Das, A., & Nairn, S. (2014). Religious attendance and physiological problems in late life. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, doi:10.1093/geronb/gbu089
Religious Attendance and Physiological Problems in Late Life
Aniruddha Das1,2 and Stephanie Nairn1
1Department of Sociology and 2Centre on Population Dynamics, McGill University, Montreal, Quebec, Canada.
Objectives. This study queried linkages of older adults’ religious attendance with their physiological health.
Method. Data were from the 2005–2006 National Social Life, Health, and Aging Project, nationally representative of U.S. adults aged 57–85 years. Analyses examined associations of religious attendance with biological states, potential gender variations in these linkages, and attenuation by this factor of health effects of spousal loss.
Results. Religious attendance was negatively associated with a system of physiological issues, consistent with miti-gation of multisystemic “weathering.” Linkages were relatively uniform with inflammatory and cardiovascular but not metabolic states and were not significantly different for women than men. Effects of spousal loss on the 2 former sub-systems were attenuated by regular religious attendance—in combined-gender analysis and among women, but not men.
Discussion. Religious attendance may buffer older adults from physiological problems and the health effects of life events such as spousal loss. More intensive analysis is needed to explain differential linkages with specific biological subsystems.
A growing literature on the ecological context of human physiological function connects membership in lower
social strata (race, socioeconomic status) to more multisys-temic “weathering”—stress-induced biological wear-and-tear exerted at least partly through chronically elevated or fluctuating neuroendocrine response (Geronimus, Hicken, Keene, & Bound, 2006; McEwen, 1998; Singer, Ryff, & Seeman, 2004; Sterling & Eyer, 1981). A potential out-come of this biosocial process is socially stratified accelera-tions in senescence (Das, 2013a; Geronimus et al., 2006; McEwen, 1998). A separate literature suggests that espe-cially in late life, when social and personal assets generally decline, religious attendance may play a key role in buffer-ing a person against psychosocial stress (Ellison, Burdette, & Hill, 2009; Koenig, George, & Titus, 2004; Koenig, Pargament, & Nielsen, 1998; Krause, 2008; Lawler-Row, 2010; Pargament, 1997; Schieman, Pudrovska, Pearlin, & Ellison, 2006)—with studies offering conflicting evidence on gender variations in this effect (Bednarowski, 1999; Bradshaw & Ellison, 2010; Cokely et al., 2013; Hintikka et al., 2000; Krause, Ellison, & Marcum, 2002; McFarland, 2010). If so, this protective impact may arguably extend to physiological weathering—both in general, or as triggered by major life transitions, a key process behind late-life health issues (Thoits, 2010; Wheaton, 1990). Due to both data and especially conceptual limitations, these linkages and moderations remain underexplored.
Using data from the 2005–2006 U.S. National Health and Social Life Project (NSHAP)—a nationally representative
probability sample of adult Americans aged 57–85—the present study began to fill these gaps. Three topics were addressed: (a) linkages between religious attendance and a range of inflammatory, metabolic, and cardiovascular states proxying multisystemic weathering; (b) potential gender variations in these associations; and (c) mitigation by religious attendance of elevated weathering risks from spousal loss.
Religious Attendance and WeatheringA large literature links participation in religious services
with better physical and mental health (Buck, Williams, Musick, & Sternthal, 2009; Koenig et al., 2004; Krause, 2008; Levin & Chatters, 2008), especially in late life (Daaleman, Perera, & Studenski, 2004; Koenig et al., 2004; Krause, 2008; Lawler-Row, 2010; Levin & Chatters, 2008). Starting with the work of psychologist Kenneth Pargament (1997), schol-ars have increasingly conceptualized these broad benefits as arising from religion’s stress-mitigating effects. Thus, studies link a strong sense of divine control with lower psychologi-cal distress among older Americans (Schieman et al., 2006) and religious attendance with more self-reported tranquil-ity (Ellison et al., 2009). Such engagement may also foster stress-buffering network connections—with multiple studies indicating that individuals who attend religious services at least once a week receive more social and emotional support (Nooney & Woodrum, 2002; Strawbridge, Shema, Cohen, & Kaplan, 2001; Taylor & Chatters, 1988). This church-based
“social capital” may also enhance psychological resilience and coping-capacity in the face of life challenges (Koenig, George, et al., 1998; Pargament, Koenig, & Perez, 2000; Pargament, Smith, Koenig, & Perez, 1998). This is espe-cially true of in late life, when individuals suffer a gener-alized loss of social and physical assets. Specifically, older adults experience fundamental changes in the structure of both their families and their broader social network. Children leave home, retirement uproots individuals from their social networks at work, parents and elders pass away, and health problems begin impeding social interaction (Hughes, Waite, Hawkley, & Cacioppo, 2004). Accordingly, older women and men strongly connected to church-centered social networks report improved mental health and perceived quality of life—especially in times of poor physical health (Koenig, George, et al., 1998; Koenig, Pargament, et al., 1998).
Despite its stress-buffering implications, linkages between religious attendance and biological weathering remain underexplored. Biodemographic literature (McEwen, 1998; Seeman et al., 2008) suggests weathering pressures on three linked physiological subsystems—inflammatory, meta-bolic (e.g., obesity, diabetic problems), and cardiovascular (e.g., blood pressure [BP], heart rate)—with scattered evi-dence indicating a pathogenic process sequentially cascad-ing through each of these complexes. Thus, multiple studies indicate a pathway from extended psychosocial stress to inflammation (Das, 2013a; McDade, Hawkley, & Cacioppo, 2006; Melamed, Shirom, Toker, Berliner, & Shapira, 2006; Weinstein, Vaupel, & Wachter, 2007)—possibly due to nor-epinephrine-driven gene expression of inflammatory media-tors (Bierhaus et al., 2003; Kiecolt-Glaser, Gouin, & Hantsoo, 2010). Downstream, inflammation has a demonstrated causa-tive role in cardiovascular problems, as well as poor blood sugar control due to insulin resistance (Grundy, Brewer, Cleeman, Smith, & Lenfant, 2004; Yudkin, 2003). More specifically, recently developed high-sensitivity C-reactive protein (CRP) assays suggest that chronic, low-grade inflam-mation (indicated by elevated CRP) is linked to subsequent incidence of cardiovascular disease (Danesh et al., 2000), type 2 diabetes (Pradhan, Manson, Rifai, Buring, & Ridker, 2001), and the “metabolic syndrome” (McDade & Hayward, 2009; Ridker, Buring, Cook, & Rifai, 2003). Studies also sug-gest a direct effect of psychosocial strain on obesity (de Wit et al., 2010) and of obesity on poor blood sugar control, dia-betes, and heart disease (Grundy et al., 2004; Yudkin, 2003). Finally, chronic antecedent stress has been directly linked to blood sugar problems (Calhoun et al., 2009; Lustman et al., 2000), as well as cardiovascular issues such as higher BP (Ariyo et al., 2000; Shinn, Poston, Kimball, Saint Jeor, & Foreyt, 2001) and heart rate (Lampert et al., 2009).
Arguably, if religious attendance in late life is indeed pro-tective against stress, it may also mitigate such pathogenic processes. Consistent with this conjecture, such engage-ment has been linked to a lower prevalence of hypertension (Koenig, George, et al., 1998), as well as lower resting heart
rate (Ellaway & Macintyre, 2006) and composite scores of biological risk (Maselko, Kubzansky, Kawachi, Seeman, & Berkman, 2007). An emerging literature in the anthropology and neuropsychology of religious rituals also suggests that emotionally charged group dynamics, common in highly devout congregations, can have positive neurophysiological and immune system effects—possibly through the produc-tion of endogenous opioid peptides (Frecska & Kulcsar, 1989; Saver & Rabin, 1997; Sosis & Alcorta, 2003). Despite these scattered findings, systematic analysis using nation-ally representative data to examine linkages between reli-gious attendance and specific physiological subsystems remains missing. Accordingly, the following hypothesis was included to examine these connections.
1. Older women and men with more frequent religious attendance will have less elevated inflammatory, meta-bolic, and cardiovascular states.
Next, while the biosocial processes delineated above arguably hold for both women and men, some scattered lit-erature also indicates gender-specific associations. Evidence is relatively uniform on women’s greater religious attend-ance, especially in late life (Balbuena et al., 2013; Koenig, 1999; Krause et al., 2002; Maselko et al., 2007; McFarland, 2010). However, studies offer contradictory findings on gen-der patterns in the health effects of this factor. Some indicate women may be more benefited—whether in terms of men-tal health (Bradshaw & Ellison, 2010; Cokely et al., 2013; Hintikka et al., 2000) or survival (Koenig, 1999; Strawbridge et al., 1997). Moreover, mental health dividends of religious attendance may possibly bypass social support, at least among women—perhaps indicating a more direct effect of subjective beliefs (Hintikka et al., 2000; Koenig, 1999; Maselko et al., 2007; McFarland, 2010). Other studies, in contrast, indicate greater benefits among men (Bednarowski, 1999; Krause et al., 2002; McFarland, 2010)—possibly due to gender differences in the nature of religious participa-tion. Ethnographic research on American women’s religious experiences suggests that they are often simultaneously insiders and outsiders in religious organizations—excluded from authority positions despite their active participation (Bednarowski, 1999). In similar vein, McFarland (2010) argues that religious roles into which women are social-ized emphasize “feminine” traits, such as being obedient, nurturing, and service oriented. The corresponding “cost of caring” may, in turn, make participation in church-centered social activity detrimental to their health. In contrast, men tend to occupy more formal and high-status roles within church organizations. Additionally, in a broader social envi-ronment where men may not be encouraged to express or share emotions, religious attendance can yield a context in which receiving support becomes comfortable. Perhaps for this reason, modest involvement in organizational religiosity decreases depression in men but not for women, and these mental health benefits rise with men’s higher levels of such
engagement. Corresponding physiological patterns remain unexplored. Accordingly, to test gender variations in the weathering implications of religious attendance, the follow-ing hypothesis was included:
2. Linkages between more frequent religious attendance and physiological states will be stronger for older men than for women.
Spousal Loss and Weathering: Mitigation by Religious Attendance?
As noted, biodemographic studies have largely focused on weathering pressures exerted by one’s broad social posi-tion (i.e., stratification by race or class). However, a large and established stress process literature emphasizes the negative psychological effects of life transitions (Butts & Pixley, 2004; Dohrenwend, 2006; Elder, 1985; Gotlib & Wheaton, 1997; Pixley, 2008)—suggesting corresponding physiological sequelae. In other words, those experiencing such events may arguably comprise a distinct “at risk” pop-ulation—with elevated weathering-induced diabetic and cardiovascular morbidity and contracted longevity. Among older adults, the loss of a spouse is perhaps the most impor-tant such turning point. While much of the literature on this life transition has focused on bereavement, the event also entails declines in a range of other assets. Marriages (espe-cially lasting ones) tend to be characterized by longstanding household divisions of labor and investments in partner-specific skills (Becker, 1981; Brines & Joyner, 1999). Apart from the immediate (and possibly transient) “shock” of bereavement, the loss of these assets and investments may also lead to long-term coping pressures and continued stress. Moreover, the event may also induce potentially last-ing financial problems, especially among women (Gadalla, 2008, 2009; Tamborini, Iams, & Whitman, 2009; Ulker, 2009; Wilmoth & Koso, 2002). Similarly, especially among men, it may come with a loss of caregiving. Particularly among older cohorts, such aid is more likely to be pro-vided by women to men than vice versa (Barusch & Spaid, 1989; Kaufman & Taniguchi, 2006; Stone, Cafferata, & Sangl, 1987). Multiple studies have also noted the preva-lence, especially in these cohorts, of “age hypergamy,” or the tendency of women to partner with men several years older than themselves (England & McClintock, 2009; Mahay & Laumann, 2004), who may thus be less physi-cally able at the time of loss and hence more strained by their own caregiving pressures. For instance, mean age at widowhood for NSHAP men was 66 years and for women was 59 years (p < .01). The incidence of this broad array of long-term stressors may explain greater morbidity and mortality rates among those whose partner has died (Carr, 2003; Christakis & Allison, 2006; Elwert & Christakis, 2006; Hughes & Waite, 2009; Keene & Prokos, 2008; Lee, DeMaris, Bavin, & Sullivan, 2001; Lillard & Waite, 1995; Schaefer, Quesenberry, & Wi, 1995; Williams, 2003).
While the negative health consequences of widowhood have been the most extensively studied, evidence sug-gests much the same sequelae with divorce or separation (Johnson, Backlund, Sorlie, & Loveless, 2000; Lillard & Waite, 1995). Apart from the loss of dyadic assets, both the event of, and the time preceding, divorce are likely to be marked by increased stress and relational friction. In a recent study, for instance, Hughes and Waite (2009) examine the effects of marital disruption—whether through divorce or widowhood—on a small set of sum-mary health measures and find that such events may cause long-term damage to health. In addition to such “intra-couple” factors, marriages also tend to be embedded in a network of friends and family members, which may rep-resent a key source of social and emotional support in late life (Carr & Utz, 2002; Elwert & Christakis, 2006). Whether due to grief and consequent social withdrawal or because one is socially connected through one’s spouse, widowhood or divorce may lead to a weakening of ties to this stress-buffering relational web. In turn, both the “pri-mary stressors” of bereavement and lost dyadic assets, and “secondary stressors” represented by these broader social deficits (Pearlin, 1999; Thoits, 2010), may poten-tially trigger weathering. Consistent with these argu-ments, a recent NSHAP-based study (Das, 2013b) finds spousal loss (whether through widowhood or divorce/separation) associated with a broad range of negative mental, metabolic, and cardiovascular states. Moreover, contrary to previous conceptions of loss as a traumatic event with transient effects (Booth & Amato, 1991; Hetherington & Kelly, 2002), physiological issues appear to be more elevated among those longer past the event—perhaps reflecting lasting coping pressures. However, it also finds physiological linkages to be more uniform among all participants and women, than men—arguably suggesting women’s deeper (and unexplained) vulnera-bility to this life transition. Building on this emerging evi-dence, it was conjectured that if religious attendance does indeed protect a person against weathering pressures, it may also mitigate the negative physiological effects of spousal loss—among women if not men. At least for mental states, some small-sample and qualitative stud-ies do suggest such buffering, with religious engagement attenuating depression and anxiety following the loss of a partner—whether through widowhood (Fry, 2001; Woo, Chan, Chow, & Ho, 2008) or divorce (Webb et al., 2010). As among older adults in general, however, the role of this factor in mitigating loss-induced biological problems has yet to be examined. Accordingly, the following hypoth-esis was included to examine this potential buffering:
3. Older adults—especially women—having experienced spousal loss, whether through widowhood or divorce/separation, will have better physiological status if they regularly attend religious services.
To summarize, a large literature demonstrates the psy-chosocial benefits of religious attendance—especially in late life. However, corresponding linkages with stress-generated physiological problems remain underexplored. Moreover, while emerging evidence suggests associations of spousal loss with a range of biological issues—especially among women—no studies have examined mitigation of these problems by religious attendance.
Method
DataData were from the nationally representative 2005–
2006 U.S. National Social Life, Health, and Aging Project (NSHAP). The sample included 1,550 women and 1,455 men aged 57–85, with an oversampling of Blacks, Hispanics, men, and those aged 75–85. In addition to self reports, data included a range of biological indicators
(including blood and saliva samples) collected at the time of interview by nonmedically trained interviewers. The survey had a weighted response rate of 75.5% (Lindau, Schumm, Laumann, Levinson, & O’Muircheartaigh, 2007; O’Muircheartaigh & Smith, 2007). In-home interviews of household-dwelling adults were conducted between July 2005 and March 2006, in both English and Spanish. Most interviewers were experienced personnel given further training by National Opinion Research Center (NORC) at the University of Chicago and remained with the project throughout the interview period. Participant consent was obtained prior to interview. Institutional review boards at the Division of the Social Sciences and NORC at the University of Chicago approved data collection procedures.
MeasuresTable 1 reports summary statistics for all variables used
in the analyses. To minimize feedback to independent
Table 1. Descriptive Statistics for Variables Used in Analyses
Notes. Data for all analyses were from the nationally representative 2005–2006 U.S. National Social Life, Health, and Aging Project (NSHAP). Italicization denotes reference category in subsequent analyses. All estimates are weighted to account for differential probabilities of selection and differential nonresponse. Design-based SEs are given in parentheses. BMI = body mass index; BP = blood pressure; CRP = C-reactive protein; EBV = Epstein–Barr virus antibody titers; HbA1c = hemoglobin A1c.
variables, outcomes were restricted to direct indicators of current physiological status rather than lifetime diagnoses of medical problems. Specifically, seven biomeasures were used to tap inflammatory, metabolic, and cardiovascular states (McEwen, 1998; Seeman et al., 2008). In prelimi-nary analysis (available on request), pairwise correlations among these variables were inconsistent, supporting a need to examine them separately rather than as a summary index. Specifically, of the 21 possible correlations, only 12 were both positive and significant at p less than .05. With the sole exception of the two BP variables, none were higher than 0.25. Moreover, as explained below, linkages of these outcomes with the study’s key predictors also diverged—a conceptually important finding.
Dependent variables.—Inflammation was indicated by CRP and Epstein–Barr virus (EBV) antibody titers—both derived from high-sensitivity assays of dried blood spots col-lected through capillary finger sticks (Williams & McDade, 2009). Due to heavy right skew, raw CRP values were log-transformed. Metabolic status was similarly indexed by two measures, for waist circumference, and poor blood sugar control as indicated by log-transformed hemoglobin A1c (HbA1c)—glycosylated hemoglobin as a percentage of total hemoglobin. As with the two inflammation measures, HbA1c was derived from dried blood spots. Finally, three cardiovascular states were examined—systolic and diastolic BP, in mm Hg and heart rate in beats per minute.
Independent variables.—Baseline associations of religious attendance with physiological states were examined through an ordinal self-report. The exact question wording was, “Thinking about the past 12 months, about how often have you attended religious services?” Responses ranged from 0 (never) to 6 (several times a week). Next, recent findings (Das, 2013b) suggest similar linkages of types of spousal loss (divorce/separation, widowhood) with these health outcomes. Moreover—especially in gender-separate models—cell-size limitations precluded separate examination of specific part-nership categories. Accordingly, mitigation of loss-induced weathering by religious attendance was explored by cross-categorizing any such marital transition (through divorce, separation, or widowhood) with regular religious attendance (once a week or more). Thus, dichotomous indicators were included for (any) spousal loss and regular religious attend-ance and spousal loss and no regular religious attendance, with those currently married/cohabiting as the reference.
Control variables.—A respondent’s age was entered linearly as a continuous variable in all analyses. Gender-combined models also included a dichotomous indicator for being female. Next, race was indicated by a set of dummy variables for Black and Hispanic/other, with non-Hispanic White as the reference category. Seventy-seven percent of women and 70% of men in the Hispanic/other category
were non-Black Hispanics, with the remainder comprised of American Indians or Alaskan natives, Asian or Pacific Islanders, and “other.” Education—proxying greater knowl-edge of health issues as well as long-term socioeconomic status—was an integer score ranging from 1 (less than a high school education) to 4 (a Bachelors degree or more). While NSHAP data included a participant’s self-reported net household assets in the preceding year, this factor was not included as a control variable—partly due to missing data problems. About 12% of NSHAP respondents refused to answer this set of sensitive questions. Moreover, current financial worth was perhaps too susceptible to feedback from health—especially among older adults, with increas-ing health care expenses (Kington & Smith, 1997). Most importantly, as argued above, declines in these assets com-prise a “primary stressor”—one among the broad array of chronic pressures induced by spousal loss—and an espe-cially important factor among women. As such, they are best conceived as a potential mediating factor rather than a confounder—such that netting out this factor would have amounted to overcontrolling. Next, all models also adjusted for any lifetime diagnosis of diabetes or hypertension by a medical doctor, as well as any history of heart failure or attack. In addition, those for the two inflammation out-comes (log CRP, EBV) controlled waist circumference and body mass index (BMI). Finally, all analyses examining mitigation of spousal-loss effects by religious attendance (Tables 5–7) adjusted for a participant’s lifetime number of marriages—ranging from 1 to 3 or more.
Missing data.—NSHAP took a randomized modulariza-tion approach to blood spot collection, to reduce respondent burden while still obtaining population-representative data (O’Muircheartaigh, Eckman, & Smith, 2009). Specifically, a random subsample of 2,494 participants was assigned to this module, with an unweighted final response rate of 82.1%, including losses due to technical difficulties (Williams & McDade, 2009). Given this sampling process, the inflamma-tion (log CRP, EBV) and blood sugar (log HbA1c) indicators were unmeasured for some participants—that is, those not assigned to the blood spot module. However, given the mod-ularization logic (random assignment to the module), these cases were Missing-At-Random, and hence (by design) did not compromise generalizability. Moreover, among those assigned, there were no significant differences between respondents and nonresponders with respect to either demo-graphics (gender, race, ethnicity, age, education, income, or marital status) or basic health status (self-reported mental or physical health or the number of doctor visits in the preced-ing 12 months). Accordingly, no values were imputed.
Analytic StrategyAs noted, to reduce the likelihood of feedback from
health status to independent variables, all outcomes were
restricted to current states. All models adjusted for age, race, and education—with combined-gender analyses also controlling a participant’s gender. Additional health-status controls were added to adjust for potential endogeneity and, more generally, the possibility that observed associa-tions were confounded by prior disease. These included any lifetime diagnosis of diabetes or (separately) hyperten-sion, as well as any history of heart failure or attack. It is acknowledged that to the extent low religious attendance and/or spousal loss indexed long-term patterns influencing the incidence of these conditions, the analyses were over-controlled and yielded conservative estimates. Finally, pre-vious literature reports a strong correlation between obesity and inflammation (Grundy et al., 2004; Yudkin, 2003), sug-gesting that failing to adjust for the former may potentially confound inflammation’s associations with stressors or stress-buffering factors (such as religiosity). Accordingly, as noted, models for both log CRP and EBV additionally controlled waist circumference as well as BMI.
All analyses were through OLS regression models. A first set tested linkages of the two inflammation (Table 2), two metabolic (Table 3), and three cardiovascular (Table 4) outcomes with frequency of religious attendance—for all participants and separately for men and women. Gender dif-ferentials were examined through postestimation Wald tests. Next, mitigation of spousal-loss effects by participation in religious services was examined by first regressing the seven outcomes on loss with and without regular (weekly or higher) religious attendance—with those currently mar-ried/cohabiting as the reference (Tables 5–7). As explained above, combination of divorce/separation and widowhood into a single “spousal loss” category was designed to avoid cell-size limitations and based on previous findings that these two statuses have similar linkages with mental and physiological health (Das, 2013b). Postestimation Wald tests were then used to examine whether the association of loss with each health outcome was significantly differ-ent (at p < .10) for those with regular religious attendance
Table 2. Associations of Religious Attendance With Inflammatory States Among U.S. Adults Aged 57–85: Coefficients (SEs)
All Men Women
Log CRPa EBVa Log CRPa EBVa Log CRPa EBVa
Control variables Agea −0.00*
(0.00)0.20
(0.27)0.00
(0.00)0.31
(0.30)−0.01* (0.00)
0.12 (0.43)
Educationb −0.07*** (0.02)
−3.35 (2.04)
−0.08*** (0.02)
−3.44 (2.54)
−0.07** (0.03)
−2.91 (2.89)
Gender (ref: menc) Womenc 0.26***
(0.04)3.28
(4.85) Ethnicity (ref: Whitec) Blackc 0.23***
(0.05)12.60** (5.34)
0.28*** (0.08)
20.36** (8.23)
0.16* (0.08)
8.70 (8.70)
Hispanic/otherc 0.06 (0.06)
−2.48 (5.88)
0.09 (0.08)
4.75 (8.42)
0.00 (0.10)
−8.94 (9.53)
Diagnosed conditions (lifetime) Diabetesc 0.00
(0.06)−1.65 (4.44)
0.05 (0.09)
−4.17 (5.84)
−0.07 (0.08)
2.00 (8.57)
Hypertensionc −0.01 (0.05)
−1.02 (3.37)
−0.05 (0.07)
−5.25 (4.99)
0.04 (0.07)
4.14 (5.48)
Heart failure or attackc 0.16*** (0.06)
7.36 (7.20)
0.22*** (0.07)
4.15 (7.10)
0.08 (0.11)
10.83 (10.86)
Obesity Waist circumferencea 0.02**
(0.01)0.89
(0.65)0.02*
(0.01)2.52**
(1.07)0.02**
(0.01)−0.26 (0.89)
BMIa 0.02*** (0.01)
0.22 (0.53)
0.01 (0.01)
−0.68 (0.95)
0.03*** (0.01)
0.75 (0.72)
Independent variable Religious attendanceb −0.04***
(0.01)−2.23** (0.96)
−0.03** (0.01)
−2.64** (1.22)
−0.04*** (0.02)
−1.94 (1.47)
N 1,834 1,869 882 902 952 967
Notes. Data for all analyses were from the nationally representative 2005–2006 U.S. National Social Life, Health, and Aging Project (NSHAP). Figures in bold represent associations statistically significant at at least p <.10. All estimates are weighted to account for differential probabilities of selection and differential nonresponse. Design-based SEs are given in parentheses. BMI = body mass index; CRP = C-reactive protein; EBV = Epstein–Barr virus antibody titers.
aContinuous variable.bOrdinal variable.cDummy variable.dAssociation significantly stronger at p <.10 than among other gender, per postestimation Wald test.*p < .10, **p < .05, ***p < .01.
than those below this threshold, relative to those partnered (Harrell, 2001). Given this theoretical focus, these analy-ses were restricted to those married at least once. To avoid endogeneity (feedback from current health to recent marital dissolution), they also excluded those divorced/separated less than 3 years (the 5th percentile for all participants). Those recently widowed were not similarly excluded. Specifically, it is argued that current health status can feed back to recent/temporally proximal marital dissolution (divorce/separation)—for example, by increasing marital stress or a partner’s dissatisfaction in marriage. The same process, however, may not apply to widowhood, since one’s own health is less likely to lead to a partner’s death.
For all tests, and despite the relatively large NSHAP sample, our minimum significance threshold was p less than .10. While a more conservative value (e.g., p < .05) may be optimal where independent variables are continu-ous, such that power is based on the full sample size, all our theoretically relevant predictors were categorical. In Tables 5–7, our (dichotomous) included categories were spousal loss with and without regular religious attendance (relative to married/cohabiting). The important Ns, for each
association, were those of the corresponding “comparison pair”—that is, cell frequencies and overall observations for the particular included category relative to the reference group (Agresti, 2007; Cohen, 1988). As Table 1 reports, the cell proportions for these two included categories—in the full sample—were 12% and 17% respectively. Their frequencies were further whittled down for gender-specific models and (as explained above) further still for variables like (log) CRP and HbA1c, which were modularized in the survey. Similarly, a range of simulation studies indicate that “coarse” ordinal independent variables (e.g., Likert items such as religious attendance in Tables 2–4) reduce statisti-cal power (often dramatically) compared to continuous ones (Martin, 1978; Russell & Bobko, 1992; Russell, Pinto, & Bobko, 1991). A more conservative significance threshold was therefore unviable. The same was true for Wald tests examining differences in individual associations based on precisely the same cell frequencies and total observations.
All analyses were conducted with the STATA 12.1 sta-tistical package (Stata Corp., 2011). Results were weighted using population weights that adjusted for the intentional oversampling of Blacks and Hispanics and also incorporated
Table 3. Associations of Religious Attendance With Metabolic States Among U.S. Adults Aged 57–85: Coefficients (SEs)
All Men Women
Waist Circumferencea Log HbA1ca
Waist Circumferencea Log HbA1ca
Waist Circumferencea Log HbA1ca
Control variables Agea −0.10***
(0.01)0.00
(0.00)−0.11*** (0.02)
0.00 (0.00)
−0.09*** (0.02)
0.00 (0.00)
Educationb −0.34*** (0.10)
−0.01 (0.00)
−0.21 (0.14)
−0.01 (0.01)
−0.49*** (0.17)
0.00 (0.00)
Gender (ref: menc) Womenc −4.16***
(0.26)−0.01* (0.01)
Ethnicity (ref: Whitec) Blackc 0.22
(−0.32)0.07***
(−0.02)−1.66**
(−0.65)0.09*
(−0.04)1.77***
(−0.46)0.05***
(−0.01) Hispanic/otherc −0.77*
(0.39)0.05***
(0.01)−1.47*** (0.54)
0.05** (0.02)
−0.09 (0.45)
0.04*** (0.01)
Diagnosed conditions (lifetime) Diabetesc 2.92***
(0.30)0.19***
(0.01)1.93***
(0.38)0.20***
(0.01)4.01***
(0.41)0.19***
(0.02) Hypertensionc 1.95***
(0.21)0.00
(0.01)1.62***
(0.32)−0.01 (0.01)
2.11*** (0.31)
0.00 (0.01)
Heart failure or attackc 0.93** (0.41)
0.00 (0.01)
0.67 (0.54)
0.00 (0.01)
1.28** (0.51)
0.00 (0.01)
Independent variable Religious attendanceb −0.02
(0.05)0.00
(0.00)0.03
(0.07)0.00
(0.00)−0.10 (0.08)
0.00 (0.00)
N 2,859 1,720 1,395 832 1,464 888
Notes. Data for all analyses were from the nationally representative 2005–2006 U.S. National Social Life, Health, and Aging Project (NSHAP). Figures in bold represent associations statistically significant at at least p <.10. All estimates are weighted to account for differential probabilities of selection and differential nonresponse. Design-based SEs are given in parentheses. HbA1c = hemoglobin A1c.
aContinuous variable.bOrdinal variable.cDummy variable.dAssociation significantly stronger at p <.10 than among other gender, per postestimation Wald test.*p < .10, **p < .05, ***p < .01.
a nonresponse adjustment based on age and urbanicity (O’Muircheartaigh & Smith, 2007). SEs were adjusted for sample stratification (sampling strata independently) and clustering (sampling individuals within each of 100 primary sampling units).
Results
Religious Attendance and WeatheringA first set of models tested linkages of the inflamma-
tion (Table 2), metabolic (Table 3), and cardiovascular (Table 4) outcomes with frequency of religious attendance. Per Hypothesis 1, results were generally consistent with a lowering of weathering by this factor. Among participants of both genders combined, for instance, the latter was nega-tively associated with both indicators of inflammation (log CRP, EBV; Table 2), as well as two out of the three car-diovascular outcomes (diastolic BP, heart rate; Table 4). Each of these negative linkages also held for the male subsample—with men attending religious services more also having lower systolic BP. While this pattern remained generally robust among women, their associations were
somewhat less uniform—with two (EBV, systolic BP) of the five inflammatory and cardiovascular outcomes not sig-nificantly linked to their religious attendance. In contrast, this factor had no associations with the two metabolic indi-cators (waist circumference, log HbA1c) among any group (Table 3). Finally, contrary to Hypothesis 2, postestimation Wald tests indicated no statistically significant gender dif-ferences in these linkages.
Spousal Loss and Weathering: Mitigation by Religious Attendance?
Next, mitigation of spousal-loss effects by participation in religious services (Hypothesis 3) was examined by first regressing the inflammation (Table 5), metabolic (Table 6), and cardiovascular (Table 7) outcomes on cross-categories of any loss (through divorce/separation or widowhood) and regular (weekly or higher) religious attendance—with those currently married/cohabiting as the reference. As noted, postestimation Wald tests were then used to examine the significance (at p < .10) of differences in loss effects across this religiosity threshold. Among participants of both gen-ders combined, results seemed somewhat consistent with the
Table 4. Associations of Religious Attendance With Cardiovascular States Among U.S. Adults Aged 57–85: Coefficients (SEs)
N 2,887 2,887 2,884 1,405 1,405 1,403 1,482 1,482 1,481
Notes. Data for all analyses were from the nationally representative 2005–2006 U.S. National Social Life, Health, and Aging Project (NSHAP). Figures in bold represent associations statistically significant at at least p <.10. All estimates are weighted to account for differential probabilities of selection and differential nonresponse. Design-based SEs are given in parentheses. BP = blood pressure.
aContinuous variable.bOrdinal variable.cDummy variable.dAssociation significantly stronger at p <.10 than among other gender, per postestimation Wald test.*p < .10; **p < .05; ***p < .01.
mitigation conjecture—with three of the seven loss effects significantly stronger among those not regularly attend-ing religious services. This pattern held, for instance, with inflammation (Table 5): only older adults losing a spouse who did not attend religious services had significantly ele-vated log CRP values—with this association stronger per Wald tests than among their more religious counterparts. Consistent with a lack of linkages between religious attend-ance and metabolic outcomes (Table 3), however, waist circumference was significantly elevated with both catego-ries of loss. Similarly, log HbA1c (poor blood sugar) was elevated only among those having experienced this event and attending religious services (Table 6). A similar lack
of differentiation was found for one of the three cardiovas-cular indicators—systolic BP—which was positively linked to spousal loss with or without regular religious attendance (Table 7). The latter did, however, seem to mitigate loss effects on diastolic BP as well as heart rate. Not only were significant elevations in these two states found only among those not regularly attending religious services, but each of these effects was significantly stronger per Wald tests than among their more religious counterparts.
Per expectations, men’s linkages were sparse: men los-ing a spouse and not regularly attending religious ser-vices had elevations in only one of the seven physiological states—heart rate (Table 7). It is possible that this lack of
Table 5. Differentiation of Inflammation Associations of Spousal Loss by Regular Religious Participation: Coefficients (SEs)
All Men Women
Log CRPa EBVa Log CRPa EBVa Log CRPa EBVa
Control variables Agea 0.00
(0.00)0.16
(0.26)0.00
(0.00)0.24
(0.32)−0.01 (0.00)
0.05 (0.41)
Educationb −0.07*** (0.02)
−3.73* (2.18)
−0.07*** (0.02)
−3.89 (2.52)
−0.06** (0.03)
−2.99 (3.08)
Gender (ref: menc) Womenc 0.27***
(0.05)2.59
(4.96) Ethnicity (ref: Whitec) Blackc 0.21***
(0.05)11.60** (5.34)
0.26*** (0.08)
20.55** (8.64)
0.11 (0.08)
6.35 (9.03)
Hispanic/otherc 0.05 (0.07)
−6.46 (6.04)
0.07 (0.09)
−1.37 (8.61)
0.00 (0.10)
−11.03 (9.98)
Diagnosed conditions (lifetime) Diabetesc −0.01
(0.07)−2.01 (4.92)
0.04 (0.10)
−2.81 (6.28)
−0.09 (0.08)
−0.86 (8.82)
Hypertensionc 0.01 (0.05)
−1.74 (3.63)
−0.05 (0.07)
−6.55 (5.56)
0.07 (0.07)
3.92 (5.83)
Heart failure or attackc 0.17*** (0.06)
8.01 (7.92)
0.23*** (0.08)
4.47 (7.73)
0.07 (0.12)
12.69 (11.28)
Number of marriagesb 0.07** (0.03)
0.31 (3.33)
0.05 (0.05)
1.04 (3.39)
0.10** (0.04)
−0.31 (6.31)
Obesity Waist circumferencea 0.02***
(0.01)0.94
(0.70)0.02**
(0.01)2.51**
(1.08)0.03**
(0.01)−0.24 (0.98)
BMIa 0.02** (0.01)
0.25 (0.56)
0.01 (0.01)
−0.69 (0.98)
0.03** (0.01)
0.86 (0.77)
Independent variables Marital status, religious attendance (ref: married/cohabitingc) Spousal loss, regular religious attendancec −0.09
(0.06)−3.62 (7.28)
0.02 (0.14)
−12.08 (11.03)
−0.11* (0.06)
−0.27 (9.26)
Spousal loss, no regular religious attendancec 0.09*,d (0.05)
3.00 (5.06)
0.14 (0.09)
3.13 (8.34)
0.03d (0.07)
4.77 (5.96)
N 1,746 1,779 845 865 901 914
Notes. Figures in bold represent associations stronger than those of spousal loss with regular church attendance, per postestimation Wald tests. “Spousal loss” combines divorce/separation and widowhood. All analyses restricted to those married at least once. All estimates are weighted to account for differential probabilities of selection and differential nonresponse. Design-based SEs are given in parentheses. BMI = body mass index; CRP = C-reactive protein; EBV = Epstein–Barr virus antibody titers.
aContinuous variable.bOrdinal variable.cDummy variable.dAssociation significantly stronger at p <.10 than that of spousal loss with regular church attendance, per postestimation Wald test.*p < .10; **p < .05; ***p < .01.
significant associations was driven by men’s smaller cell sizes. Specifically, only 21.5% of all NSHAP men were cur-rently divorced/separated or widowed—less than half the corresponding figure among women (48.9%).
Perhaps as a result, women’s findings were somewhat more consistent with mitigation conjecture (Hypothesis 3)—with four of their seven loss effects significantly stronger among those without regular religious attendance. Thus, log CRP (inflammation) was lower among women having lost a spouse but attending religious services, than those partnered—with this effect significantly different than among their less religious peers (Table 5). Women’s waist circumference, in contrast, was positively associ-ated with both categories of their loss—although the link-age was stronger for those with lower religious attendance (Table 6). Loss effects on women’s log HbA1c, however, seemed unmitigated by this factor, positive for those with as well as without regular religious attendance. The same
was true of systolic BP—significantly elevated only among women losing a spouse who attended religious services (Table 7). As in the combined-gender models, however, this factor did differentiate linkages of women’s loss with at least two of their three cardiovascular states—diastolic BP and heart rate. Relative to the reference group, both were significantly higher only among women losing a spouse and not regularly attending religious services—with each asso-ciation stronger per Wald tests than for their more religious counterparts.
DiscussionThis study began by noting that recent literature on the
ecological context of human physiological function links stress-induced physiological problems (i.e., weathering) not simply to social stratification (by race or socioeco-nomic status), but also to life transitions such as spousal
Table 6. Differentiation of Metabolic Associations of Spousal Loss by Regular Religious Participation: Coefficients (SEs)
All Men Women
Waist Circumferencea Log HbA1ca,d
Waist Circumferencea Log HbA1ca
Waist Circumferencea Log HbA1ca
Control variables Agea −0.11***
(0.01)0.00
(0.00)−0.11*** (0.02)
0.00 (0.00)
−0.11*** (0.02)
0.00 (0.00)
Educationb −0.40*** (0.11)
−0.01 (0.00)
−0.27* (0.14)
−0.01 (0.01)
−0.56*** (0.19)
0.00 (0.00)
Gender (ref: menc) Womenc −4.45***
(0.27)−0.02** (0.01)
Ethnicity (ref: Whitec) Blackc 0.17
(0.37)0.07***
(0.02)−1.49** (0.67)
0.09* (0.05)
1.62*** (0.51)
0.06*** (0.01)
Hispanic/otherc −0.78** (0.37)
0.05*** (0.01)
−1.44*** (0.51)
0.06** (0.02)
−0.15 (0.47)
0.04*** (0.01)
Diagnosed conditions (lifetime) Diabetesc 2.78***
(0.31)0.19***
(0.01)1.88***
(0.38)0.20***
(0.02)3.74***
(0.44)0.19***
(0.02) Hypertensionc 1.91***
(0.20)−0.01 (0.01)
1.64*** (0.32)
−0.01 (0.01)
2.06*** (0.30)
0.00 (0.01)
Heart failure or attackc 0.97** (0.41)
0.00 (0.01)
0.74 (0.54)
0.00 (0.01)
1.39*** (0.52)
0.00 (0.01)
Number of marriagesb 0.02 (0.22)
−0.01 (0.01)
0.04 (0.30)
0.00 (0.01)
−0.07 (0.27)
−0.01* (0.01)
Independent variables Marital status, religious attendance (ref: married/cohabitingc) Spousal loss, regular religious attendancec 0.68**
(0.30)0.02**
(0.01)0.20
(0.73)0.03
(0.02)0.79**
(0.34)0.02**
(0.01) Spousal loss, no regular religious attendancec 0.68**
(0.34)0.01
(0.01)−0.62 (0.49)
−0.01 (0.02)
1.60***,d (0.42)
0.02* (0.01)
N 2,707 1,635 1,326 795 1,381 840
Notes. Figures in bold represent associations stronger than those of spousal loss with regular church attendance, per postestimation Wald tests. “Spousal loss” combines divorce/separation and widowhood. All analyses restricted to those married at least once. All estimates are weighted to account for differential probabilities of selection and differential nonresponse. Design-based SEs are given in parentheses. HbA1c = hemoglobin A1c.
aContinuous variable.bOrdinal variable.cDummy variable.dAssociation significantly stronger at p <.10 than that of spousal loss with regular church attendance, per postestimation Wald test.*p < .10; **p < .05; ***p < .01.
loss. Moreover, scattered evidence indicates that especially in late life, participation in religious services may serve as a buffer against such pathogenic processes.
Results were generally consistent with mitigation of weathering by religious attendance (Hypothesis 1). Among participants of both genders combined, greater religious attendance was negatively associated with indicators of inflammation (log CRP, EBV) (Table 2) and with those of cardiovascular states (diastolic BP, heart rate) (Table 4). Metabolic measures—waist circumference and log HbA1c (proxying deficits in blood sugar control)—however, seemed unlinked to religious attendance (Table 3). The same pattern held even more consistently among men—with only metabolic states not associated with their reli-gious attendance. Women’s findings also generally followed expectations but were somewhat less uniform. However, contrary to expectations (Hypothesis 2), postestimation Wald tests indicated no significant gender differences in
these associations—suggesting a consistent benefit of reli-gious participation among older adults. It is argued that the subsystem-specific pattern of linkages above may indicate a need to move beyond single, integrated constructs like “weathering,” and toward nuanced conceptual models that can accommodate differentiated physiological impacts of psychosocial assets and pressures.
NSHAP data also precluded mediation analysis—that is, of whether these patterns were driven by psychological factors (a sense of divine control), social ones (support from church-centered social networks), or other unmeasured dimensions of religiosity. Longitudinal studies, with better religion indica-tors, are therefore needed to establish mechanisms. Moreover, it is possible that these linkages indicate feedback from cur-rent health states to the capacity to attend religious services. As noted, however, all analyses of physiological outcomes adjusted for any lifetime diagnosis of diabetes or (separately) hypertension, as well as any history of heart failure or attack.
Table 7. Differentiation of Metabolic Associations of Spousal Loss by Regular Religious Participation: Coefficients (SEs)
All Men Women
Systolic BPa
Diastolic BPa
Heart Ratea
Systolic BPa
Diastolic BPa Heart Ratea Systolic BPa
Diastolic BPa
Heart Ratea
Control variables Agea 0.26***
(0.05)−0.34*** (0.03)
−0.17*** (0.03)
0.14* (0.08)
−0.46*** (0.05)
−0.35*** (0.06)
0.38*** (0.09)
−0.22*** (0.04)
0.02 (0.05)
Educationb −0.37 (0.37)
−0.11 (0.27)
−0.70*** (0.18)
0.32 (0.58)
0.22 (0.33)
−0.60* (0.31)
−1.08* (0.61)
−0.43 (0.38)
−0.83** (0.33)
Gender (ref: menc) Womenc −2.54***
(0.75)1.28***
(0.45)0.87*
(0.50) Ethnicity (ref: Whitec) Blackc 2.59**
(1.15)2.83***
(0.88)2.36***
(0.80)3.09
(1.85)2.76**
(1.07)0.89
(1.37)2.35
(1.49)2.94**
(1.12)3.71***
(0.79) Hispanic/otherc −2.07
(1.31)−1.32* (0.71)
1.34 (0.97)
−1.96 (1.72)
0.05 (1.04)
1.35 (1.49)
−2.07 (1.83)
−2.70** (1.13)
1.63* (0.92)
Diagnosed conditions (lifetime) Diabetesc 1.43
(1.24)−3.04*** (0.81)
3.02*** (0.94)
0.87 (1.41)
−3.87*** (1.15)
3.07** (1.29)
2.11 (1.84)
−1.98* (1.00)
3.29** (1.25)
Hypertensionc 6.84*** (0.85)
2.92*** (0.54)
−1.21* (0.69)
6.48*** (1.25)
2.94*** (0.77)
−0.59 (1.08)
6.87*** (1.12)
2.71*** (0.68)
−2.08*** (0.64)
Heart failure or attackc −0.98 (1.62)
−1.02 (1.01)
−1.17 (1.05)
0.14 (1.88)
−1.01 (1.23)
−0.59 (1.28)
−2.33 (1.93)
−0.74 (1.40)
−1.83 (1.13)
Number of marriagesb 0.36 (0.81)
0.31 (0.44)
0.68 (0.58)
−0.57 (0.85)
0.22 (0.41)
0.92 (0.86)
1.44 (1.16)
0.46 (0.68)
0.52 (0.51)
Independent variables Marital status, religious attendance (ref: married/cohabitingc)
Spousal loss, regular religious attendancec
2.43** (1.13)
−0.18 (0.67)
0.63 (0.77)
−0.78 (2.18)
−1.42 (1.44)
1.86 (1.65)
2.82* (1.45)
−0.20 (0.78)
−0.34 (1.01)
Spousal loss, no regular religious attendancec
3.62** (1.36)
2.13***,d (0.70)
3.36***,d (0.76)
2.92 (1.99)
1.09 (0.99)
2.78** (1.31)
3.85 (2.30)
2.58**,d (1.17)
3.32***,d (0.89)
N 2,731 2,731 2,728 1,333 1,333 1,331 1,398 1,398 1,397
Notes. Figures in bold represent associations stronger than those of spousal loss with regular church attendance, per postestimation Wald tests. “Spousal loss” combines divorce/separation and widowhood. All analyses restricted to those married at least once. All estimates are weighted to account for differential probabilities of selection and differential nonresponse. Design-based SEs are given in parentheses. BP = blood pressure.
aContinuous variable.bOrdinal variable.cDummy variable.dAssociation significantly stronger at p <.10 than that of spousal loss with regular church attendance, per postestimation Wald test.*p < .10; **p < .05; ***p < .01.
In addition, each of these associations remained robust in sup-plementary analysis (not shown) adding controls for one’s total number of diagnosed conditions (lifetime), functional health as indexed by activities of daily living (Katz, 1983; Katz, Down, Cash, & Grotz, 1970), and current antidepressant use—also suggesting a causal effect of religious attendance.
Next, results were somewhat consistent with mitigation of negative psychological and physiological sequelae of spousal loss by religious attendance (Hypothesis 3). In combined-gender models, and among women, those having lost a spouse and not regularly attending religious services had elevated inflammatory (Table 5) and cardiovascular states (Table 7). Consistent with a lack of linkages between religious attend-ance and metabolic indicators (Table 3), however, these pos-sible benefits extended to waist circumference only among women and did not apply to log HbA1c (poor blood sugar control) for any group (Table 6). Moreover, whether because of their lower physiological vulnerability to loss, or smaller cell sizes, this potential buffering did not hold true for men. In summary, then, this prosocial behavior seems to yield at least some cardiovascular and perhaps inflammatory benefits for older women but not men with spousal loss.
Finally, the analyses had several limitations. Most impor-tantly, these were cross-sectional data, making it impossible to establish causal precedence, and segregate feedback effects. In particular, despite restriction of all outcomes to current states, there remains the potential for feedback from health to reli-gious attendance and spousal loss. Thus, for instance, mor-bidity-induced functional issues could make it difficult for an older individual to attend religious services regularly. As noted, however, all physiological analyses controlled diagnosed dia-betes, hypertension, and previous heart failure or attack—and results in Tables 2–4 remained fully robust in supplementary analysis (not shown) adjusting for one’s total number of diag-nosed conditions, functional health, and current antidepressant use—suggesting a causal rather than feedback process. Indeed, as noted, to the extent low religious attendance and/or spousal loss indexed long-term patterns influencing the incidence of current morbidities, these analyses were overcontrolled and yielded conservative estimates. Moreover, while health issues could potentially lower remarriage rates among unpartnered individuals in worse health, a range of studies report low and declining overall remarriage rates among older adults (Cooney & Dunne, 2001; Lee et al., 2001), along with a lower desire for and more constraints on repartnering (Carr, 2004; Sweeney, 2010)—suggesting perhaps that nonselection into remarriage may not be a major factor behind the reported linkages. This is especially true for older women, for whom remarriage rates may be as low as 2% (Smith, Zick, & Duncan, 1991). As pre-viously reported (Das, 2013b), among all NSHAP participants over age 60, only 5.1% of men and 2.0% of women had initi-ated a marriage since that age, also consistent with a low base-line incidence of new partnerships in late life.
Magnitudes of associations were small, especially in Tables 5–7, and may not indicate effect sizes relevant to
intervention. Additionally, as noted, analyses presented in Table 4 combined divorce/separation and widowhood into a single “spousal loss” category—based partly on previous studies finding similar linkages of these types with physi-ological states and partly due to cell-size limitations, espe-cially in gender-separate models. However, cross-categories of these forms of loss with regular religious attendance may possibly indicate substantively different life conditions. Thus, for instance, lack of religious attendance among those divorced/separated may proxy more “liberal” lifestyles cor-related with health, rather than deficits in psychosocial buff-ers against stress. In separate robustness checks (available on request) regressing weathering indicators on cross-cate-gories of regular church attendance with divorce/separation and (separately) widowhood, results did remain substan-tively similar. Specifically, while fewer associations reached significance due to smaller cell sizes, religious attendance mitigated associations of both forms of loss with physiologi-cal states—among all participants and among women—sug-gesting that underlying lifestyle propensities may not be a major confounder. Next, time since loss could not be con-trolled in Table 4, given its inapplicability to the reference category (those currently partnered). The possibility of temporal rhythms in patterns explored is acknowledged. As noted, however, contrary to previous findings of loss as a traumatic event with transient effects, recent NSHAP results indicate that these (sparsely examined) physiological issues may be more elevated among those longer past the event—perhaps reflecting lasting coping pressures (Das, 2013b).
Finally, due to a lack of appropriate indicators as well as inadequate cell sizes, this study could not examine poten-tial improvements in physiological status with spousal loss among those with prior marital burdens, due to release from long-term “role stress” (Keene & Prokos, 2008; Schulz, Newsome, Fleissner, Decamp, & Nieboer, 1997; Schulz et al., 2003). It is noted that the current study was focused more on potential mitigation of loss effects (by religious attendance) among individuals who are negatively affected by this life transition—a buffering perhaps less important among those released from stress by the event.
ConclusionResults from this nationally representative U.S. study
provide important new information on the role of reli-gious attendance as a buffer against stress-induced bio-logical problems—whether among older adults in general or those having lost a spouse. An important next step for model-building is to examine mediatory pathways—espe-cially the potential sequence connecting life processes to chronic psychological arousal and physiological break-down (Seeman et al., 2008; Sterling and Eyer, 1981). A large and established stress process literature offers rich insights into the psychological—and hence potentially physiological—implications of specific life trajectories and
“turning points” within them. While some of these events may be socially stratified (more common among those in lower socioeconomic or ethnic strata), and hence part of the complex of stressors generated by stratification, others are more randomly distributed. Moreover, early events can be causally antecedent to at least socioeconomic stratification. Multiple studies indicate that these experiences, and atten-dant stress-proliferation, may induce “cumulative (socioec-onomic) disadvantage” (Hayward & Gorman, 2004). These sociological models, however, have yet to be extended to weathering studies, which remain anchored in simple con-ceptions of stratification. Deeper insights into the aging process could be developed by linking these literatures, through a model of health over the life course as a “punctu-ated equilibrium”—a sequence of stabilizations and turning points, triggered by events, constraints, and assets at multi-ple life stages (Das, Laumann, & Waite, 2012).
Acknowledgments
We thank the Editor of the Journal of Gerontology: Social Sciences and three anonymous reviewers for their helpful comments and suggestions. A. Das guided the conception and design of the study and conducted most analyses. S. Nairn contributed to literature review, theoretical framing, and writing.
Correspondence
Correspondence should be addressed to Aniruddha Das, PhD, Department of Sociology, McGill University, Room 712, Leacock Building, 855 Sherbrooke Street West, Montreal, Quebec H3A 2T7, Canada. E-mail: [email protected].
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