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. Author manuscript; available in PMC: 2022 Jan 1.
Published in final edited form as: Psychosom Med. 2021 Nov-Dec;83(9):987–994. doi: 10.1097/PSY.0000000000000976

The Cumulative Impact of Chronic Stressors on Risks for Myocardial Infarction in U.S. Older Adults

Matthew E Dupre 1,2,3,4, Heather R Farmer 5, Hanzhang Xu 6,7, Ann Marie Navar 8, Michael G Nanna 2,9, Linda K George 3,4,10, Eric D Peterson 8
PMCID: PMC8578196  NIHMSID: NIHMS1719358  PMID: 34297011

Abstract

Objective:

To investigate the association between cumulative exposure to chronic stressors and the incidence of myocardial infarction (MI) in U.S. older adults.

Methods:

Nationally-representative prospective cohort data of adults aged 45 and older (n=15,109) were used to investigate the association between the cumulative number of chronic stressors and incidence of MI in U.S. older adults. Proportional hazards models adjusted for confounding risk factors and differences by sex, race/ethnicity, and history of MI were assessed.

Results:

The median age of participants was 65 years, 714 (4.7%) had a prior MI, and 557 (3.7%) had an MI during follow-up. Approximately 84% of participants reported at least one chronic stressor at baseline and more than half reported 2 or more stressors. Multivariable models showed that risks for MI increased incrementally from 1 chronic stressor (HR=1.28; 95% CI, 1.20–1.37) to 4 or more chronic stressors (HR=2.71; 95% CI, 2.08–3.53) compared with those who reported no stressors. These risks were only partly reduced after adjustments for multiple demographic, socioeconomic, psychosocial, behavioral, and clinical risk factors. In adults who had a prior MI (P value for interaction=.038), we found that risks for a recurrent event increased substantially from 1 chronic stressor (HR=1.30; 95% CI, 1.09–1.54) to 4 or more chronic stressors (HR=2.85; 95% CI, 1.43–5.69).

Conclusions:

Chronic life stressors are significant independent risk factors for cardiovascular events in U.S. older adults. The risks associated with multiple chronic stressors were especially high in adults with a previous MI.

Keywords: chronic stress, myocardial infarction, social determinants of health, stress proliferation

INTRODUCTION

Nearly 1 million Americans will experience a first or recurrent myocardial infarction (MI) this year, and nearly 1-in-7 will die as a result (1). In 2015, the American Heart Association (AHA) issued a scientific statement calling for more research to address the psychosocial factors contributing to the “third arm of risk” for cardiovascular disease (CVD) (2). There is now increasing evidence to suggest that long-term exposure to stress contributes to the development and progression of coronary heart disease (3–8). Studies have shown that individuals who face ongoing stressors are much more likely to engage in unhealthy behaviors (smoking, inactivity, etc.) (9,10) and exhibit heightened physiological responses (elevated cortisol, inflammation, etc.) (2,11,12) that put them at increased risk for an acute coronary event. There is also evidence to suggest that exposure to chronic stressors increases the risk for a recurrent coronary event in individuals with a history of CVD (3,13).

Prior studies suggest that chronic stress contributes to cardiovascular-related pathology through a complex nexus of social, behavioral, and physiological processes that can trigger the cascade of multiple biological regulatory systems (2,12,14–17). When a stressor is perceived as challenging or threatening, a physiological stress response is activated—primarily from the sympathetic nervous system and the hypothalamic-pituitary-adrenal axis (HPA-axis)—releasing catecholamines and glucocorticoids to manage the body’s response to the stressor (fight-or-flight response; 12,16,18). Although this is generally a protective/adaptive process, prolonged exposure to persistent, ongoing stressors may result in the dysregulation of these systems (“wear and tear”) that can increase vulnerability to a wide range of health problems, including CVD (12,19–22). However, much of what we know about chronic stress and MI is based on exposure to a specific stressor (caregiving, unemployment, etc.) or in a specific population (nurses, veterans, etc.) (6,14,23–27).

According to recent estimates, more than half of all U.S. adults report having at least two chronic stressors in their life; and upwards of a quarter report three or more sources of stress (28–30). Research shows that exposure to one stressor often leads to stressors in other domains of life (stress proliferation)—arising from financial strain, caregiving, close relationships, and elsewhere. For example, financial hardship and/or family discord often follow the loss of employment (31); likewise, the demands of caregiving may proliferate to tensions in one’s marriage or work obligations (32). However, studies have not considered how the accumulation of chronic stressors impact risks for MI.

This study is the first prospective investigation of the cumulative impact of chronic stress on risks for MI in U.S. older adults. Data from a large nationally-representative study of middle-aged and older adults were used to examine how the number of chronic stressors was associated with the incidence of MI while adjusting for multiple socioeconomic, psychosocial, behavioral, and clinical factors. We also examined whether the associations differed by sex, race/ethnicity, and history of MI.

METHODS

Study Population

Nationally-representative data from the Health and Retirement Study (HRS) were used for analysis. Sponsored by the National Institute on Aging and the Social Security Administration, the HRS is the largest ongoing prospective study of middle-aged and older adults in the United States (33). Launched in 1992, the HRS has interviewed more than 20,000 study participants every 24 months and has added multiple new cohorts since 1998 to maintain a nationally-representative (and aging) sample of U.S. older adults over time. Since 2006, a 50% random sample of HRS participants is selected in alternating waves to complete an enhanced face-to-face interview. As part of these procedures, data are collected from detailed physical exams, blood-spot samples, and a Psychosocial and Lifestyle Questionnaire every 48 months to supplement the core survey responses for all HRS participants. Further details of the multistage sampling design, data collection procedures, and response rates have been documented extensively elsewhere (34–37). The HRS survey data are publicly available and the physiological data are available to researchers with an approved Sensitive Data Access Use Agreement. The study was deemed exempt by the Duke University Institutional Review Board because the data were de-identified.

Data for the current study come from 17,134 participants who completed the HRS psychosocial interview and were followed from 2006 to 2016. The study was limited to adults aged 45–85 at baseline to reduce selection bias at advanced ages and included adults with complete data on age, sex, race/ethnicity, and chronic stressors at baseline (Supplemental Figure 1, Supplemental Digital Content). The final analytic sample included 15,109 participants who contributed 89,730 person-years over the 10-year study period. The sampling characteristics (age, sex, race/ethnicity, and geographic region) of participants in the final analytic sample were consistent with participants who completed the psychosocial interview and the overall HRS survey.

Measurement

Ongoing chronic stressors were ascertained based on responses to the Psychosocial and Lifestyle Questionnaire administered in the HRS (30,34,38–42). Participants were asked whether or not they were experiencing any of the following problems for the last twelve months or longer: (1) personal health problems, (2) problems in a close relationship, (3) financial strain, (4) housing problems, or (5) providing care to a family member or friend. Three additional stressors —i.e., physical or emotional problems in a spouse/child, problems with drugs or alcohol in a family member, and difficulties at work—were assessed in preliminary analyses and ultimately dropped due to their low frequency and/or relevance to all study participants (e.g., retired, never married, no children, etc.). The cumulative number of ongoing chronic stressors was included as a time-varying measure and was winsorized (4+ stressors were grouped) to account for the skewed distribution of stressors and to reduce potential bias from outliers (4%) who reported experiencing all five stressors (39,40).

Multivariable models adjusted for background demographic factors that included age (years), sex (male or female), race/ethnicity (Non-Hispanic White, non-Hispanic Black, non-Hispanic other, or Hispanic), and geographic region (South or other region). Previously identified cardiovascular risks were also examined as possible factors contributing to the associations and included educational attainment (in years), employment status (currently employed, unemployed, or retired), household income (total household income [in dollars] logged), marital status (currently married or not), living arrangement (lives alone, with 2–4 persons, or 5+ persons), social support (based on 3-item scale; range=0–3), depressive symptoms (measured by the 8-item Center for Epidemiologic Studies Depression [CES-D] scale; range=0–8), current smoking status (currently smokes or not), alcohol use (no alcohol consumption, moderate consumption [1–2 drinks/day], or heavy consumption [≥ 3 drinks/day]), physical inactivity (engages in moderate/vigorous physical activity or not), body mass index ([BMI], calculated as weight in kilograms divided by height in meters squared), any reported limitations in activities of daily living (ADL), self-reported disease diagnoses (hypertension [HTN], diabetes mellitus [DM], chronic obstructive pulmonary disease [COPD], cancer, and other [non-MI] cardiovascular-related conditions), systolic blood pressure ([BP], mmHg), total cholesterol (mg/dL), and C-reactive protein ([CRP], <1.0 mg/L, 1.0–3.0 mg/L, or >3.0 mg/L) (34–37,43). Further details of the study covariates are provided in Supplemental Table 1.

With the exception of age, sex, and race/ethnicity, all covariates were time-varying in the analyses to maintain the temporal order of chronic stressors and covariates prior to a subsequent MI. Missing data were limited across study measures (0–1.8%)—with the exception of systolic BP (12.1%), cholesterol (24.0%), and CRP (24.7%). Results from Little’s MCAR test suggested that data were not missing completely at random (Chi-square=11109.72, p < .001; 44). To reduce bias in estimation, we used multiple imputation methods (chained equations) to account for missing data in covariates included the multivariable models described below (44,45). Additional analyses using complete data (listwise deletion) produced results that were consistent with those reported here.

Outcome Measure

Incidence of MI was the main outcome for analysis. Study participants were first asked “has a doctor ever told you that you had a heart attack, coronary heart disease, angina, congestive heart failure, or other heart problems?” For those who reported yes, participants were then asked if they “had a heart attack or myocardial infarction” in the past 2 years (since the last interview) and in what month and year it occurred. Although participants’ reports of MI are less precise than clinical data, studies have shown that self-reported MI has a moderate to high degree of sensitivity, specificity, and overall agreement with medical data (46–49). The measures used in this study are also consistent with those used by AHA and the Centers for Disease Control and Prevention (CDC) when reporting national estimates of MI (1,50). For adults who had an MI, the outcome corresponds to the number of months from study entry until the date of the event. Incident MI events were ascertained after the assessment of chronic stressors and other covariates based on the timing of interview dates and subsequent event dates. For those who did not experience an MI, the outcome corresponds to the number of months until respondents were last observed to be disease-free. Adults who reported an MI prior to baseline (n=714; 4.7%) were included to account for risks associated with a first or recurrent MI. Participants who died during the 10-year study period (n=2,358; 15.6%) were censored at their time of death (primary analyses) and treated as a competing risk (sensitivity analyses) as described below.

Statistical Analysis

Baseline characteristics were computed for all HRS participants, by number of stressors, and by MI outcome status. Bivariate comparisons were calculated with Wilcoxon-Mann-Whitney, Kruskall-Wallis, and χ2 tests as appropriate. Multivariable Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for MI associated with the number of chronic stressors. Preliminary analyses assessed the count of chronic stressors as continuous and categorical variables. Results from likelihood-ratio tests, Bayesian information criterion, and Wald tests—along with the graded magnitude of estimated coefficients—indicated that the continuous measure was more efficient and most appropriate for analysis. Results from these analyses are presented at incremental numbers of stressors (0–4) to facilitate interpretation.

Cumulative hazard rates adjusted for age, sex, race/ethnicity, and region were plotted to describe overall differences in MI related to the number of chronic stressors. A series of multivariable models were then estimated to examine the association between chronic stressors and MI while adding measures for demographic background, socioeconomic factors, psychosocial factors, behavioral factors, and clinical factors. A final set of analyses included interactions to test for differences by sex, race/ethnicity, and prior MI.

Several sets of sensitivity analyses were also conducted. First, competing-risk models were estimated to assess potential bias due to mortality during the study period (51). Results from these models were nearly identical to those presented here—with only negligible changes in the point estimates (± 0.001). Second, tests of interactions with analysis time and tests of Schoenfeld residuals indicated that the proportional hazards assumption was not violated. Third, results from weighted and unweighted data were consistent in our preliminary analyses; therefore, the data were not weighted because the multivariable models included variables related to the sampling design (age, sex, race, region) to produce unbiased estimates (52). Fourth, sensitivity analyses that removed the health-related stressor (as a potential proxy of clinical status/severity) produced results that were consistent with the fully-identified models. Finally, the number of tied events relative to the number at risk was low; and partial likelihood estimation was nearly identical using Breslow (reported herein) and Efron approximations. All analyses were conducted using Stata 16.1.

RESULTS

Baseline characteristics of the study participants are presented by outcome status (Table 1) and by number of chronic stressors (Supplemental Table 2). The median age of study participants was 65 years, 714 (4.7%) had a prior MI, and 557 (3.7%) had an MI during follow-up. Adults who had an MI were more likely to be older, male, non-Hispanic white, living in the South, retired, and have lower levels of education and income than those without an event. Adults with unfavorable psychosocial characteristics, unhealthy behaviors, and poor physiological status also had higher rates of MI than their counterparts. Approximately 84% of participants reported at least one chronic stressor at baseline and more than half reported 2-or-more stressors. Overall rates of MI were higher in participants who reported exposure to greater numbers of chronic stressors (P ≤ .001). Personal health problems, financial strains, and caregiving were the most frequently reported sources of ongoing stress (Supplemental Table 3).

Table 1.

Characteristics of Study Participants at Baseline, HRS

Total
(n = 15,109)		 MI Group
(n = 557)		 Non-MI Group
(n = 14,552)		 P value Missing
 Number of chronic stressors, mean (SD) 1.8 (1.2) 2.0 (1.2) 1.8 (1.2) <.001
 Number of chronic stressors
  0 2459 (16.3) 58 (10.4) 2401 (16.5) <.001
  1 4438 (29.4) 163 (29.3) 4275 (29.4)
  2 3946 (26.1) 143 (25.7) 3803 (26.1)
  3 2396 (15.9) 106 (19.0) 2290 (15.7)
  4+ 1870 (12.4) 87 (15.6) 1783 (12.3)
Demographic Background
 Age, mean (SD), y 65 (16) 68 (15) 65 (16) <.001
 Sex (male) 6340 (42.0) 304 (54.6) 6036 (41.5) <.001
 Race/ethnicity
  Non-Hispanic White 10704 (70.9) 422 (75.8) 10282 (70.7) .023
  Non-Hispanic Black 2404 (15.9) 72 (12.9) 2332 (16.0)
  Non-Hispanic other race 434 (2.9) 8 (1.4) 426 (2.9)
  Hispanic 1567 (10.4) 55 (9.9) 1512 (10.4)
 Region (South) 6145 (40.7) 253 (45.4) 5892 (40.5) .020 5 (0.03)
Socioeconomic Factors
 Educational attainment, mean (SD),y 12.8 (3.0) 12.2 (2.9) 12.9 (3.0) <.001 60 (0.4)
 Employment status
  Employed 5090 (33.7) 125 (22.4) 4965 (34.1)
  Unemployed 1638 (10.8) 60 (10.8) 1578 (10.8) <.001
  Retired 8381 (55.5) 372 (66.8) 8009 (55.0)
 H.H. income, median (IQR), $ thousands 42.9 (59.5) 35.4 (45.1) 43.2 (60.2) <.001
Psychosocial Factors
 Currently married 9733 (64.4) 357 (64.1) 9376 (64.4) .869 1 (0.01)
 Living arrangement
  Lives alone 3041 (20.1) 116 (20.8) 2925 (20.1)
  2–4 persons 11224 (74.3) 412 (74.0) 10812 (74.3) .862
  5+ persons 844 (5.6) 29 (5.2) 815 (5.6)
 Social support, mean (SD) 2.1 (0.5) 2.1 (0.6) 2.1 (0.5) .034 40 (0.3)
 Depressive symptoms, mean (SD) 1.4 (2.0) 1.9 (2.3) 1.4 (1.9) <.001 266 (1.8)
Behavioral Factors
 Currently smokes 2274 (15.1) 124 (22.3) 2150 (14.9) <.001 91 (0.6)
 Alcohol consumption
  None 9401 (62.3) 384 (68.9) 9017 (62.1) .003 25 (0.2)
  Moderate 4278 (28.4) 125 (22.4) 4153 (28.6)
  Heavy 1405 (9.3) 48 (8.6) 1357 (9.3)
 Physical inactivity 2648 (17.5) 131 (23.5) 2517 (17.3) <.001 15 (0.1)
Clinical Factors
 Body mass index, mean (SD) 28.7 (6.2) 29.3 (5.9) 28.7 (6.2) .027 190 (1.3)
 ADL limitations 2176 (14.4) 111 (19.9) 2065 (14.2) <.001
 Diagnoses
  Prior MI 714 (4.7) 91 (16.3) 623 (4.3) <.001
  Hypertension 8600 (57.0) 397 (71.5) 8203 (56.4) <.001 13 (0.1)
  Diabetes 3247 (21.5) 192 (34.5) 3055 (21.0) <.001 9 (0.1)
  COPD 1505 (10.0) 83 (14.9) 1422 (9.8) <.001 9 (0.1)
  Other cardiovascular conditions 3395 (22.5) 250 (44.9) 3145 (21.6) <.001 4 (0.03)
  Cancer 2110 (14.0) 96 (17.2) 2014 (13.9) .024 6 (0.04)
 Systolic BP, median (IQR), mm Hg 127.3 (25.7) 134.0 (28.7) 127.3 (25.3) <.001 1832 (12.1)
 Total cholesterol, median (IQR), mg/dL 195.1 (56.8) 192.8 (57.8) 195.1 (56.8) .552 3619 (24.0)
 C-reactive protein
  <1.0 mg/L 3190 (28.0) 86 (20.5) 3104 (28.3)
  1.0–3.0 mg/L 4147 (36.5) 160 (38.1) 3987 (36.4) <.001 3734 (24.7)
  >3.0 mg/L 4038 (35.5) 174 (41.4) 3864 (35.3)
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Abbreviations: HRS, Health and Retirement Study; MI, myocardial infarction; HH, household; ADL, activities of daily living; COPD, chronic obstructive pulmonary disease; BP, blood pressure.

Note. Values reported as percentages, means (standard deviation [SD]), or medians (interquartile range [IQR]).

Figure 1 illustrates the cumulative hazards of MI associated with the number of chronic stressors after adjusting for age, sex, race/ethnicity, and geographic region. The estimated HRs increased significantly from adults who reported 1 chronic stressor (HR=1.28; 95% CI, 1.20–1.37) to those who reported 4 or more chronic stressors (HR=2.71; 95% CI, 2.08–3.53) compared with those who reported no stressors (P<.001). Further adjustments for socioeconomic status, psychosocial factors, health behaviors, and clinical factors only partially attenuated the association between chronic stressors and MI (Table 2). The fully adjusted model showed that risks for MI increased by approximately 10% for every additional chronic stressor that was reported (HR=1.10; 95% CI, 1.02–1.18; P=.014). Moreover, we found that the stress associated with one’s health and financial status had the strongest associations with risks for MI (Supplemental Table 4); but that the individual stressors did not incur the same level of risk as experiencing multiple stressors.

Figure 1.

Figure 1.

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Cumulative Hazards of Myocardial Infarction Associated with Number of Chronic Stressors, HRS 2006–2016 (n=15,109)

Abbreviations: HR, hazard ratio; CI, confidence interval; HRS, Health and Retirement Study.

Note: Model adjusted for age, sex, race/ethnicity, and geographic region. Differences in HRs for MI were statistically significant (p < .001).

Table 2.

Adjusted Hazard Ratios for Myocardial Infarction Associated with the Number of Chronic Stressors, HRS 2006–2016 (n=15,109)

Number of Chronic Stressors†
1 Stressor
HR (95% CI)		 2 Stressors
HR (95% CI)		 3 Stressors
HR (95% CI)		 4+ Stressors
HR (95% CI)
Model 1: (demographic background) 1.28 (1.20–1.37) 1.65 (1.44–1.88) 2.11 (1.73–2.58) 2.71 (2.08–3.53)
Model 2: (Model 1 + socioeconomic factors) 1.25 (1.17–1.34) 1.57 (1.37–1.79) 1.96 (1.61–2.39) 2.45 (1.88–3.20)
Model 3: (Model 2 + psychosocial factors) 1.20 (1.12–1.29) 1.44 (1.25–1.66) 1.73 (1.40–2.14) 2.08 (1.57–2.75)
Model 4: (Model 3 + behavioral factors) 1.18 (1.10–1.27) 1.40 (1.21–1.61) 1.65 (1.33–2.05) 1.95 (1.47–2.60)
Model 5: (Model 4 + clinical factors) 1.10 (1.02–1.18) 1.21 (1.04–1.40) 1.33 (1.06–1.66) 1.46 (1.08–1.97)
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Abbreviations: HRS, Health and Retirement Study; HR, hazard ratio; CI, confidence interval.

†

Reference group is no chronic stressors.

Model 1 included age, sex, race/ethnicity, and geographic region.

Model 2 included Model 1 covariates + education, household income, and employment status.

Model 3 included Model 2 covariates + marital status, living arrangement, social support, and depressive symptoms.

Model 4 included Model 3 covariates + smoking, alcohol use, and physical inactivity.

Model 5 included Model 4 covariates + body mass index, functional limitations, prior MI, hypertension, diabetes, chronic obstructive pulmonary disease, cancer, other [non-MI] cardiovascular-related conditions, systolic BP, total cholesterol, and C-reactive protein.

Although the magnitudes of the HRs were larger among women, Hispanics, and non-Hispanic Blacks than among men and non-Hispanic whites, respectively, the interaction terms for sex and race/ethnicity were not statistically significant. However, we found that the impact of chronic stressors was especially pronounced among adults who had a previous MI (P value for interactions <.05). Figure 2 shows that in adults without a history of MI, the risks for a first event ranged from HR=1.21 (95% CI, 1.13–1.30) in those with 1 chronic stressor to HR=2.17 (95% CI, 1.63–2.90) in those with 4 or more chronic stressors. In adults who had a prior MI, we found that risks for a recurrent event ranged from HR=1.47 (95% CI, 1.25–1.75) to HR=4.72 (95% CI, 2.40–9.28), respectively. In the fully-adjusted model, the risks for MI decreased and ranged from HR=1.07 (95% CI, 0.99–1.16) to HR=1.31 (95% CI, 0.95–1.80) in adults without a history of MI; and ranged from HR=1.30 (95% CI, 1.09–1.55) to HR=2.85 (95% CI, 1.43–5.69) in adults who had a prior MI.

Figure 2.

Figure 2.

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Adjusted Hazard Ratios for Myocardial Infarction (MI) Associated with the Number of Chronic Stressors in Adults With and Without Prior MI, HRS 2006–2016 (n=15,109)

Abbreviations: HR, hazard ratio; CI, confidence interval; HRS, Health and Retirement Study.

Note: Interactions between chronic stress and prior MI were statistically significant in all models (P < .05).

Model 1 included age, sex, race/ethnicity, and geographic region.

Model 2 included Model 1 + education, household income, and employment status.

Model 3 included Model 2 + marital status, living arrangement, social support, and depressive symptoms.

Model 4 included Model 3 + smoking, alcohol use, and physical inactivity.

Model 5 included Model 4 + body mass index, functional limitations, prior MI, hypertension, diabetes, chronic obstructive pulmonary disease, cancer, other [non-MI] cardiovascular-related conditions, systolic BP, total cholesterol, and C-reactive protein.

DISCUSSION

This study was the first to examine the cumulative impact of chronic stressors on risks for MI in a large nationally-representative cohort of U.S. adults. Results showed that exposure to multiple chronic stressors had large and incremental associations with risks of MI that were not fully accounted for by socioeconomic, behavioral, psychosocial, or clinical factors. These findings were consistent in men and women and across major racial and ethnic groups. However, we found that the risks associated with chronic stressors were especially high in adults with a history of MI. Overall, the findings suggest that chronic exposure to stressors are cumulative and potentially detrimental sources of risk for developing an acute coronary event.

The major findings from this study contribute to a wider understanding of how social determinants of health (SDOH) influence the development of MI. Chronic stressors are often discussed as fundamental mechanisms driving health disparities and the pathways by which SDOH “get under the skin.” Yet, much of what we know about chronic stress and risks for acute coronary events is based on a specific stressor (e.g., marital strain) or a specific population (e.g., caregivers). Our findings provide new evidence of how multiple chronic stressors contribute to differential exposure and vulnerability to MI in U.S. adults. The cardiovascular risks attributable to chronic stressors are largely consistent with the findings recently documented for divorce, unemployment, and other stressful life events (8,53,54). An important area for future research should involve early identification and/or interventions to mitigate the negative consequences of multiple chronic stressors to reduce risks of MI and other adverse outcomes. Likewise, studies should investigate whether biomedical, behavioral, or psychological resources can lessen the unhealthy stress response(s) that result from major life events such as job loss, divorce, and sickness.

The results of this study also contribute to growing evidence that the risks associated with chronic stress are of the magnitude of other established clinical risk factors for CVD (1,2,55). In our study, we found that the multivariable-adjusted risks related to hypertension (HR=1.31) and diabetes (HR=1.55) were comparable to the risks observed in adults who reported 4+ chronic stressors (HR=1.46)—and were even much lower than the risks related to 2, 3, or 4 stressors (HRs=1.69, 2.20, and 2.85, respectively) in adults with a previous MI. These findings are consistent with recent studies that have also documented excess cardiovascular risks related to other SDOH (2,53,54). Although we are cautious in making direct comparisons to established risk factors for MI, these findings should increase awareness of the sizeable risks associated with chronic stress and encourage future studies to identify viable interventions to prevent cardiovascular events in adults facing adversity.

This study also showed that the negative consequences of chronic stressors were especially detrimental to those who suffered a prior MI. These findings corroborate evidence to suggest that adults with pre-existing illness or other physiological deficits are more vulnerable to the effects of stress. For example, studies have shown that among adults with diagnosed heart disease (e.g., MI, heart failure), those who face stress at home or at work have significantly worse outcomes than those without such stressors (56–58). In adults with a prior MI, we found that risks for a recurrent event were upwards of 70–185% greater in those with 2–4+ chronic stressors compared with those who reported no stressors. These findings have potentially important implications for informing clinical practice and improving prognoses after MI through interventions that may target stress management (6,56,59).

A notable finding from this study was that many of the most widely cited behavioral and physiological factors attributable to stress did not fully explain the associations. Our analysis showed that taking into account smoking, exercise, systolic BP, and a wide range of other factors only partially reduced the association between chronic stressors and risks for MI. Prior studies have also conceptualized chronic stress as operating through prolonged and repeated activation of physiological systems that contribute to cumulative “wear and tear” (e.g., allostatic load) across multiple biological regulatory systems (e.g., cardiovascular, endocrine, immune) which leave the body vulnerable to disease (12,16,18,57,59–62). Thus, it is possible that other unmeasured physiological factors—such as changes in cortisol, [nor]epinephrine, sleep, etc.—may be important mechanisms contributing to the observed differences in MI. It is also possible that the current study lacked sufficient specificity in measurement to fully account for the complex pathways linking chronic stressors to MI risks.

The results of this study are not without limitations. First, we recognize that the analyses are based on self-reported diagnoses of MI that were not formally adjudicated. Although studies have shown that self-reported MI has a moderate to high degree of sensitivity, specificity, and overall agreement with medical data (46–48,63)—we acknowledge that the HRS may have under/over-reported cases of MI, particularly among some sociodemographic groups (e.g., due to differences in symptom awareness, care-seeking behaviors, and/or atypical presentation of MI). Additional studies are warranted to further validate these findings with formal clinical events classification of MI and with other possible forms of cardiovascular disease. Second, although the HRS data were robust in the number and scope of measured covariates, it is possible that additional unmeasured factors—such as HTN treatment, revascularization, or stress counseling—may have contributed to differences in MI. Likewise, measures of sleep and/or medication adherence may be particularly relevant in patients with a history of MI. Third, although the stress associated with one’s health and financial status had the strongest associations with risks for MI, our sensitivity analyses showed that removal of either health or financial stressors produced results that were consistent with the fully-identified models. Furthermore, our analyses showed that the separate chronic stressors were not independently associated with MI—suggesting that it is an accumulation of stressors across multiple domains that puts individuals at especially high risks of MI. Finally, our study focused on chronic stressors that occur within major domains of life (i.e., financial issues, social relationships, health, housing, and caregiving); therefore, it is unknown whether and to what extent an accumulation of specific stressful life events and/or lifetime traumas may influence risks on MI.

In sum, the results from our study demonstrated the large and incremental impact of one’s cumulative exposure to chronic stressors on risks for a major coronary event. The elevated risks associated with chronic stressors were largely universal among men, women, and among those from diverse racial/ethnic backgrounds. However, the risks associated with multiple chronic stressors were especially high in adults with a history of MI. Additional studies are needed to further explore the possible social, behavioral, and/or biological mechanisms contributing to these associations and to assess how such information can be used to target vulnerable segments of the population who may be at risk of a first or recurrent MI.

Supplementary Material

FINAL PRODUCTION FILE: SDC

ACKNOWLEDGEMENTS

Role of the Sponsor:

The NIA, NIMHD, and NHLBI had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication

Conflicts of Interest and Source of Funding/Support:

No conflicts of interest declared. Support for this study was provided in part by the National Institute on Aging (NIA) for Dr. Farmer (T32AG000029) and Drs. Dupre and Xu (R03AG064303); the National Institute on Minority Health and Health Disparities (NIMHD) for Dr. Xu (U54MD012530); and the National Heart, Lung, and Blood Institute (NHLBI) for Dr. Nanna (T32HL069749) and Dr. Navar (K01HL133416).

Acronyms:

MI

myocardial infarction

AHA

American Heart Association

CVD

cardiovascular disease

HRS

Health and Retirement Study

BMI

body mass index

ADL

activities of daily living

HTN

hypertension

DM

diabetes mellitus

COPD

chronic obstructive pulmonary disorder

BP

systolic blood pressure

CRP

C-reactive protein

CDC

Centers for Disease Control and Prevention

HR

hazard ratio

CI

confidence interval

SDOH

social determinants of health

Footnotes

This work was presented at the 2020 Annual Meeting of the Gerontological Society of America.

Conflict of Interest: None declared.

Publisher's Disclaimer: Disclaimer: The views expressed in this article are those of the authors and do not necessarily reflect those of NIA, NIMHD, NHLBI, or Duke University.

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