Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2024 Oct 1.
Published in final edited form as: Aging Ment Health. 2024 Mar 29;28(10):1343–1350. doi: 10.1080/13607863.2024.2335390

The association between religious beliefs and values with inflammation among middle-age and older adults

Katherine Carroll Britt a,b, Augustine CO Boateng a,b, Joshua Sebu b,c, Hayoung Oh b,d, Ruby Lekwauwa e, Lauren Massimo a, Benjamin Doolittle e
PMCID: PMC11390335  NIHMSID: NIHMS1982756  PMID: 38553253

Abstract

Objectives:

Dimensions of religion and spirituality are associated with better emotional, physical, and cognitive health. However, the underlying physiological mechanisms are not well known. We investigated the relationship between dimensions of religion and spirituality with levels of C-reactive protein (CRP), a biomarker of systematic inflammation, in middle-aged and older adults in the United States.

Methods:

In this descriptive longitudinal study using secondary data, we used proportional odds models of the generalized estimating equation (GEE) to assess the association between religious beliefs and values and religious service attendance with CRP levels from respondents (n = 2,385) aged 50 years and older in the Health and Retirement Study from 2006 to 2014.

Results:

Middle-aged to older adults who reported higher religious beliefs and values had lower levels of CRP, controlling for age, sex, education, marital status, race, household income, and health, such as hypertension, diabetes, cancer, and body mass index (BMI).

Conclusion:

Religious beliefs and values are associated with lower CRP levels among middle-aged and older adults in the U.S. This study adds to the understanding of biological processes underlying the relationship between dimensions of religion and spirituality with better cognitive and physical health, potentially through inflammation.

Keywords: religion, spirituality, health and retirement study, cognition, dementia, resilience, protective factor, biomarker

Introduction

Dimensions of religion and spirituality have been associated with reduced mortality, morbidity, and better cognitive function. In a longitudinal study among 74,000 women, weekly religious observance was associated with a 37% reduction in all-cause mortality over a 16-year period (Li et al., 2016). This relationship has also been noted in longitudinal studies of other populations, including African Americans and Mexican Americans (Hill et al., 2005; VanderWeele et al., 2017), as well as for specific disease processes, including coronary artery disease, stroke, respiratory illness, and other infectious diseases (Hummer et al., 1999; Oman et al., 2002; Rogers et al., 2010). As some of these comorbidities are risk factors for dementia, it is no surprise that dimensions of religion and spirituality, such as religious beliefs, meaning, and values, religious service attendance, prayer, spiritual practice, and religious affiliation, are also associated with better cognitive health in older adults (Britt et al., 2022; Hosseini et al., 2019). The underlying physiological mechanisms, however, are unclear.

Several mechanisms for this association have been proposed, including increased access to community support, adaptive coping strategies, positive emotions, and reduced engagement in risk behaviors such as alcohol and drug use (George et al., 2002; Koenig et al., 2012). Such resources for coping with stress may influence the framing of a situation, providing a sense of meaning and purpose and affecting physiological response and, in turn, physical health (Koenig et al., 2012). Increasingly, dimensions of religion and spirituality are favorably associated with biological functions, such as telomere length (Hill et al., 2017), cortisol levels, epinephrine levels, and inflammatory markers (Suh et al., 2019).

A framework for understanding associations between a stressor, dimensions of religion and spirituality, and health outcomes is called the vulnerability-stress model incorporating religiosity/spirituality (VSMRS) (see Figure 1) (Zwingmann et al., 2011). Based on two established theories, the diathesis-stress model (Ingram & Price, 2001; Zuckerman, 2009) and the transactional theory of stress and coping (Lazarus & Folkman, 1984), the VSMRS posits that when exposed to a challenge or stressor, an individual’s health will result from a combination of individual and social factors such as predispositions, health resources, and coping behaviors to that stressor. Five dimensions of religion and spirituality are incorporated into this framework as predispositions, resources, and coping behaviors an individual may use which affect health outcomes and include (1) intensity of religion/spirituality, (2) religious and spiritual resources, (3) religious and spiritual coping, (4) spiritual needs, and (5) spiritual well-being.

Figure 1.

Figure 1.

Open in a new tab

The Vulnerability-Stress model incorporating religiosity/spirituality (VSMRS), which includes (1) centrality of religion, (2) religious and spiritual resources, (3) spiritual needs, (4) religious and spiritual coping, and (5) spiritual well-being.

The psychoneuroimmunology (PNI) theory informs potential relationships between psychological stress and negative emotions prompting an inflammatory response in the body (Renna, 2021). PNI suggests that psychological stress may trigger the release of cytokines, chemical messengers that can cause inflammation and lead to an increase in C-reactive protein (CRP) levels. PNI research has shown that chronic stress and negative emotions such as depression and anxiety can activate pro-inflammatory immune pathways and lead to elevated levels of CRP. Conversely, positive emotions such as happiness and optimism have been associated with lower levels of CRP (Renna, 2021). Based on this theory, religious beliefs and values and religious service attendance may play a positive role in psychological states by influencing the immune system and levels of inflammation, thus exerting a protective effect against chronic diseases marked by inflammation. As systemic inflammation, such as CRP, is associated with an increased risk of cognitive decline and dementia (Hegazy et al., 2022; Lewis & Knight, 2021), dimensions of religion and spirituality have the potential to serve as protective factors to reduce the risk of cognitive decline and dementia.

When faced with life challenges, individuals may turn to religion and spirituality to provide meaning, framing the situation for greater understanding. Prompting positive emotions such as hope and optimism, dimensions of religion and spirituality may provide comfort and resources for coping, thus impacting an individual’s stress appraisal process (Algahtani et al., 2022; Braam & Koenig, 2019). This, in turn, may have an effect on psychological stress with a reduction of anxiety and depression (Lucchetti et al., 2021). Research demonstrates that psychological stress affects emotions and can trigger inflammatory activity and increase attentional processing of negative information (Callaghan and Tottenham, 2016; Pace et al., 2006; Slavich & Irwin, 2014). Chronic stress and depression are associated with an increased risk of cognitive impairment and dementia (Wallensten et al., 2023). CRP as a measure of systemic inflammation is associated with increased mortality (Li et al., 2017) and other adverse health outcomes, such as a higher risk of cognitive decline and dementia (Hegazy et al., 2022; Noble et al., 2010), morbidity in cardiovascular disease, hypertension, stroke (Avan et al., 2018; Sesso et al., 2003), and major depression (Köhler-Forsberg et al., 2017).

Social dimensions of religion and spirituality, such as attending religious services and group practices such as prayer and meditation, offer social engagement opportunities, prompting further resources for support and interaction. Systematic reviews of studies report the importance of social connectedness for cognitive health (Kelly et al., 2017; Piolatto et al., 2022). Research suggests religion and spirituality may offer cognitive benefits, not only through decreasing stress and promoting beneficial physiological effects but also through cognitively engaging exercise with higher cortical function through abstract thinking as individuals contemplate morals and ideas related to the sacred or transcendent (Koenig et al., 2023). In addition, positive associations are reported between religion and spirituality with individually identified dementia risk factors, including age, cardiovascular health, and physical activity, and negative associations with cancer, smoking, diabetes, alcohol, depression, and hypertension (Koenig et al., 2023) making them an interesting candidate to examine for better cognitive health potentially through inflammation reduction.

It is possible that dimensions of religion and spirituality (i.e. personal beliefs about transcendence, meaning in the universe, and community values of love and virtue) and attendance at religious services influence chronic inflammatory markers in the body, such as CRP, which would contribute to our understanding of the relationship between religious observance and health outcomes. Several studies have evaluated the association between religious observance and CRP (Suh et al., 2019). Though the majority of studies report a positive association between religion and spirituality with lower CRP levels, a few studies have shown a neutral association (Aksungar et al., 2007; Ford et al., 2006; Holt-Lunstad et al., 2011; King et al., 2001; Lucchese & Koenig, 2013; Suh et al., 2019). Furthermore, these studies were often limited by study duration, as the longest study duration was four years. Due to the temporal variability in inflammation (Ockene et al., 2001), we evaluated inflammation over an extended period of time.

Using data from the Health and Retirement Study, we conducted a descriptive longitudinal study to examine the association between dimensions of religion and spirituality with systemic inflammation. Our study is informed by the PNI theory and the VSMRS framework, which provides a better understanding of how dimensions of religion and spirituality may play a role in stress on physical and cognitive health outcomes. Using the VSMRS as a guide, we included two dimensions of religion and spirituality: religious beliefs and values using a broad and validated measure and religious service attendance and examined their association with CRP as a health outcome over time. By using a large, nationally representative database of American citizens, we advance the extant literature examining two dimensions of religion and spirituality, a multidimensional construct, and markers of inflammation (e.g. CRP) longitudinally over a period of eight years.

Methods

Data

The study uses data from the University of Michigan Health and Retirement Study (HRS). This is a longitudinal panel survey that began in 1992 and collects social, demographic, health, and psychological data from a representative sample of more than 20,000 noninstitutionalized U.S. adults ages 50 and older (Health & Retirement Study, 2019; RAND, 2019). Additional psychosocial and biomarker data were collected beginning in 2006. Further information on the data collection process is available from HRS (hrsonline.isr.umich.edu).

The present study pooled respondents’ data from the core interview, tracker file, the Leave-Behind Questionnaire, which addresses psychosocial data, and biomarker data. Our sample inclusion criteria included participants aged 50 years and older who provided religious beliefs and values, religious service attendance, and biomarker data of CRP on three occasions from 2006 to 2014. Exclusion criteria included participants who did not participate in the Leave-Behind or biomarker surveys. In total, 21,867 observations from 10,897 respondents were eligible (see Supplementary Table 1). The sampling weight of the baseline year (2006) was applied to the analysis. However, the variable had 4,736 missing observations and a further 948 with zero values. Applying the sample weights of zero drops out those observations from the study. Hence, in total 5,684 observations were dropped based on the sample weights. Further, a case-wise deletion was implemented where there is missingness in any of the variables used in the analysis (N = 2,666). We restrict the data to participants that appear in all three rounds of the sample. In all 6,362 observations were dropped. Our analysis sample thus comprises 7,155 observations made up of 2,385 individuals.

Measures

Dimensions of religion and spirituality

The Brief Multidimensional Measure of Religiousness/Spirituality, a validated, non-sectarian tool (BMMRS), was used to measure religious and spiritual beliefs, meaning, and values (Fetzer Institute, 2003). An index is created by averaging the scores across 4 items from questions such as, “I believe in a God who watches over me,” “The events of my life unfold according to a divine or greater plan,” “I try hard to carry my religious beliefs over into all my other dealings in life,” and “I find strength and comfort in my religion” (α = 0.93). Responses have a range of 1– 6 (strongly disagree to strongly agree). Religious service attendance is measured by the answer to the question, “How frequently have you attended religious services over the past year?” was self-reported. Responses varied from never (0) to more frequently than once per week (5). Responses were dichotomized to compare high and low religious attendance. High religious attendance has been defined in the literature as occurring at least once a week or more frequently; low religious attendance has been defined as one or more times a year or not at all (Koenig et al., 2012; VanderWeele et al., 2017). The categorization of reactions into high and low is in accordance with earlier studies and is supported by theoretical and empirical parallels between individual responses within each group (Coin et al., 2010; Corsentino et al., 2009; Kidwai et al., 2014; Koenig et al., 2004).

C-reactive protein (CRP) μg/mL

CRP is a biomarker of systemic inflammation. We used high-sensitivity CRP data ascertained using the dried blood spot (DBS) process that HRS transformed into serum CRP values for analysis. Recommended for use by HRS and as previously reported, the CRP data is adjusted to account for any potential between-lab measurement differences in CRP collection (Crimmins et al., 2013). CRP data are continuous scores starting around 0.015 μg/mL with higher scores indicating greater systemic inflammation. Slightly elevated CRP levels are generally considered between 3 and 10 μg/mL (Verma & Yeh, 2003) with higher values suggesting acute illness or infection (Pearson et al., 2003).

Covariates

Participant baseline characteristics included sex (male, female), education in years (0–17), marital status (not married, married), race/ethnicity (White/Caucasian, Black/African American, Other), household income (continuous), age (years) and the square of age. Squaring age helps capture the non-linear relationship between age and health by more accurately modeling the effect of age. It is expected that middle-aged adults would have better health outcomes than older adults, who typically experience deteriorating health (Yashin et al., 2007). Body Mass Index (BMI) was measured as normal <25 kg/m2) and overweight/obese (BMI ≥ 25 kg/m2) (Kuczmarski & Flegal, 2000).

Statistical analysis

The association between religious beliefs and values and religious attendance with average CRP across three-time points was examined using panel data modeling using the Generalized Estimating Equation (GEE), a marginal model typically used for longitudinal analysis in biomedical studies. GEE produces efficient estimates of the coefficients by considering over-time correlations while estimating the parameters. GEE is a population-level method that uses the quasi-likelihood function to produce population-averaged estimates of the parameters. In this longitudinal study, we anticipate that participants’ past health states will influence their current health status. Consequently, the data will likely exhibit within-subject correlations due to repeated measures. Ignoring this correlation within respondents can introduce significant bias into the analysis. Therefore, adopting a Generalized Estimating Equations (GEE) approach will yield less biased estimates. In addition, we performed a complete case analysis to control for missing cases and to enhance the reliability of the data set (White & Carlin, 2010). Subsequently, we undertook a series of robust checks, including multiple imputations, to reinforce the overall validity of our analysis. Data analysis was performed using STATA 18 by applying the xtgee command. The significance level was set at p < 0.05 based on a two-tailed test.

Results

Descriptive analysis

Descriptive results can be found in Table 1 per HRS wave. Respondents of old age increased from 49.2% in 2006, to 65.9% in 2010 and finally to 78.6% in 2014; 59.2% were female, 71.2% were married, and had an average of 13.18 (SD 2.75) years of education. Average household income decreased from $74,644.81 (SD 137,981.09) to 66,693.26 (SD 73,631.47) in 2010 but increased in 2014 to 68,142,41 (SD 88,088.46). Respondents were majority White/Caucasian (87.4%), followed by Black/African American (8.8%), and Other (3.8%). More than half of the population reported having hypertension increasing over the periods (51.4%, 59.5% and 65.5%) and overweight/obese BMI, however, decreasing over the period (73.0%, 72.5% and 70.0%), while other non-communicable chronic diseases such as diabetes (17.8%, 23.6% and 26.3%) and cancer (12.1%, 15.6% and 20.1%) were less than half however, increasing over the period. The study outcome CRP was a mean level of 3.846 μg/mL (SD: 7.852). The outcome of religious beliefs and values had a mean of 14.74 (SD: 4.33) in 2006 which was pretty medium but this increased to a higher mean of 19.71 (SD: 5.90) and 19.68 (SD: 6.02) in 2010 and 2014 respectively (highest score possible is 24), and religious service attendance was 57.4% in 2006 almost staying the same in 2010 (57.7%) but decreased marginally (56.1%) in 2014.

Table 1.

Descriptive characteristics (7,155 observations for N = 2,385) Health and Retirement Study participants.

2006 2010 2014
N 2,385 2,385 2,385
CRP 3.916 (7.330) 3.320 (6.554) 3.333 (7.133)
Religious beliefs & values 14.740 (4.326) 19.708 (5.902) 19.678 (6.022)
Religious attendance
 Low 1,015 (42.6%) 1,010 (42.3%) 1,047 (43.9%)
 High 1,370 (57.4%) 1,375 (57.7%) 1,338 (56.1%)
Age
 Middle age 1,211 (50.8%) 813 (34.1%) 510 (21.4%)
 Old age 1,174 (49.2%) 1,572 (65.9%) 1,875 (78.6%)
Sex
 Male 972 (40.8%) 972 (40.8%) 972 (40.8%)
 Female 1,413 (59.2%) 1,413 (59.2%) 1,413 (59.2%)
Race
 White/Caucasian 2,086 (87.5%) 2,086 (87.5%) 2,086 (87.5%)
 Black/African American 209 (8.8%) 209 (8.8%) 209 (8.8%)
 Other 90 (3.8%) 90 (3.8%) 90 (3.8%)
Years of education 13.182 (2.753) 13.182 (2.753) 13.182 (2.753)
Married
 No 686 (28.8%) 800 (33.5%) 939 (39.4%)
 Yes 1,699 (71.2%) 1,585 (66.5%) 1,446 (60.6%)
Household income 74,644.809 (137,981.086) 66,693.262 (73,613.469) 68,142.410 (88,088.460)
Hypertension
 No 1,160 (48.6%) 965 (40.5%) 823 (34.5%)
 Yes 1,225 (51.4%) 1,420 (59.5%) 1,562 (65.5%)
Diabetes
 No 1,960 (82.2%) 1,823 (76.4%) 1,758 (73.7%)
 Yes 425 (17.8%) 562 (23.6%) 627 (26.3%)
Cancer
 No 2,096 (87.9%) 2,014 (84.4%) 1,906 (79.9%)
 Yes 289 (12.1%) 371 (15.6%) 479 (20.1%)
BMi
 Other 643 (27.0%) 657 (27.5%) 715 (30.0%)
 Overweight/Obese 1,742 (73.0%) 1,728 (72.5%) 1,670 (70.0%)
Open in a new tab

Note: Mean of categorical variables are interpreted as proportions of the unadjusted sample.

Abbreviation: SD = standard deviation, BMi = body mass index (calculated as weight in kilograms divided by height in meters squared).

a

Categorized according to the recommendations of the Centers for Disease Control and Prevention (CDC): Equal to and/or above 25 mg/L - Overweight/ Obese.

Generalized Estimating equation (GEE) analysis

Results from our generalized estimating equations can be found in Table 2, controlling for both religion and spirituality dimensions. In the fully adjusted model, only the association between religious beliefs and values with CRP was negative and significant (B: −0.05, 95% [CI: −0.09, −0.01]). Furthermore, in the fully adjusted analyses, covariates had significant associations with CRP, although directionality was contingent on the variable. For instance, diagnosis of hypertension (B: 0.70, 95% CI: [0.24,1.17]) and BMI (B: 1.37, 95% CI: [0.98,1.77]) were significant and positively associated with CRP.

Table 2.

Data on religious beliefs and values, religious service attendance and CRP (N = 2,385), 2006–2014 Health and Retirement Study.

Coefficient 95% Confidence interval
Religious beliefs & values −0.05* [−0.09, −0.01]
Religious attendance: (Base: low) 0.00 [0.00, 0.00]
 High 0.05 [−0.50, 0.61]
Age: (Base: Middle age)
 Old age −0.20 [−0.58, 0.17]
Female 0.76** [0.26, 1.26]
Race: (Base: White/Caucasian)
 Black/African American 1.46* [0.33, 2.58]
 Other −0.59 [−1.55, 0.38]
Years of education −0.18*** [−0.26, −0.09]
Married 0.09 [−0.35, 0.54]
Log of HH income −0.14 [−0.34, 0.07]
Hypertension 0.70** [0.24, 1.17]
Diabetes 0.09 [−0.43, 0.61]
Cancer 0.68 [−0.07, 1.42]
BMi: (Base: Other)
 Overweight/Obese 1.37*** [0.98, 1.77]
Constant 6.26*** [3.62, 8.89]
Observations 7155
Chi2 135.39***
Open in a new tab

95% confidence intervals in brackets.

*

p < 0.05,

**

p < 0.01,

***

p < 0.001.

Compared to White/Caucasian persons, reporting as Black/African American was associated with higher CRP levels (B: 1.46, 95% CI: [0.33,2.58]). Being female was also significantly positively associated with CRP (B:0.76, 95% CI: [0.26,1.26]). However, years of education had a significant association with CRP (B: −0.145, 95% CI: [−0.211, −0.078]).

Robustness check

As a robustness check, we performed data imputation to address missing values (White & Carlin, 2010). This resulted in an increase in the number of participants from 2,385 in the case-wise deletion sample to 3,320 in the imputed sample. Data imputation was carried out using Blimp 3 software. The results are presented in Table 3. Consistent with the findings in Table 2, only religious beliefs and values exhibited a significant negative association with CRP (B = −0.05, 95% CI [−0.09, −0.02]) in the data imputation model.

Table 3.

Data on religious beliefs and values, and religious service attendance and CRP (N = 2,385), 2006–2014 Health and Retirement Study (imputed data).

Coefficient 95% Confidence interval
Religious beliefs & values −0.05** [−0.09, −0.02]
Religious attendance: (Base: low)
 High −0.14 [−0.57, 0.29]
Age: (Base: Middle age)
 Old age −0.40* [−0.75, −0.05]
Female 0.82*** [0.36, 1.28]
Race: (Base: White/Caucasian)
 Black/African American 1.54*** [0.77, 2.31]
 Other 0.04 [−1.02, 1.10]
Years of education −0.16*** [−0.23, −0.09]
Married −0.03 [−0.45, 0.39]
Log of HH income −0.06 [−0.19, 0.08]
Hypertension 0.59** [0.18, 1.00]
Diabetes 0.27 [−0.18, 0.72]
Cancer 0.85* [0.15, 1.55]
BMi: (Base: Other)
 Overweight/Obese 1.33*** [0.95, 1.72]
Constant 5.51*** [3.56, 7.46]
Observations 9960
Chi2 171.07***
Open in a new tab

95% confidence intervals in brackets.

*

p < 0.05,

**

p < 0.01,

***

p < 0.001.

Discussion

Our analysis of the relationship between religious values and beliefs with CRP levels among middle and older adults showed a well-correlated inverse relationship over eight years. The present study informs the ongoing investigation of the potential pathways through which one dimension of religion and spirituality (i.e., religious beliefs and values) may influence cognitive and physical health. The study also found that being an older Black adult was positively correlated with increased CRP levels compared to their white counterparts. These findings are similar to other studies examining race/ethnicity and CRP over an extended fifteen-year period (Fuller-Rowell et al., 2015). In addition, being female was positively associated with increased CRP levels compared to males. The difference in CRP levels by race and gender among older adults is also consistent with previous studies (Farmer et al., 2021; Khera et al., 2005).

Our findings on religious service attendance differ from a previous study that reports older adults who attended religious services weekly or more had greater reductions in CRP levels over a four-year study period (Suh et al., 2019) or only amongst Black but not White adults (Ferraro & Kim, 2014). In our study, religious beliefs and values increased while religious service attendance decreased over time. As adults age and develop health conditions (i.e., diabetes, cardiovascular issues), additional responsibilities, and functional changes, it is possible that these hurdles affect their religious service attendance. Our findings show that religious beliefs and values increase over time and therefore suggest that this may be a stronger indicator of improved health outcomes compared to religious service attendance for adults aged 52–104 years old.

The mechanisms through which religious beliefs and values influence CRP levels are not well understood, although evidence points to an indirect influence through stress.

Psychological stress, poor mental health, and unhealthy behaviors have a systemic detrimental impact on cardiovascular, neurological, and endocrinological such as cortisol and adrenaline (McEwen, 1998). For example, in response to stress, the body reacts by releasing interleukin-6 as a compensatory response (Dhabhar, 2009), which in turn, activates CRP (Volanakis, 2001). As such, the relationship between the dimension of religion and spirituality, stress, and CRP levels arises from a complex interplay of psychological, social, and biological mechanisms. Psychologically, engaging in dimensions of religion and spirituality can provide comfort and meaning, leading to reduced stress and anxiety. This reduced psychological burden translates to decreased physiological stress responses, and potentially influencing CRP production, a marker of inflammation. Socially, religious communities offer support networks and a sense of belonging, acting as buffers against the physical effects of stress (Acevedo et al., 2014; Whitehead & Bergeman, 2020).

In addition, many aspects of religious values promote healthy lifestyles by discouraging harmful behaviors like smoking (Sartor et al., 2020) and encouraging physical activity (Modell & Kardia, 2020), both of which can directly impact CRP levels. Biologically, practices like meditation and prayer, prominent in many religions, can activate the parasympathetic nervous system, promoting relaxation and potentially lowering inflammation (Amjadian et al., 2020; Mohandas, 2008; Stanley, 2013). On a cellular level, these practices may even influence the expression of genes (Waller et al., 1990) related to inflammation and stress responses.

It is notable that Black men and women tend to have higher CRP levels compared to White individuals (Khera et al., 2005), with Black women registering the highest among all racial and gender groups (Nagar et al., 2021). Despite this, Black individuals and those from various ethnic groups appear to gain more substantial benefits from religious and spiritual engagement (Chatters et al., 2009; Deseret News, 2022). Such involvement may be key in reducing stress and its associated physiological effects, including inflammation, as indicated by CRP levels.

Religious beliefs and values impart a sense of purpose, positive coping mechanisms, psychological well-being, and reduced health risk among older adults, which may influence stress levels. Holding religious beliefs and values may prompt individuals to participate in social groups and communities. For example, it provides older adults with an opportunity to engage in social activities and connect with other members of their community with a shared space for support with resources (Ellison et al., 2019). This social support network may act as a buffer against stress and help older adults cope with life’s challenges (Chai, 2022; Ejova et al., 2021; Latkin & Curry, 2003). According to a study by Del-Pino-Casado et al. (2018), social support can reduce the harmful effects of stress on health outcomes as people age.

In addition, religious beliefs and values may promote the development of positive coping mechanisms by framing a situation for greater understanding. For example, religious teachings may encourage forgiveness, patience, and resilience, which can help individuals cope with stressors (O’Brien et al., 2019). In addition, prayer and meditation can serve as tools to help individuals manage stress (Tavares et al., 2019). Religious beliefs and values may also provide older adults with a sense of purpose and meaning in life, which may inform one’s outlook and promote positivity and motivation in the face of life stressors (Ardelt & Ferrari, 2019; Haney & Rollock, 2020; Steptoe & Fancourt, 2019).

Dimensions of religion and spirituality have been linked to higher psychological well-being among older adults (Koenig et al., 2012). This includes a greater sense of life satisfaction and happiness, providing a greater sense of control over life circumstances (McDougle et al., 2016), which may help older adults feel less stressed. Involvement in religion and spirituality can also lead to reduced health risk behaviors. For example, some religious teachings may encourage healthy behaviors such as avoiding alcohol, tobacco, drug use, or risky sexual behaviors (Francis et al., 2019; Koenig et al., 2012), decreasing an individual’s risk of poor health conditions.

Our study was limited to two measures of religion and spirituality, religious beliefs and values from a validated instrument (Fetzer Institute, 2003) and religious service attendance. Additional measures such as prayer, meditation, spiritual practices, meaning, and life purpose could further elucidate the aspects of religion and spirituality that benefit cognitive and physical health. This study is also limited by potential recall bias, as both measures of religion and spirituality were self-reported. Future studies could explore causal inferences between religious beliefs and values with biological markers.

Conclusion

Our study found that higher religious beliefs, meaning, and values but not religious service attendance are associated with lower CRP levels among middle-aged and older U.S. adults. This work contributes to a greater understanding of the biological mechanisms underlying the relationship of dimensions of religion and spirituality with better cognitive and physical health, potentially through inflammation. Considering the growing economic and social burden of cognitive decline and dementia internationally, identifying innovative solutions to assist middle-aged and older adults in maintaining their religious and spiritual connection with their religious beliefs and values could support better inflammatory, cognitive, and physical health.

Supplementary Material

Supplementary Table 1

Acknowledgments

The content is solely the authors’ responsibility and does not necessarily represent the official views of the National Institutes of Health, Jonas Philanthropies, or the Rita & Alex Hillman Foundation.

Funding

This work was supported by the National Institutes of Health, National Institute on Nursing Research (5 T32NR009356), Jonas Philanthropies through the Jonas Mental Health/Psychology Scholar Program, and the Rita & Alex Hillman Foundation through The Hillman Scholars in Nursing Innovation Fund at the University of Pennsylvania School of Nursing. The HRS (Health and Retirement Study) is sponsored by the National Institute on Aging (Grant Number NIA U01AG009740) and is conducted by the University of Michigan.

Footnotes

Disclosure statement

No potential conflict of interest was reported by the author(s).

Ethics approval

Original data collection for the Health and Retirement Study received IRB approval for data collection from the University of Michigan.

Supplemental data for this article can be accessed online at https://doi.org/10.1080/13607863.2024.2335390.

Availability of data & material

Data are publicly available through registration at https://hrs.isr.umich.edu/about.

References

  1. Acevedo GA, Ellison CG, & Xu X (2014). Is it really religion? Comparing the main and stress-buffering effects of religious and secular civic engagement on psychological distress. Society and Mental Health, 4(2), 111–128. 10.1177/2156869313520558 [DOI] [Google Scholar]
  2. Aksungar FB, Topkaya AE, & Akyildiz M (2007). Interleukin-6, C-reactive protein and biochemical parameters during prolonged intermittent fasting. Annals of Nutrition and Metabolism, 51(1), 88–95. 10.1159/000100954 [DOI] [PubMed] [Google Scholar]
  3. Algahtani FD, Alsaif B, Ahmed AA, Almishaal AA, Obeidat ST, Mohamed RF, Kamel RM, Gul I, & Hassan SUN (2022). Using spiritual connections to cope with stress and anxiety during the COVID-19 pandemic. Frontiers in Psychology, 13(915290). 10.3389/fpsyg.2022.915290 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Amjadian M, Bahrami Ehsan H, Saboni K, Vahedi S, Rostami R, & Roshani D (2020). A pilot randomized controlled trial to assess the effect of Islamic spiritual intervention and of breathing technique with heart rate variability feedback on anxiety, depression and psycho-physiologic coherence in patients after coronary artery bypass surgery. Annals of General Psychiatry, 19, 1, 46. 10.1186/s12991-020-00296-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Ardelt M, & Ferrari M (2019). Effects of wisdom and religiosity on subjective well-being in old age and young adulthood: Exploring the pathways through mastery and purpose in life. International Psychogeriatrics, 31(4), 477–489. 10.1017/S1041610218001680 [DOI] [PubMed] [Google Scholar]
  6. Avan A, Tavakoly Sany SB, Ghayour-Mobarhan M, Rahimi HR, Tajfard M, & Ferns G (2018). Serum C-reactive protein in the prediction of cardiovascular diseases: Overview of the latest clinical studies and public health practice. Journal of Cellular Physiology, 233(11), 8508–8525. 10.1002/jcp.26791 [DOI] [PubMed] [Google Scholar]
  7. Braam AW, & Koenig HG (2019). Religion, spirituality and depression in prospective studies: A systematic review. Journal of Affective Disorders, 257, 428–438. 10.1016/j.jad.2019.06.063 [DOI] [PubMed] [Google Scholar]
  8. Britt KC, Kwak J, Acton G, Richards KC, Hamilton J, & Radhakrishnan K (2022). Measures of religion and spirituality in dementia: An integrative review. Alzheimer’s Dement, 8, e12352. 10.1002/trc2.12352 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Callaghan BL, & Tottenham Nim. (2016). The Stress Acceleration Hypothesis: Effects of early-life adversity on emotion circuits and behavior. Current Opinion in Behavioral Sciences, 7, 76–81. 10.1016/j.cobeha.2015.11.018 29644262 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Chai L (2022). Does religion buffer against the detrimental effect of cyberbullying victimization on adults’ health and well-Being? Evidence from the 2014 Canadian General Social Survey. Journal of Interpersonal Violence, 37(21–22), NP19983–NP20011. 10.1177/08862605211050092 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Chatters LM, Taylor RJ, Bullard KM, & Jackson JS (2009). Race and ethnic differences in religious involvement: African Americans, Caribbean blacks and non-Hispanic whites. Ethnic and Racial Studies, 32(7), 1143–1163. 10.1080/01419870802334531 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Coin A, Perissinotto E, Najjar M, Girardi A, Inelmen EM, Enzi G, Manzato E, & Sergi G (2010). Does religiosity protect against cognitive and behavioral decline in Alzheimer’s dementia ? Current Alzheimer Research, 7(5), 445–452. 10.2174/156720510791383886 [DOI] [PubMed] [Google Scholar]
  13. Corsentino EA, Collins N, Sachs-Ericsson N, & Blazer DG (2009). Religious attendance reduces cognitive decline among older women with high levels of depressive symptoms. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 64(12), 1283–1289. 10.1093/gerona/glp116 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Crimmins E, Faul J, Kim JK, Guyer H, Langa K, Ofstedal MB, … Weir D (2013). HRS Documentation Report Documentation of Biomarkers in the 2006 and 2008 Health and Retirement Study. https://hrs.isr.umich.edu/publications/biblio/5954
  15. Del-Pino-Casado R, Frías-Osuna A, Palomino-Moral PA, Ruzafa-Martínez M, & Ramos-Morcillo AJ (2018). Social support and subjective burden in caregivers of adults and older adults: A meta-analysis. PLoS One, 13(1), e0189874. 10.1371/journal.pone.0189874 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Deseret News. (2022). Marist Poll. Faith in America Survey. https://media.deseret.com/media/misc/pdf/faith-in-america/Faith-in-America-SurveySummary-Report.pdf?_ga=2.60230637.1360664744.1706305043-590004380.1706305041
  17. Dhabhar FS (2009). A hassle a day may keep the pathogens away: The fight-or-flight stress response and the augmentation of immune function. Integrative and Comparative Biology, 49(3), 215–236. 10.1093/icb/icp045 [DOI] [PubMed] [Google Scholar]
  18. Ejova A, Milojev P, Worthington EL, Sibley C. G. c 2. J., & Bulbulia J (2021). Church attendance buffers against longer-term mental distress. Religion, Brain & Behavior, 11(2), 123–138. 10.1080/2153599X.2020.1831580 [DOI] [Google Scholar]
  19. Ellison CG, Deangelis RT, Hill TD, & Froese P (2019). Sleep quality and the stress-buffering role of religious involvement: A mediated moderation analysis. Journal for the Scientific Study of Religion, 58(1), 251–268. 10.1111/jssr.12581 [DOI] [Google Scholar]
  20. Farmer HR, Wray LA, & Haas SA (2021). Race, Gender, and Socioeconomic Variations in C-Reactive Protein Using the Health and Retirement Study. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 76(3), 583–595. 10.1093/geronb/gbaa027 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Ferraro KF, & Kim S (2014). Health benefits of religion among Black and White older adults? Race, religiosity, and C-reactive protein. Social Science & Medicine (1982), 120, 92–99. 10.1016/j.socscimed.2014.08.030 [DOI] [PubMed] [Google Scholar]
  22. Fetzer Institute. (2003). Brief Multidimensional Measure of Religiousness/Spirituality: 1999. In Group NW (Ed.), Multidimensional measurement of religiousness/spirituality for use in health research: A report of the Fetzer Institute/National Institute on Aging Working Group (2nd ed., pp. 85–88). John E. Fetzer Institute. [Google Scholar]
  23. Ford ES, Loucks EB, & Berkman LF (2006). Social integration and concentrations of C-reactive protein among US adults. Annals of Epidemiology, 16(2), 78–84. 10.1016/j.annepidem.2005.08.005 [DOI] [PubMed] [Google Scholar]
  24. Francis JM, Myers B, Nkosi S, Petersen Williams P, Carney T, Lombard C, Nel E, & Morojele N (2019). The prevalence of religiosity and association between religiosity and alcohol use, other drug use, and risky sexual behaviours among grade 8–10 learners in Western Cape, South Africa. PloS One, 14(2), e0211322. 10.1371/journal.pone.0211322 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Fuller-Rowell TE, Curtis DS, Doan SN, & Coe CL (2015). Racial disparities in the health benefits of educational attainment: A study of inflammatory trajectories among African American and white adults. Psychosomatic Medicine, 77(1), 33–40. 10.1097/PSY.0000000000000128 [DOI] [PubMed] [Google Scholar]
  26. George LK, Ellison CG, & Larson DB (2002). Explaining the relationships between religious involvement and health. Psychological Inquiry, 13(3), 190–200. 10.1207/S15327965PLI1303_04 [DOI] [Google Scholar]
  27. Haney AM, & Rollock D (2020). A matter of faith: The role of religion, doubt, and personality in emerging adult mental health. Psychology of Religion and Spirituality, 12(2), 247–253. 10.1037/rel0000231 [DOI] [Google Scholar]
  28. Health and Retirement Study. (2019). RAND HRS Longitudinal File 2016 (V1) Public Use Dataset. Produced and distributed by the University of Michigan with funding from the National Institute on Aging (grant number NIA U01AG009740). University of Michigan [Google Scholar]
  29. Hegazy SH, Thomassen JQ, Rasmussen IJ, Nordestgaard BG, Tybjaerg-Hansen A, & Frikke-Schmidt R (2022). C-reactive protein levels and risk of dementia-Observational and genetic studies of 111,242 individuals from the general population. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 18(11), 2262–2271. 10.1002/alz.12568 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Hill TD, Angel JL, Ellison CG, & Angel RJ (2005). Religious attendance and mortality: An 8-year follow-up of older Mexican Americans. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 60(2), S102–S109. 10.1093/geronb/60.2.s102 [DOI] [PubMed] [Google Scholar]
  31. Hill TD, Vaghela P, Ellison CG, & Rote S (2017). Processes Linking Religious Involvement and Telomere Length. Biodemography and Social Biology, 63(2), 167–188. 10.1080/19485565.2017.1311204 [DOI] [PubMed] [Google Scholar]
  32. Holt-Lunstad J, Steffen PR, Sandberg J, & Jensen B (2011). Understanding the connection between spiritual well-being and physical health: An examination of ambulatory blood pressure, inflammation, blood lipids and fasting glucose. Journal of Behavioral Medicine, 34(6), 477–488. 10.1007/s10865-011-9343-7 [DOI] [PubMed] [Google Scholar]
  33. Hosseini S, Chaurasia A, & Oremus M (2019). The Effect of Religion and Spirituality on Cognitive Function: A Systematic Review. The Gerontologist, 59(2), e76–e85. 10.1093/geront/gnx024 [DOI] [PubMed] [Google Scholar]
  34. Hummer RA, Rogers RG, Nam CB, & Ellison CG (1999). Religious involvement and U.S. adult mortality. Demography, 36(2), 273–285. 10.2307/2648114 [DOI] [PubMed] [Google Scholar]
  35. Ingram RE, & Price JM (2001). Vulnerability to psychopathology: Risk across the lifespan. The Guilford Press. [Google Scholar]
  36. Kelly ME, Duff H, Kelly S, McHugh Power JE, Brennan S, Lawlor BA, & Loughrey DG (2017). The impact of social activities, social networks, social support and social relationships on the cognitive functioning of healthy older adults: a systematic review. Systematic Reviews, 6(1), 259. 10.1186/s13643-017-0632-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Khera A, McGuire DK, Murphy SA, Stanek HG, Das SR, Vongpatanasin W, Wians FH Jr, Grundy SM, & de Lemos JA (2005). Race and gender differences in C-reactive protein levels. Journal of the American College of Cardiology, 46(3), 464–469. 10.1016/j.jacc.2005.04.051 [DOI] [PubMed] [Google Scholar]
  38. Kidwai R, Mancha BE, Brown QL, & Eaton WW (2014). The effect of spirituality and religious attendance on the relationship between psychological distress and negative life events. Social Psychiatry and Psychiatric Epidemiology, 49(3), 487–497. 10.1007/s00127-013-0723-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. King DE, Mainous AG 3rd, Steyer TE, & Pearson W (2001). The relationship between attendance at religious services and cardiovascular inflammatory markers. International Journal of Psychiatry in Medicine, 31(4), 415–425. 10.2190/F4MP-KLYE-VED4-3LDD [DOI] [PubMed] [Google Scholar]
  40. Koenig HG, George LK, & Titus P (2004). Religion, spirituality, and health in medically ill hospitalized older patients. Journal of the American Geriatrics Society, 52(4), 554–562. 10.1111/j.1532-5415.2004.52161.x [DOI] [PubMed] [Google Scholar]
  41. Koenig HG, King DE, & Carson VB (2012). Handbook of religion and health (2nd ed.). Oxford University Press. [Google Scholar]
  42. Koenig HG, VanderWeele T, & Petite JR (2023). Handbook of religion and health (3rd ed.). Oxford University Press. [Google Scholar]
  43. Köhler-Forsberg O, Buttenschøn HN, Tansey KE, Maier W, Hauser J, Dernovsek MZ, Henigsberg N, Souery D, Farmer A, Rietschel M, McGuffin P, Aitchison KJ, Uher R, & Mors O (2017). Association between C-reactive protein (CRP) with depression symptom severity and specific depressive symptoms in major depression. Brain, Behavior, and Immunity, 62, 344–350. 10.1016/j.bbi.2017.02.020 [DOI] [PubMed] [Google Scholar]
  44. Kuczmarski RJ, & Flegal KM (2000). Criteria for definition of overweight in transition: Background and recommendations for the United States. The American Journal of Clinical Nutrition, 72(5), 1074–1081. 10.1093/ajcn/72.5.1074 [DOI] [PubMed] [Google Scholar]
  45. Latkin CA, & Curry AD (2003). Stressful neighborhoods and depression: A prospective study of the impact of neighborhood disorder. Journal of Health and Social Behavior, 44(1), 34–44. [PubMed] [Google Scholar]
  46. Lazarus RS, & Folkman S (1984). Stress, appraisal, and coping. Springer. [Google Scholar]
  47. Lewis NA, & Knight JE (2021). Longitudinal associations between C-reactive protein and cognitive performance in normative cognitive ageing and dementia. Age and Ageing, 50(6), 2199–2205. 10.1093/ageing/afab152 [DOI] [PubMed] [Google Scholar]
  48. Li S, Stampfer MJ, Williams DR, & VanderWeele TJ (2016). Association of religious service attendance with mortality among women. JAMA Internal Medicine, 176(6), 777–785. 10.1001/jamainternmed.2016.1615 [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Li Y, Zhong X, Cheng G, Zhao C, Zhang L, Hong Y, Wan Q, He R, & Wang Z (2017). Hs-CRP and all-cause, cardiovascular, and cancer mortality risk: A meta-analysis. Atherosclerosis, 259, 75–82. 10.1016/j.atherosclerosis.2017.02.003 [DOI] [PubMed] [Google Scholar]
  50. Lucchese FA, & Koenig HG (2013). Religion, spirituality and cardiovascular disease: Research, clinical implications, and opportunities in Brazil. Revista Brasileira de Cirurgia Cardiovascular: Orgao Oficial da Sociedade Brasileira de Cirurgia Cardiovascular, 28(1), 103–128. 10.5935/1678-9741.20130015 [DOI] [PubMed] [Google Scholar]
  51. Lucchetti G, Koenig HG, & Lucchetti ALG (2021). Spirituality, religiousness, and mental health: A review of the current scientific evidence. World Journal of Clinical Cases, 9(26), 7620–7631. 10.12998/wjcc.v9.i26.7620 [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. McDougle L, Konrath S, Walk M, & Handy F (2016). Religious and secular coping strategies and mortality risk among older adults. Social Indicators Research, 125(2), 677–694. 10.1007/s11205-014-0852-y [DOI] [Google Scholar]
  53. McEwen B (1998). Protective and damaging effects of stress mediators. The New England Journal of Medicine, 338(3), 171–179. 10.1056/NEJM199801153380307 [DOI] [PubMed] [Google Scholar]
  54. Modell SM, & Kardia SLR (2020). Religion as a Health Promoter During the 2019/2020 COVID Outbreak: View from Detroit. Journal of Religion and Health, 59(5), 2243–2255. 10.1007/s10943-020-01052-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Mohandas E (2008). Neurobiology of spirituality. MENS Sana Monographs, 6(1), 63–80. 10.4103/0973-1229.33001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Nagar SD, Conley AB, Sharma S, Rishishwar L, Jordan IK, & Mariño-Ramírez L (2021). Comparing genetic and socioenvironmental contributions to ethnic differences in C-reactive protein. Frontiers in Genetics, 12, 738485. 10.3389/fgene.2021.738485 [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Noble JM, Manly JJ, Schupf N, Tang MX, Mayeux R, & Luchsinger JA (2010). Association of C-reactive protein with cognitive impairment. Archives of Neurology, 67(1), 87–92. 10.1001/archneurol.2009.308 [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. O’Brien B, Shrestha S, Stanley MA, Pargament KI, Cummings J, Kunik ME, Fletcher TL, Cortes J, Ramsey D, & Amspoker AB (2019). Positive and negative religious coping as predictors of distress among minority older adults. International Journal of Geriatric Psychiatry, 34(1), 54–59. 10.1002/gps.4983 [DOI] [PubMed] [Google Scholar]
  59. Ockene IS, Matthews CE, Rifai N, Ridker PM, Reed G, & Stanek E (2001). Variability and classification accuracy of serial high-sensitivity C-reactive protein measurements in healthy adults. Clinical Chemistry, 47(3), 444–450. 10.1093/clinchem/47.3.444 [DOI] [PubMed] [Google Scholar]
  60. Oman D, Kurata JH, Strawbridge WJ, & Cohen RD (2002). Religious attendance and cause of death over 31 years. International Journal of Psychiatry in Medicine, 32(1), 69–89. 10.2190/RJY7-CRR1-HCW5-XVEG [DOI] [PubMed] [Google Scholar]
  61. Pace TWW, Mletzko TC, Alagbe O, Musselman DL, Nemeroff CB, Miller AH, & Heim CM (2006). Increased stress-induced inflammatory responses in male patients with major depression and increased early life stress. The American Journal of Psychiatry, 163(9), 1630–1633. 10.1176/ajp.2006.163.9.1630 16946190 [DOI] [PubMed] [Google Scholar]
  62. Pearson TA, Mensah GA, Alexander RW, Anderson JL, Cannon RO 3rd, Criqui M, Fadl YY, Fortmann SP, Hong Y, Myers GL, Rifai N, Smith SC Jr, Taubert K, Tracy RP, & Vinicor F, American Heart Association. (2003). Markers of inflammation and cardiovascular disease: Application to clinical and public health practice: A statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation, 107(3), 499–511. 10.1161/01.cir.0000052939.59093.45 [DOI] [PubMed] [Google Scholar]
  63. Piolatto M, Bianchi F, Rota M, Marengoni A, Akbaritabar A, & Squazzoni F (2022). The effect of social relationships on cognitive decline in older adults: An updated systematic review and meta-analysis of longitudinal cohort studies. BMC Public Health, 22(1), 278. 10.1186/s12889-022-12567-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. RAND. (2019). RAND HRS Longitudinal File 2016 (V1). Produced by the RAND Center for the Study of Aging, with funding from the National Institute on Aging and the Social Security Administration. RAND. [Google Scholar]
  65. Renna ME (2021). A review and novel theoretical model of how negative emotions influence inflammation: The critical role of emotion regulation. Brain, Behavior, & Immunity - Health, 18, 100397. 10.1016/j.bbih.2021.100397 [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Rogers R, Krueger P, & Hummer R (2010). Religious attendance and cause-specific mortality in the United States. In Ellison CG & Hummer RA (Eds.), Religion, families, and health: Population-based research in the United States (pp. 292–320). Rutgers. [Google Scholar]
  67. Sartor CE, Hipwell AE, & Chung T (2020). Public and private religious involvement and initiation of alcohol, cigarette, and marijuana use in Black and White adolescent girls. Social Psychiatry and Psychiatric Epidemiology, 55(4), 447–456. 10.1007/s00127-020-01830-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Sesso HD, Buring JE, Rifai N, Blake GJ, Gaziano JM, & Ridker PM (2003). C-reactive protein and the risk of developing hypertension. JAMA, 290(22), 2945–2951. 10.1001/jama.290.22.2945 [DOI] [PubMed] [Google Scholar]
  69. Slavich GM, & Irwin MR (2014). From stress to inflammation and major depressive disorder: A social signal transduction theory of depression. Psychological Bulletin, 140(3), 774–815. 10.1037/a0035302 [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Stanley R (2013). Pathophysiologic Basis and Application of Spiritual Healing Practices in Chronic Illness. In Chronic illness, spirituality, and healing: diverse disciplinary, religious, and cultural perspectives (pp. 85–114). Palgrave Macmillan; US. [Google Scholar]
  71. Steptoe A, & Fancourt D (2019). Leading a meaningful life at older ages and its relationship with social engagement, prosperity, health, biology, and time use. Proceedings of the National Academy of Sciences of the United States of America, 116(4), 1207–1212. 10.1073/pnas.1814723116 [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Suh H, Hill TD, & Koenig HG (2019). Religious attendance and biological risk: A national longitudinal study of older adults. Journal of Religion and Health, 58(4), 1188–1202. 10.1007/s10943-018-0721-0 [DOI] [PubMed] [Google Scholar]
  73. Tavares JL, Ronneberg CR, Miller EA, & Burr JA (2019). Stress and inflammation among older adults: The moderating role of religiosity. Journal of Religion, Spirituality & Aging, 31(2), 187–202. 10.1080/15528030.2018.1536910 [DOI] [Google Scholar]
  74. VanderWeele TJ, Yu J, Cozier YC, Wise L, Argentieri MA, Rosenberg L, Palmer JR, & Shields AE (2017). Attendance at religious services, prayer, religious coping, and religious/spiritual identity as predictors of all-cause mortality in the black women’s health study. American Journal of Epidemiology, 185(7), 515–522. 10.1093/aje/kww179 [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Verma S, & Yeh ET (2003). C-reactive protein and atherothrombosis–beyond a biomarker: An actual partaker of lesion formation. American Journal of Physiology. Regulatory, Integrative and Comparative Physiology, 285(5), R1253–R1256. 10.1152/ajpregu.00170.2003 [DOI] [PubMed] [Google Scholar]
  76. Volanakis JE (2001). Human C-reactive protein: Expression, structure, and function. Molecular Immunology, 38(2–3), 189–197. 10.1016/s0161-5890(01)00042-6 [DOI] [PubMed] [Google Scholar]
  77. Wallensten J, Ljunggren G, Nager A, Wachtler C, Bogdanovic N, Petrovic P, & Carlsson AC (2023). Stress, depression, and risk of dementia - a cohort study in the total population between 18 and 65 years old in Region Stockholm. Alzheimer’s Research & Therapy, 15(1), 161. 10.1186/s13195-023-01308-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  78. Waller NG, Kojetin BA, Bouchard TJ Jr., Lykken DT, & Tellegen A (1990). Genetic and environmental influences on religious interests, attitudes and values: A study of twins reared apart and together. Psychological Science, 1(2), 138–142. 10.1111/j.1467-9280.1990.tb00083.x [DOI] [Google Scholar]
  79. White IR, & Carlin JB (2010). Bias and efficiency of multiple imputation compared with complete-case analysis for missing covariate values. Statistics in Medicine, 29(28), 2920–2931. 10.1002/sim.3944 [DOI] [PubMed] [Google Scholar]
  80. Whitehead BR, & Bergeman CS (2020). Daily religious coping buffers the stress–affect relationship and benefits overall metabolic health in older adults. Psychology of Religion and Spirituality, 12(4), 393–399. 10.1037/rel0000251 [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Yashin AI, Arbeev KG, Kulminski A, Akushevich I, Akushevich L, & Ukraintseva SV (2007). Health decline, aging and mortality: How are they related? Biogerontology, 8(3), 291–302. 10.1007/s10522-006-9073-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  82. Zuckerman M (2009). Vulnerability to psychopathology: A biosocial model (1st ed.) American Psychological Association. [Google Scholar]
  83. Zwingmann C, Klein C, & Büssing A (2011). Measuring religiosity/spirituality: theoretical differentiations and categorization of instruments. Religions, 2(3), 345–357. https://www.mdpi.com/2077-1444/2/3/345 10.3390/rel2030345 [DOI] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Table 1
NIHMS1982756-supplement-Supplementary_Table_1.docx (39.6KB, docx)

Data Availability Statement

Data are publicly available through registration at https://hrs.isr.umich.edu/about.

RESOURCES