Examining Between-Group Differences in Social Network Density and High-Sensitivity C-Reactive Protein in Older Adults: Implications for the Hispanic Mortality Paradox

INTRODUCTION

Hispanic/Latino(x) and African American/Black older adults living in the United States experience disproportionately high levels of cardiometabolic disease compared with their non-Hispanic White (NHW) counterparts. These health disparities stem from high stress burdens including lower access to education, income, consistent and quality health care, and exposure to interpersonal prejudice (1,2). As disparities persist, factors associated with resilience to these stressors are most prudent to inform current health equity agendas. Resilience-based health interventions capitalize on the strengths of a community or cultural group and shift the focus from individual deficits to working with strong social infrastructures to optimize feasible structural change (3).

A robust literature demonstrates interpersonal social resources such as network size as being associated with long-term health, citing stress-buffering and behavioral processes as potential mechanisms. Several meta-analyses show strong associations between social network size and lower risk for cardiovascular disease and early death (4,5). These associations have been replicated with cardiometabolic end points such as high-sensitivity C-reactive protein (hs-CRP), an acute-phase protein and indicator of tissue death and systemic inflammation (e.g., tumor necrosis factor α, monocytes, and interleukin 6), and a robust predictor of cardiovascular disease incidence, and progression (6–8). Although myriad factors influence hs-CRP in an aging population, structural and psychosocial factors such as stress and social networks also influence this end point. Furthermore, the uneven distribution of structural stress burden carried by racial-ethnic minority groups has led past research to investigate the potential for social infrastructure to act as a resilience factor for inflammatory processes including hs-CRP. Such studies have revealed potential modifiable pathways upon which to maximize strengths in social infrastructures to improve health and well-being in these populations (9).

However, one limitation of readily used network scales is their lack of ability to measure density, or the connections between network members. Little work has focused on network density and its association with health outcomes and end points. A dense network organization may facilitate an infrastructure where the burden of stressors can be quickly distributed among members and health-relevant information can be shared more easily—rendering an individual less vulnerable to challenges (10). Current work in this area has found that network density is associated with greater self-esteem and efficacy in young adults, as well as less risk for the mistreatment of older adults (11,12). Although little research has assessed how this specific aspect of network infrastructure may contribute to cardiometabolic risk including inflammatory end points such as hs-CRP in adults across the life span (13). The purposes of this study were to understand the association between network density and 5-year hs-CRP, and to understand whether this association varies across racial-ethnic groups in an older sample.

Race and ethnicity are social variables that capture an amalgam of social advantage, disadvantage, and shared culture and language. Although there are few studies examining nuanced differences in social capital across racial-ethnic groups of older adults, past research suggests that racial and ethnic identity as well as social advantage/disadvantage help to shape social infrastructure and sensitivity to social resources differentially (14–16). For example, NHW adults tend to endorse individualism, emphasizing the goals and values of an individual as opposed to a group (17). In addition, this group has greater generational wealth and socioeconomic status when compared with other racial-ethnic groups in the United States. This disparity is a direct consequence of historical slavery and structural racism, which also drives social exclusion and prejudice directed at non-White groups. Given these historical experiences, Hispanic/Latino(x) and non-Hispanic African American/Black older adults may be more inclined to align themselves in networks where emotional and tangible support are commonplace. For example, Hispanic/Latino(x) and non-Hispanic African American/Black adults tend to endorse more interdependent values, emphasizing the goals of a group versus the individual (18–20). Hispanic/Latino(x) adults tend to endorse high values of familism, or the tendency to prioritize time and resources toward family needs (20,21). African American/Black adults value familial older adults as natural mentors, potentially looking to older siblings, aunts or uncles, and grandparents for guidance (22). They also draw from institutional group involvement including church-related and political/activism groups to form their social networks and support (23,24). In addition, African American/Black adults endorse greater levels of familism when compared with their NHW counterparts in a sample of caregivers (25). Taken together, these studies suggest that racial-ethnic differences in social organization and values may influence how these groups offset stress from structural burdens (14).

A large proportion of literature on social networks and health has focused on network size and/or the specific make up of members within a network (network diversity) (26–28). Results from these studies show mixed results. On the one hand, larger supportive networks are associated with better cardiometabolic health outcomes for both healthy and clinical populations. For example, larger social networks as measured by the Social Network Index are associated with lower stroke incidence and mortality from cardiovascular disease in older adults (29). Family versus friend ties seem to have a greater influence on health in this regard. For instance, in a community sample of adults, a greater number of supportive family members (but not friends) were associated with lower hs-CRP levels; however, this association for older adults has not been explored (30,31). Health benefits from supportive ties also extend to one’s spouse, illustrating the interpersonal benefits of a supportive network (32). On the other hand, some social network infrastructures can be detrimental. In a study of older adults, Goldman (31) found that network members holding primary “bridging” positions, or positions connecting kin and non-kin members in their network, had higher hs-CRP than those that do not serve as primary bridges. Authors suggest that this finding may be due to high social strain among these individuals (31). Given that the available literature on the salutary effects of family versus friend ties is focused on both adults and older adults, these effects may vary by age or life stage.

The gestalt of these results suggests that it is important to consider how race and ethnicity may moderate these associations in an older sample. For example, racial-ethnic groups that endorse interdependent social values may be differentially sensitive to a densely interconnected social network. Some research has revealed that race-ethnicity moderates the relationship between similar constructs like social support and hs-CRP. For instance, Uchino et al. (9) found that higher perceived social support was associated with lower hs-CRP levels in African American/Black adults, but not in NHW or Hispanic/Latino(x) adults. The relationship between network density, race-ethnicity, and hs-CRP has not been examined in diverse older adults, but could offer key insight into how a network can collectively manage stress experienced by an individual.

Network density is unique because it ignores specific connections from an individual to others in their network. Instead, network density measures the degree to which personal network members are connected to one another (33). Within a social network, connections are represented by “ties,” which may be binary or weighted. Network density is equal to the number of ties between network members (alters) divided by the number of possible ties (33). The density of a weighted network is the average of the tie weights across all possible ties (33). A densely connected network would contain individuals who are in close contact with one another. Conversely, a loosely connected network would contain individuals who do not know one another.

Past literature suggests that the lack of social connectedness can influence health through inflammatory pathways (34,35). Specifically, isolation may lead to upregulated inflammatory processes given a higher probability for wounds (i.e., isolated people are more vulnerable to threats) (34). The vulnerability of an individual may indeed vary by the interconnectedness of one’s network. For example, resources travel more quickly among members working as a team versus a set of isolated individuals who happen to be connected to the same individual. Therefore, a dense network organization may be a critical factor in mitigating structural stress burdens, especially in interdependent groups (36).

Given that hs-CRP is associated with high stress burden and is a key biomarker for cardiovascular disease risk, individuals within dense networks may enjoy optimal cardiometabolic health (37). Network density has been examined in the context of older adult mistreatment where Schafer and Koltai (11) found that dense (versus diffuse) personal networks were protective against the mistreatment of older adults. Authors of this study argued that dense networks provide structural protection against potential perpetrators (11). However, to our knowledge, no work has investigated whether dense network structures may influence cardiometabolic health in the three largest racial-ethnic groups in the United States.

This study aimed to understand a) the association between network density and cardiometabolic health as measured by 5-year hs-CRP and b) whether this relationship was moderated by race-ethnicity. We hypothesized that greater network density was associated with lower hs-CRP, 5 years later. Furthermore, given interdependent social values, we expected both non-Hispanic African American/Black and Hispanic/Latino(x) older adults with greater network density to experience a greater negative association between network density and 5-year hs-CRP as compared with NHW older adults with comparable network densities.

METHODS Data Source and Sample

We examined the association between network density and hs-CRP in older Hispanic/Latino(x), non-Hispanic/African American Black, and NHW older adults from the National Social Life and Aging Project (NSHAP), yielding a total sample of N = 2921 respondents. The NSHAP is a nationally representative study examining social relationships and health in older adults living in the United States. The NSHAP used a multistage area probability design described elsewhere (38). Wave 1 data collection commenced in 2005 until 2006, and respondents were resurveyed 5 and 10 years later (wave 2, 2010–2011; wave 3, 2015–2016). Study personnel conducted in-home interviews at each wave with an original wave 1 cohort of 3005 older adults aged 57 to 85 years with a mean age of 69.3 years. Although several studies classify adults who are younger than 65 years “middle-aged,” we follow the definition of “older persons” offered by the United Nations as 60 years and older, as well as the NSHAP’s reference to their samples as an “older population” (39,40). Eighty-four participants who self-reported their race-ethnicity to be non-Hispanic Asian or Pacific Islander (n = 35), non-Hispanic American Indian or Alaskan Native (n = 22), and non-Hispanic Other (n = 13), or did not know or refused to answer the questions about race-ethnicity (n = 15) were excluded from the study. The small number of participants in these groups precluded meaningful analyses. This exclusion was indeed a limitation, and future studies should seek to overrepresent respondents from these often-overlooked subpopulations. Of the sample returning at wave 2 (N = 2193), baseline hs-CRP was missing for 762 participants. We found that respondents who reported having “some college” and African American/Black older adults were more likely to have a missing baseline hs-CRP value. There were no other significant differences across substantive variables among those who were missing a baseline hs-CRP measure versus those who were not. Our final sample included N = 1431 respondents.

Network Density

Social network analysis was used to calculate network density from respondents’ ego-nets. Respondents were asked to name the number of confidants (alters) in their network with whom they have regular contact via the following, “Now we are going to ask you some questions about your relationships with other people. We will begin by identifying some of the people you interact with on a regular basis.” Next, respondents were asked to estimate to what degree their confidants talk to one another (ties) by the question, “How frequently do [name1] and [name2] talk to each other?” Responses ranged from 0 = “have never spoken to each other” to 4 = “once a month,” to 8 = “every day.” Network density is equal to the number of ties between alters divided by the number of possible ties. Ties may be binary (0 or 1) or weighted as in this study. Weights ranged from 0 to 1 and were the ratio of the frequency to which each alter speaks to one another divided by the highest possible score a respondent can endorse for this question. The density of a weighted network is the average of the tie weights across all possible ties (33). Detailed information regarding the collection and measurement of NSHAP respondent ego-nets may be found elsewhere (41).

Race-Ethnicity

Race-ethnicity is a sociocultural and political construct. This study included race-ethnicity as a social proxy for myriad interpersonal and systematic advantages and disadvantages. Respondents of the NSHAP self-reported their race-ethnicity characterized by Hispanic or Latino, non-Hispanic African American or Black, and NHW. Hispanic/Latino(x) respondents may come from any race. Race-ethnicity should not be construed as a biological variable.

High-Sensitivity C-Reactive Protein

High-sensitivity CRP (in milligrams per liter) was collected at waves 1 and 2 using dried blood spots retrieved during home visits/interviews for respondents in the NSHAP. A thorough review of the NSHAP blood spot protocol is available elsewhere (42). Note: hs-CRP at wave 3 is not publicly available currently.

Covariate Adjustment

Covariate and control variables were chosen based on prior literature and the use of a directed acyclic graph model. Directed acyclic graph models are epidemiological tools used to identify important confounds, mediators, and moderating factors with respect to investigator’s hypotheses or assumptions about health processes (43). Standard epidemiological controls including age, sex, and education were considered and included as inflammatory conditions often increase with age and are sensitive to social and economic opportunities often segregated across both gendered and educational divides (44,45). Marital status at both waves 1 and 2 were included as covariates in adjusted models because couple status may influence the size of one’s social network and health outcomes alike (46,47). On the other hand, because marital status is often considered a social network variable on its own, planned sensitivity analyses were conducted with and without marital status (see Statistical Analyses). Health variables were included as potential confounds and variables associated with the missingness at wave 2 (see Statistical Analyses). Smoking, waist circumference, and current cardiometabolic disease were included as potential confounds given their strong association with hs-CRP (48–50). Likewise, because literature demonstrates a strong link between smoking and hs-CRP levels, we also modeled the interaction between wave 1 hs-CRP and smoking behavior (38). Depressive symptoms and alcohol consumption were associated with missingness at wave 2 and were thus included in all models. Light to moderate alcohol consumption is also associated with optimal hs-CRP levels in adults (51).

All covariate and control variables were measured at the initial interview. Demographic variables included age, sex, and marital status. Age was measured continuously in years, sex had two levels including “male” and “female,” and marital status had four levels including “married or living as married,” “divorced or separated,” “never married,” and “widowed.” Although historically conflated with biological sex assigned at birth, sex is a social construct shaped by myriad sociological and political factors. The NSHAP does not ask about biological sex assigned at birth but simply asks, “I am required to ask you the following: are you male or female?” We acknowledge that, although a binary representation of sex is common, it does not capture the continuum and potential fluidity of sex identity. Self-reported educational attainment was used as a proxy for socioeconomic status including the levels, “less than high school,” “high school diploma or equivalent,” “some college or vocational school,” and a “bachelor’s degree or greater.”

Health variables included smoking, alcohol consumption, waist circumference, presence of cardiometabolic disease, and depressive symptoms. Both smoking and alcohol consumption were self-reported, and smoking behavior included the following levels: “nonsmoker” and “current smoker.” The alcohol consumption variable was a combination of two questions including whether a participant currently drinks alcoholic beverages (“yes,” “no”) and the number of alcoholic beverages one consumes per week. If participants responded “no” to being a current drinker, they were coded as “0,” whereas those participants who reported being a current drinker were given their reported number of alcoholic beverages consumed per week. Waist circumference was measured with a tape measure in inches (40). Depressive symptoms were measured using an 11-item version of the Center for Epidemiologic Studies Depression Scale, Revised, which is a scale for depressive symptoms and has been validated in older populations (52). An example item is as follows: “During the past week, I felt that everything I did was an effort.” Respondents may endorse a 4-point Likert scale ranging from 1 to 4, with 1 = “rarely or none of the time,” 2 = “some or a little of the time,” 3 = “occasionally or a moderate amount of time,” and 4 = “most of the time.” This scale displayed adequate internal consistency in the sample total and across groups (total Cronbach α = .80; Hispanic/Latino(x) α = .84; non-Hispanic African American/Black α = .79; NHW α = .79).

Statistical Analyses

All data preparation and statistical analyses were conducted using R Statistical Software version 4.0.3 (53). The primary outcome, wave 2 hs-CRP, was log transformed to facilitate normally distributed model residuals in multiple, general linear regression models with Gaussian links. Wave 2, log-transformed hs-CRP was regressed on the interaction between network density and race-ethnicity, their main effects, and wave 1 hs-CRP. Models were adjusted for the following demographic characteristics: age, sex, marital status at waves 1 and 2, and educational attainment. Smoking behavior, the interaction of smoking behavior by wave 1 hs-CRP, waist circumference, presence of cardiometabolic disease, alcohol consumption, and depressive symptoms were included in all models as potential health confounds. All models were adjusted to account for the probability of selection, with poststratification adjustments for nonresponse. Approximately 8.1% of respondents in this study sample were lost to follow-up at wave 2. A missing mechanisms analysis was conducted to ascertain predictors of missingness. Variables associated with missingness at wave 2 were included in all models, including depressive symptoms and alcohol consumption.

Sensitivity Analysis

Three sensitivity analyses were performed. Because marital status may be associated with both network density and hs-CRP, it was included in all adjusted models as a potential confound. However, because marital status is commonly considered a social network variable on its own, we conducted a sensitivity analysis with marital status excluded from models to assess whether the addition of this variable biased our results. We also assessed whether our results changed when controlling for the potential interaction of marital status and network density on 5-year hs-CRP. In addition, previous research has demonstrated that sex also influences social integration with women having larger social networks than men (54). Thus, we also controlled for the interactive effect of sex by network density to assess whether our results changed.

RESULTS

Adjusted participant demographics across race-ethnicity are presented in Table 1. The sample was 54.4% female sex and reported an average age of 69.2 years. The sample was mostly NHW (66.9%), followed by non-Hispanic Black/African American (22.3%), and lastly Hispanic/Latino(x) (10.8%). Most participants reported being married or coupled (59.4%) and having completed some college (31.8%). Average network density (potential range, 0–1) was significantly higher in Hispanic/Latino(x) older adults (M = 0.62, standard error [SE] = 0.04; b = 0.16, se = 0.04, 95% confidence interval [CI] = 0.11–0.21, p < .001) when compared with NHW older adults (M = 0.45, SE = 0.01) and with non-Hispanic Black/African American older adults (M = 0.53, SE = 0.03; b = 0.11, se = 0.03, 95% CI = 0.05–0.16, p < .001). Likewise, non-Hispanic African American/Black older adults had significantly greater network density when compared with NHW older adults (b = 0.08, se = 0.03, 95% CI = 0.02–0.14, p = .002). The range of network density for all groups was 0 to 1. Network density was greater in male- versus female-identified older adults (b = 0.10, se = 0.02, 95% CI = 0.06–0.13, p < .001), and older adults with less than a high school degree had the highest network density (M = 0.60, SE = 0.03) when compared with all other educational attainment levels (all b values >0.06, all 95% CIs between 0.01 and 0.10). High-sensitivity CRP was significantly greater at baseline in non-Hispanic African American older adults (M = 5.16, SE = 0.91) when compared with both NHW older adults (M = 2.59, SE = 0.29; b = 1.68, se = 0.62, 95% CI = 0.47–2.89; p = .007), and Hispanic/Latino(x) older adults (M = 2.82, SE = 0.41; b = 1.52, se = 0.64, 95% CI = 0.26–2.77, p = .016). Married or coupled older adults (M = 0.60, SE = 0.01) had the highest network density when compared with older adults reporting other marital statuses (all b values >0.06, all 95% CIs between 0.01 and 0.11).

TABLE 1 - Descriptions and Summary Statistics for Substantive Variables Total (N = 1431) Hispanic/Latinx (n = 156) African American/Black (n = 195) Non-Hispanic White (n = 1080) Mean (SE) a Mean (SE) a Mean (SE) a Mean (SE) a Age, y 69.67 (0.27) 68.45 (0.82) 69.21 (0.84) 70.04 (0.28) Alcohol consumption (drinks per week) 1.32 (0.07) 0.84 (0.19) 0.45 (0.10) 1.65 (0.09) Cardiometabolic disease b, % No 63.95 61.68 51.52 67.88 Yes 36.05 39.32 48.48 32.12 Depressive symptoms (CES-D-11) 16.13 (0.16) 17.01 (0.51) 16.55 (0.50) 15.83 (0.17) Education status, % Less than high school 20.07 56.29 28.89 10.27 High school diploma/equivalent 24.78 8.98 26.10 27.72 Some college/vocational school 31.80 25.73 28.37 33.94 Bachelor’s degree or greater 23.35 9.00 16.65 28.07 Sex, % Male 45.61 47.70 32.37 48.61 Female 54.39 52.30 67.63 51.39 High-sensitivity C-reactive protein 3.08 (0.27) 2.82 (0.41) 5.16 (0.91) 2.59 (0.29) Network density 0.49 (0.01) 0.62 (0.03) 0.50 (0.03) 0.46 (0.01) Smoking behavior, % Current 14.42 11.45 25.01 12.29 Nonsmoker 85.58 88.55 74.99 87.71 Wave 1 marital status, % Married or living as married 59.44 61.04 35.29 65.36 Divorced or separated 13.41 12.42 29.50 9.44 Never married 2.92 2.10 6.19 2.25 Widowed 24.14 24.44 29.02 22.95 Wave 2 marital status, % Married or living as married 53.45 55.28 33.72 58.22 Divorced or separated 12.73 13.48 26.16 9.07 Never married 2.91 2.66 6.07 2.14 Widowed 30.09 28.57 34.05 30.57

SE = standard error; CES-D-11 = Center for Epidemiologic Studies Depression Scale, Revised.

All measures represented were measured at wave 1 (baseline) unless otherwise noted.

a Means and standard errors were weighted to adjust for the probability of selection and nonresponse.

b Cardiometabolic disease is a binary variable where 1 = a participant reported “yes” to having at least one of the following: myocardial infarction, heart failure, leg angioplasty, stroke, or diabetes, and 0 = reporting “no” to any of the cardiometabolic conditions.

Results detailing hypotheses tests are included in Table 2. There was no main effect of network density on 5-year hs-CRP. Next, the interaction between network density and race-ethnicity was modeled and found to be statistically significant (Wald χ2(2, 1242) = 3.31, p = .037). Simple slopes analyses revealed that Hispanic/Latino(x) older adults with high network density (+1 standard deviation above mean) had significantly lower hs-CRP levels when compared with Hispanic/Latino(x) older adults with low (−1 standard deviation below mean) network density (b = −0.73, se = 0.31, 95% CI = −1.33 to −0.13, standardized β = −0.16, p = .018), and this within-group difference was significantly greater than the within-group difference in NHW older adults (b = 0.89, se = 0.36, 95% CI = 0.19–1.59, standardized β = −0.16, p = .013). Network density did not vary within NHW or non-Hispanic African American/Black older adults. See Figure 1.

TABLE 2 - Main Effects, Conditional Effects, on Wave 2 hs-CRP Main Effects Conditional Main Effects With Race/Ethnicity by Density Interaction χ 2(2, 1242) = 3.31; p = .037 Unstandardized Standardized p Unstandardized Standardized p b (se) 95% CI β b (se) 95% CI β Network density by race/ethnicity (NHW) — — — — — — Hispanic/Latino(x) — — — −0.89 (0.36) −1.59 to −0.19 −0.16 .013 Non-Hispanic Black — — — 0.08 (0.48) −0.85 to 1.01 0.01 .866 Network density −0.04 (0.16) −0.22 to 0.54 −0.01 .796 0.16 (0.19) −0.22 to 0.54 0.03 .414 Race/Ethnicity (non-Hispanic White) — — — — — — Hispanic/Latino(x) −0.02 (0.12) −0.25 to 0.20 −0.01 .829 0.47 (0.23) 0.03 to 0.92 0.12 .038 Non-Hispanic Black 0.15 (0.13) −0.09 to 0.40 0.04 .218 0.09 (0.29) −0.48 to 0.66 0.03 .753 Wave 1 hs-CRP 0.14 (0.03) 0.01 to 0.07 0.18 <.001 0.14 (0.03) 0.01 to 0.07 0.18 <.001 Age 0.01 (0.01) −0.01 to 0.02 0.04 .362 0.01 (0.01) −0.01 to 0.02 0.04 .381 Sex (male) −0.32 (0.09) −0.49 to −0.15 −0.14 <.001 −0.31 (0.09) −0.48 to −0.14 −0.13 <.001 HS status (completed HS) — — — — — — Less than HS 0.21 (0.13) −0.03 to 0.46 0.07 .089 0.24 (0.13) −0.01 to 0.48 0.08 .058 Some college 0.09 (0.10) −0.10 to 0.29 −0.02 .353 0.11 (0.10) −0.08 to 0.30 0.04 .268 Bachelor’s+ −0.05 (0.10) −0.25 to 0.14 0.09 .583 −0.04 (0.10) −0.23 to 0.16 −0.01 .704 Wave 1 marital status (married) — — — — — — Divorced/separated 0.07 (0.20) −0.32 to 0.47 0.02 .715 0.10 (0.20) −0.29 to 0.50) 0.03 .607 Never married −0.19 (0.22) −0.63 to 0.25 −0.03 .390 −0.25 (0.24) −0.72 to 0.22 −0.03 .305 Widowed −0.01 (0.14) −0.30 to 0.27 −0.01 .917 −0.01 (0.14) −0.28 to 0.27 −0.00 .969 Wave 2 marital status (married) — — — — — — Divorced/Separated −0.03 (0.21) −0.44 to 0.38 −0.01 .872

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