Social Support Definition
In general, social support refers to the various ways in which individuals aid others. Social support has been documented as playing an important and positive role in the health and well-being of individuals. To receive support from another, one must participate in at least one important relationship. However, social support has often been summarized as a network of individuals on whom one can rely for psychological or material support to cope effectively with stress. Social support is theorized to be offered in the form of instrumental support (i.e., material aid), appraisal/informational support (i.e., advice, guidance, feedback), or emotional support (i.e., reassurance of worth, empathy, affection).
Perceived and Conditional Social Support
Perceived social support is support that an individual believes to be available, regardless of whether the support is actually available. Perception of support may be a function of the degree of intimacy and affection within one’s relationships. Compared with actual support, perceived support may be just as important (and perhaps more so) in improved health and well-being. Actually, perceived support appears to correlate more closely with health status than does actual social support. Similar to actual support, perceived support may heighten the belief that one is able to cope with current situations, may decrease emotional and physiological responses to events, and may positively alter one’s behavior.
Conditional support is defined as one’s expectation of receiving support only after fulfilling certain expectations or requirements. Conditionality of support is correlated with actual support. For example, those who offer little support will only be supportive given the fulfillment of certain expectations.
Buffering and Direct Effects Hypotheses
Social support is theorized to affect health through one of two routes: (1) an indirect, buffering, or mediational route and (2) a direct, main-effects route. The stress-buffering hypothesis has been more frequently studied than the main-effects hypothesis. The stress-buffering hypothesis asserts that an individual’s social network supplies the individual with the resources needed to cope with stressful events and situations. Accordingly, the beneficiary aspects of support are only seen during stressful periods. That is, the stress-buffering hypothesis posits that social support tends to attenuate (weaken) the relationships between stressful life events and negative physical or psychological difficulties, such as cardiovascular disorders and depression. In addition, proponents of the stress-buffering model believe that support will only be effective when there is good support-environment fit (i.e., type of support provided matches the situational demands). For example, having someone offer empathy and reassurance will be helpful when a person has lost a loved one, but receiving empathy may be useless when one is facing stresses associated with financial difficulties.
Conversely, the main-effects hypothesis postulates that social support is beneficial whether one is going through a stressful event or not. The main-effects hypothesis asserts that the extent of an individual’s participation in the social network plays a vital role in the degree of social support benefits. In other words, there is a direct monotonic link between social support in one’s social network and well-being (i.e., the more support, the greater one’s well-being).
A related concept to social support is social integration. Social integration is defined as an individual’s involvement in a wide variety of social relationships. Social integration can also refer to the quality of the social relationship. For example, negative social relationships could have negative effects on health, whereas positive social relationships and interactions usually have a beneficial effect on health and well-being. Previous research has demonstrated that social integration tends to be a main effect. That is, one’s relationships with others may provide multiple avenues of information to influence health-related behaviors.
Social Support and Stress
The presence of a support network has been found to reduce the negative effects of stress. The support of one’s social network can act as a buffer to stress in many ways. For example, individuals in one’s support network can offer less threatening explanations for stressful events (e.g., instead of being called into the boss’s office to be fired, perhaps it is to be asked to head a special committee instead). A positive social support network can also increase an individual’s self-esteem and self-efficacy. For example, effective coping strategies may be suggested (e.g., a list of pros and cons or a priority list). In addition, the support network may suggest solutions to current problems or stressors being faced. Having a support group can also alter perceptions of the stressor by decreasing the perceived importance of the stress. Furthermore, having a supportive group of people surrounding a person can result in increased positive behaviors such as more exercise, proper rest, and better eating habits. Likewise, interactions with others may help distract attention from the problem.
Strong social networks can buffer against social pain (e.g., loss of a loved one, betrayal, exclusion) as well as buffer against negative aspects of other relationships. For example, widows with a confidant (someone to talk to about personal things) were less depressed than were widows without a confidant. One caveat to this buffering effect is that for support to buffer the effects of stress, the supporter cannot also be a source of conflict or additional stress. As such, having a strong and stable support network may lessen the negative effects of stress. In addition, support is associated with adaptive coping to stressful events and greater protection from the negative effects of stress.
Social Support and Health
Social support also has important effects on one’s health and well-being. Overall, support has been linked with good health and well-being as well as improved adjustment to specific illnesses, such as cardiovascular disorders and cancer. For example, having a strong support network has been correlated with lower mortality rates, less depression, better adherence to medical treatment, greater health-related behaviors (e.g., lower rates of smoking), maintenance of health behaviors, lower incidences of cardiovascular disorders, and improved adjustment to breast cancer. Furthermore, social support has been linked to adaptation to surgery. That is, patients who had a social support network received lower doses of narcotics, displayed less anxiety, and were released from the hospital sooner than were individuals who had no type of social support.
Conversely, lack of social support has been associated with increased anxiety and depression, an increase in cardiovascular problems, feelings of helplessness, and unhealthy behaviors (e.g., sedentary lifestyle, habitual alcohol use). For example, a lack in parental support predicted potential increases in depressive symptoms and onset of depression in adolescent girls. That is, girls who had very little to no support from their parents were more likely to develop depression than were girls who had parental support. In addition, females reporting low levels of perceived support also have more eating problems than do females reporting high levels of support.
Social Support and Self-Esteem
Researchers have suggested that social support is one of the key elements that influence self-esteem, especially the support of one’s parents early in development. Perceived support, rather than actual support, has been most frequently examined in relation to self-esteem. Researchers have found that the best predictor of self-esteem in adolescents is the amount of perceived social support from their classmates and the degree of parental approval they receive. In other words, an individual’s perceptions of support tend to influence his or her reports of self-esteem. Therefore, the more support one believes he or she is receiving, the higher his or her self-reported self-esteem. Furthermore, social support moderates the level of self-esteem depending on the degree of competence in an area. In other words, people who are highly competent in an area but receive little support report lower levels of self-esteem than do people who are highly competent but receive a lot of social support. In addition, the higher the degree of conditional support, the lower one’s self-esteem will be.
Negative Aspects of Social Support
Although the benefits of social support are well known, there may also be negative aspects. For example, a difference in the desired support and actual support received can result in poorer psychosocial adjustment in breast cancer survivors. Among older adults, too much social support can heighten the negative impact of stress, perhaps by eliciting feelings of incompetency, lower self-esteem, and less self-control. In addition, being the provider of social support may take a toll on the providers’ physical health, psychological well-being, and emotional resources. The act of providing support, especially over a long duration, may be taxing because of the amount of emotional, financial, and mental resources that must be made available to provide such support.
Attachment Style and Social Support
Adult attachment style has been consistently linked to individual differences in actual and perceived social support. The relative quality of support caregivers provide young children is believed to influence how they perceive themselves and others in the future. In other words, internal working models that involve expectations about whether others will provide support develop. Research has found that adults with secure working models are more likely to believe they will receive support when needed and are more satisfied with the support they receive compared with adults with insecure working models. In addition, secure attachment has been positively associated with seeking social support and providing support to others.
Personality and Social Support
Evidence supports a link between Big Five personality traits (i.e., Extraversion, Agreeableness, Conscientiousness, Neuroticism, Openness to Experience) and social support. Specifically, there appears to be a reciprocal relationship between personality characteristics and support. Personality traits likely influence relationships (and thus support and perceptions of support). In turn, support will affect relationships. As such, changes in personality characteristics have been positively related to changes in perceptions of support.
Agreeableness and Extraversion are two dimensions that have been previously related to interpersonal behavior. For example, Agreeableness has been linked to interpersonal behaviors reflecting a need to maintain positive relations with others. Consequently, Agreeableness has been found to be most strongly associated with support and perceived support. Research has shown that Agreeableness positively predicts the amount of support received. Furthermore, providing job-related support mediates the relationship between Agreeableness and received job-related support. Similarly, Extraversion has been linked to support in non-job-related and positive job-related events. Extraversion and received job-related support are mediated by job-related support provided. In addition, Extraversion plays a role in the perceived support received by children from parents, but not vice versa.
Gender Differences in Social Support
Much of the early research in gender differences of social support used self-report measures and found that women are more skillful providers of support than are men. For example, wives affirm their husbands at a greater rate than husbands affirm their wives and more frequently offer support in post-stress situations than husbands offer. In addition, wives will complete more household chores (and thus relieve some stress and pressure) when the husband has had a stressful workday. Studies observing support behavior (i.e., observing supportive behavior rather than self-report measures) among marital couples have not found these gender differences and instead find that husbands and wives offer comparable support to one another.
Recent research indicates that the skill of providing social support is similar among husbands and wives. It has been suggested that the key distinction in previously found gender differences lies in when spouses offer support. For example, wives offer greater amounts of support when their husbands are experiencing greater stress whereas when wives experience increased stress, husbands do not necessarily offer greater support. In other words, women are more likely to provide greater support during severely stressful times than are men.
Evidence indicates that social support may differentially affect men and women. For example, widows with support experienced improved quality of life, greater well-being, and increased self-esteem, whereas these elements were negatively correlated with received social support among widowers. Support received by men can be moderated by their desire to be independent. Men who have a strong desire to be independent are more likely to react negatively to social support than are men who do not have a strong desire to be independent or who desire to be dependent. In women, the influence of social support does not appear to be contingent on the desire to be independent.
Culture and Social Support
A possible determinant in the decision to seek or solicit social support may be one’s culture or the norms that govern that culture. For example, individuals in Eastern cultures are less likely to solicit social support from their social network than individuals in Western cultures are. This cultural pattern seems counterintuitive since Eastern cultures tend to be collectivistic and emphasize interdependence, whereas Western cultures tend to be individualistic and emphasize independence. It would seem as though individuals in collectivistic cultures would be the ones to seek and solicit help from their social support network. However, research has shown that the opposite is true. That is, individuals in individualistic cultures are those who are soliciting help from their social support network. The underlying reason for this counterintuitive pattern may be the result of cultural norms, such as cultural norms that discourage the use of a social support network when solving problems and coping with stress.
Workplace Social Support
The amount of social support one receives from others in the workplace depends on numerous factors such as social competence, reciprocity relationships, and job commitment. For example, individuals who are socially competent tend to receive a greater amount of emotional and instrumental support from coworkers than do individuals who are not as socially competent. However, many studies show that an individual’s support network is usually a network of people outside of his or her job such as family members, spouses, and so forth. In any case, support given in the workplace positively predicts support received.
Social support has also been shown to moderate the relationship between long work hours and physical health symptoms. In other words, physical health tends to decrease when an individual has long work hours and lacks social support. Conversely, individuals who have a social support network tend to be buffered against the adverse effects of longer working hours.
Social Support Influences
Perceived social support and actual social support are both influential in a multitude of facets in one’s life. Social support can have either a direct (or main) effect or a buffering (or mediation) effect on one’s health. The influence of social support can be seen widely from an effect in the workplace to intimate relationships. In addition, social support has effects on one’s health, ability to handle stress, and self-esteem level. Furthermore, one’s personality, cultural background, and gender may influence or moderate the effects of stress.
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Evaluating the buffering vs. direct effects hypotheses of emotional social support on inflammatory markers: The Multi-Ethnic Study of Atherosclerosis
Briana Mezuk, PhD,1Ana V. Diez Roux, PhD MD,2 and Teresa Seeman3
4Department of Epidemiology and Community Health, Virginia Commonwealth University
5Center for Integrative Approaches to Health Disparities, University of Michigan School of Public Health
6School of Medicine, Division of Geriatrics, University of California – Los Angeles
Corresponding author: Briana Mezuk, PhD, Virginia Commonwealth University School of Medicine, Department of Epidemiology and Community Health, PO Box 980212, Richmond, VA 23298, ude.ucv@kuzemb, Phone: 804-628-2511, Fax: 804-628-2510
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Social support is associated with cardiovascular disease mortality, however the physiologic mechanisms underlying this relationship remains unspecified. This study evaluated the association of social support with inflammatory markers associated with cardiovascular risk: C-reactive protein (CRP), interleukin-6 (IL-6), and fibrinogen. We evaluated two competing models of the support-inflammation relationship: first, that low social support is directly associated with inflammation, and second, that high support acts to buffer the effect of stress on inflammation. Using data from the baseline interview of the Multi-Ethnic Study of Atherosclerosis (N = 6,814, 53% female, age 45–84 years) we assessed the independent and interacting associations of social support and stress with inflammation. Social support was measured by the Emotional Social Support Index. Stressors in multiple domains (work, family, finances, interpersonal) were assessed. Serum CRP, IL-6, and fibrinogen were analyzed from fasting samples using high-sensitivity assays. Multivariate linear regression, including models stratified by gender and age group (45 – 64 and 65 – 84 years), was used to assess the direct and buffering relationships between social support, stress, and inflammation. In bivariate analyses low social support was associated with higher levels of all three markers. In adjusted models, low support was associated with higher lnCRP (B: 0.15, 95% CI: 0.01, 0.30) among men but not women. High social support buffered the relationship between stress and CRP among middle-aged women only (P for interaction 0.042). Overall, social support was only modestly associated with inflammation in this relatively healthy sample, and these relationships varied by age and gender.
Keywords: social support, inflammation, aging, gender differences
Investigations of the interrelationships between the social environment and health have established that low social support, poor social integration and social isolation are associated with increased mortality, particularly from cardiovascular disease (CVD) (Berkman et al., 2003; Brummett et al., 2001; Frasure-Smith et al., 2000). Despite this epidemiologic evidence, the physiologic mechanisms underlying these relationships remain unspecified (Berkman et al., 2003; Knox & Uvnas-Moberg, 1998). Several researchers have speculated that alterations in immune function may be a mechanism by which psychosocial exposures, including social support, affect health. In particular, low social support has been associated with elevated levels of circulating inflammatory markers, including cytokines (e.g., interleukin-6 (IL-6), TNF-α), acute phase proteins (e.g., C-reactive protein), and clotting factors (e.g., fibrinogen) (Seeman, Berkman, Blazer, & Rowe, 1994; B. N. Uchino, Holt-Lunstad, Uno, Betancourt, & Garvey, 1999) that have been implicated in risk of CVD. However, not all studies have reported a significant association between social support and systemic inflammation (McDade, Hawkley, & Cacioppo, 2006); and even in those instances where support is associated with inflammation, it is unclear whether this relationship is due to a direct (i.e., independent) influence on physiology, or if support simply buffers (i.e., moderates) the effect of negative experiences (e.g., daily hassles, caregiving, stressful life events) which have direct effects on physiology (Cohen & Wills, 1985).
An integrative framework of the ways social experiences influence health should address the potential that the relationship between social support and physiologic indicators such as inflammation may vary by age and sex (Seeman and Crimmins 2001). As social roles evolve over the life course (i.e., marriage, parenthood), the influence of social experiences on health may also change. As with other psychosocial characteristics, social support may have cumulative effects over time, as well as acute effects in the context of events that affect social life (i.e., divorce, retirement) (Uchino et al. 1999). Also, many aspects of the receipt and provision of social support vary by sex (i.e., women are more likely to experience widowhood and are more likely to be caretakers than men) (Moen, 2001), and thus the implications for social relations to health may likewise differ for men and women (Ajrouch, Blandon, & Antonucci, 2005) Consistent with this general framework, there is suggestive evidence that the physiologic correlates of social integration and support vary by age and gender (Ford, Loucks, & Berkman, 2006; Hughes, 2007). For example, Ford and colleagues (2006) reported that low social integration was associated with elevated C-reactive protein among older men, but not among women or younger men (Ford et al., 2006). Loucks and colleagues (2006) also reported a significant association between CRP levels and social integration among older men but not older women (Loucks, Berkman, Gruenewald, Seeman 2006). However, relatively few studies have systematically examined variation by age and gender in this relationship, and most have only examined a single indicator of immune function. Thus, a systematic investigation of whether the relationship between social support and inflammatory indicators of CVD risk varies by age and gender is warranted.
The goal of this paper is to explore the relationship between social support and three markers of inflammation that have been implicated in CVD, interleukin-6, fibrinogen, and C-reactive protein, using the Multi-Ethnic Study of Atherosclerosis (MESA). The MESA sample was free of clinical atherosclerotic disease at baseline, and thus it is well-suited for examining the relationship between social support and physiologic changes isolated from the confounding effects of pre-existing CVD that may mask true associations or create spurious ones. While alterations in these inflammatory markers may not have immediate clinical significance, they may be early indicators of cardiovascular disease risk.
We investigated two main questions: (1) Is low social support directly associated with these inflammatory markers? and (2) Does high social support buffer the relationship between stress and inflammation? We hypothesized that if buffering is predominant, the association between stress and inflammation will be stronger among those experiencing lower social support than among those experiencing higher social support. However, if the direct model is predominant, the association of chronic stress with inflammation will not vary by level of support (and the association of social support with inflammation will not vary by stress level). In addition, we investigated whether these associations varied by age and gender.
MESA is an on-going population-based multi-site study of the predictors of subclinical cardiovascular disease. Participants aged 45–84 years and free of clinical CVD at baseline (e.g., never experienced a heart attack, stroke, transient ischemia attack, heart failure, angina, atrial fibrillation, or cardiovascular procedures) were recruited from six study sites (Baltimore City and Baltimore County, MD; Chicago, IL; Forsyth County, NC; Los Angeles County, CA; New York City, NY; and St. Paul, MN). The final sample was 53% female, 40% non-Hispanic white, 30% African American, 20% Hispanic, and 10% Asian. Details of the sampling design and study procedures have been discussed previously (Bild et al., 2002). This report is restricted to the baseline MESA sample with complete data on the measures of social support, stress, and markers of inflammation (N = 6,153, 90% of the baseline sample). Participants excluded from the analysis (N = 611) were older than those included (mean age 66.0 vs. 61.9 years, p < 0.02), but otherwise did not differ from the remaining sample in terms of race, gender, education, employment, income, marital status, body mass index (BMI), smoking status, or experience of stress (data not shown).
This study was approved by the Institutional Review Board at each site and all participants provided informed consent.
The primary independent variable was perceived emotional social support (ESS), indicated by the Emotional Social Support Index (ESSI, range: 6 – 30, Cronbach’s alpha: 0.88) which consists of six 5-point likert-scored items concerning availability of emotional support (e.g., Is there someone available to you whom you can count on to listen to you when you need to talk? 1 = None of the time, 2 = A little of the time, 3 = Some of the time, 4 = Most of the time, 5 = All of the time), with higher values indicating more available emotional support (ENRICHD, 2000; Mitchell et al., 2003). The ESSI has modest correlations with other indices of social support (i.e., Perceived Social Support Scale) (Mitchell et al., 2003). Because exploratory analyses indicated that the relationship between social support and inflammation was non-linear, the summed scale score was categorized to indicate low (score <12), moderate (score 12 – 24) or high (score ≥ 25) levels of ESS based on previous literature on social support and health in later life. In addition, each item was dichotomized as indicating low (score ≤ 2 or below) or moderate/high ESS (score ≥ 3).
Stress was measured by a composite of five items concerning contemporaneous, on-going stressors in five domains (i.e., personal health, health of a friend/relative, work-life, financial matters, and relationships with friends/relatives), with higher values indicating more stressors (Bromberger & Matthews, 1996). Each item that was endorsed was rated on a three-point scale in terms of stressfulness (1 = Not very stressful, 2 = Moderately stressful, 3 = Very stressful) (range: 0 – 5 very stressful events). The scores on this scale were strongly left-skewed, with 66% of the sample reporting only experiencing zero or one very stressful events, and therefore these responses were then combined into a dichotomous variable indicating presence of at least one very stressful event. In addition, to categorize stressors as either recent-onset or long-standing, participants were also asked if each of the stressors endorsed had been going on for 6 months or longer. If a participant responded positively to this duration question for at least on stressor, they were classified as experiencing chronic stress.
The main factors investigated as moderators of the relationship between ESS and the markers of inflammation were gender and age group, dichotomized as middle- age (45 – 64 years, N = 3543) and older adults (65 – 84 years, N = 2648).
Additional factors included as covariates were age (centered on the sample mean, 61.9 years), sex, race/ethnicity (modeled as an indicator variable with non-Hispanic whites as the reference group), educational attainment (dichotomized as at least some college versus high school or less (reference)), employment status (dichotomized as currently working versus other (reference)), annual gross household income (categorized as <$20,000 (reference), $20,000 to <$40,000, $40,000 to < $75,000, and ≥$75,000), and marital status (categorized as current married (reference), divorced/separated, never married, and widowed). Three additional factors known to influence inflammatory markers, current smoking status (with former/never smoker as the reference), BMI (kg/m2), and number of alcohol drinks per week were included. Two health conditions, hypertension and diabetes, were also included. Hypertension was dichotomously indicated as systolic blood pressure ≥ 140 mm Hg or diastolic ≥ 90 mm Hg from the average of three resting blood pressure readings, or use of antihypertensive medications. Diabetes was determined by the American Diabetes Association 2003 fasting glucose criteria (≥ 7.0mmol/L) or use of insulin or other hypoglycemic medications (American Diabetes Association, 2006). Consistent with previous MESA reports using these inflammatory markers, recent infection status was dichotomously coded based on self-report of cold or flu, sinus infection, urinary tract infection, tooth infection, bronchitis, or pneumonia in the preceding two weeks and accounted for in the regression models (Ranjit et al., 2007). Use of non-steroidal anti-inflammatory drugs (NSAIDs) was also recorded.
All variables were assessed at the baseline MESA interview concurrently with the measurement of serum inflammatory markers.
The primary outcomes were three markers of inflammation, interleukin-6 (IL-6, pg/mL), C-reactive protein (CRP, mg/L), and fibrinogen antigen (mg/dL) which have been shown to be associated with risk of cardiovascular morbidity and mortality. We conducted separate analyses with each marker as an evaluation of the robustness of the relationships to inflammation more generally. The standardized procedures for the collection, processing, shipping, and storage of blood samples have been previously described (Bild et al., 2002). Fasting venous blood samples were taken from participants at baseline and processed at a centralized laboratory. IL-6 was measured using ultrasensitive enzyme-linked immunosorbant assay (ELISA) (R&D Systems, Minneapolis, MN). High-sensitivity CRP was measured by nephelometry (BNII nephelometer, Dade-Behring Inc., San Mateo, CA). Fibrinogen antigen was also measured by nephelometery (BNII N antiserum to human fibrinogen, Dade-Behring, San Mateo, CA).
Initially we used multivariate analysis of variance (MANOVA) to compare mean levels of the three inflammatory markers by emotional social support and investigate interactions between ESS, gender, and age group. We used the non-parametric Wilcoxon rank-sum test for linear trend to evaluate whether covariates varied across levels of ESS (categorized as low, moderate and high, described above). We used a series of linear regression models to assess the independent association between levels of ESS and the three markers of inflammation as the outcomes. Values of the inflammatory markers were log-transformed in order to normalize their distributions to better meet the model assumptions. High ESS was the most prevalent category (55.2% of the sample), and was used as the reference group for the analyses evaluating the direct associations between low and moderate emotional support and inflammation (Hypothesis 1). In order to evaluate whether high levels of ESS buffered the association between stress and inflammation, we dichotomized support as high versus moderate/low, with the latter as the reference group (Hypothesis 2). We evaluated the statistical significance of the interaction between this dichotomous indicator of high ESS with the dichotomous indicator of stress (both recent onset and chronic) in order to determine whether the relationship between social support and inflammation varied by exposure to stress.
The initial multivariate regression model was adjusted for age, gender, race/ethnicity, educational attainment, income, employment status, and marital status. The second model was additionally adjusted for additional behavioral and biomedical risk factors for inflammation including smoking status, alcoholic drinks per week, body mass index, hypertension, diabetes, NSAID use, and recent infection status. We also conducted post-hoc sensitivity analyses by (1) adjusting for depressive symptoms as indicated by the Centers for Epidemiologic Studies Depression (CESD) scale (Radloff 1977; Ranjit et al., 2007); (2) adjusting for self-reported arthritis; and (3) excluding participants who reported a recent infection from the analysis, in order to better account for residual effects these exposures may have on inflammation. We examined whether the direct and stress-buffering association between support and inflammation varied by age and gender in stratified analyses. Any substantial differences were tested by including appropriate interaction terms in the regression models. All analyses were conducted using STATA v.9 software (StataCorp, College Station, TX). All p-values refer to two-tailed tests.
The sample overall reported high levels of emotional social support, and level of ESS was similar for men and women (M = 24.7 (SD = 5.2) for men, M = 23.8 (SD 5.2) for women out of a possible score of 30). Approximately one-third of the sample reported experiencing a very stressful event, whether recent onset or chronic. Women reported substantially more recent onset (M: 1.35 vs. 1.05, p<0.001) and chronic (M: 1.21 vs. 0.95, p<0.001) stress than men. Lower levels of support were associated with younger age, being male, having lower household income, marital status, being a current smoker, and prevalence of both recent onset and chronic stress. The three inflammatory makers were moderately correlated with each other (r2 = 0.41 to 0.46, all p < 0.001). Mean levels of all inflammatory markers were higher among those reporting low ESS relative to high, although this pattern was only statistically significant for fibrinogen (Table 1). Mean levels of inflammatory markers were higher in women than in men and increased with age.
Participant characteristics by emotional social support, Multi-Ethnic Study of Atherosclerosis (2000 – 2002)
MANOVA indicated no relationship between the continuous measure of emotional support and the three inflammatory markers. However, levels of the markers did vary according to the categories of low, moderate, and high levels of ESS (F = 2.42, p<0.024), consistent with the exploratory analysis indicating the relationship was non-linear. Interaction terms between ESS levels and gender and ESS and age were not statistically significant (data not shown).
Evaluating the Direct Hypothesis
Bivariate regression indicated that low levels of ESS were associated with elevated levels of all three inflammatory markers in the sample overall (Tables 2 – 4), consistent with the direct hypothesis. After adjustment for demographic and socioeconomic characteristics, low ESS remained significantly associated with elevated CRP and fibrinogen, but not IL-6 (Model 1, Tables 2 – 4). After additional adjustment for health behaviors and biomedical factors, only CRP remained significantly associated with low support (Model 2, Tables 2 – 4). Stratification by sex indicated that the association of ESS with CRP was stronger and more likely to be statistically significant in men than in women (p for interaction 0.039 in fully-adjusted model). Within each gender there was no evidence that the association between low ESS differed significantly by age for CRP, IL-6 or fibrinogen (p for interaction > 0.05 for all markers).
Evaluating the direct model: Mean difference in log-IL-6 by categories of emotional social support
Evaluating the direct model: Mean difference in log-Fibrinogen by categories of emotional social support
We conducted sensitivity analyses to determine whether depressive symptoms, arthritis, or recent infection were strong confounders in the stress-social support relationship. When CESD score was included in the models presented in Tables 3 – 5 the results did not change appreciably, and the interpretation that social support is only weakly directly associated with inflammation was upheld (data available upon request). Neither additional adjustment for arthritis, nor excluding participants who had experienced a recent infection (N = 1,467), substantially influenced the results (data available upon request)
Evaluating the direct model: Mean difference in log-CRP by categories of emotional social support
Evaluating the buffering model: Mean difference in log-CRP associated with emotional social support, chronic stress, and their interaction
Evaluating the Buffering Hypothesis
Stress was consistently associated with elevated levels of all inflammatory markers in main effect models (data not shown). However, there was no support for the stress-buffering hypothesis in the full sample or sex stratified analyses, either in bivariate or multivariable regression models for any of the inflammatory markers (Table 5 shows results for CRP only. The other inflammatory markers revealed similar patterns and are not shown). In age- and sex-stratified analyses, interactions terms were consistently negative, consistent with a buffering, but the magnitude of the heterogeneity was small and it was not statistically significant except in the case of 45–64 year old women. In this group, there was evidence that high ESS buffered the association between high stress and CRP in the fully-adjusted models (p for interaction 0.042). There was no evidence of buffering for the other two markers among middle-age women. Additional analyses focused on chronic stress (lasting 6 months or longer) produced similar results (data not shown).
Sensitivity analysis: Marriage as a proxy for emotional social support
Marriage is a key source of social support, particularly for older adults, and ESS and levels of IL-6, CRP and fibrinogen varied significantly by marital status (all p < 0.001). We therefore conducted a series of post-hoc analyses to evaluate whether marital status moderated the association between stress and inflammation. In multivariate regression analyses, the relationship between stress and inflammation did not significantly differ by marital status in the sample overall, indicated by the non-significant interaction terms between marital status and stress (data not shown). Similar results were obtained in the age- and sex-stratified analyses.
The main finding from this study is that perceived emotional social support has little influence, either through direct or stress-buffering pathways, on inflammatory markers in this diverse sample of adults free of prevalent CVD. These findings are broadly consistent with recent reports that indicate only modest associations between perceived social support and integration with inflammation after accounting for perceived stress (McDade et al., 2006). There was modest evidence that the relationship between ESS and inflammation differed for men and women and by age. Among men, there was evidence to support the direct hypothesis of social support but only for CRP. In adjusted models there was evidence that high ESS buffered the association between high stress and CRP, but only for middle-age women. However, because these relationships were only observed with one of the three inflammatory markers examined, they should be interpreted with caution.
In fully-adjusted analyses, there was no evidence to support either the direct or buffering hypotheses for IL-6 or fibrinogen. The inconsistency in the relationships among ESS and the three inflammatory markers is noteworthy because it suggests that the association between social support and inflammation is not equivalent across physiologic systems. These markers were only moderately correlated, and each has different responsiveness to social stressors (Ranjit et al., 2007) and may be influenced by health behaviors, particularly smoking and obesity, to differing degrees (Ozbay, Fitterling, Charney, & Southwick, 2008; Piché et al., 2005).
These findings are somewhat consistent with previous reports suggesting that the relationship between social support and health differs for women and men over the life span (Akiyama & Antonucci, 1996; Loucks, Berkman, Gruenewald, & Seeman, 2006), but suggest that in adults free from major health problems such as CVD these differences are less pronounced. Several studies have reported gender differences in the associations between social integration with inflammatory markers (Ford et al., 2006; Loucks et al., 2006; Loucks et al., 2006) or measures of cardiovascular activity (Hughes, 2007). In particular, similar to our findings, several previous studies have found a direct association between measures of support or integration and inflammatory markers among men but not women. The reasons for this gender difference are unclear, although there is suggestive evidence that men and women differentially utilize social support as a coping strategy in the face of ongoing stress and may appraise stress differently (Chaplin, Hong, Bergquist, & Sinha, 2008; Gerin, Milner, Chawla, & Pickering, 1995; Unger, McAvay, Bruce, Berkman, & Seeman, 1999). Future research should work towards identifying the specific contexts and points in the life course in which gender differences in social support and health are expected to be most relevant.
The primary strength of this study is the sample composition and measures of inflammation. The MESA sample was free of CVD at baseline, thus reducing the likelihood that poor health status confounded the relationship between inflammation and support (i.e., individuals who report low support may do so because they have limited functioning due to health problems that are themselves associated with inflammation). Data on inflammatory markers were available on over 90% of the baseline sample and samples were collected using a standardized protocol in clinical settings.
The findings should be interpreted in light of the study limitations. Foremost, this study only explored the relationship between systemic inflammation and emotional social support, and it is possible that other aspects of social life, such as caregiving and social integration, which are also associated with morbidity and mortality, are more strongly associated with these markers. For example, a growing body of evidence suggests that perceived loneliness is associated with inflammatory markers (Hawkley & Cacioppo, 2003; Steptoe, Owen, Kunz-Ebrecht, & Brydon, 2004). These contrasting findings indicate that high levels of emotional social support cannot be conceptualized or treated as equivalent to low levels of loneliness (and vice versa) in terms of the relationship to physiology, despite similarities in these constructs. Also, other measures of social support, such as instrumental (i.e., assistance with specific tasks) or provision of support may also be more relevant to inflammation. In addition, the relatively high levels of ESS reported in the sample, and the relatively low variance in the inflammatory markers may have contributed to the failure to detect significant relationships. Finally, the measure of chronic stress may not have captured all meaningful aspects of the stress process that are relevant to health (e.g., we could not examine stress appraisal or coping, nor other aspects of stress exposure including daily hassles). The measure of chronic stress may be confounded with low ESS since some of the events included in this measure referenced social relationships, a salient limitation particularly in light of the cross-sectional nature of the study.
While the finding that ESS was generally not associated with inflammation, in either the directly or stress-buffering models, is surprising in light of the consistent epidemiologic relationships between social support and heath, these results indicate that other mechanisms may underlie the relationship between social support and health (Hawkley & Cacioppo, 2003; B. Uchino, 2006). For example, ESS may operate on health through other pathways such as improved access to services (i.e., having supportive ties may facilitate treatment seeking), through the relationship between ESS and health-related behaviors (i.e., smoking, diet, exercise), via psychological states such as depression, or through stress-linked biological mechanisms not involving inflammation. In addition, other dimensions of social life such as integration and isolation and perceived loneliness may be stronger predictors of inflammation (Ford et al., 2006; Seeman et al., 1994) than the ESS measure we studied.
Overall our results suggest that ESS is modestly associated with levels of CRP in men and that it may buffer the effects of stress in women. Given the large number of comparisons we performed these results need to be confirmed in other large samples. Consistently with prior work, these findings illustrate the utility of examining how factors such as gender and age influence the relationship between social life and health.
This research was supported by the Robert Wood Johnson Health and Society Scholars program and the Michigan Center for Integrative Approaches to Health Disparities, P60 MD002249 funded by the National Center on Minority Health and Health Disparities, and by contracts N01-HC-95159 through N01-HC-95169 from the National Heart, Lung, and Blood Institute. The authors thank the other investigators, the staff, and the participants of the MESA study for their valuable contributions.
List of Abbreviations
|BMI||Body mass index|
|ELISA||enzyme-linked immunosorbant assay|
|MESA||Multi-Ethnic Study of Atherosclerosis|
|NSAID||Non-steroidal anti-inflammatory drug|
|PSS||Perceived social support|
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Competing interests: All authors declare they have no conflicting interests.
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