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. Author manuscript; available in PMC: 2024 Apr 1.
Published in final edited form as: J Community Psychol. 2022 Sep 17;51(3):978–997. doi: 10.1002/jcop.22936

A longitudinal study of social, religious, and spiritual capital and physical and emotional functioning in a national sample of African Americans

Eddie M Clark 1, Lijing Ma 2, Beverly R Williams 3, Debarchana Ghosh 4, Crystal L Park 5, Emily Schulz 6, Nathaniel Woodard 7, Cheryl L Knott 8
PMCID: PMC10006284  NIHMSID: NIHMS1834588  PMID: 36115065

Introduction

While social capital is characterized in different ways, definitions typically include factors such as social resources, social engagement, collective efficacy, and perceptions of trust, mutuality, and social cohesion (Gilbert & Dean, 2012; Putnam, 2007). An abundance of research links social capital to good health (Gilbert & Dean, 2012; Moore et al., 2014; Villalonga-Olives et al., 2020). However, few studies have explored how religious and spiritual capital contribute to health. Religious capital includes the resources derived from one’s faith community while spiritual capital encompasses resources stemming from one’s relationship with God or a higher power (Holt, Schulz, Williams, Clark, & Wang, 2012). The present study builds on prior research (Holt et al., 2012) by examining how social, religious, and spiritual capital are associated with physical functioning, emotional functioning, and depressive symptoms in a 2.5-year longitudinal study of African American adults. In addition, we explore the moderating relationships between social, religious, and spiritual capital and their association with physical and mental health.

Social Capital

Social capital has been defined as the collective benefit that comes from reciprocally cooperative and helpful relationships (Santorius, 2003). Social capital can refer to the process by which people secure benefits via their membership in social networks or other social organizations including norms and social trust that facilitate cooperation for mutual benefit (Portes, 1998; Putnam, 2000). Further, social capital is the aggregate of resources linked to a network of mutual acquaintances (Bourdieu, 1986). Social support (socioemotional, instrumental, informational) has been used by some researchers as a measure of neighborhood cohesion and community competence, which are dimensions of social capital (Lochner et al., 1999). Social support from one’s religious congregationis part of operationalization of religious social capital (Maselko, Hughes, and Cheney, 2011).

Many dimensions of social capital have been identified and a variety of measures of have been developed. For example, bridging, bonding, and linking refer to the group contexts in which social capital flows. Bonding social capital are resources that are accessed within a tightly connected network of relationships. Bridging social capital are the resources that may be accessed across loosely coupled networks. Linking social capital are the norms of respect and networks of trust uniting individuals and groups (Moore & Kawachi, 2017). Researchers have also utilized the notions of cognitive and structural social capital to describe the underlying interpretive and compositional frameworks of social networks. Cognitive social capital is understood as a resource providing a shared system of meaning within groups including trust, reciprocity, and support. Structural social capital is construed as the number or density of civic or neighborhood associations and the extent that individuals participate in these social networks (Moore & Kawachi, 2017). Social capital research has suffered from measurement challenges, inconsistent operationalizations, unique unpublished instruments, and unreported psychometric properties of existing instruments (Perry et al., 2008).

Using a systematic process, Perry and colleagues (2008) developed a theory-based social capital instrument and evaluated its psychometric properties. They identified three factors of social capital accordant with both the conceptual definitions discussed and other social capital instruments: social support, interconnectedness, and community participation. Social support refers to the extent to which the individual can access help from others in their community. Interconnectedness refers to the extent the individual trusts and feels good about their community. Community participation refers to the extent the individual feels they can influence what happens in their community, both alone and with others. Perry et al. report strong psychometric properties for their instrument, including acceptable internal reliability and an interpretable factor structure. While the factor labels used by Perry and colleagues and the current study are different than some prior work (e.g., they do not use terms such as bonding and bridging to identify their social capital factors), the factors Perry et al. identified (social support, interconnectedness, community participation) are associated with other conceptualizations and measures of social capital (e.g., trust, cooperation, access to resources, bonding, linking, cognitive, support).

Religious and Spiritual Capital

Religious capital has sometimes been referred to as religious social capital or faith-based social capital with somewhat different but overlapping operationalizations (Bartowski & Xu, 2007; Irwin, Lagory, Ritchey, & Fitzpatrick, 2008; Maselko, Hughes, & Cheney, 2011). The Holt et al. (2012) religious capital measure, based on the Perry et al. (2008) social capital measure discussed above, also included the three factors – social support, interconnectedness, and community participation. The religious capital measure assessed the extent to which the individual had someone they could call on for help from their church or faith community (social support), the extent to which they trust and feel good about their church or faith community (interconnectedness), and the extent to which they can influence what happens in their church or faith community (community participation). The Holt et al. (2012) religious capital measure is similar to the Maselko, Hughes, and Cheney (2011) measure of religious social capital. One advantage of the Holt et al. (2012) religious capital measure is that it does not include church attendance frequency, which has been criticized in health research as lacking in conceptual clarity on what is being measured (Idler et al., 2009; Maselko et al., 2011).

The Holt et al. (2012) spiritual capital measure, also based on the Perry et al. (2008) three-factor social capital measure, assessed the extent to which individuals would call on God for help finding assistance (social support), the extent to which God can be trusted and they feel good about their relationship with God (interconnectedness), and the extent to which they believe that in working together with God they can make changes in their community (community participation). Holt et al. (2012) found that the measures of religious and spiritual capital and their subscales had good internal reliability, were distinct from general religiosity, and measurement models confirmed their factor structures in a national sample of African American adults.

We acknowledge that there is overlap between the constructs of spiritual capital and spirituality, although there is variability in how the public defines spirituality (Handal et al., 2017; Holt, Clark, & Osuji, 2006; Mattis, 2000). The current operationalization of spiritual capital focuses not only on one’s personal connection with God, but also the extent that one calls on God for assistance and seeks God’s help to make changes in their faith community. In addition, we acknowledge that there is overlap in religious social support and religious capital. However, the operationalization of religious capital, based on Perry et al.’s (2008) social capital research, includes the extent to which they trust and feel good about their faith community, and the extent to which one can influence what happens in their faith community, alone or working with others (community participation).

In sum, the current study uses the Holt et al. (2012) instruments adapted from the Perry et al. (2008) social capital measure, to assess two additional forms of capital – religious capital and spiritual capital. Holt et al. (2012)’s goal was to provide a close adaptation so that the three types of capital could be compared in future research, an approach similar to that of Maselko, Hughes, & Cheney (2011).

Theoretical Frameworks

Social Capital Theory states that different types of capital are not mutually exclusive (Schuller, 2006; Schuller & Theisens, 2010). Analyses that explore the interaction between these different types of social capital can be beneficial in determining the dynamics of knowledge creation and use (Schuller, 2006; Schuller & Theisens, 2010). Prior work has suggested the importance of examining the moderating relationships pertaining to social capital and health and calls on expanding social capital research “to understand better the various strategies and contexts in which individuals and groups access and mobilise social capital for health benefits” (Moore & Kawachi, 2017, p. 516).

Social Network Theory provides a useful framework for understanding the influence of capital on health by emphasizing the importance of interpersonal connections (Valente, 2015), including family, friends, and faith communities. Capital empowers the group to effectively maintain health-related social norms (e.g., do not smoke in nonsmoking areas), pursue collective health-related action (e.g., protests supporting mask-wearing in schools during the COVID-19 pandemic), and the exchange of valued resources (e.g., provide rides to medical appointments).

In addition, the Social Ecological Model suggests health is affected by the interaction between the individual, the group/community, and the physical, social, and political environments (Israel et al., 2003; Sallis et al., 2008). Social capital may include bringing food to a sick neighbor, religious capital may include financial support from church members, and spiritual capital may include prayer and bringing comfort and meaning to life (Elgar et al., 2020; Jay & Andersen, 2018).

Social Capital, Religious Capital, and Health

Religiosity is an important part of the African American community (Belgrave & Allison, 2019). African Americans report high levels of religious engagement, including church membership, prayer, and reading religious material (Chatters et al., 2009). Research documents a connection between religiosity and health behaviors within this population (Bediako et al., 2011; Clark, Williams, Huang, Roth, & Holt, 2018; Landor et al., 2011; Mattis & Watson, 2009; Waldraon-Perrine et al., 2011;). For example, religious beliefs and behaviors predicted higher fruit consumption, less smoking, and lower alcohol use in an African American adult sample (Holt et al., 2014).

A variety of studies, including some specific to African Americans, have found a relationship between social capital and health (e.g., Beaudoin, 2009; Cheney et al., 2016; Dean et al., 2014). Social capital was associated with reduced smoking relapse during a two-year longitudinal study (Moore et al., 2014) and mediated the relationship between community racial prejudice and mortality (Lee et al., 2015). Higher levels of social capital in the workplace buffered against workplace stress (Jay & Andersen, 2018) and social capital was associated with better self-rated health (Arezzo & Giudici, 2017). Social capital was related to better community health (Poortinga, 2012), lower COVID-19 deaths (Elgar et al., 2020), health message recall (Viswanath et al., 2006), perception of fewer barriers to healthcare, and higher healthcare satisfaction (Perry et al., 2008).

Neighborhood factors such as residential segregation may impact African Americans differently than other groups due to the institutionalized oppression (Gilbert & Dean, 2013; Lewin et al., 2011). One study found that when neighborhood social cohesion was high, racial discrimination had no association with depressive symptoms. However, when cohesion was low, increased racial discrimination was associated with increased depressive symptoms (Powell Hammond et al., 2009).

While most studies find that higher levels of social capital are associated with better health, some studies found evidence for negative social capital in that social capital may be associated with poorer health. For example, in a study of COVID-19 related deaths, one study found that higher mortality was linked to higher trust and group affiliations. The authors speculated that trust and belonging to groups were associated with more deaths due to behavioral contagion and the incongruence with physical distancing practices. Further, negative consequences may result from limited opportunities, excessive demands, and limited freedoms. Negative consequences may be more likely to occur within the context of bonding social capital when group members’ access to more diverse resources are limited and negative norms and behaviors are enforced more strongly on group members (Moore, Daniel, Gavin, et al., 2009; Moore & Kawachi, 2017; Portes, 1998).

Since social capital is operationalized differently across studies and different studies assess different aspects of health, it difficult to determine the dimensions of social capital that are most related to various health behaviors and outcomes. However, some studies suggest that dimensions related to social support and interconnectedness are related to health. Examples include, auxiliary friendships that provide rides to medical appointments (Beaudoin, 2009), use of drug treatment programs, self-help groups, and association with non-drug using social network (Cheney et al., 2016), network social capital (Moore et al., 2014), number of social capital establishments such as sports facilities and clubs, political and business organizations (Lee et al., 2015), and bridging social capital (Arezzo & Guidici, 2017; Jay & Anderson, 2018; Poortinga, 2011). There were some studies suggesting the importance of community participation, noting the relationship of collective efficacy and civic engagement to health (Elgar et al., 2020).

Relatively few studies have examined the association between religious capital and health. Using a measure similar to the current study’s religious and social capital measures, a prior study found a negative relationship between religious social capital and neighborhood social capital (Maselko et al., 2011). Another study examined the effectiveness of a faith-based HIV intervention for African American women and achieved favorable results by changing the existing intervention; increasing structural religious capital through church ministries participation, focusing on religious values and norms (e.g., doctrines related to avoiding sexual situations) such as increasing discussion with religious leaders, and reducing negative religious coping (Wingood et al., 2013). While some prior studies have examined religious capital, the only studies that have specifically examined spiritual capital are from the Religion and Health in African Americans (RHIAA) project.

Past Studies of Capital from the Religion and Health in African Americans (RHIAA) Project

The current study uses data from the RHIAA project, a national survey designed to test a theoretical model of the religion-health connection (e.g., Holt et al., 2013). A cross-sectional analysis of personality and social capital that used the first wave of the same sample as the current study found that higher social capital was related to lower depressive symptoms. However, this relationship was moderated by personality such that higher social capital was related to lower depressive symptoms among persons with low conscientiousness, low extraversion, or high neuroticism. (Clark et al., 2018). Another cross-sectional analysis found that those higher on the community participation factor of spiritual capital reported lower depressive symptoms (Holt, Schulz, Williams, Clark, Wang, & Southward, 2012). Most relevant to the present study, one cross-sectional analysis found evidence that higher social capital predicted positive emotional functioning and that religious capital made a significant additional contribution to the prediction of emotional functioning (Holt et al., 2012). One purpose of the present study is to build on the Holt et al. (2012) study with a longitudinal analysis and examine the additive model and the possible moderating relationships between the social, religious, and spiritual capital and health.

Moderating Relationships Between Social, Religious, and Spiritual Capital and Health

No prior studies have examined the moderation relationships between social, religious, and spiritual capital. Consistent with the Social Network and Social Ecological Models, different types of capital may provide different benefits. In addition, individuals may not have all types of capital available to them. Consequently, there are many possibilities for how different types of capital may interact in their association with health. Prior investigations have suggested the existence of these moderation relationships. For example, it may be that those who do not have spiritual capital will rely more on social capital or it may be that when people have abundant religious capital, they rely less on social capital (Maselko et al., 2011). An additional possibility is that health outcomes are best when social, religious, and spiritual capital are all simultaneously high. This moderation approach is also aligned with prior studies that examined the interactions between different dimensions of capital as they related to health-related variables (Arezzo and Guidici, 2017; Viswanath et al. 2006). These examples illustrate the necessity of examining the possible moderation relationships between the three types of capital and their association with health to examine whether the relationship between one type of capital and health changes depending on the quantity of another type of capital.

Examining the contributions of each type of capital to health will aid the development of effective health behavior interventions. One-size-fits-all interventions are often ineffective (Kreuter et al., 2005) and identifying the conditions under which certain types of capital are more or less effective can help in targeting or tailoring interventions. Both Social Network Theory and the Social Ecological Model, as well as theoretical and research work by others (Moore & Kawachi (2017; Schuller, 2006; Schuller & Theisens, 2010), suggest the utility of investigating how one type of capital may moderate the relationship of another type of capital on health behaviors and health outcomes. Not only would it be useful to examine an additive model, but we may find that some types of capital may have a stronger or weaker relationship to health depending the strength of other types of capital.

The Present Study

Holt, Schulz, Williams, Clark, & Wang (2012) examined the relationship between social, religious, and spiritual capital and health, but was limited by (1) their use of a cross-sectional analysis and (2) their examination of only additive effects models. Building on Holt et al. (2012), we examined whether social, religious, and spiritual capital assessed at Time 1 (T1) would predict changes in physical functioning, emotional functioning, and depressive symptoms 2.5 years later at Time 2 (T2). This study uses an African American sample, a group that is not only highly religious (Taylor et al., 2011) but also carries a greater health burden than European Americans (Williams, 2012). We predicted that social, religious, and spiritual capital at T1 would predict increases in physical and emotional functioning and decreases in depressive symptoms at T2. Finally, not only did we examine the additive model of social, religious, and spiritual capital, but we explored possible moderations between the three types of capital based on Social Network Theory and the Social Ecological Model.

Method

Participants and Response Rate

As part of the RHIAA project (Holt et al., 2013), a professional sampling firm generated a call list of households from all 50 United States using probability-based methods. The firm obtained home phone numbers from publicly available data such as motor vehicle records. Participants were self-identified as African American and were age 21 or older. Participants who agreed to be re-contacted were called 2.5 years after T1 and interviewers administered the Time 2 (T2) survey. Both interviews were approximately 45 minutes. The study was approved by the Institutional Review Board.

The response rate at T1 was calculated as the proportion of complete interviews to the total number of eligible individuals. Only 13 individuals who were screened and eligible refused to participate, resulting in an upper bound response rate of 98% (803/816). The overall response rate was 27%, 803 accepted/(803 accepted + 2,195 refused). Another 379 individuals were not eligible for various reasons: 31 were younger than 21 years, 159 refused to provide an age for use in eligibility screening, and 189 were not African American. A total of 3,390 calls were made (summing each of these dispositions). A brief refusal survey was conducted to compare responders to non-responders (N = 73). Compared to responders, non-responders were older (non-responders M = 65.52 years old, SD = 15.28 vs. responders M = 56.01 years old, SD = 15.00), more likely to be men (62.0% for non-responders vs. 47.2% for responders), and less likely to have attended 1 to 3 years of college (14.1% for non-responders vs. 25.8% for responders). Our overall response rate of 27% is similar to those in the Methodology Reports of the National Institutes of Health/National Cancer Institute’s Health Information National Trends Surveys (HINTS), which recruits nationally representative samples of Americans who are asked about their use of health information (National Cancer Institute, 2003).

A total of 792 participants (375 men, 417 women) completed measures at T1 and 299 participants completed measures at T2, resulting in a retention rate from T1 to T2 of 38%. It should be noted that the original study (at T1) did not include a planned follow-up assessment. However, once funding became available, these participants were re-contacted and asked to complete a follow-up interview in the absence of any retention activities, resulting in a lower response rate.

The analytic sample for the present paper comprises individuals who provided data for both waves of data collection (N = 299). Those who completed the T2 interview, compared to those who did not (N = 493), were significantly older (58.59 vs. 54.28 years old, p < .001). However, there was no gender difference (OR 0.81, 95% CI 0.61–1.09). More retained participants had a college degree than non-retained participants (59.53% vs. 49.08%, OR 0.66, 97% CI 0.49–0.88). There was no difference in reporting “poor” self-rated health (OR 0.60, 95% CI 0.34–1.07), in having an income greater than $30k (OR 0.92, 95% CI 0.67–1.26), or in being married or living with partner (OR 0.99, 95% CI 0.74–1.32).

Measures

Social Capital

An existing social capital instrument was used consisting of nine items comprising three factors: social support (e.g., ‘If a medical emergency arose in your home, would you be likely to call your neighbors for help?’), interconnectedness (e.g., ‘Would you say most people in this community can be trusted?’) and community participation (e.g., ‘Would you say you can influence decisions that affect your community?’) (Perry et al., 2008). A 4-point Likert-type format (1 = strongly disagree to 4 = strongly agree) was used with higher scores indicating greater social capital. The three-factor solution showed a fit to the data and was supported in a confirmatory sample. Overall reliability was good in the present study (α = .87).

Religious capital

The religious capital instrument was adapted directly from the social capital instrument discussed above (validation is discussed in Holt, Schulz, Williams, Clark, & Wang, 2012). This adaptation involved modifying references to ‘neighbors’ and ‘people in your community’ to ‘people in my religious/spiritual community’. The adaptation was conducted purposively so that items closely mirrored the original social capital instrument, facilitating the use of the instruments in comparative analyses. Religious capital involves a social support factor (e.g., ‘If I needed a ride to the doctor, I would be likely to call on someone in my religious/spiritual community for a ride.’), an interconnectedness factor (e.g., ‘My religious/spiritual community is a good place for kids to grow up.’) and a community participation factor (e.g., ‘I can influence decisions that affect my religious/spiritual community.’). The religious capital scale consisted of nine items assessed in 4-point Likert-type format (1 = strongly disagree, 4 = strongly agree) with higher scores indicating higher levels of these beliefs. Overall reliability was good in the present study (α = .89).

Spiritual capital

The instrument to assess spiritual capital also was adapted directly from the Perry et al. (2008) social capital instrument (validation is discussed in Holt, Schulz, Williams, Clark, & Wang, 2012). This adaptation involved modifying references to ‘God’, reflecting spiritual capital. Spiritual capital also involves a social support factor (e.g., ‘If a medical emergency arose in my home, I would be likely to call on God for help.’), an interconnectedness factor (e.g., ‘I expect to maintain my relationship with God for a long time.’), and a community participation factor (e.g., ‘By working together with God, I can influence decisions that affect my community.’). The spiritual capital scale consisted of nine items assessed in 4-point Likert-type format (1 = strongly disagree, 4 = strongly agree) with higher scores indicating higher levels of these beliefs. Overall scale reliability was good in the present study (α = .90).

Physical and emotional functioning

The Medical Outcomes Study Short Form (SF-12) is a widely used, health-related quality of life measure that evaluates physical functioning, role limitations resulting from physical health problems, bodily pain, general health, vitality, social functioning, role limitation resulting from emotional problems and mental health (Stewart et al., 1988). The SF-12 includes physical and mental health summary scale scores (SF-12 Physical Component Summary and SF-12 Mental Component Summary). This 12-item short form has been shown to have reliability and validity comparable with the longer versions. The test–retest reliability for both the physical (.89) and the emotional (.76) functioning scales was acceptable. Known groups validity was evidenced as well (Ware, Kosinski, & Keller, 1996; Ware et al., 2002). Due to the nature of scoring, inter-item reliability is usually not reported.

Depressive symptoms

Depressive symptoms were assessed with the Center for Epidemiological Studies Depression Scale (CES-D; Radloff, 1977). The CES-D has been validated with an African American sample (Makambi et al., 2009; Roth et al., 2008). Participants were asked the frequency of depressive symptoms in the past (e.g., “I had crying spells” and “I felt that everything I did was an effort”; rarely/less than 1 day … all of the time/5–7 days). Higher scores indicate more depressive symptoms. Test-retest reliability and internal consistency were high in previous normal and patient populations (α = .87). Internal reliability in the current study was good (α = .88).

Demographics

A standard demographic module assessed participant characteristics including gender, age, relationship status, educational attainment, work status, and household income before taxes.

Analytic Methods

First, we computed means, standard deviations, and intercorrelations between the primary study variables. Second, we performed hierarchical linear regression analyses on each of the health outcomes – physical functioning, emotional functioning, and depressive symptoms. For example, we performed hierarchical linear regression analysis to predict residual change in T2 physical functioning since we controlled for T1 physical functioning. Centered scores were used for the predictor variables that were entered in the regression analyses. In Step 1 we entered the control variables of T1 physical functioning: education, age, and income. In Step 2, we entered T1 social capital, T1 religious capital, and T1 spiritual capital (additive model). In Step 3, we entered the interactions: T1 social capital × T1 religious capital, T1 social capital × T1spiritual capital, T1 religious capital × T1 spiritual capital, and T1 social capital × T1 religious capital × T1 spiritual capital. Similar analyses were carried out for emotional functioning and depressive symptoms.

Results

Analytic Sample Demographics

The analytic sample (N = 299) included 167 women and 132 men. The average age was 58.59 years (SD = 12.92), with an age range from 21 to 89 years and participants indicated a median income in the $30,000 to $40,000 category. Many (41.1%) were married or living with a partner, had a high school education (31.8%), 1 to 3 years of college (25.4%), or 4 years of college (34.1%), and worked full-time (28.8%) or were retired (34.8%). Geographically, our participants were from the Southern (59.8%), Midwestern (19.1%), Northeastern (18.1%), and Western (1.7%) United States based on the US Census regions. The distribution of regional percentages was similar to that reported for African Americans in the 2010 US Census (Rastogi et al., 2011).

Correlations

As seen in Table 1, social, religious, and spiritual capital were positively intercorrelated. In addition, higher T1 social capital, higher T1 religious capital, and higher T1 spiritual capital were associated with higher T2 emotional functioning. Lower T1 social capital and lower T1 religious capital were related to higher T2 depressive symptoms. T1 social capital, T1 religious capital, and T1 spiritual capital were not associated with T2 physical functioning.

Table 1.

Correlations, Means, and Standard Deviations of Primary Study Variables

Variable M (SD) Social Capital T1 Religious Capital T1 Spiritual Capital T1 Physical Functioning T2 Emotional Functioning T2 Depressive Symptoms T2
Social Capital T1 34.32 (6.14)
Religious Capital T1 36.71 (5.91) .48***
Spiritual Capital T1 40.18 (5.53) .33*** .51***
Physical FunctioningT2 43.26 (11.35) .07 .10 .11
Emotional FunctioningT2 51.94 (10.10) .22*** .15* .15* .13*
Depressive SymptomT2 31.71 (9.36) −.22*** −.14* −.12 −.34*** −.68***
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Note: N ranges from 235 to 298.

*

p < .05,

**

p < .01,

***

p < .001

Regression Analyses

Physical Functioning

We performed a hierarchical linear regression analysis to predict residual change in T2 physical functioning (Table 2). At Step 2, we examined the additive model with the main effects for social, religious, and spiritual capital added. Only the spiritual capital main effect approached significance (β = 0.12, t = 1.70, p = .090) with higher spiritual capital being marginally associated with higher physical functioning. In Step 3, we entered all the two- and three-way interactions to examine moderation. The only significant effect in Step 3 was the T1 social capital × T1 religious capital interaction, β = 0.23, t = 2.75, p = .007 (Figure 1). Simple slopes analyses indicated that for low T1 religious capital participants, those with high social capital had lower T2 physical functioning than those with lower T1 social capital, slope gradient = −0.46, t = −2.00, p = .047. However, for high T1 religious capital participants, there was no relationship between T1 social capital and T2 physical functioning, slope gradient = 0.24, t = 1.41, p = .16.

Table 2.

Hierarchical Regression Results for Physical Functioning at Time 2

Variable B 95% CI for B SE B β R 2 ΔR2
LL UL
Step 1 .37 .37***
 Constant 43.64*** 42.23 45.05 0.72
 Age T1 −0.06 −0.18 0.05 0.06 −.07
 Income T1 0.58 −0.13 1.29 0.36 .12
 Education T1 −0.32 −2.05 1.41 0.88 −.03
 Physical Functioning T1 0.59*** 0.45 0.72 0.07 .55***
Step 2 .39 .03
 Constant 43.63*** 42.23 45.03 0.72
 Age T1 −0.07 −0.19 0.04 0.06 −.08
 Income T1 0.58 −0.13 1.28 0.36 .12
 Education T1 −0.38 −2.09 1.33 0.87 −.03
 Physical Functioning T1 0.57*** 0.44 0.71 0.07 .54***
 Social Capital T1 −0.09 −0.36 0.19 0.14 −.04
 Religious Capital T1 0.18 −0.13 0.48 0.16 .09
 Spiritual Capital T1 0.24 −0.04 0.52 0.14 .12
Step 3 .43 .04*
 Constant 43.36*** 41.84 44.88 0.77
 Age T1 −0.06 −0.17 0.06 0.06 −.06
 Income T1 0.71* 0.01 1.41 0.36 .14*
 Education T1 −0.35 −2.05 1.36 0.86 −.03
 Physical Functioning T1 0.58*** 0.45 0.72 0.07 .55***
 Social Capital T1 −0.11 −0.42 0.20 0.16 −.05
 Religious Capital T1 0.08 −0.24 0.39 0.16 .04
 Spiritual Capital T1 0.19 −0.09 0.47 0.14 .10
 Social Capital T1 × Religious Capital T1 0.06** 0.02 0.11 0.02 .23**
 Social Capital T1 × Spiritual Capital T1 −0.03 −0.08 0.02 0.02 −.09
 Religious Capital T1 × Spiritual Capital T1 −0.02 −0.05 0.01 0.02 −.11
 Social Capital T1 × Religious Capital T1 × Spiritual Capital T1 0.001 −0.003 0.004 0.002 .03
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Note. CI = Confidence Interval; LL = Lower limit; UL = Upper limit.

*

p < .05.

**

p < .01.

***

p < .001.

Figure 1.

Figure 1

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T2 Physical Functioning as a Function of T1 Social Capital and T1 Religious Capital Controlling for Covariates and T1 Physical Functioning

Emotional Functioning

We performed a hierarchical linear regression analysis to predict residual change in T2 emotional functioning (Table 3). At Step 2, we examined the additive model with the main effect of social, religious, and spiritual capital added. Only the spiritual capital main effect approached significance (β = 0.14, t = 1.86, p = .064) indicating that higher spiritual capital was marginally related to better emotional functioning. In Step 3, we added all the two- and three-way interactions to examine moderation. At Step 3, only the T1 spiritual capital main effect approached significance with higher T1 spiritual capital marginally predicting higher T2 emotional functioning, β = .14, t = 1.79, p = .075. None of the interactions were significant at Step 3.

Table 3.

Hierarchical Regression Results for Emotional Functioning at Time 2

Variable B 95% CI for B SE B β R 2 ΔR2
LL UL
Step 1 .23 .23***
 Constant 52.04*** 50.83 53.25 0.61
 Age T1 0.03 −0.07 0.12 0.05 .04
 Income T1 0.63* 0.02 1.24 0.31 .16*
 Education T1 0.26 −1.21 1.73 0.75 .03
 Emotional Functioning T1 0.38*** 0.26 0.51 0.06 .41***
Step 2 .25 .02
 Constant 51.99*** 50.79 53.20 0.61
 Age T1 0.01 −0.08 0.11 0.05 .02
 Income T1 0.60 −0.01 1.21 0.31 .15
 Education T1 0.32 −1.15 1.79 0.74 .03
 Emotional Functioning T1 0.36*** 0.23 0.49 0.07 .38***
 Social Capital T1 0.11 −0.13 0.36 0.12 .07
 Religious Capital T1 −.10 −0.36 0.17 0.13 −.06
 Spiritual Capital T1 .23 −0.01 0.47 0.12 .14
Step 3 .26 .01
 Constant 51.95*** 50.61 53.29 0.68
 Age T1 0.02 −0.08 0.11 0.05 .02
 Income T1 0.63* 0.01 1.25 0.31 .16*
 Education T1 0.36 −1.14 1.86 0.76 .04
 Emotional Functioning T1 0.35*** 0.21 0.48 0.07 .37***
 Social Capital T1 0.06 −0.21 0.34 0.14 .04
 Religious Capital T1 −0.08 −0.36 0.20 0.14 −.05
 Spiritual Capital T1 0.22 −0.02 0.47 0.13 .14
 Social Capital T1 × Religious Capital T1 0.03 −0.01 0.07 0.02 .13
 Social Capital T1 × Spiritual Capital T1 −0.03 −0.07 0.01 0.02 −.13
 Religious Capital T1 × Spiritual Capital T1 −0.002 −0.03 0.03 0.01 −.02
 Social Capital T1 × Religious Capital T1 × Spiritual Capital T1 <0.001 −0.003 0.004 0.002 .02
Open in a new tab

Note. CI = Confidence Interval; LL = Lower limit; UL = Upper limit.

*

p < .05.

**

p < .01.

***

p < .001.

Depressive Symptoms

We performed a hierarchical linear regression analysis to predict residual change in T2 depressive symptoms (Table 4). At Step 2, we examined the additive model with the main effect of social, religious, and spiritual capital added. Only the spiritual capital main effect approached significance (β = −0.14, t = 1.96, p = .052) indicating that higher spiritual capital was marginally related to lower depressive symptoms. In Step 3, we added all the two- and three-way interactions to examine moderation. At Step 3, there was a marginally significant spiritual capital main effect (β = −0.12, t = −1.68, p = .096) indicating that higher spiritual capital was marginally and negatively related to depressive symptoms. However, this is qualified by a marginally significant T1 social capital × T1 spiritual capital interaction, β = .14, t = 1.77, p = .079 (Figure 2). Simple slopes analyses indicated that among low T1 spiritual capital participants, those with higher T1 social capital reported lower depressive symptoms than those with lower T1 social capital, slope gradient = −0.35, t = −2.21, p = .03. However, among high T1 spiritual capital participants, there was no difference between low and high T1 social capital participants on depressive symptoms, slope gradient = 0.05, t = 0.26, p = .79.

Table 4.

Hierarchical Regression Results for Depressive Symptoms at Time 2

Variable B 95% CI for B SE B β R 2 ΔR2
LL UL
Step 1 .33 .33***
 Constant 31.69*** 30.49 32.88 0.61
 Age T1 0.08 −0.09 0.10 0.05 .01
 Income T1 −0.86** −1.46 −0.26 0.31 −.21**
 Education T1 1.11 −0.36 2.57 0.74 .11
 Depressive Symptoms T1 0.53*** 0.40 0.66 0.07 .52***
Step 2
 Constant 31.81*** 30.64 33.00 0.60 .37 .04*
 Age T1 0.03 −0.07 0.12 0.05 .04
 Income T1 −0.79** −1.38 −0.19 0.30 −.19**
 Education T1 1.06 −0.38 2.50 0.73 .11
 Depressive Symptoms T1 0.52*** 0.39 0.65 0.07 .51***
 Social Capital T1 −0.15 −0.38 0.09 0.12 −.09
 Religious Capital T1 −0.03 −0.29 0.22 0.13 −0.02
 Spiritual Capital T1 −0.23 −0.47 0.002 0.12 −0.14
Step 3
 Constant 32.10*** 30.81 33.39 0.66 .40 .03*
 Age T1 0.03 −0.07 0.12 0.05 .03
 Income T1 −0.76** −1.36 −0.16 0.30 −.19**
 Education T1 0.84 −0.61 2.28 0.73 .08
 Depressive Symptoms T1 0.54*** 0.40 0.67 0.07 .52***
 Social Capital T1 −0.14 −0.40 0.12 0.13 −.08
 Religious Capital T1 −0.07 −0.34 0.19 0.13 −.04
 Spiritual Capital T1 −0.20 −0.44 0.04 0.12 −.12
 Social Capital T1 × Religious Capital T1 −0.03 −0.07 0.01 0.02 −.13
 Social Capital T1 × Spiritual Capital T1 0.04 −0.004 0.08 0.02 .14
 Religious Capital T1 × Spiritual Capital T1 −0.02 −0.05 0.01 0.01 −.13
 Social Capital T1 × Religious Capital T1 × Spiritual Capital T1 0.002 −0.001 0.01 0.002 .14
Open in a new tab

Note. CI = Confidence Interval; LL = Lower limit; UL = Upper limit.

*

p < .05.

**

p < .01.

***

p < .001.

Figure 2.

Figure 2

Open in a new tab

T2 Depressive Symptoms as a Function of T1 Social Capital and T1 Spiritual Capital Controlling for Covariates and T1 Depressive Symptoms

Discussion

The present study is based on the Social Network Theory and the Social Ecological Model, and builds on prior cross-sectional research by Holt et al. (2012). We longitudinally investigated the relationship of T1 social, religious, and spiritual capital with T2 physical functioning, T2 emotional functioning, and T2 depressive symptoms 2.5 years later in a national sample of African American adults. We examined both the additive model (main effects for social, religious, and spiritual capital) and a moderation model (the two- and three-way interactions between the three types of capital) in predicting T2 physical functioning, emotional functioning, and depressive symptoms.

In partial support of our hypotheses, correlational results (Table 1) indicated that African American adults who had higher T1 social capital also had better T2 emotional functioning and lower T2 depressive symptoms 2.5 years later. However, the correlational results do not control for T1 emotional functioning and T1 depressive symptoms, respectively.

Also, consistent with our hypotheses, we found some evidence that religious and spiritual capital improved our ability to predict health outcomes when added to the regression equations. Regarding physical functioning, in the additive model, higher spiritual capital was marginally related to higher physical functioning. In addition, religious capital significantly moderated the role of social capital’s relationship with physical functioning such that social capital predicted poorer physical functioning if participants also had low religious capital. The results for low religious capital participants were unexpected. Some researchers have examined negative social capital, which refers to the deleterious impact that social capital can have on health (Moore & Kawachi, 2017; Villalonga-Olives & Kwachi, 2017). They cite research that negative outcomes can stem from “closed networks” which diminish individuals’ access to other resources. In our analyses, it is plausible that the combination of high social capital and low religious capital limits individuals’ access to a broader and more diverse instrumental and motivational resources for enhancing physical functioning. Alternatively, our results may be related to the multicollinearity between social capital and religious capital (Table 1). Given the high level of religiosity among African Americans (Taylor et al., 2011), it is not surprising that their perceptions of capital in their general community would overlap with their perceptions of capital in their faith community. Another possible explanation is that there are other neighborhood or institutional variables, such as segregation, that account for this unexpected finding (Gilbert & Dean, 2013).

Regarding emotional functioning, there was marginal evidence from our regression analyses additive model that persons with higher T1 spiritual capital also had higher T2 emotional functioning and this marginal effect persisted even in the moderation model. This relationship is weaker but consistent with cross-sectional research (Holt et al., 2012). Given that this is a longitudinal study with capital assessed at T1 and health outcomes assessed 2.5 years later at T2, it is not surprising that the relationships are weaker than prior cross-sectional analyses.

Regarding depressive symptoms, higher spiritual capital was marginally related to lower depressive symptoms in the additive model. There also was marginal evidence that spiritual capital moderated the relationship between social capital and depressive symptoms such that social capital was associated with lower depressive symptoms but only when spiritual capital was low (Figure 2). The depressive symptoms related to low spiritual capital were buffered by having high social capital. When participants had either high social capital or high spiritual capital, their depressive symptoms were relatively low. The group most at risk for depressive symptoms were those with both low social and low spiritual capital. Social capital may bring tangible, instrumental, and informational support, but spiritual capital may bring comfort and meaning to life from a higher power. Having at least one of high social capital or high spiritual capital seems important to protecting against depressive symptoms.

The present study has some notable strengths as well as limitations. The strengths of this study include a longitudinal design, which provides additional insight into possible causal processes, as well as focusing on African Americans, who carry a larger health burden than European Americans (Williams, 2012). In addition, this is the first study to explore the possible moderation relationships between social, religious, and spiritual capital as they relate to health. One limitation of the present study is that our population-based national sample of African Americans is not representative of all African Americans. In addition, like many self-report studies, participants’ responses may be biased by faulty memory or socially desirable responding.

Future research should expand our understanding of the substance of social, religious, and spiritual capital. A qualitative study asking African American adults about the nature, distinguishing characteristics, and relevant neighborhood institutions for each type of capital would be highly beneficial to researchers, practitioners, and policy makers. Longitudinal investigations of the relationship between the three types of capital and other health behaviors would be useful to inform practice and policy. Examining the variables that moderate and mediate the relationships between the capital and health behaviors would be useful for policy and practice. For example, further examination of whether capital buffers against the negative physical and psychological effects of racial discrimination, segregation, and neighborhood violence is needed, and if so, through what mechanisms does this buffering occur. A cluster analyses examining the how the factors of social, religious, and spiritual capital - social support, interconnectedness, community participation – are associated with physical and mental health outcomes would provide information on the conditions under which capital operates. Finally, the investigation of the association of other types of capital (e.g., ethical capital) and health is warranted (Williams, Woodby, & Drentea, 2010).

Results of the present study may have implications for the development of health-related interventions and policy that facilitate African Americans capitalizing on their social, religious, or spiritual capital. Intervention delivery may vary depending on whether the population is low or high on social, religious, or spiritual capital, essentially tailoring interventions on the three types of capital. Interventions that assist individuals with developing and integrating a wider range of social, religious and spiritual resources may be particularly helpful in protecting against depressive symptoms. Capital not only involves social support, but also includes factors such as interconnectedness and community engagement. Research examining the relationship between perceptions of neighborhood safety and depressive symptoms among urban African Americans and Latinos living in a subsidized housing communities identified a mediating role for social capital (sense of community belonging) (Gonyea et al., 2018). For example, the Multiphase Optimization Strategy (MOST), a novel framework developed to optimize interventions, i.e., to test the effectiveness of intervention delivery strategies using a factorial design may facilitate building a combination of their social, religious, and spiritual capital may be particularly helpful in protecting against depressive symptoms (Collins, 2018; Marshall et al., 2016). Another method to encourage building these types of capital is to target healthcare providers. Healthcare providers can encourage patients not only to elicit and accept social support, but also to engage with their communities, including their faith community and their personal relationship with God, as appropriate given their individual belief system. Public policy could be developed to align with the community’s desired goals, leveraging the community’s existing capital and supporting the improvement of the capital that needs bolstering. This could include policies to make it easier to access community resources and connect with neighbors by supporting community organizations and activities related to health (Moore & Kwachi, 2017).

In conclusion, the present study supports the importance of capital over time on physical and emotional functioning and depressive symptoms. These results have implications for policy development as well as interventions with individuals and healthcare providers.

Acknowledgements

The team acknowledges the work of OpinionAmerica who conducted participant recruitment/retention and data collection activities for the present study. We also thank Cort Rudolf for his statistical consultation.

Funding

This study was funded by grants from the National Cancer Institute (#1 R01 CA154419) and a grant from the Duke University Center for Spirituality, Theology, and Health, through the John Templeton Foundation (#11993). The study was approved by the University of Maryland Institutional Review Board (#373528-1 and #08-0329).

Footnotes

Declaration of Conflicting Interests

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

Contributor Information

Eddie M. Clark, Saint Louis University

Lijing Ma, Saint Louis University.

Beverly R. Williams, University of Alabama – Birmingham

Debarchana Ghosh, University of Connecticut.

Crystal L. Park, University of Connecticut

Emily Schulz, University of Northern Arizona.

Nathaniel Woodard, University of Maryland.

Cheryl L. Knott, University of Maryland

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