Screening for Psychological Distress and Risk of Cardiovascular Disease and Related Mortality: A SYSTEMATIZED REVIEW, META-ANALYSIS, AND CASE FOR PREVENTION : Journal of Cardiopulmonary Rehabilitation and Prevention

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Special Section: Invited Reviews on Important Topics in Prevention

Screening for Psychological Distress and Risk of Cardiovascular Disease and Related Mortality


Gaffey, Allison E. PhD; Gathright, Emily C. PhD, FAACVPR; Fletcher, Lauren M. MLIS, MA; Goldstein, Carly M. PhD, FAACVPR

Author Information
Journal of Cardiopulmonary Rehabilitation and Prevention: November 2022 - Volume 42 - Issue 6 - p 404-415
doi: 10.1097/HCR.0000000000000751


What is novel?

  • This meta-analysis of research published in the last 5 yr demonstrates that psychological distress evaluated with brief screening measures is only associated with a 28% greater risk of first-onset cardiovascular disease (CVD).
  • These results are comparable to those from previous meta-analyses including data based on formal psychological evaluations or medical record diagnoses, suggesting that screeners alone are sufficient for capturing the CVD risk associated with psychological distress.

What are the clinical and/or research implications?

  • Using brief psychological screeners in clinical or community settings is feasible and helpful for early CVD risk stratification.
  • Even without meeting criteria for high psychological distress, patients may benefit from gold standard evidence-based interventions or additional supportive resources to aid CVD primary prevention.

Primary prevention initiatives are gaining in prevalence to forestall the onset of cardiovascular disease (CVD).1,2 In the United States (US), patients and their health care providers are currently afforded the most advanced biobehavioral toolkit for cardiovascular risk reduction.3 Still, with an obesity epidemic, sedentary lifestyles, an aging population, and broadening social health disparities, CVD prevalence and associated costs of health care and human life continue to rise.4

Psychological health is an important dimension of cardiovascular health and well-being.5,6 Significant evidence from epidemiology, psychology, psychiatry, cardiology, and public health shows that psychological distress (ie, elevated symptoms of depression, anxiety, post-traumatic stress disorder (PTSD), or perceived psychosocial stress) is associated with earlier CVD onset, more rapid CVD progression, poorer prognosis, and an increased risk of related death.7–14 INTERHEART, a global, case-control study of first myocardial infarction, was one of the largest investigations to demonstrate the importance of psychological health: the population attributable risk of psychological stress and depression was 33%, which exceeded the risk associated with some traditional factors for CVD (eg, hypertension and physical inactivity).15 Additional, prospective cohort studies and meta-analytic summaries have since reinforced these findings, offering compelling evidence that psychological distress—based on clinical diagnoses, formal diagnostic interviews, or self-reported symptoms—is involved in the risk for, and burden of, CVD.9,12–14,16–18

With accumulating evidence linking psychological health and risk for CVD,19 leaders in cardiovascular medicine increasingly acknowledge the importance of psychological health in cardiac and vascular risk.5,20 Contradictory to this acknowledgment, and despite cardiovascular rehabilitation's longstanding empirically-based focus on psychological health and stance that psychological health is as equally important as traditional CVD risk factors, professional associations in cardiovascular medicine continue to be cautious about translating evidence concerning psychological health and cardiovascular risk into clinical guidelines for distress screening and management. Most prominently, the American Heart Association (AHA) recently updated their cardiovascular health metric to “The Essential 8” to include sleep, and suggested that psychological health serves as a context for other health factors (eg, sleep and weight), but that greater evidence is needed to guide the implementation of psychological screening and management.19 Historically, this tempered enthusiasm may have translated into a greater emphasis on psychological distress surveillance in patients with established CVD (eg, AHA Recommendations for Screening, Referral, and Treatment for Depression focused on patients with coronary heart disease) rather than identifying opportunities for primary prevention.21 As the cardiovascular risk that is associated with psychological distress likely begins well before CVD onset, and managing such symptoms appears strategic for reducing cardiovascular risk, patients and providers alike would benefit from the earlier identification of psychological distress.

Across medicine, policymakers, thought leaders, and professional organizations are advocating for more widespread surveillance of psychological distress in routine care settings. For example, since 2009, the US Preventive Services Task Force has recommended annual depression screening among adults aged ≥18 yr and highlighted increased depression risk among those with CVD,22 and the Centers for Medicare & Medicaid Services has covered annual depression screening for adults since 2011,23 but changes to US health care policy develop slowly. As the current health care delivery landscape demands efficient evaluation of patient distress,24 efforts to monitor psychological health using brief, validated self-report measures rather than more burdensome, comprehensive, psychological evaluations or psychiatric interviews continue to gain momentum. Several recent meta-analyses have summarized literature concerning psychological distress and initial CVD risk.7,9–11,14 Yet, no such investigation has specifically focused on the use of brief, self-report screening measures to evaluate distress. This effort is integral to creating screening guidelines for psychological distress in the service of CVD prevention, efforts that will particularly benefit populations with a high risk of CVD.

The primary objective of this investigation was to update and extend literature concerning psychological health and the incidence of new-onset CVD or related mortality by conducting a systematized review of all recent studies in which psychological distress was identified with brief, self-report screening measures only. A complementary objective was to quantify the strength of recent evidence via meta-analysis. Given the breadth of this literature, and past meta-analyses of subdomains of psychological health, a final objective was to identify opportunities for further research concerning psychological health screening and CVD and to develop recommendations for applying these results to improve the implementation of such measures in CVD primary prevention.



The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement25 was used to guide the literature search and associated statistical analyses. Studies were included in the systematized review if they were (1) published in the last 5 yr (2017-2022), to provide estimates based on the most recent state of this science, (2) designed to evaluate the prospective association of psychological health (ie, symptoms of depression, anxiety, PTSD, psychosocial stress, or general mental health-related quality of life) that was assessed at baseline with a validated self-report measure, and risk for incident CVD events, diagnoses, hospitalization, or related mortality, (3) participants were aged ≥18 yr and free from a diagnosed psychiatric disorder at baseline, (4) participants did not have CVD at baseline or CVD was controlled in analyses of more heterogeneous samples, and (5) the follow-up duration was ≥6 mo. Studies were excluded if psychological health was assessed with a formal psychological evaluation or psychiatric interview, or if the predictor was based on a psychiatric diagnosis derived from the medical record. Due to the different pathophysiology of stroke compared with other types of CVD and recent findings highlighting the complexity of psychological distress as a predictor of fatal and nonfatal ischemic stroke,26,27 investigations that included stroke within a composite endpoint were excluded. Despite being a common endpoint, studies that focused on hypertension were also excluded due to being a risk factor for CVD rather than established CVD per se; and further, since the first diagnosis of hypertension typically predates CVD by many years, prevention processes and timelines are likely very different. We excluded records from non-peer-reviewed sources such as theses, dissertations, and conference abstracts, due to different standards of peer review. We also excluded studies not available in English. The primary meta-analysis was limited to studies reporting adjusted HR and associated 95% CI (or other information allowing for their calculation) for an association between psychological distress and a relevant CVD outcome. Studies that only reported continuous HR were excluded because our primary interest was in determining whether high distress (relative to low or no distress) was associated with CVD risk.


A medical librarian (L.M.F.) searched the MEDLINE (Ovid), Embase (, and American Psychological Association (APA) PsycInfo (EBSCO) databases for relevant journal articles. The final search was conducted on May 16, 2022. The following search terms were among those used to identify the appropriate articles: anxiety; depression; depressive disorder; stress disorders, posttraumatic; posttraumatic stress disorder; perceived stress; psychosocial stress; stress; GAD-7; PHQ-9; Patient Health or Penn State Worry or General Health Questionnaire; DBI or STAI or BAI or BDI-II; or state-trait or (Spielberger or mental health) W3 (inventory HDRS or Ham-D or HADS or CESD or CES-D or HDI or SDS or GDS or HADS-D; Hamilton or hospital or center for epidemiologic studies or self-rating or geriatric or Zung self-rating) W3 (depression scale); CVD; coronary disease; myocardial infarction; myocardial ischemia; death, sudden, cardiac; coronary artery disease; atrial fibrillation; heart failure; peripheral artery disease; peripheral vascular diseases; risk; incidence; or new or onset or risk or predict; and all the possible combinations of these terms.

Duplicate records were removed via auto-deduplication in EndNote 20 and manual deduplication. Title and abstract screening were completed in Covidence according to inclusion and exclusion criteria outlined earlier, and irrelevant articles were excluded. Next, the full texts of the remaining articles were thoroughly examined according to the criteria, and unrelated studies were again excluded in EndNote. To maintain objectivity, screening and data extraction activities were performed by two independent reviewers (A.E.G. and E.C.G.). To ensure a comprehensive search, the reference lists used within all the collected articles were manually reviewed. Interrater reliability was assessed for full-text review, with raters agreeing on 77% of the records. Discrepancies were resolved through discussion until consensus was reached.


A total of 3943 records were initially identified through the database searches: MEDLINE (n = 1616), Embase (n = 1733), and APA PsycInfo (n = 594). Of the initial search, 498 duplicate records were removed, and 3445 records were eligible for title and abstract screening.

Data from the final studies were extracted using detailed coding forms. Items included: article title, name of first author, year of publication, place of study, sample size, assessment method, demographics of the sample (average age, sex, race and ethnicity, and marital status), type of study, the prevalence of depression, anxiety, and stress, method of assessing psychological distress, CVD outcomes, and statistical details (ie, maximally adjusted HR and 95% CI, covariates). For inclusion in the meta-analysis, when studies with overlapping samples were identified, we prioritized the study with the largest sample, which reported an association between baseline psychological distress and a relevant outcome. When studies with overlapping samples reported different cardiovascular outcomes, we prioritized the study reporting the most relevant cardiovascular outcome. If studies reported HR associated with tertiles or quantiles, the highest category was included. Fixed-effects methods were used to combine subgroups and derive a study-level effect. For studies reporting outcomes associated with more than one metric of psychological distress (ie, depression and anxiety), we prioritized the nondepression psychological construct, given the more limited number of such studies. We requested additional information from authors of five additional studies, but none responded in the allotted time (ie, 4 mo).


For the primary analysis, adjusted HRs reflecting the association between psychological distress and CVD morbidity risk were used as the measure of effect; other measures of relative risk were considered equivalent for the purposes of this analysis. Hazard ratios > 1 indicated that psychological distress (eg, high symptoms of depression) was associated with a greater incidence of CVD. As part of a sensitivity analysis, a broader definition of relative risk was used to pool adjusted HRs and unadjusted or adjusted ORs of associations between psychological distress and risk of CVD morbidity or mortality.

Random-effects procedures with a restricted information maximum likelihood approach were used to aggregate effect sizes (ie, logarithmic adjusted HR) and corresponding 95% CI to estimate the overall effect, which was converted back to an HR.28,29 The Q statistic was computed to assess heterogeneity (ie, inferred from a significant value). Outcome consistency across studies was estimated based on the I2 index and its corresponding 95% CI.30,31I2 values of 25%, 50%, and 75% are interpreted as low, medium, or high heterogeneity.32 Analyses were conducted using the Stata meta package Version 16 (Stata Corp., College Station, Texas).33

We assessed publication bias for analyses with outcomes that were reported in ≥10 studies.34 Visual inspection of funnel plots and Egger's test were used to evaluate the possibility of publication bias and small study effects, respectively.35–37


Of the 3445 records from the original search, 3251 were excluded in the title and abstract review, and 166 records were excluded in the full-text review. Ultimately, 28 investigations met the inclusion criteria and had an endpoint of CVD morbidity or mortality, of which 18 were included in our analyses (Figure 1 includes additional details of the study selection process).

Figure 1.:
PRISMA 2020 flow diagram of screening and selection procedures. This figure is available in color online (


Altogether, the studies represented 658 331 participants (58.1% women; 66.9% White [n = 13 reported data on race]; and 67.0% married or cohabiting [n = 11 reported relevant data]). Characteristics of the included prospective cohort studies are depicted in the Table, separated by the type of psychological distress. Most investigations included samples of healthy adults (n = 13), although others were limited to adults of middle-aged and older (n = 10), members of specific racial/ethnic groups (n = 3), men (n = 2), post-9/11 emergency workers (n = 1), or US military veterans (n = 1). Most participants were self-selected from the broader population (n = 21), but some were recruited through a clinical contact (n = 4), electronic health records (n = 1), or other means (n = 4; eg, employed in the British Civil Service). In terms of risk factors for CVD, 21.9% of participants smoked (n = 24), 11.2% had diabetes (n = 19), 41.7% had hypertension (n = 17), and the average body mass index was 26.3 ± 4.4 (n = 11).

Table - Characteristics of the Included Studies, Separated by Type of Psychological Distress
Study Region Baseline, yr Sample, n Follow-up Duration, mo Age, Mean or Median, yr Women, % Measure of Psychological Distress CVD Outcomes Covariates
Deschenes et al (2020)38 Quebec, Canada 2009-2010 33 455 84 53 57 PHQ CAD, HF, MI Age, sex, ethnicity, education, smoking, alcohol, PA, cholesterol, DM, HTN
Dixon et al (2022)39 12 Southeastern US states 2002-2009 23 937 132 53 (median) 64 CES-D HF Age, sex, race, HTN, HLD, DM, BMI, smoking, income, education, employment, marital status, alcohol, PA, number of close friends, depression, antidepressant use, cerebrovascular disease
Feng et al (2020)40 Nord-Trøndelag County, Norway 2006-2008 37 402 96 53 57 HADS-Depression AF Age, sex, weight, height, smoking, occupation, marital status, PA, alcohol use, chronic disorders, blood glucose, BP, triglycerides, HDL, CRP
Gaffey et al (2022)41 Jackson, Mississippi, USA 2000-2004 2 651 120 53 (median) 64 CES-D HF Age, education, income, HTN, DM, CHD, eGFR, total cholesterol, LVEF, alcohol abuse, smoking, obesity, PA, HR, SBP
Garg et al (2019)42 Six US sites (Baltimore, MD; Chicago, IL; Forsyth County, NC; Los Angeles, CA; New York City, NY; St Paul, MN) 2000-2002 6 664 156 62 53 CES-D AF Age, sex, race, education, income, clinic site, cigarette smoking, BMI, height, DM, glucose, SBP, PA, statin use, antihypertensive use, alcohol use
Han et al (2021)43 28 provinces in China 2011-2012 8 621 84 58 48 CES-D Composite Age, sex, zip code, education, smoking, alcohol use, BMI, SBP, antidepressant use, medical history
Harshfield et al (2020)44 Consortium of 21 studies from Europe, North America, and Australia ERFC: 1974-2010 162 036 114 63 73 CES-D CAD Age, sex (stratified), smoking, DM
Karlsen et al (2021)45 Six US sites (Birmingham, AL; Minneapolis, MN; Palo Alto, CA; Pittsburg, PA; Portland, OR; San Diego, CA) 2003-2005 3 095 144 76 0 GADS MI, HF, other Age, anxiety, education, ethnicity, DM, antidepressant use, smoking, alcohol use, BP, cholesterol, BMI, PA
Ladwig et al (2017)46 Germany 1984-1985 3 428 120 58 0 von Zerssen symptom checklist: Depression/Exhaustion subscale CAD mortality Age, HCL, obesity, HTN, smoking, DM
Lemogne et al (2017)47 France 1993 10 541 252 48 26 CES-D Composite Age, sex, occupational grade, parental history of CVD, alcohol use, smoking, PA, BMI, HTN, dyslipidemia, DM, sleep complaints
Li et al (2019)48 28 provinces in China 2011-2012 12 417 48 58 51 CES-D Composite Age, sex, residence, marital status, education, smoking, alcohol use, SBP, BMI, history of diabetes, HTN, DLP, CKD, antihypertensives, DM medication, lipid lowering therapy
Li et al (2020)49 28 provinces in China 2011-2012 6 810 24 58 53 CES-D Composite Age, sex, residence, marital status, baseline CES-D, education, smoking, alcohol use, obesity, HTN, DM, DLP, chronic kidney disease, inflammation
Piantella et al (2021)50 London, England 1997-1999 7 610 132 56 3 General Health Questionnaire-Depression CAD Age, gender, smoking, BMI
Poole and Steptoe (2018)51 England 2004 2 472 120 63 51 CES-D CAD Age, sex, ethnicity, cohabitation, wealth, smoking, SMI, alcohol use, regular physical activity, cognitive function, HTN
Poole and Jackowska (2019)52 England 2014-2015 5 034 72 66 55 CES-D MI, other Age, sex, relationship status, income, BMI, smoker, alcohol use, PA, HTN, sleep problems
Rantanen et al (2020)53 Harjavalta and Kokemäki, Finland 2005-2007 2 522 96 58 56 Beck Depression Inventory MI, PAD, angina, CAD Age, gender, education, smoking, alcohol use, PA, HTN, DLP
Remch et al (2018)54 New York City, USA 2012-2013 5 971 48 51 17 PHQ MI, CV events Age, sex, BP, total cholesterol, BMI, tobacco use, respirator use
Vu et al (2021)55 Four US sites: Washington County, MD, Forsyth County, NC, Suburbs of Minneapolis, MN, and Jackson, MS 2011-2013 6 025 66 75 59 CES-D HF Age, sex, race, education, income, smoking, alcohol use, PA, DM, BMI, HR, eGFR
Yu et al (2022)56 Guizhou province, China 2010-2012 7 735 84 44 52 PHQ MI Age, sex, ethnicity, education, marriage, occupation, smoking, alcohol use, PA, history of T2DM, HTN, DLP, BMI
Zhu et al (2022)57 28 provinces in China 2013-2014 9 595 60 58 52 CES-D CAD, HF, MI angina, other Age, gender, marital status, education, residency, smoking, alcohol use, HTN, DM, DLP, sleep duration
Feng et al (2020)40 Nord-Trøndelag County, Norway 2006-2008 37 402 96 53 57 HADS-Anxiety AF Age, sex, weight, height, smoking, occupation, marital status, physical activity, alcohol use, chronic disorders, metabolic components (glucose, BP, triglycerides, HDL, CRP)
Karlsen et al (2020)45 Six US sites (Birmingham, AL; Minneapolis, MN; Palo Alto, CA; Pittsburg, PA; Portland, OR; San Diego, CA) 2000-2002 3 095 180 76 0 GADS MI, HF, other Age, education, ethnicity, smoking, BMI, PA, alcohol use, DM, BP, cholesterol, antidepressant use, anxiety
Remch et al (2018)54 New York City, USA 2012-2013 5 971 48 51 17 PCL-C (civilian) MI, composite Age, sex, BMI, use of a respirator, BP, total cholesterol, tobacco use
Scherrer et al (2020)58 USA 2008-2012 1 079 84 49 17 PCL Composite Age, race, gender, marital status, health insurance, depression, anxiety, sleep disorder, substance use, smoking, DM, HTN, HLD, obesity, duration of PTSD psychotherapy, antidepressant use
Psychosocial stress
Graff et al (2017)59 Denmark 2010 114 337 48 Largest age group: 55-64 (22.6%) 54 PSS AF Physical and psychiatric comorbid conditions, SES, lifestyle factors
Santosa et al (2021)60 21 countries 2001-2003 118 706 122 50 59 Composite: PSS, Recent Adverse Life Events, Financial Stress CAD Age, sex, education, marital status, location, obesity, HTN, smoking, DM, family history of CVD, center
General mental health/health-related quality of life
Bonaccio et al (2018)61 Molise region, Italy 2005 17 102 60 53 53 Mental HRQoL CAD Age, sex, education, household income, occupational class, marital status, cancer, DM, HTN, HCL, psychological assessment, PA, BMI, diet, smoking, physical/metal health, CRP
Nilsson et al (2020)62 County of Östergötland, Sweden 2003-2004 1 001 156 57 50 SF-36 Mental Health Subscale MI, composite Age, sex, and reporting at least one disease and/or neck/back pain
Phyo et al (2021)63 Australia, USA 2010-2014 19 106 56 74 (median) 56 Medical Outcomes Study, SF-12 Mental Component Scale Composite Age, sex, race and ethnicity, education, living situation, country, smoking, alcohol use, PA
Pinheiro et al (2019)64 USA 2003-2007 22 229 101 64 58 HRQoL, SF-12 Mental Component Summary score MI, composite Age, sex, race, education, relationship status, access to care, income, health insurance, residence, DM, HTN, AF, medication use, LVH, BMI, cholesterol, hsCRP, eGFR, CKD
Wimmelman et al (2021)65 Copenhagen, Denmark 2009-2011 6 750 72 54 31 Satisfaction with Life Scale, SF-36 Vitality subscale Composite Age, sex, education, BMI, smoking, alcohol use, coronary calcium index, employment, social support
Abbreviations: AF, atrial fibrillation; BMI, body mass index; BP, blood pressure; CAD, coronary artery disease; CES-D, Center for Epidemiologic Studies Depression Scale; CHD, coronary heart disease; CKD, chronic kidney disease; CV, cardiovascular; CVD, cardiovascular disease; DLP, dyslipidemia; DM, diabetes mellitus; eGFR, estimated glomerular filtration rate; ERFC; GADS, Goldberg Anxiety and Depression Scales; HADS, Hospital Anxiety and Depression Scales; HCL, hypercholesterolemia; HDL, high-density lipoprotein; HF, heart failure; HR, heart rate; HRQoL, health-related quality of life; hsCRP, high-sensitivity c-reactive protein; HLD, hyperlipidemia; HTN, hypertension; LVH, left ventricular hypertrophy; LVEF, left ventricular ejection fraction; MI, myocardial infarction; PA, physical activity; PAD, peripheral artery disease; PCL, PTSD Checklist; PHQ, Patient Health Questionnaire; PSS, Perceived Stress Scale; PTSD, post-traumatic stress disorder; SBP, systolic blood pressure; SES, socioeconomic status; SF-12, Short Form-12; SF-36, Short Form-36; T2DM, type 2 diabetes mellitus.
aDuration of follow-up is reported as average rather than total.

The period of data collection ranged considerably, with the earliest baseline in 1974 and the most recent baseline in 2015. The average follow-up period was 98.3 ± 45.5 mo. Most investigations examined depressive symptoms (n = 20) or general mental health symptoms (n = 5), and a few examined symptoms of anxiety (n = 2), PTSD (n = 2), and stress (n = 2). Of the studies that focused on depression, the Center for Epidemiological Studies Depression Scale was particularly common (n = 12), and other measures consisted of the Patient Health Questionnaire (n = 3), the Beck Depression Inventory (n = 1), the Goldberg Anxiety and Depression Scales (n = 1), the Hospital Anxiety and Depression Scales-Depression subscale (n = 1), and the Depression and Exhaustion subscale of the von Zerssen symptom checklist. Anxiety was assessed with the Goldberg Anxiety and Depression Scales (n = 1), and the Hospital Anxiety and Depression Scales-Anxiety subscale (n = 1). Assessment of PTSD was conducted with the PTSD Checklist-Civilian version (n = 2). Stress was assessed with the Perceived Stress Scale (n = 1) or a composite of that scale, major adverse life events, and financial stress in the past year (n = 1). Finally, other general mental health screening was conducted with the SF-36 Mental Health Subscale (n = 1), Mental Health Related Quality of Life Scale (n = 1), SF-12 Mental Component Summary score (n = 2), and the Satisfaction with Life Scale (n = 1).

Outcomes consisted of a composite endpoint (n = 10), coronary artery disease (n = 9), myocardial infarction (n = 8), atrial fibrillation (n = 3), and heart failure (n = 6), although many studies included distinct tests of more than one outcome. Documentation of outcomes was most often based on a diagnosis or an event (eg, hospitalization; n = 15), and data were collected via self-report (n = 13), from a national register/database (n = 9), or by medical chart review (n = 6).


Out of the studies that met criteria and were reviewed, 15 studies that reported associations between baseline psychological distress and subsequent risk of CVD had sufficient data to include in the primary analysis. Overall, high symptoms of distress were associated with a 28% greater risk of CVD morbidity (95% CI, 1.18-1.39; Figure 2). Analyses of heterogeneity among the studies showed that effects were moderately heterogenous (Q[14] = 28.99, P= .010, I2= 48%). Study results were also summarized by distinct dimensions of psychological health (Figure 3). Evidence of publication bias was not observed, and relevant plots are depicted in the Supplemental Digital Content Figure (available at:

Figure 2.:
Forest plot depicting analyses of psychological distress identified via brief screening measures and CVD morbidity and mortality, published 2017-2022 (n = 15). This figure is available in color online (
Figure 3.:
Psychological distress and risk of incident CVD and related mortality, by type of measure. Abbreviations: HRQoL, health-related quality of life; MH, mental health; PTSD, post-traumatic stress disorder. This figure is available in color online (

A sensitivity analysis was conducted treating ORs as equivalent to HR and including studies with CVD mortality as the outcome (overall, n = 18; Figure 4). Like results from the primary analyses, high distress was associated with a 28% greater risk of CVD morbidity and mortality. Analyses of the studies showed that effects were heterogenous (Q[17] = 54.54, P< .001, I2=63%).

Figure 4.:
Forest plot depicting sensitivity analysis of psychological distress and CVD morbidity and mortality (n = 18). Abbreviations: HRQoL, health-related quality of life; MH, mental health; PTSD, post-traumatic stress disorder. This figure is available in color online (


This systematized review consisted of 28 studies published from 2017 to 2022, which focused on self-reported psychological distress identified by brief screeners and incident CVD morbidity and mortality. Variability in methodology and statistical reporting resulted in 15 investigations available for the primary systematized meta-analysis. Overall, psychological distress (ie, elevated symptoms of depression, anxiety, PTSD, stress, or worse mental health-related quality of life) was associated with a 28% increased risk of CVD morbidity or mortality. Although multiple dimensions of psychological health were combined for the primary analysis, the observed effects were in a similar direction and range as previous meta-analyses of distinct psychological dimensions, and which included psychiatric diagnoses (eg, relative risks of 1.21-1.909–11,13,16,66). Our investigation reaffirms the importance of psychological distress in cardiovascular risk, and more prominently suggests that psychological health captured with “brief and valid methods ... that can then be documented within the medical records”19 may be sufficient to approximate the associated CVD risk and guide intervention.

Past reviews and meta-analyses of psychological health and CVD risk have targeted unidimensional psychological health, with the most recent versions published in 2016-2019.7,9–11,14 However, as recently stated in the AHA Presidential Advisory, “Psychological health is multidimensional ... a contextual driver of cardiovascular health.”19 Psychological disorders and different dimensions of psychological symptoms are also highly comorbid.67 Understanding associations between one aspect of psychological health and one CVD outcome provides foundational evidence, but may complicate potential assessment processes, leading clinicians to assume that all dimensions must be assessed and making the evidence less digestible or actionable. For example, if there are separate, significant findings concerning the associations of depression, anxiety, and psychosocial stress in relation to heart failure, there may be uncertainty about what to target if patient symptoms are clinically elevated on all measures and with limited access to mental health providers. Given the complexity of lifestyle modification to improve CVD risk and the importance of psychological distress for adherence and maintenance of such changes,19 targeting multiple aspects of risk concordantly with psychological health using tailored strategies may be most successful.68 In other words, meet the patient where they are starting CVD prevention from, and apply knowledge about their psychological health to tailor their prevention moving forward.

A clear gap from existing research is the limited evaluation of sex and gender differences. Compared with men, women have distinct experiences of trauma throughout the lifespan, unique sources of psychosocial stress, increased perceived stress during adulthood, and show different presentations of psychological distress, including a twofold greater lifetime prevalence of depression and some anxiety disorders.69–72 These distinct vulnerabilities and presentations likely translate to sex differences in CVD risk, physiological mechanisms, CVD onset, and presentation, all of which are integral to CVD primary prevention.48,51,56,57,65,73,74 In a follow-up to the primary INTERHEART analyses, compared with men, women with moderate or high psychosocial distress showed a greater risk of myocardial infarction (OR: 2.58 vs 3.49).75 Additionally, women may be un- or undertreated for depression: among 1075 women participating in primary prevention and cardiac rehabilitation, 39% still reported depressive symptoms meeting the threshold for depression.76 Despite these well-recognized distinctions and gaps in care, few cohort studies or meta-analyses of psychological health and CVD risk have reported effects separately by sex.41,42 This delineation is required to understand potential subgroup differences in psychological risk and to mount a better clinical offense for men and women, respectively. A pioneer in this endeavor has been the European Society of Cardiology, which has already made significant efforts toward sex-specific CVD risk stratification and that which includes mental health.77

The present results provide additional data substantiating the utility of integrated psychological care within CVD primary prevention and supporting research and clinical recommendations to extend this work. To begin, there is considerable scientific heterogeneity in evaluating and treating psychological contributions to CVD risk, including the variables used for statistical adjustment. Next, many studies do not statistically control for the use of psychotropic medications; this oversight is problematic as certain medication classes (ie, selective serotonin reuptake inhibitors) may contribute to vascular risk78 and have also been associated with a lower risk of recurrent acute coronary syndrome (ACS) in patients with post-ACS depression.79 Related, open questions are which domains of psychological health are most important when evaluating CVD risk, which screening measures are preferable, and how to best combine brief assessments.19 To help bridge this evidentiary gap, more rigorous tests of the prospective associations between psychosocial stress, particularly assessed with the Perceived Stress Scale or validated measures of specific types of stress (eg, financial, caregiving), and CVD risk are needed. Moreover, self-reported psychological distress may vary depending on the life circumstances of an individual, yet the reviewed studies only provide a one-time snapshot of distress and generally do not account for changes in distress over time or due to psychological treatment. While yearly screening for depression has been recommended for primary care,22 the frequency of psychological screening needed to monitor cardiovascular risk is unknown. As another area of focus, for decades there has been a call for more experimental evidence concerning behavioral and biological underpinnings of psychological-CVD associations and clinical trials of stepped care approaches (eg, using the Patient Health Questionnaire-9 to screen followed by a more comprehensive evaluation and treatment).10 This research is important, yet one should consider whether future mechanistic studies will actually help individuals significantly more than receiving available, validated, self-report screeners and gold standard behavioral and pharmacological treatments.

There is a continued cost to delaying implementation of psychological distress screening in primary prevention, particularly given the close associations between psychological health and other lifestyle factors implicated in cardiovascular health, and more generally, patient motivation, engagement, and adherence to treatment. Even if associations between psychological distress and incident CVD are not causal, meta-analytic evidence supports the utility of assessing psychological health, particularly given the high comorbidity between psychological disorders that have been linked to cardiovascular risk—anxiety, depression, and PTSD.67 Screening for psychological distress may be especially advantageous to mediate social determinants of health that systematically increase CVD risk among certain racial, ethnic, and socioeconomic groups; this approach can be readily employed in clinical-, community-, and population-based health care settings.19 Interestingly, the present effect of psychological distress was observed despite variability in study locales, demographics, and different approaches to psychological and cardiovascular health management. Possible mechanisms of action for the observed effect of psychological distress could be those associated with self-care. For example, individuals who are distressed may be less likely to care for themselves, adhere to medical advice or medications, and engage in riskier health behaviors, offering an added reason to screen for distress in prevention settings.

Alleviating psychological distress should be a health care priority at any stage in patient-centered cardiovascular care—whether primordial prevention, primary prevention among those with a family history of CVD or who are otherwise high risk, prehabilitation to prepare for nonurgent cardiac surgery, or secondary prevention after a major surgical intervention or cardiovascular event. Integrated primary care offers one promising clinical service delivery model, which includes psychological distress assessment and management, and can be adapted for CVD prevention.80–83 Besides benefiting patients, this model could be financially advantageous for single-payer and managed care systems alike.84,85 In the US, health policy should be informed by robust randomized clinical trials and links to meaningful benchmarks including quality of life and reduced health care expenditures; those trials to date concerning psychological risk and CVD lag millions of dollars behind investments in understanding biomedical factors—and cannot catch up. To create better policy, preventive cardiology should draw from the excellent data supporting psychosocial care in cardiovascular rehabilitation and from other models of integrated care for noncommunicable chronic diseases, to invest more readily in interprofessional training and team-based care.84,86 Thus, we are left to reflect on whether the current evidence is sufficient and whether there is an ethical imperative to begin implementing that evidence and refining approaches over time.


Our study summarizes the most recent evidence concerning psychological distress assessed by self-reported screening and cardiovascular risk among adults. Still, there were limitations to this investigation. First, studies that assessed different psychological health dimensions were combined in the primary analysis, which is an uncommon statistical approach. However, we prioritized this approach given the high degree of comorbidity between the psychological disorders of focus, and a goal of broadly understanding the effect of psychological distress. Given the small number of studies assessing dimensions of psychological health besides depression, conclusions should be interpreted cautiously. Similarly, the duration of follow-up and outcomes were varied; additional research is needed to clarify whether the strength of the association between elevated psychological distress and CVD onset differs by cardiovascular outcome (eg, ACS, coronary artery disease, peripheral vascular disease, vs heart failure). Second, there was considerable heterogeneity in the methods and statistical analyses from the included studies. For example, most studies did not report unadjusted effects, and many did not screen for pharmacological treatments of psychological health or sleep, which have long-term implications for cardiovascular health.78,79 In the meta-analysis we only included studies that provided dichotomous data to prioritize clinical interpretability, but excluding continuous data may over- or underestimate prognostic effects.87 Third, there are recognized subgroup differences in psychological distress prevalence and CVD risk but most included studies did not present data by sex or race. Future investigations should do so to better understand associations at the population level and among distinct demographic groups; these data may encourage scientific replication and inform more tailored primary prevention initiatives. Fourth, although we excluded or statistically accounted for known CVD, it is possible that individuals with elevated psychological distress had subclinical or undiagnosed, and therefore, uncontrolled CVD. Fifth, studies with stroke or hypertension as primary outcomes or included in a composite outcome were excluded due to the differing etiology or clinical timelines involved with such vascular events or conditions, although other meta-analyses have shown similar associations between psychological distress and risk for incident stroke.88 Sixth, with a spotlight on sleep in CVD risk,19 and well-described comorbidity between psychological disorders and sleep deficiency (eg, insomnia),67 sleep may be a more or less critical point of management than psychological distress. Seventh, methodologically, we did not include the Newcastle-Ottawa scale, which is often used to evaluate risk of bias in nonrandomized studies. Risk of publication bias was otherwise formally assessed, but further investigation should be considered. Finally, although every effort was made to identify relevant studies, some records may have been inadvertently missed in the systematized review processes.


This meta-analysis included recent investigations of the prospective effect of psychological distress on CVD morbidity and mortality in which psychological health was assessed with brief, self-report measures only. Our results showed meaningful effects, reaffirming and extending evidence to account for psychological distress in CVD primary prevention, particularly using validated screeners. In short, psychological health screening can be useful for providers to elucidate CVD risk more comprehensively, and management of psychological distress may reduce CVD risk and increase quality of life. Unfortunately, screening for psychological health continues to be the exception rather than the norm in CVD prevention. More research concerning measures of stress and sex-specific associations will help, and best practices for the implementation of such screening and clinical decision support in cardiovascular medicine should be tested and delineated. Still, when merging the current data concerning psychological health and CVD risk with distress screening approaches from other clinical specialties, there may already be sufficient evidence to implement distress screening for primary prevention of CVD and doing so may be more beneficial and ethical than not screening.


The authors are grateful to Laurie E. Storlazzi for her assistance in preparing the manuscript and to Matthew M. Burg, PhD for providing feedback on the initial draft.


1. Arnett DK, Blumenthal RS, Albert MA, et al. 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019;140(11):e596–e646.
2. Thomas H, Diamond J, Vieco A, et al. Global atlas of cardiovascular disease. Glob Heart. 2018;13(3):143–163.
3. Orth-Gomér K, Schneiderman N. Behavioral Medicine Approaches to Cardiovascular Disease Prevention. London, England: Psychology Press; 2013:1–336.
4. Tsao CW, Aday AW, Almarzooq ZI, et al. Heart disease and stroke statistics—2022 update: a report from the American Heart Association. Circulation. 2022;145(8):e153–e639.
5. Levine GN, Cohen BE, Commodore-Mensah Y, et al. Psychological health, well-being, and the mind-heart-body connection: a scientific statement from the American Heart Association. Circulation. 2021;143(10):e763–e783.
6. Lloyd-Jones DM, Hong Y, Labarthe D, et al. Defining and setting national goals for cardiovascular health promotion and disease reduction: the American Heart Association's strategic Impact Goal through 2020 and beyond. Circulation. 2010;121(4):586–613.
7. Edmondson D, von Känel R. Post-traumatic stress disorder and cardiovascular disease. Lancet Psychiatry. 2017;4(4):320–329.
8. Hare DL. Depression and cardiovascular disease. Curr Opin Lipidol. 2021;32(3):167–174.
9. Batelaan NM, Seldenrijk A, Bot M, van Balkom AJLM, Penninx BWJH. Anxiety and new onset of cardiovascular disease: critical review and meta-analysis. Br J Psychiatry. 2016;208(3):223–231.
10. Carney RM, Freedland KE. Depression and coronary heart disease. Nat Rev Cardiol. 2017;14(3):145–155.
11. Emdin CA, Odutayo A, Wong CX, Tran J, Hsiao AJ, Hunn BHM. Meta-analysis of anxiety as a risk factor for cardiovascular disease. Am J Cardiol. 2016;118(4):511–519.
12. Richardson S, Shaffer JA, Falzon L, Krupka D, Davidson KW, Edmondson D. Meta-analysis of perceived stress and its association with incident coronary heart disease. Am J Cardiol. 2012;110(12):1711–1716.
13. Vahedian-Azimi A, Moayed MS. Updating the meta-analysis of perceived stress and its association with the incidence of coronary heart disease. Int J Med Rev. 2019;6(4):146–153.
14. Kivimäki M, Steptoe A. Effects of stress on the development and progression of cardiovascular disease. Nat Rev Cardiol. 2018;15(4):215–229.
15. Yusuf S, Hawken S, Ôunpuu S, et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet. 2004;364(9438):937–952.
16. Dar T, Radfar A, Abohashem S, Pitman RK, Tawakol A, Osborne MT. Psychosocial stress and cardiovascular disease. Curr Treat Options Cardiovasc Med. 2019;21(5):1–17.
17. Van der Kooy K, van Hout H, Marwijk H, Marten H, Stehouwer C, Beekman A. Depression and the risk for cardiovascular diseases: systematic review and meta analysis. Int J Geriatr Psychiatry. 2007;22(7):613–626.
18. Gan Y, Gong Y, Tong X, et al. Depression and the risk of coronary heart disease: a meta-analysis of prospective cohort studies. BMC Psychiatry. 2014;14:371.
19. Lloyd-Jones DM, Allen NB, Anderson CAM, et al. Life's Essential 8: updating and enhancing the American Heart Association's construct of cardiovascular health: a presidential advisory from the American Heart Association. Circulation. 2022;146(5):e18–e43.
20. Pool LR, Ning H, Huffman MD, Reis JP, Lloyd-Jones DM, Allen NB. Association of cardiovascular health through early adulthood and health-related quality of life in middle age: the Coronary Artery Risk Development in Young Adults (CARDIA) Study. Prev Med. 2019;126:105772.
21. Lichtman JH, Bigger JT Jr, Blumenthal JA, et al. Depression and coronary heart disease: recommendations for screening, referral, and treatment: a science advisory from the American Heart Association Prevention Committee of the Council on Cardiovascular Nursing, Council on Clinical Cardiology, Council on Epidemiology and Prevention, and Interdisciplinary Council on Quality of Care and Outcomes Research: endorsed by the American Psychiatric Association. Circulation. 2008;118(17):1768–1775.
22. Siu AL, US Preventive Services Task Force (USPSTF); Bibbins-Domingo K, Grossman DC, et al. Screening for depression in adults: US Preventive Services Task Force recommendation statement. JAMA. 2016;315(4):380–387.
23. Centers for Medicare & Medicaid Services. Screening for depression in adults.
24. Privett N, Guerrier S. Estimation of the time needed to deliver the 2020 USPSTF preventive care recommendations in primary care. Am J Public Health. 2021;111(1):145–149.
25. Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097.
26. May M, McCarron P, Stansfeld S, et al. Does psychological distress predict the risk of ischemic stroke and transient ischemic attack? The Caerphilly Study. Stroke. 2002;33(1):7–12.
27. Carney RM, Freedland KE. Psychological distress as a risk factor for stroke-related mortality. Stroke. 2002;33(1):5–6.
28. Lipsey MW, Wilson DB. Practical Meta-analysis. Thousand Oaks, CA: SAGE Publications, Inc; 2001.
29. Veroniki AA, Jackson D, Viechtbauer W, et al. Methods to estimate the between-study variance and its uncertainty in meta-analysis. Res Synth Methods. 2016;7(1):55–79.
30. Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557–560.
31. Huedo-Medina TB, Sánchez-Meca J, Marín-Martínez F, Botella J. Assessing heterogeneity in meta-analysis: Q statistic or I² index? Psychol Methods. 2006;11(2):193–206.
32. Higgins JPT, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21(11):1539–1558.
33. StataCorp LP. Stata Statistical Software: Release 15 (2017). College Station, TX: StataCorp LP; 2017.
34. Lau J, Ioannidis JPA, Terrin N, Schmid CH, Olkin I. The case of the misleading funnel plot. BMJ. 2006;333(7568):597–600.
35. Sterne JA, Egger M. Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis. J Clin Epidemiol. 2001;54(10):1046–1055.
36. Egger M, Smith GD, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629–634.
37. Begg CB, Mazumdar M. Operating characteristics of a rank correlation test for publication bias. Biometrics. 1994;50(4):1088–1101.
38. Deschênes SS, Burns RJ, Graham E, Schmitz N. Depressive symptoms and sleep problems as risk factors for heart disease: A prospective community study. Epidemiol Psychiatr Sci. 2020;29:e50.
39. Dixon DD, Xu M, Akwo EA, et al. Depressive symptoms and incident heart failure risk in the Southern Community Cohort Study. JACC Heart Fail. 2022;10(4):254–262.
40. Feng T, Malmo V, Laugsand LE, et al. Symptoms of anxiety and depression and risk of atrial fibrillation-The HUNT study. Int J Cardiol. 2020;306:95–100.
41. Gaffey AE, Cavanagh CE, Rosman L, et al. Depressive symptoms and incident heart failure in the Jackson Heart Study: differential risk among black men and women. J Am Heart Assoc. 2022;11(5):e022514.
42. Garg PK, O'Neal WT, Diez-Roux AV, Alonso A, Soliman EZ, Heckbert S. Negative affect and risk of atrial fibrillation: MESA. J Am Heart Assoc. 2019;8(1):e010603.
43. Han L, Shen S, Wu Y, Zhong C, Zheng X. Trajectories of depressive symptoms and risk of cardiovascular disease: Evidence from the China Health and Retirement Longitudinal Study. J Psychiatr Res. 2021;145:137–143.
44. Harshfield EL, Pennells L, Schwartz JE, et al. Association between depressive symptoms and incident cardiovascular diseases. JAMA. 2020;324(23):2396–2405.
45. Karlsen HR, Saksvik-Lehouillier I, Stone KL, Schernhammer E, Yaffe K, Langvik E. Anxiety as a risk factor for cardiovascular disease independent of depression: a prospective examination of community-dwelling men (the MrOS study). Psychology Health. 2021;36(2):148–163.
46. Ladwig KH, Baumert J, Marten-Mittag B, Lukaschek K, Johar H, Fang X, Ronel J, Meisinger C, Peters A. Room for depressed and exhausted mood as a risk predictor for all-cause and cardiovascular mortality beyond the contribution of the classical somatic risk factors in men. Atherosclerosis. 2017;257:224–231.
47. Lemogne C, Meneton P, Wiernik E, Quesnot A, Consoli SM, Ducimetière P, Nabi H, Empana JP, Hoertel N, Limosin F, Goldberg M. When blue-collars feel blue: depression and low occupational grade as synergistic predictors of incident cardiac events in middle-aged working individuals. Circ Cardiovasc Qual Outcomes. 2017;10(2):e002767.
48. Li H, Zheng D, Li Z, et al. Association of depressive symptoms with incident cardiovascular disease in middle-aged and older Chinese adults. JAMA Netw Open. 2019;2(12):e1916591.
49. Li H, Qian F, Hou C, et al. Longitudinal changes in depressive symptoms and risks of cardiovascular disease and all-cause mortality: a nationwide population-based cohort study. J Gerontol A Biol Sci Med Sci. 2020;75(11):2200–2206.
50. Piantella S, Dragano N, Marques M, McDonald SJ, Wright BJ. Prospective increases in depression symptoms and markers of inflammation increase coronary heart disease risk-The Whitehall II cohort study. J Psychosom Res. 2021;151:110657.
51. Poole L, Steptoe A. Depressive symptoms predict incident chronic disease burden 10 years later: findings from the English Longitudinal Study of Ageing (ELSA). J Psychosom Res. 2018;113:30–36.
52. Poole L, Jackowska M. The association between depressive and sleep symptoms for predicting incident disease onset after 6-year follow-up: findings from the English Longitudinal Study of Ageing. Psychol Med. 2019;49(4):607–616.
53. Rantanen AT, Korkeila JJ, Kautiainen H, Korhonen PE. Non-melancholic depressive symptoms increase risk for incident cardiovascular disease: a prospective study in a primary care population at risk for cardiovascular disease and type 2 diabetes. J Psychosm Res. 2020;129:109887.
54. Remch M, Laskaris Z, Flory J, Mora-McLaughlin C, Morabia A. post-traumatic stress disorder and cardiovascular diseases: a cohort study of men and women involved in cleaning the debris of the World Trade Center Complex. Circ Cardiovasc Qual Outcomes. 2018;11(7):e004572.
55. Vu K, Claggett BL, John JE, et al. Depressive symptoms, cardiac structure and function, and risk of incident heart failure with preserved ejection fraction and heart failure with reduced ejection fraction in late life. J Am Heart Assoc. 2021;10(23):e020094.
56. Yu L, Chen Y, Wang N, et al. Association between depression and risk of incident cardiovascular diseases and its sex and age modifications: a prospective cohort study in southwest China. Front Pub Health. 2022;10:765183.
57. Zhu C, Wang J, Wang J, et al. Associations between depressive symptoms and sleep duration for predicting cardiovascular disease onset: a prospective cohort study. J Affect Disord. 2022;303:1–9.
58. Scherrer JF, Salas J, Schneider FD, et al. PTSD improvement and incident cardiovascular disease in more than 1,000 Veterans. J Psychosom Res. 2020;134:110128.
59. Graff S, Prior A, Fenger-Grøn M, Christensen B, Glümer C, Larsen FB, Vestergaard M. Does perceived stress increase the risk of atrial fibrillation? A population-based cohort study in Denmark. Am Heart J. 2017;188:26–34.
60. Santosa A, Rosengren A, Ramasundarahettige C, et al. Psychosocial risk factors and cardiovascular disease and death in a population-based cohort from 21 low-, middle-, and high-income countries. JAMA Netw Open. 2021;4(12):e2138920.
61. Bonaccio M, Di Castelnuovo A, Costanzo S, et al. Health-related quality of life and risk of composite coronary heart disease and cerebrovascular events in the Moli-sani study cohort. Eur J Prev Cardiol. 2018;25(3):287–297.
62. Nilsson E, Festin K, Lowén M, Kristenson M. SF-36 predicts 13-year CHD incidence in a middle-aged Swedish general population. Qual Life Res. 2020;29(4):971–975.
63. Phyo AZ, Ryan J, Gonzalez-Chica DA, et al. Health-related quality of life and incident cardiovascular disease events in community-dwelling older people: a prospective cohort study. Int J Cardiol. 2021;339:170–178.
64. Pinheiro LC, Reshetnyak E, Sterling MR, Richman JS, Kern LM, Safford MM. Using health-related quality of life to predict cardiovascular disease events. Qual Life Res. 2019;28(6):1465–1475.
65. Wimmelmann CL, Andersen NK, Grønkjaer MS, Hegelund ER, Flensborg-Madsen T. Satisfaction with life and SF-36 vitality predict risk of ischemic heart disease: a prospective cohort study. Scand Cardiovasc J. 2021;55(3):138–144.
66. Fransson EI, Nordin M, Magnusson Hanson LL, Westerlund H. Job strain and atrial fibrillation—results from the Swedish Longitudinal Occupational Survey of Health and meta-analysis of three studies. Eur J Prev Cardiol. 2018;25(11):1142–1149.
67. Davidson KW, Alcántara C, Miller GE. Selected psychological comorbidities in coronary heart disease: challenges and grand opportunities. Am Psychol. 2018;73(8):1019–1030.
68. Franklin BA, Myers J, Kokkinos P. Importance of lifestyle modification on cardiovascular risk reduction: counseling strategies to maximize patient outcomes. J Cardiopulm Rehabil Prev. 2020;40(3):138–143.
69. Bale TL, Epperson CN. Sex differences and stress across the lifespan. Nat Neurosci. 2015;18(10):1413–1420.
70. Altemus M, Sarvaiya N, Epperson CN. Sex differences in anxiety and depression clinical perspectives. Front Neuroendocrinol. 2014;35(3):320–330.
71. Medina-Inojosa JR, Vinnakota S, Garcia M, et al. Role of stress and psychosocial determinants on women's cardiovascular risk and disease development. J Womens Health. 2019;28(4):483–489.
72. Supraja T, Bhargavi C, Chandra PS. Stress among women—causes and consequences. In: Stress and Struggles: The Comprehensive Book on Stress, Mental Health and Mental Illness. Coventary, England and Bengaluru, India: Indo-UK Stress and Mental Health Group; 2020:427–449.
73. Lee SK, Khambhati J, Varghese T, et al. Comprehensive primary prevention of cardiovascular disease in women. Clin Cardiol. 2017;40(10):832–838.
74. Cho L, Davis M, Elgendy I, et al. Summary of updated recommendations for primary prevention of cardiovascular disease in women: JACC state-of-the-art review. J Am Coll Cardiol. 2020;75(20):2602–2618.
75. Anand SS, Islam S, Rosengren A, et al. Risk factors for myocardial infarction in women and men: insights from the INTERHEART study. Eur Heart J. 2008;29(7):932–940.
76. Bhardwaj M, Price J, Landry M, Harvey P, Hensel JM. Association between severity of depression and cardiac risk factors among women referred to a cardiac rehabilitation and prevention clinic. J Cardiopulm Rehabil Prev. 2018;38(5):291–296.
77. Fegers-Wustrow I, Gianos E, Halle M, Yang E. Comparison of American and European Guidelines for primary prevention of cardiovascular disease: JACC guideline comparison. J Am Coll Cardiol. 2022;79(13):1304–1313.
78. Gaffey AE, Rosman L, Burg MM, et al. Posttraumatic stress disorder, antidepressant use, and hemorrhagic stroke in young men and women: a 13-year cohort study. Stroke. 2021;52(1):121–129.
79. Davidson KW, Bigger JT, Burg MM, et al. Centralized, stepped, patient preference–based treatment for patients with post–acute coronary syndrome depression: CODIACS vanguard randomized controlled trial. JAMA Intern. Med. 2013;173(11):997–1004.
80. Goldstein CM, Gathright EC, Garcia S. The relationship between depression and medication adherence in cardiovascular disease: the perfect challenge for the integrated care team. Patient Prefer Adher. 2017;11:547–559.
81. Piolanti A, Gostoli S, Gervasi J, Sonino N, Guidi J. A trial integrating different methods to assess psychosocial problems in primary care. Psychother Psychosom. 2019;88(1):30–36.
82. Castañeda SF, Gallo LC, Garcia ML, et al. Effectiveness of an integrated primary care intervention in improving psychosocial outcomes among Latino adults with diabetes: the LUNA-D study. Transl Behav Med. 2022;12(8):825–833.
83. Blount A. Integrated primary care: organizing the evidence. Fam Syst Health. 2003;21(2):121–134.
84. Kearney LK, Zeiss AM, McCabe MA, et al. Global approaches to integrated care: best practices and ongoing innovation. Am Psychol. 2020;75(5):668–682.
85. Lemmens LC, Molema CCM, Versnel N, Baan CA, de Bruin SR. Integrated care programs for patients with psychological comorbidity: a systematic review and meta-analysis. J Psychosom Res. 2015;79(6):580–594.
86. Gaffey AE, Harris KM, Mena-Hurtado C, Sinha R, Jacoby DL, Smolderen KG. The Yale Roadmap for health psychology and integrated cardiovascular care. Health Psychol. 2022;41(10):779–791.
87. Nicholson A, Kuper H, Hemingway H. Depression as an aetiologic and prognostic factor in coronary heart disease: a meta-analysis of 6362 events among 146 538 participants in 54 observational studies. Eur Heart J. 2006;27(23):2763–2774.
88. Wium-Andersen MK, Wium-Andersen IK, Prescott EIB, Overvad K, Jørgensen MB, Osler M. An attempt to explain the bidirectional association between ischaemic heart disease, stroke and depression: a cohort and meta-analytic approach. Br J Psychiatry. 2020;217(2):434–441.

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