)
 
0.65
(0.45-0.96)
*
0.62
(0.42-0.93)
*
   Would you say that most of the time people try to be helpful? (Ref; Yes (High SC))
Depends
1.26
(0.81-1.95)
 
1.27
(0.84-1.92)
 
1.29
(0.72-2.32)
 
0.95
(0.67-1.34)
 
 
No (Low SC)
1.69
(1.00-2.87)
 
1.72
(1.07-2.77)
*
1.49
(0.84-2.64)
 
1.29
(0.99-1.67)
 
   Do you think most people would try to take advantage of you if they got a chance? (Ref; Yes (Low SC))
Depends
0.94
(0.54-1.65)
 
0.94
(0.60-1.48)
 
1.15
(0.60-2.22)
 
0.90
(0.41-1.95)
 
 
No (High SC)
1.10
(0.49-2.49)
 
1.11
(0.52-2.38)
 
1.33
(0.49-3.60)
 
1.21
(0.42-3.50)
 
Social support
             
   Do you have someone who listens to your concerns and complaints? (Ref; Yes (High SC))
No (Low SC)
1.36
(0.80-2.30)
 
1.36
(0.86-2.14)
 
1.11
(0.62-1.99)
 
1.22
(0.57-2.61)
 
   Do you have someone who looks after you when you are sick and stay in bed for a few days? (Ref; Yes (High SC))
No (Low SC)
0.86
(0.60-1.24)
 
0.86
(0.59-1.26)
 
0.84
(0.50-1.43)
 
0.85
(0.45-1.60)
 
   Do you have someone who acknowledges your existence and value? (Ref; Yes (High SC))
No (Low SC)
1.31
(0.65-2.66)
 
1.32
(0.74-2.36)
 
1.05
(0.56-1.95)
 
0.91
(0.55-1.51)
 
Generalised reciprocity
             
   Do you listen to someone's concerns and complaints? (Ref; Yes (High SC))
No (Low SC)
2.31
(1.49-3.58)
*
2.38
(1.56-3.63)
*
1.57
(0.96-2.55)
 
1.40
(0.71-2.77)
 
   Do you look after someone when he/she is sick and stays in bed for a few days? (Ref; Yes (High SC))
No (Low SC)
1.71
(1.18-2.47)
*
1.72
(1.23-2.39)
*
0.92
(0.63-1.35)
 
0.73
(0.51-1.05)
 
Social network
             
   Political organization or group (Ref; yes)
No (Low SC)
1.55
(0.58-4.09)
 
1.55
(0.79-3.02)
 
1.25
(0.42-3.76)
 
1.48
(0.63-3.46)
 
   Industrial or trade association (Ref; yes)
No (Low SC)
2.92
(0.58-14.64)
 
4.19
(1.46-12.02)
*
1.95
(0.38-9.97)
 
2.51
(0.77-8.14)
 
   Volunteer group (Ref; yes)
No (Low SC)
1.76
(0.81-3.83)
 
1.75
(1.09-2.80)
*
1.06
(0.38-2.95)
 
0.95
(0.54-1.67)
 
   Citizen or consumer group (Ref; yes)
No (Low SC)
1.76
(0.45-6.90)
 
2.07
(1.00-4.30)
 
1.14
(0.21-6.11)
 
0.92
(0.56-1.51)
 
   Religious organization or group (Ref; yes)
No (Low SC)
1.17
(0.77-1.80)
 
1.19
(0.95-1.50)
 
1.25
(0.73-2.14)
 
1.54
(0.84-2.85)
 
   Sports group or club (Ref; yes)
No (Low SC)
2.32
(1.41-3.82)
*
2.33
(1.72-3.17)
*
1.42
(0.78-2.59)
 
1.72
(1.11-2.68)
*
   Neighbourhood association / Senior citizen club / Fire-fighting team (Ref; yes)
No (Low SC)
1.19
(0.94-1.52)
 
1.22
(1.03-1.44)
*
1.11
(0.86-1.43)
 
1.19
(0.95-1.48)
 
   Leisure activity group (Ref; yes)
No (Low SC)
2.24
(1.36-3.68)
*
2.32
(1.52-3.54)
*
1.54
(0.92-2.57)
 
1.60
(1.10-2.32)
*
   How often do you see your friends? (Ref; Once or more/month)
Several/year
1.00
(0.64-1.58)
 
0.99
(0.68-1.42)
 
0.92
(0.58-1.46)
 
0.87
(0.40-1.87)
 
 
   Rarely
2.41
(1.31-4.45)
*
2.44
(1.40-4.26)
*
1.64
(0.90-2.98)
 
1.62
(0.82-3.22)
 
 
   Having no friend
3.40
(2.10-5.52)
*
3.55
(2.37-5.32)
*
1.81
(1.02-3.23)
*
2.10
(0.71-6.26)
 
Multiple imputation Cox proportional hazard models: the Aichi Gerontological Evaluation Study (AGES), Aichi, Japan, 2003-2008, Women1.
1 Adjusted for age, BMI, self-rated health, current illness, smoking history, alcohol consumption, exercise, equivalent income and education.
* Statistically significant variable (p < 0.05).

Discussion

To the best of our knowledge, this study is the first prospective cohort study to assess the relationships between various social capital measures and mortality. In addition, this is the first cohort study on the relationship between social capital and mortality in a non-Western country. The present study showed that the structural social capital variable (friendship network) was a good predictor for all-cause mortality among older Japanese. Among men, it was the frequency of meetings with friends that was important, with those meeting their friends rarely having higher mortality, while was it was the lack of friends that was indicative of higher mortality among women. In addition, low general trust was related to lower mortality among women, suggesting that general trust has a different meaning among older Japanese women than among men.
Our results suggested the existence of culture differences in the association between trust and health. In addition, it is possible that the specific questions used to measure trust may also play a role. In our study, the question about general trust ("Generally speaking, would you say that most people can be trusted?") measures the trust for strangers, not group members [28]. In Japan, a relatively collectivist society with intense group ties, human relations are based on mutual assurance between group members rather than mutual trust between out-group members [11, 13]. The systems of mutual assurance, monitoring and sanctioning, within groups make the Japanese society safe and stable though closed [11, 13]. In such a society with strong ties, people can relatively easily obtain social support [29]. Though Japanese society is gradually changing recently because of globalisation, older people have lived in this traditional type of society for a long time throughout their life-course. Our results could suggest that Japanese older women who did not trust others would adapt well to the collectivist society with intense group ties and benefit from the society. In this Japanese older generation, men tended to work outside while women were predominantly housewives, therefore, men had to communicate with out-group members during their work and this may have contributed to developing their general trust towards strangers. In contrast, lower general trust measured by the question "Would you say that most of the time people try to be helpful?" tended to be associated with higher mortality among both men and women. This may be a more applicable question for measuring general trust among older Japanese, as this cohort may refer to their group members as "people" when answering this question. Previous cohort studies have not used general questions on trusting people to measure social capital. In Finland, a prospective study determined the beneficial effect of trust on all-cause mortality among women aged 30-99 years, not men [2]. Their measure of trust was based on the number of and trust in close friends. In this study, we did not use the factor/principal component analysis to check the association between detailed, not combined, social capital variables and mortality. As the results, various social capital variables were included into the models and different association of trust questions on mortality were shown though this method had the possibility of a type 1 error. Further prospective research assessing trust and mortality with considering various culture backgrounds is needed.
Our results are partially consistent with those of previous studies. Social network and social support are positively associated with health. A meta-analysis of social relationships and mortality determined that strong structural social relationships (social network) and functional social relationships (social support) increased the likelihood of survival [30]. In line with this, our study showed significant associations between friendship network and mortality (meet friends rarely for men; HR = 1.30 (95%CI = 1.10-1.53), having no friends for women; HR = 1.81 (95%CI = 1.02-3.23)); however, social support was not significantly associated with mortality. Although we considered diagnosed diseases and excluded from our study people with limitations in basic activities of daily living, it is possible that people included in the study may have had latent fatal diseases and consequently needed some help; this may have affected our results about social support and mortality. The concept of generalised reciprocity is based on the assumption that when people provide resources, good turns will be repaid at some unspecified time in the future, perhaps even by an stranger [31]. It does not entail tit-for-tat calculations in which individuals can be sure that a good turn will be repaid quickly and automatically [31]. Therefore, we used variables about the provision of social support as generalised reciprocity variables. In our study, generalised reciprocity showed marginal though non-significant association with mortality (HR = 1.27 (95%CI = 0.95-1.70) for men and HR = 1.57 (95%CI = 0.96-2.55) for women). A prospective cohort study in Finland showed that leisure participation was significantly though marginally associated with reduced all-cause mortality (HR = 0.94 (95%CI = 0.89-1.00) for men and HR = 0.96 (95%CI = 0.91-1.00) for women). In our study, covariate adjusted HRs of leisure participation were again marginal, though non-significant (HR = 1.29 (95%CI = 0.94-1.77) for men and HR = 1.54 (95%CI = 0.92-2.57) for women). The meaning of volunteering varies in the societies of different cultures [8] and relationships between volunteering and mortality are not consistent across studies [35]. In our study, covariate adjusted HR of volunteer participation was marginal though non-significant for men (HR = 1.30 (95%CI = 0.95-1.77)) and non-significant for women (HR = 1.06 (95%CI = 0.38-2.95)).
There are several plausible pathways linking social capital to health [32]. At first, social capital may affect individual health by influencing health-related behaviours through promotion of more rapid diffusion of health information and by exerting social control over deviant health-related behaviours [32]. Second, higher social capital may promote health by increasing access to local services and amenities [32]. Good access to service such as transportation, clinics and community health centres could improve health. Third, there are associations between social capital and psychological distress [33, 34]. Social networks and social support can buffer the negative effects of life events on mental health [34]. Fourth, the communities with higher social capital produce more egalitarian patterns of political participation that result in the implementation of policies which ensure the security of all its members [32].
The results of this study have important public health implications. Among older Japanese, structural social capital variable related to friendship network were found to be significantly associated with mortality regardless of various covariates. This result suggests the possibility that public investment to promote social network may reduce the mortality among older people.
Our study has a number of limitations and strengths. The follow-up period (4.29 years) was relatively short. There was a potential bias caused by latent fatal disease though we considered diagnosed diseases and limitations in basic activities of daily living at baseline. In addition, the response rate was 50.4%; therefore, the results may have been affected by selection bias. Hanibuchi et al. previously conducted ecological analysis that assessed associations between community-level social capital and response rate using another data set from the AGES project and found that higher response rates were significantly associated with higher social capital [35]. Therefore, respondents of this study might have higher social capital than non-respondents. Although our results showed significant effects of some dimensions of social capital on all-cause mortality, this low response rate might have attenuated that association. In addition, compared with government data, our study respondents tended to be younger. It could be argued that healthier and younger people tend to respond to our questionnaire while people with higher risks of mortality tend to not participate. If so, this might have contributed to an underestimation of the association between poor social capital and mortality. As a strength, the present study used various social capital variables. Although the validity and reliability of the social capital variables were not been directly examined, a previous study using AGES project data checked the association between social capital variables based on our survey and voting rate, rate of volunteer registration and rate of social participation based on public social survey data [35]. Mean response of trust variable measured by our survey significantly associated with rate of volunteer registration in each community. Similarly, social network variables were significantly associated with voting rate.

Conclusions

In conclusion, friendship network, a measure of individual social capital, was a good predictor for all-cause mortality among older Japanese. In addition, low general trust was related to lower mortality among women. Further studies examining the different effect of social capital between Western and non-Western countries are needed.

Acknowledgements

This study used data from the Aichi Gerontological Evaluation Study (AGES). This survey was conducted by the Nihon Fukushi University Center for Well-being and Society as one of their research projects, and supported by a grant of Strategic Research Foundation Grant-aided Project for Private Universities from Ministry of Education, Culture, Sport, Science, and Technology, Japan (MEXT), 2009-2013.
The authors wish to thank Dr. Tomoya Hanibuchi and Dr. Georgios Tsakos for helpful comments on an earlier draft.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://​creativecommons.​org/​licenses/​by/​2.​0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

JA had the idea for the study, participated in its design, performed the statistical analysis and drafted the manuscript as a principal author. KK helped develop the idea of the study, participated in acquiring the data and with design, and edited the manuscript. HH participated in acquiring the data and critically revising the manuscript. SVS participated in design of study, data analysis and critically revised the manuscript. CM, NK, YI, KS and KO participated in design of study and critically revised the manuscript. All authors read and approved the final manuscript.
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