Does Gender Moderate the Relationship Between Social Capital and Life Satisfaction? Evidence From Urban China

Abstract

The present study aimed to test the moderating effect of gender on the relationship between social capital and life satisfaction among older adults in urban China. A quota sampling method was used to select 456 older adults aged 60 and older from 16 local communities in Suzhou city in 2015. Hierarchical multiple regression was employed to test the proposed models. The associations between family social capital and life satisfaction were higher among older men than women. Trust and helping others were stronger predictors of older women’s life satisfaction than their male counterparts. Citizenship activities affected life satisfaction among older men only. The findings highlight the important role of social capital in sustaining and/or improving life satisfaction among both older women and men. Policy and intervention implications are discussed.

Keywords

community social capital family social capital life satisfaction gender

The concept of social capital has attracted great attention in the field of gerontology and health research. Empirical evidence has consistently suggested that social capital is associated with a number of well-being outcomes among older populations, including life satisfaction (Ajrouch, 2007; Theurer & Wister, 2010; Yamaoka, 2008), depression (Cao, Li, Zhou, & Zhou, 2015), self-rated health (Yip et al., 2007), and physical and emotional health (Norstrand & Xu, 2012). Social capital plays an important role in understanding both individual and contextual factors of well-being in older age across cultures and countries.

However, findings of research on the effects of specific social capital indicators (e.g., trust, reciprocity, organization membership, and social participation) on life satisfaction are inconclusive. This limits the utilization of social capital as evidence and guideline in policy strategies and intervention designs. Gender and culture might be two potential intervening variables that deserve further investigation. First of all, although men and women have differences in social participation and interpretation of life satisfaction, most studies averaged the effects of social capital indicators across women and men. Second, the interpretation and application of social capital vary across cultures and countries. We are not certain whether each social capital indicator has a beneficial effect on life satisfaction among older Chinese adults. Therefore, this research aims to investigate the empirical relationships between social capital and life satisfaction among older adults by gender in the context of urban China.

The Concept of Social Capital: Definitions, Measurement Levels, and Dimensions

There are various definitions and theoretical foundations of social capital (De Silva, McKenzie, Harpham, & Huttly, 2005; Nyqvist, Forsman, Giuntoli, & Cattan, 2013). The definition of social capital by Putnam is widely adopted in health research (De Silva et al., 2005; Nyqvist et al., 2013). Putnam et al. (1993, p. 167) described social capital as “features of social organization, such as trust, norms, and networks, that can improve the efficiency of society by facilitating coordinated actions.” According to this definition, social capital is considered as collective asset and manifested by social trust, reciprocity, civic participation, and community networks. Bourdieu, Coleman, and Lin also made significant contributions to social capital theory by examining the profit or returns of social capital from an individual perspective (Bourdieu, 1986; Coleman, 1988; Lin, 1999). Bourdieu (1986) defined social capital as a form of group resources that benefit individuals as a consequence of their membership in social networks. Coleman (1988) defined social capital as social resources embedded in individuals’ social connections in social systems where they share common memberships, social norms and obligations, trustworthiness, and information channels. Besides social capital from community networks (hereafter community social capital), Coleman emphasized the importance of social capital embedded from family systems (hereafter family social capital). Furthermore, Lin (1999) investigated social capital from the perspective of how individuals use social resource and make investment in their social networks with expected returns. While previous scholars emphasized the significance of density or closure of social networks, Lin stressed the role of bridges in social networks. The density of a social network can be used to preserve social resources and fulfill both individual and collective interests. Bridges, on the other hand, can be used to exchange information and search social resources, which are not available in present networks.

Social capital not only has various definitions but also can be measured from different levels (e.g., individual, family, community, and even national levels; De Silva et al., 2005; Nyqvist et al., 2013). There is no consensus on the measurement levels and tools of social capital in the literature. How to measure social capital should vary based on local contexts. Furthermore, the theoretical framework of social capital puts great emphasis on its multidimensional nature (De Silva et al., 2005). Social capital consists of two important dimensions: cognitive and structural. The former reflects individuals’ subjective perceptions of the quality of social relationships including social trust, reciprocity, and norms. The latter is characterized by objective quantities of social relationships and activities including organization membership, social participation, and citizenship activities (Harpham, Grant, & Thomas, 2002; Nyqvist et al., 2013). These two dimensions are associated with each other but influence health through different pathways (Harpham et al., 2002).

The Aging Population in China

With 222 million people aged 60 years or older, China is currently the home to a fourth of the world’s older population (World Bank, 2016). In the past two decades, China has experienced unprecedented economic growth, with an increase in per capita gross domestic product from US$193 in 1980 to US$6,807 in 2013 (World Bank, 2016). This income growth has been accompanied by fundamental but gradual socioeconomic transformations without large-scale social or political upheavals. Such social and economic transitions have both positive and negative impacts on the well-being of older adults. On the one hand, China’s economic boom makes a huge contribution to poverty reduction (Ravallion, 2008). In the past decade, reforms of medical insurance and pension systems in China have also provided universal coverage in both rural and urban areas. Furthermore, the current generation has witnessed rapid development in social infrastructure and health resources, especially in urban areas. On the other hand, the increasing income gap between the rich and the poor, regional disparities in economic development, limited welfare benefits for the poor and the unemployed, and large geographic distances among generations due to rural-to-urban migration all lead to great challenges to the traditional family-based aged care systems in China.

Despite the rapid changes in average family size and traditional household structure in Chinese societies, families are still considered the most important source of support for older Chinese adults (Lin & Yi, 2011). Chinese families’ obligations for caring for their older members have been emphasized and promoted by both Chinese law and the 10th to 13th Five-Year Plan for the Development of China Undertakings for the Aged (2000–2020; State Council of China, 2017). Community social capital is considered a compensatory resource for older adults, especially for those who have difficulty receiving adequate support from their families (Lu, Lum, & Lou, 2016).

In the present study, social capital embedded from communities and families are two important factors, which could preserve social resources and generate potential health benefits for residents/members of communities and families. These two factors not only coexist but also complement each other (Furstenberg, 2005; Lu et al., 2016). However, there is a lack of Chinese studies examining social capital from both family and community sources simultaneously. Therefore, we adopted the conceptualization of community social capital and family social capital (Coleman, 1988; Putnam, Leonardi, & Nanetti, 1993). We focused on examining the empirical relationships between social capital and well-being by gender in the context of urban China. Specifically speaking, how do current social capital indicators affect Chinese older women’s and men’s well-being? Can social capital be applied as a policy instrument to promote the benefits and buffer against the negative side effects of such social changes? If so, which social capital indicators should policy makers consider? Based on our findings, we draw policy recommendations related to how the concept of social capital can be implicated in non-Western, urban, and developing societies. China can also provide insights for countries and regions with similar socioeconomic and cultural contexts.

Social Capital and Life Satisfaction

A growing body of research has begun to examine the relationships between social capital and a variety of well-being measures among older adults. It has been increasingly acknowledged that social capital is an important determinant of well-being in Asia (Yamaoka, 2008), Europe (Forsman, Nyqvist, Schierenbeck, Gustafson, & Wahlbeck, 2012), North America (Theurer & Wister, 2010), and Australia (Sum, Mathews, Pourghasem, & Hughes, 2008). Yet the existing literature primarily focuses on developed countries, and the findings on life satisfaction have been mixed. Empirical evidence from research among high-income countries suggests that social capital indicators, both structural (measured by organization membership) and cognitive (measured by social trust), have been correlated with better life satisfaction among older population. According to these studies, the possible mechanisms of social capital on older adults’ life satisfaction can be via community organization and collective actions to provide social support, cohesive social networks to buffer against the adverse effects of emotional stress, and promotion of civic participation in communities (Nyqvist et al., 2013). However, the findings vary in strength depending on the level of analysis, different conceptualization and measurement of social capital, country characteristics, and the socioeconomic status of study samples. For example, some studies focusing on individual-level social capital indicators, such as organization membership, social trust, reciprocity, and civic participation, found that these are positively associated with better life satisfaction (Ajrouch, 2007; Theurer & Wister, 2010; Yamaoka, 2008). However, evidence from cross-national studies among Organization for Economic Cooperation and Development and European countries showed no correlation between country-level social capital indicators (social trust and membership in voluntary organizations) and life satisfaction (Kennelly, O’Shea, & Garvey, 2003; Poortinga, 2006).

Evidence from empirical studies showed that western-based social capital theory and its conceptualization might not be fully applicable in Chinese society. For example, Yip et al. (2007) found that cognitive community social capital (measured by trust) is positively correlated with three outcome variables (subjective well-being, psychological health, and self-reported health) at the individual level and subjective well-being/psychological health at the community level as well. However, they found that structural community social capital (measured by organization membership) was not statistically significantly associated with these three outcome variables among the older Chinese population. Furthermore, Norstrand and Xu (2012) reported a statistically significant association between individual-level cognitive community social capital (measured by reciprocity) and physical and emotional health among older urban Chinese adults. These findings suggest that mechanisms through which social capital influences well-being in China are more consistently related to cognitive rather than structural community social capital. However, some important structural community social capital indicators, such as citizenship activities, have rarely been examined in Chinese contexts. Therefore, no clear patterns show that these social capital indicators would function the same way as in Western societies.

Furthermore, a number of studies have been conducted to examine supportive resources from families and their roles in affecting life satisfaction among older adults in China (Chen & Silverstein, 2000; Lou & Lu, 2013). Research has suggested that supportive resources generated from Chinese families not only significantly alleviate economic hardships among older adults but also improve their physical and mental health (Lu, Lou, Zuo, & Chi, 2015; Lu, Xu, Lou, & Chi, 2016). Few studies, however, have examined supportive resources from both families and communities simultaneously and their associations with life satisfaction in a Chinese context.

Gender Differences in the Relationship Between Social Capital and Life Satisfaction

There is some evidence that the impacts of social capital on life satisfaction might vary by gender among older adults. Using data from a cross-sectional survey in East Asia, Yamaoka (2008) found that when social capital was measured by organization membership, sense of trust, trust in organizations, and person to consult, it had protective effects on life satisfaction for women. However, the same effect was not found for men. Furthermore, Ellaway and Macintyre (2007) found that women and men were affected by different aspects of social capital in the United Kingdom. Being involved in social activity had a protective effect on health satisfaction among women only, whereas being involved in a social organization was associated with better mental health among men (Ellaway & Macintyre, 2007).

Much less is known about gender difference in social capital in China. Within economic development, there is some indication that social capital functions differently between men and women in improving life satisfaction. For example, Lu, Lou, Zuo, and Chi (2015) found that family social capital might be particularly important for the well-being of older men compared to older women in rural China. Chuang and Chuang (2008) used neighborhood closeness, political influence, social contact, social trust, and social participation as indicators of social capital. The results indicated that community social capital has a larger effect on women than men in Taiwan.

Compared to their male counterparts, older women tend to enjoy wider social networks in later life and spend more time sustaining social relationships in families and communities (Moon, Park, & Cho, 2010; Warr, 2006). Therefore, families might be particularly important for men at an older age, especially after their retirement. We hypothesize that family social capital has a larger effect on the life satisfaction of men than women (Hypothesis 1).

Furthermore, the caregiving norms in urban China might explain the reason why older women are more likely to be involved in informal reciprocity and caregiving activities in their neighborhoods. Therefore, older women might benefit more from relatively high levels of neighborhood closeness than men. We hypothesize that cognitive community social capital plays a more important role in affecting life satisfaction among older women than men. Specifically speaking, we predict that the association between trust and life satisfaction is stronger among women than men (Hypothesis 2). We also predict that the association between reciprocity and life satisfaction is stronger among women than men (Hypothesis 3).

Finally, with regard to community activities, men are more likely to participate in citizenship activities compared to their female counterparts (Einolf, 2011). Involvement in activities that fit with gendered divisions of social roles and responsibilities might have benefits for the life satisfaction of these older adults (Calasanti, 2010). We hypothesize that the association between citizenship activities and life satisfaction is stronger among men than women (Hypothesis 4).

Method

Sampling

The present study was an original study using data from a community survey conducted in Gusu district, Suzhou city, by the Department of Social Work of Renmin University of China in late 2015. As one of the most developed cities in China, the population of Suzhou is aging rapidly. The proportion of older adults aged 60 and above in Suzhou is higher than the national average level (25% vs. 16% in 2017; United Nations, 2017). Life expectancy for residents living in urban Suzhou is 83.97 years (United Nations Development Programme [UNDP], 2015). Gusu district is located in the central area of Suzhou. According to Chinese street system, district is a subdivision of a city. Street is the lower level of political division. Community is the smallest political division and local administrative boundary in an urban Chinese city. Gusu district consists of 17 streets (the 17 streets are reorganized into 8 streets in 2017). The population of Gusu district was around 1 million in 2016. All streets shared common features with naturally occurring retirement community: One third of local residents were 60 years or older. The majority of the respondents had resided in local communities for more than one decade (Suzhou Department of Civil Affairs, 2015). More than 90% of local residents owned their living places. The majority of real estate were small buildings built in the 1980s and 1990s. A number of community aged care services had been provided to local residents living in these streets including food delivery, house cleaning, volunteering, and recreational activities. Therefore, we consider Gusu district a suitable place to investigate social capital and life satisfaction among older urban Chinese adults.

A quota sampling method was adopted to select respondents aged 60 years or older from local communities. First, we selected one or two communities from each of the 16 of the 17 streets in Gusu district. Second, we interviewed 25 respondents from each community. All respondents were recommended and recruited through community centers and the committee on aging. To be selected for the survey, respondents had to (1) be 60 years old or older, (2) have local household registration status (hukou), (3) have lived in the local community more than 6 months in the past year, and (4) be cognitively capable of participating in the interview (Crum, Anthony, Bassett, & Folstein, 1993). Thirty trained interviewers conducted face-to-face interviews at the respondents’ homes and local community centers. The survey included detailed information about the respondents’ sociodemographic characteristics, social capital, and health. Finally, 456 respondents successfully completed the survey. Response rates were above 90% in all communities.

Measurement

Dependent variable

The dependent variable was life satisfaction. We used the 9-item Life Satisfaction Scale for Chinese older adults to measure life satisfaction (Lou, Chi, & Mjelde-Mossey, 2008). Respondents were asked their satisfaction levels in eight life domains including family ties and interactions, relationships with spouse, friendship, health, housing, food, and economic status. Respondents were also asked their overall evaluation of their satisfaction with their lives. Respondents indicated their answers on a 5-point Likert-type scale (1 = strongly disagree, 3 = neutral, and 5 = strongly agree). Average scores were calculated, with higher scores indicating higher life satisfaction levels. The estimate of Cronbach’s α for this scale was .872.

Independent variable

The independent variables were family social capital and community social capital indicators. With regard to community social capital, all indicators were selected from the Short Social Capital Assessment tool and the World Bank’s social capital questionnaire (De Silva, Huttly, Harpham, & Kenward, 2007; Grootaert, Narayan, Jones, & Woolcock, 2003). Cognitive community social capital was assessed by trust in local communities and reciprocity among neighbors. Respondents were asked whether they believed and are willing to help when they need it. Respondents were also asked whether they agreed with the following five statements: (1) “the majority of local residents can be trusted” (trust in local communities), (2) “the majority of local residents are willing to help you when necessary” (perceived support from others), (3) “local residents not only care about their benefits but also respect other’s interests” (willingness to cooperate with others), (4) “you recognized the local communities as a big family and have the feelings of belonging to the family” (feelings of belonging), and (5) “the majority of local residents get along with each other” (get along). Responses to these five statements were assessed on a 5-point Likert-type scale ranging from strongly disagree to strongly agree. Respondents were also asked whether they helped their neighbors and friends out (helping others). Respondents indicated their answers on a 5-point Likert-type scale ranging from never helping to always helping.

Structural community social capital was assessed by the number of membership organizations, social participation, and citizenship activities. We asked respondents whether they had had memberships in the following organizations in the past year: political parties, labor unions, women’s groups, community associations, religious groups, credit groups, charity groups, sports groups, and neighborhood committees (De Silva et al., 2007). Their responses were recoded as a binary variable (0 = no, 1 = yes). Summed scores were calculated, with higher scores indicating more organization memberships. Respondents were asked how frequently they participated in social activities organized by the above organizations. Respondents indicated their answers on a 6-point scale (1 = never, 3 = several times per year, and 6 = more than twice per week). Finally, respondents were asked whether they had collaborated with other members in local communities to solve a common problem in the past year. Their responses were recoded as a binary variable (0 = no, 1 = yes).

With regard to family social capital, this multicomponent concept can be measured by family network structure and the quality of family support and relationship (Alvarez, Kawachi, & Romani, 2017). Compared to number of children and other structural components, family support was found to be a stronger predictor of health outcomes among older populations (Lou & Lu, 2013). Therefore, we chose to measure family social capital from family network support perspective (Alvarez et al., 2017; Siegler, 2014). We used the 4-item Multidimensional Scale of Perceived Social Support to measure family social capital (Zhang & Norvilitis, 2002; Zimet, Dahlem, Zimet, & Farley, 1988). Respondents were asked whether they agreed with the following four statements: (1) “My family really tries to help me,” (2) I get the emotional support from my family, (3) I can discuss my problems with my family, and (4) My family is willing to help me make decisions on important issues. Respondents indicated their answers on a 5-point Likert-type scale (1 = strongly disagree, 3 = neutral, and 5 = strongly agree). Average scores were calculated, with higher scores indicating higher quality family relationships. The estimate of Cronbach’s α for this scale was .917.

Moderator

Respondents’ gender is the moderator in the present study. Gender was assessed by a binary variable (0 = women, 1 = men).

Control variables

We controlled for respondents’ sociodemographic characteristics and health status in the model. Control variables included age, marital status, educational attainment, living arrangement, financial satisfaction, functional health, self-rated health, and chronic diseases. Age was self-reported. Marital status, living arrangement, educational attainment, and self-rated health were classified dichotomously (0 = living with others, 1 = living alone; 0 = primary school or lower, 1 = secondary school or higher; and 0 = very poor/poor/fair, 1 = good/very good). Moreover, respondents were asked whether they had had adequate money to cover their living costs in the past 3 months. Respondents indicated their answers on a 5-point Likert-type scale (1 = very inadequate, 3 = fair, and 5 = very adequate). Functional health was assessed using the Barthel Index (Mahoney & Barthel, 1965). Finally, respondents were asked whether they had any of the six most common chronic diseases among older adults in China. The answers were recoded as binary variables (0 = no, 1 = yes). Summed scores were used to represent the number of chronic diseases.

Data Analysis

Descriptive statistics were conducted to present sociodemographic characteristics and health variables among older adults. Hierarchical regression analysis was performed to test whether gender moderated the association between social capital and life satisfaction. Life satisfaction was the dependent variable. At the first step, respondents’ sociodemographic characteristics and health status were entered into the model. At the second step, family and community social capital variables were entered into the model. We regressed life satisfaction on social capital variables after controlling for sociodemographic and health variables. At the third step, we entered two-way interaction terms of gender and separate social capital indicators into the model to examine whether the associations between social capital and life satisfaction varied by gender. We deleted interaction terms with nonsignificant regression coefficients from the model by using the backward elimination method. The final regression model included all social capital indicators, control variables, and four interaction terms. We also calculated regression coefficients for social capital indicators by running two regression models separately for women and men. The percentage of missingness of all variables was lower than 5%. Listwise deletion was used to handle missingness, resulting in a final sample of 423 respondents (237 women and 186 men). Data analyses were performed using SPSS 19.0 software (Field, 2009).

Results

Descriptive Statistics

We present the characteristics of the respondents by gender in Table 1. Gender differences in age, marital status, living arrangement, financial satisfaction, and health status were statistically nonsignificant. Specifically, the average age of men and women was 71.3 (SD = 7.1) and 70.1 (SD = 7.5) years, respectively. Around three quarters of the respondents were married, and less than one fifth lived alone. Also, 89.9% of the respondents owned their own apartments. Around 90% of the respondents were retired and considered a pension their major income. More than 70% of the respondents reported that they had adequate income to cover their living costs. Furthermore, 90.6% of the respondents had no limitations in activities of daily living (ADLs). Only 26.8% of the respondents were free of the six most common chronic diseases among older adults in China. The average number of chronic diseases was 1.2. However, men had better educational attainment than women. In all, 43% of women had a primary school education or less. This figure was only 25.4% for men.

Table 1.
Sample Characteristics.

Variable Men (N = 206) Women (N = 250)

N (%) Mean (SD) N (%) Mean (SD)

Age 71.3 (7.1) 70.1 (7.5)

60–69 88 (42.7) 133 (53.2)

70–79 86 (41.6) 85 (34.0)

≥80 32 (15.7) 32 (12.8)

Marital status

Married 158 (76.7) 184 (73.6)

Other marital status 48 (23.3) 66 (26.4)

Lives alone

Yes 36 (17.5) 43 (17.2)

No 170 (82.5) 207 (82.8)

Education

Primary school or lower 52 (25.4) 107 (43.0)

Secondary school or higher 153 (74.6) 142 (57.0)

Financial satisfaction

Inadequate/very inadequate 13 (6.3) 25 (10.0)

Fair 37 (18.0) 52 (20.8)

Adequate/very adequate 156 (75.7) 173 (69.2)

Functional health 98.7 (4.7) 99.0 (4.6)

Disease 1.2 (1.0) 1.24 (1.1)

Note. N = 456.

Regression Model of Life Satisfaction

We present the results of multiple regression analyses in Table 2. No correlation between control and social capital variables exceeded .60. All variance inflation factor (VIF) estimates were lower than 10, and tolerance estimates were higher than .2 (Field, 2009). Therefore, there was no evidence of multicollinearity. The Durbin–Watson estimate was 1.877. The model explained 40.5% of the variation in life satisfaction.

Table 2.
Multiple Regression for Social Capital and Life Satisfaction.

Variable 1 2 3

B SE β B SE β B SE β

Constant 3.559 .755 2.032 .637 — 2.317 .759

Age −0.003 .004 −.040 −0.002 .003 −.029 −0.002 .003 −.026

Gender −0.001 .052 −.001 −0.046 .044 −.042 −0.311 .302 −.282

Marital status 0.175 .080 .136* 0.176 .067 .137** 0.172 .066 .134*

Living arrangement 0.038 .092 .025 0.063 .077 .042 0.068 .076 .045

Education −0.081 .056 −.070 −0.042 .048 −.037 −0.030 .048 −.026

Financial satisfaction −0.158 .029 −.268* −0.098 .024 −.167* −0.101 .024 −.171***

Functional health 0.010 .007 .071 0.001 .006 .004 0.002 .005 .012

Self-rated health 0.133 .054 .121* 0.097 .045 .088* 0.108 .044 .098*

Disease −0.020 .026 −.037 −0.028 .022 −.052 −0.019 .021 −.035

Family social capital 0.198 .030 .270* 0.147 .038 .201*

Cognitive community social capital

Trust in local community 0.123 .033 .180* 0.187 .042 .272*

Perceived support from others 0.041 .035 .065 0.040 .034 .063

Helping others 0.049 .027 .082† 0.099 .034 .166

Get along 0.158 .045 .188* 0.161 .044 .191***

Willingness to cooperate with others −0.018 .028 −.029 −0.027 .028 −.046

Feelings of belonging 0.004 .040 .004 −0.009 .039 −.012

Structural community social capital

Membership number 0.028 .018 .070 0.027 .018 .067

Social participation −0.017 .013 −.056 −0.021 .013 −.071

Citizenship activities 0.045 .050 .038 −0.026 .064 −.021

Interaction terms

Family Social Capital × Men 0.137 .059 .540*

Trust in Local Community × Men −0.131 .055 −.497*

Helping Others × Men −0.102 .049 −.342*

Citizenship Activities × Men 0.171 .096 .106†

F 6.922* 16.134* 14.437***

Adjusted R ² .112 .405 .423

†p < .05 (one tailed). p < .05. p < .01. p < .001.

Family social capital was found to have the largest impacts on life satisfaction (β = .270, t = 6.490, p < .001). Results also showed that respondents who had higher levels of social trust in local communities were more likely to be satisfied with their lives (β = .180, t = 3.717, p < .001), as were respondents who often helped their neighbors and friends out (β = .082, t = 1.815, p < .05, one tailed) and those who believed that most of their neighbors got along with each other (β = .188, t = 3.538, p < .001). No other social capital indicators were significant predictors of life satisfaction.

Moderation Effect of Gender on Social Capital and Life Satisfaction

A gender difference in the association between family social capital and life satisfaction was identified (interaction term: β = .540, t = 2.331, p < .05). The association between family social capital and life satisfaction was found to be larger among older men than older women (women: β = .208, t = 3.675, p < .001; men: β = .340, t = 5.487, p < .001). Additionally, gender differences in the association between cognitive community social capital and life satisfaction were identified (interaction term of trust: β = −497, t = −2.383, p < .05; interaction term of helping others: β = −.342, t = −2.062, p < .05). Both trust and helping others were found to have significant impacts on life satisfaction among women only (trust among women: β = .285, t = 4.420, p < .001; trust among men: β = .034, t = 0.461, p > .1; helping others among women: β = .181, t = 2.937, p < .01; helping others among men: β = −.025, t = −0.373, p > .1). Finally, the gender difference in the association between structural community social capital and life satisfaction was marginally significant (interaction term: β = .106, t = 1.781, p < .05, one tailed). Citizenship activities were found to be significantly associated with life satisfaction among older men only at the .1 level (women: β = −.036, t = −0.635, p = .526; men: β = .127, t = 1.967, p = .051). We tested interaction terms between gender and other social capital variables. All these interaction terms were statistically nonsignificant, indicating that gender did not play the moderating role between the relationships between these variables and life satisfaction. In this case, differences in the effect sizes of some social capital variables (i.e., get along and perceived support from others) on life satisfaction across women and men groups might result from differences in the sample sizes and variations in data (Gravetter & Forzano, 2015). Table 3 shows the results of regression models for older women and men. The plots of the interaction effects are available upon request.

Table 3.
Multiple Regression for Social Capital and Life Satisfaction by Gender.

Variable Men Women

B SE β B SE β

Constant 0.959 0.840 — 2.978 1.046 —

Age 0.006 0.004 .085 −0.008 0.005 −.109†

Marital status 0.123 0.112 .095 0.172 0.087 .135*

Live arrangement −0.057 0.129 −.038 0.121 0.099 .080

Education −0.066 0.074 −.054 −0.019 0.065 −.017

Financial satisfaction −0.100 0.039 −.159 −0.098 0.033 −.174

Functional health 0.008 0.007 .071 −0.007 0.010 −.038

Self-rated health 0.072 0.063 .067 0.140 0.063 .126*

Disease −0.042 0.033 −.077 −0.006 0.029 −.011

Family social capital 0.253 0.046 .340* 0.150 0.041 .208*

Trust in local community 0.022 0.048 .034 0.209 0.047 .285***

Perceived support from others 0.108 0.052 .169* 0.017 0.048 .027

Helping others −0.015 0.039 −.025 0.109 0.037 .181**

Get along 0.133 .064 .166* 0.172 0.062 .194**

Willingness to cooperate with others −0.011 0.043 −.017 −0.025 0.039 −.042

Feelings of belonging 0.017 0.054 .022 −0.051 0.059 −.059

Membership number 0.009 0.026 .025 0.040 0.026 .096

Social participation −0.027 0.019 −.089 −0.023 0.020 −.074

Citizenship activities 0.150 0.076 .127† −0.043 0.068 −.036

F 10.045 9.434

Adjusted R ² .468 .391

^† p < .05 (one tailed). p < .05. p < .01. p < .001.

Discussion

In the present study, we tested family social capital and community social capital and their influences on life satisfaction simultaneously in an urban Chinese context. The findings highlight the important role of family and cognitive community social capital in sustaining and/or improving life satisfaction among older urban Chinese adults. Our findings also demonstrate a more nuanced understanding of the association between social capital and life satisfaction by highlighting the gender differences. Whereas cognitive community social capital indicators (i.e., trust and helping others) are stronger predictors of older women’s life satisfaction, family social capital and structural community social capital indicators (i.e., family social capital and citizenship activities) are more important for older men.

The findings added new empirical evidence to the theory of social capital from a Chinese perspective. We proposed three important implications: First, family and community are two important sources of social capital for older adults in China. Family social capital was found to play more important roles in influencing life satisfaction in later life compared to community social capital. Our findings add new empirical evidence by suggesting that the associations between family social capital and life satisfaction are higher among older men. Hypothesis 1 was supported. This might partially be because older women tend to have wider social networks than older men, especially after retirement (Moon et al., 2010; Warr, 2006). In other words, older men are less likely to have alternative sources of support than older women. Under such circumstances, family social capital could be particularly important for older men.

Second, cognitive community social capital was found to have larger impacts on life satisfaction than structural community social capital in Chinese contexts. This is consistent with the findings of previous Chinese studies (Norstrand & Xu, 2012; Yip et al., 2007). The findings of the present study add new evidence by showing that the association between cognitive community social capital and life satisfaction was stronger among older women. Hypotheses 2 and 3 were supported. We argued that older women are more likely to be involved in informal reciprocities among friends and neighbors and willing to provide support to others when necessary (e.g., childcare and health care). Involvement in informal reciprocity and caring activities fits with the Chinese cultural understanding of the idea of womanhood, which has a direct influence on divisions of labor, social responsibilities, activity participation, and social status among older women and men (Calasanti, 2010).

Third, our findings indicate that the interaction effect of citizenship activities and gender is marginally significant. Hypothesis 4 was partially supported. This provides new insights into how structural community social capital affects older women and men differently. Compared to their female counterparts, older men are more likely to be involved in formal, political, and civic organizations and more willing to participate in citizenship activities (Einolf, 2011). Involvement in citizenship activities fits with cultural understandings of manhood in China, which could indirectly lead to higher levels of life satisfaction among men. Therefore, citizenship activities could be particularly important for encouraging older men to engage in community lives and function as a basis to foster trust and reciprocity.

This study has two important policy implications. Family is still the most important source of support for older adults in China. However, family-based aged care systems encounter great challenges from decreased average family sizes, intergenerational geographic distance, urbanization, and modernization. Policy makers should put great emphasis on building formal support systems to help Chinese families care for their older members, including caregiver education programs, respite care, and day care centers. Furthermore, how local residents feel about their community lives really matters for their mental health. Cognitive community social capital indicators should be included in the evaluation systems for future community building programs. Finally, two important implications for intervention are proposed: (1) older men with low levels of family social capital deserve particular attention from intervention designers. Their major social needs and mental health status should be further explored through detailed needs assessment and (2) our research findings suggest that interventions aiming to improve informal reciprocity among neighborhood might result in improvements in older women’s life satisfaction. However, it is unlikely that such interventions would have a major impact on men’s life satisfaction. Intervention about citizenship activities and social activities organized through formal organizations would be more appropriate for older men.

However, this study has several limitations. First, the data were cross-sectional in nature. Therefore, we were unable to examine the potential bidirectional relationship between social capital and life satisfaction. The mechanisms linking social capital and life satisfaction and the moderating role of gender should be further investigated in lager samples by using longitudinal study designs. Second, future studies should be conducted to compare community and/or regional disparities in terms of social capital and life satisfaction in later life. Third, while family social capital is a multidimensional concept, we only measured one aspect of family social capital from a family network support perspective. Future studies need to examine the multicomponents of family social capital and their impacts on mental health, with a particular focus on family structure and intergenerational family interactions. Fourth, future longitudinal studies are needed to examine the potential bidirectional relationship between cognitive and structural community social capital. Finally, the data were selected from naturally retired urban communities in Gusu district. The levels of trust, reciprocity, and social participation were relatively high. Furthermore, we used quota sampling to recruit respondents. Therefore, the sample was not randomly selected. Findings can only be considered as tentative and illustrative for older adults living in urban Chinese communities with similar social and cultural backgrounds.

Variable	Men (N = 206)	Women (N = 250)
Age		71.3 (7.1)		70.1 (7.5)
60–69	88 (42.7)		133 (53.2)
70–79	86 (41.6)		85 (34.0)
≥80	32 (15.7)		32 (12.8)
Marital status
Married	158 (76.7)		184 (73.6)
Other marital status	48 (23.3)		66 (26.4)
Lives alone
Yes	36 (17.5)		43 (17.2)
No	170 (82.5)		207 (82.8)
Education
Primary school or lower	52 (25.4)		107 (43.0)
Secondary school or higher	153 (74.6)		142 (57.0)
Financial satisfaction
Inadequate/very inadequate	13 (6.3)		25 (10.0)
Fair	37 (18.0)		52 (20.8)
Adequate/very adequate	156 (75.7)		173 (69.2)
Functional health		98.7 (4.7)		99.0 (4.6)
Disease		1.2 (1.0)		1.24 (1.1)

Variable	1	2	3
Constant	3.559	.755		2.032	.637	—	2.317	.759
Age	−0.003	.004	−.040	−0.002	.003	−.029	−0.002	.003	−.026
Gender	−0.001	.052	−.001	−0.046	.044	−.042	−0.311	.302	−.282
Marital status	0.175	.080	.136*	0.176	.067	.137**	0.172	.066	.134*
Living arrangement	0.038	.092	.025	0.063	.077	.042	0.068	.076	.045
Education	−0.081	.056	−.070	−0.042	.048	−.037	−0.030	.048	−.026
Financial satisfaction	−0.158	.029	−.268***	−0.098	.024	−.167***	−0.101	.024	−.171***
Functional health	0.010	.007	.071	0.001	.006	.004	0.002	.005	.012
Self-rated health	0.133	.054	.121*	0.097	.045	.088*	0.108	.044	.098*
Disease	−0.020	.026	−.037	−0.028	.022	−.052	−0.019	.021	−.035
Family social capital				0.198	.030	.270***	0.147	.038	.201***
Cognitive community social capital
Trust in local community				0.123	.033	.180***	0.187	.042	.272***
Perceived support from others				0.041	.035	.065	0.040	.034	.063
Helping others				0.049	.027	.082†	0.099	.034	.166**
Get along				0.158	.045	.188***	0.161	.044	.191***
Willingness to cooperate with others				−0.018	.028	−.029	−0.027	.028	−.046
Feelings of belonging				0.004	.040	.004	−0.009	.039	−.012
Structural community social capital
Membership number				0.028	.018	.070	0.027	.018	.067
Social participation				−0.017	.013	−.056	−0.021	.013	−.071
Citizenship activities				0.045	.050	.038	−0.026	.064	−.021
Interaction terms
Family Social Capital × Men							0.137	.059	.540*
Trust in Local Community × Men							−0.131	.055	−.497*
Helping Others × Men							−0.102	.049	−.342*
Citizenship Activities × Men							0.171	.096	.106†
F		6.922***	16.134***		14.437***
	Adjusted R ²		.112		.405			.423

Variable	Men	Women
Constant	0.959	0.840	—	2.978	1.046	—
Age	0.006	0.004	.085	−0.008	0.005	−.109†
Marital status	0.123	0.112	.095	0.172	0.087	.135*
Live arrangement	−0.057	0.129	−.038	0.121	0.099	.080
Education	−0.066	0.074	−.054	−0.019	0.065	−.017
Financial satisfaction	−0.100	0.039	−.159**	−0.098	0.033	−.174**
Functional health	0.008	0.007	.071	−0.007	0.010	−.038
Self-rated health	0.072	0.063	.067	0.140	0.063	.126*
Disease	−0.042	0.033	−.077	−0.006	0.029	−.011
Family social capital	0.253	0.046	.340***	0.150	0.041	.208***
Trust in local community	0.022	0.048	.034	0.209	0.047	.285***
Perceived support from others	0.108	0.052	.169*	0.017	0.048	.027
Helping others	−0.015	0.039	−.025	0.109	0.037	.181**
Get along	0.133	.064	.166*	0.172	0.062	.194**
Willingness to cooperate with others	−0.011	0.043	−.017	−0.025	0.039	−.042
Feelings of belonging	0.017	0.054	.022	−0.051	0.059	−.059
Membership number	0.009	0.026	.025	0.040	0.026	.096
Social participation	−0.027	0.019	−.089	−0.023	0.020	−.074
Citizenship activities	0.150	0.076	.127†	−0.043	0.068	−.036
F	10.045			9.434
Adjusted R ²	.468			.391

Footnotes

Acknowledgment

Gratitude goes to the China Women’s University for funding this research as well as to those who participated in the survey.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This study was supported by China Women’s University (Grant Number: 1100031503).

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Variable	Men (N = 206)		Women (N = 250)
Variable	N (%)	Mean (SD)	N (%)	Mean (SD)
Age		71.3 (7.1)		70.1 (7.5)
60–69	88 (42.7)		133 (53.2)
70–79	86 (41.6)		85 (34.0)
≥80	32 (15.7)		32 (12.8)
Marital status
Married	158 (76.7)		184 (73.6)
Other marital status	48 (23.3)		66 (26.4)
Lives alone
Yes	36 (17.5)		43 (17.2)
No	170 (82.5)		207 (82.8)
Education
Primary school or lower	52 (25.4)		107 (43.0)
Secondary school or higher	153 (74.6)		142 (57.0)
Financial satisfaction
Inadequate/very inadequate	13 (6.3)		25 (10.0)
Fair	37 (18.0)		52 (20.8)
Adequate/very adequate	156 (75.7)		173 (69.2)
Functional health		98.7 (4.7)		99.0 (4.6)
Disease		1.2 (1.0)		1.24 (1.1)