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. Author manuscript; available in PMC: 2023 Oct 1.
Published in final edited form as: J Aging Health. 2022 Apr 11;34(6-8):961–972. doi: 10.1177/08982643221083118

The Association of Dispositional Optimism and Pessimism With Cardiovascular Disease Events in Older Adults: A Prospective Cohort Study

Heather Craig 1, Joanne Ryan 1,2, Rosanne Freak-Poli 1, Alice Owen 1, John McNeil 1, Robyn L Woods 1, Carlene Britt 1, Andrew Tonkin 1, Danijela Gasevic 1,3
PMCID: PMC10026003  NIHMSID: NIHMS1878730  PMID: 35410519

Abstract

Objective:

Positive psychosocial factors may protect against cardiovascular disease (CVD). We aimed to determine the association of optimism and pessimism with CVD events in community-dwelling older adults.

Methods:

11,651 adults aged 70 years and over, participants of the ASPREE Longitudinal Study of Older Persons (ALSOP), were followed-up for 4.7 years (median). The association of optimism and pessimism (assessed as separate constructs by revised Life Orientation Test) and incident CVD events (composite and components) was assessed by Cox regression adjusted for demographic, socioeconomic and health factors.

Results:

No association was observed between optimism and pessimism with composite CVD events. Being more pessimistic was associated with a greater risk of fatal coronary heart disease, while being more optimistic was associated with a lower risk of non-fatal myocardial infarction.

Conclusions:

Optimism and pessimism may shape cardiovascular health of older adults; and we argue these psychosocial factors should be researched as separate constructs.

Keywords: cardiovascular disease, optimism, pessimism, LOT-R, cohort-study, cardiac health

Introduction

Cardiovascular disease (CVD) is the leading contributor to disease burden globally, with 17.8 million deaths caused by CVD, 330 million years of life lost, and a further 35.6 million years of life lived with disability in 2017 (GBD Causes of Death Collaborators, 2018; GBD DALYs & HALE Collaborators, 2018). Older age is an independent risk factor for CVD (Rodgers et al., 2019). One in six (16%) of the global population is expected to be aged over 65 years by 2050—an increase in the proportion of older adults from one in 11 people (9%) in 2019 (UN DESA Population Division, 2019). The greater proportion of older adults in the population is expected to result in an age-related increase in CVD, bringing with it a sizeable burden in terms of mortality, morbidity, disability, functional decline and healthcare costs (Yazdanyar & Newman, 2009).

CVD is a complex, multifactorial disease associated with various risk factors such as age, genetic, behavioral and biomedical risk factors, and social determinants (Dahlöf, 2010). Psychosocial risk factors have also been identified as risk factors for CVD, and argued to be associated with the pathogenesis and management of CVD (Schneiderman et al., 2019). Some psychosocial factors, such as pessimism, have been reported to increase the risk of CVD, while others, such as optimism, may have a “health-buffering” effect by promoting the likelihood of positive physiological functioning and an individual engaging in healthy behaviors (such as eating a more nutritious diet and getting adequate exercise) (Rozanski, 2016).

Optimism may be understood as a tendency to have favorable futuristic expectations, whereas pessimism is the tendency to predict the worst (9). Optimism is considered to be both a trait and a state component of personality, and though partly heritable, it is also influenced by life experience and environment and may be modified through interventions (Kluemper et al., 2009; Malouff & Schutte, 2017). One of the most commonly measured forms of optimism is dispositional optimism, a relatively stable trait of positive expectations, which is most frequently measured by the validated, revised version of the Life Orientation Test (LOT-R), developed by Scheier et al. (1994). When Scheier et al. (1994) developed the LOT-R, they provided the view that dispositional optimism was unidimensional, and that optimism and pessimism were polar opposites. However, since then, other researchers have argued that optimism and pessimism are distinct, separate constructs (Felt et al., 2020; Robinson-Whelen et al., 1997; Roy et al., 2010; Serlachius et al., 2015). The concept that optimism and pessimism are separate constructs is further supported by a recent argument that there are different outcomes associated with optimism and pessimism, and that correlations between the subscale scores of optimism and pessimism on the LOT-R are low (Felt et al., 2020).

Researching the association between optimism and CVD may be particularly important in older adults, as it has been argued that prior to the approximate age of 70, levels of optimism gradually increase, while after age 70, optimism gradually decreases and pessimism is thought to increase (Chopik et al., 2015, 2020). It has also been reported that as people age, optimism and pessimism become more independent of one another (Herzberg et al., 2006; Robinson-Whelen et al., 1997) providing a rationale for studying optimism and pessimism as separate constructs in an older adult population.

Optimism is one of the most well researched psychological assets for health. Our systematic review (Craig et al., 2021) of 25 studies reports that higher optimism is associated with a lower risk of all-cause mortality (pooled RR = 0.85, 95% CI = 0.79–0.91), while pessimism is associated with an increased risk of premature death (pooled RR = 1.15, 95% CI: 1.08–1.24). Rozanski et al. (2019) undertook a systematic review and meta-analysis of the association between optimism and risk for future cardiovascular events and reported that from 10 studies, optimism was associated with a lower risk of CVD events (RR 0.65, 95% CI = 0.51–0.78). Prior research also highlights the association of greater optimism with lower risk of CVD mortality (Kim et al., 2017), superior cardiovascular health (e.g., Kubzansky et al., 2018), cardiac health promoting behaviors (Boehm et al., 2018), as well as work demonstrating the association of optimism and CVD risk in older adults (Anthony et al., 2016). However, the results of the recent meta-analysis on the association between optimism and risk of CVD (Rozanski et al., 2019) indicate that evidence researching older adults is scarce, and that only a single study assessed optimism and pessimism as separate construct (Anthony et al., 2016). Therefore, by researching optimism and pessimism as separate constructs, our study aims to determine the association of optimism and pessimism with a range of CVD events in a large sample of males and females aged 70 years and over.

Methods

Study Population

ASPREE (ASPirin in Reducing Events in the Elderly study) enrolled 19,114 older, community-dwelling adults living in the United States (US) or Australia between 2010 and 2014 who were free of major physical disability, dementia, and had no prior CVD events. (J. J. McNeil et al., 2017).

Recruitment was community based mainly through clinical trial centers (US), or undertaken in collaboration with selected primary care physicians (Australia) who screened willing patients for suitability to take part in the study through their community-based practices (Grimm et al., 2013; J. J. McNeil et al., 2017). Namely, community-dwelling individuals interested in participating in the ASPREE were screened for suitability and eligibility by phone and then, after informed consent was obtained, the study eligibility was confirmed at an “inperson” visit. 83,376 older adults underwent phone screening, and the most common reasons for exclusion during recruitment were a history of CVD, compliance of <80% during the 4-week placebo run-in, cognitive decline/dementia indicated by a 3MS score of <78, not independent in self-care, as assessed by Katz Activities of Daily Living, low hemoglobin, high blood pressure or the opinion of the GP co-investigator. The overarching aim of ASPREE was to investigate whether a daily, low-dose of aspirin had health benefits for older individuals (J. J. McNeil et al., 2019), and the results have been published elsewhere (McNeil, Nelson et al., 2018; McNeil, Wolfe et al., 2018; McNeil, Woods et al., 2018).

A subsample of Australian participants was also recruited to the ASPREE Longitudinal Study of Older Persons (ALSOP) sub-study (J. J. McNeil et al., 2019). The ALSOP sub-study included measures of various factors potentially contributing to aging health or disease—self-reported medical or health features, lifestyle, behavioral, social, and environmental indicators (J. J. McNeil et al., 2019). ALSOP required participants to complete a series of baseline questionnaires, and then biennial questionnaires thereafter. Of the participants who were invited to take part in ALSOP (16,703 individuals), 12,896 returned the social baseline questionnaire, which contained the LOT-R used to assess optimism and pessimism. A comparison of baseline characteristics between participants included in analysis and those excluded is provided in the Supplemental Table S1.

Measures and Scales

Assessment of Optimism and Pessimism.

The LOT-R was used to measure both optimism and pessimism. This brief questionnaire consists of 10 items. Four filler items were omitted to reduce the burden on participants completing the questionnaire (Kim et al., 2019). Three positively worded items make up the optimism subscale, while three negatively worded items make up the pessimism subscale. Participants responded on a 5-point Likert scale that ranges from 1 = strongly disagree to 5 = strongly agree. The six item LOT-R has good test-retest reliability, and it also has both convergent and discriminant validity (Scheier et al., 1994).

In this study we assessed the optimism and pessimism subscales of the LOT-R separately, based on the most recent evidence stating the independence of optimism and pessimism as constructs, which has been described previously in this paper (Herzberg et al., 2006; Robinson-Whelen et al., 1997; Serlachius et al., 2015).

The data were negatively skewed; thus, optimism and pessimism were categorized into tertiles (T1-T3), with a higher tertile representing higher optimism/pessimism which was aligned with the publication by Anthony et al. (2016). For optimism, T1 (the lowest optimism tertile) was classified as LOT-R subscale scores of 3–11; T2, subscale scores 12–13; and T3, subscale scores 14–15. For pessimism, T1 was classified as LOT-R subscale scores of 3–4; T2, subscale scores 5–8; and T3 (highest pessimism), subscale scores of 9–15.

Assessment of CVD outcomes.

The primary outcome for this analysis is the prespecified CVD secondary endpoint of the ASPREE clinical trial (McNeil, Wolfe et al., 2018). This composite outcome included coronary heart disease death, non-fatal myocardial infarction (MI), fatal or non-fatal stroke, and hospitalization from heart failure (McNeil, Wolfe et al., 2018).

Any death which could be attributed to the underlying cause of coronary heart disease (CHD), in addition to death from myocardial infarction or sudden cardiac death was used to define fatal coronary heart disease (McNeil, Wolfe et al., 2018). The definition of non-fatal MI was based on that from the European Society of Cardiology and the American College of Cardiology (Alpert et al., 2000). The definition of fatal stroke was any death caused by obstruction or rupture in the intracranial or extracranial cerebral arterial system. Non-fatal stroke was defined as per the World Health Organization: clinical signs of focal or global disturbance of cerebral function that developed quickly and lasted at least 24 hours (excluding those cases whereby the disturbance is interrupted by surgery or death), and caused by ischemic or hemorrhagic cerebro-vascular disease (rather than another apparent cause) (WHO, 1989). Hospitalization for heart failure was defined as a participant having an unplanned stay of at least one night within a hospital (including the emergency department, observation unity or inpatient unit), or a similar facility, because of heart failure and other criteria to substantiate the diagnosis (Alpert et al., 2000).

In addition, major adverse cardiovascular events (MACE) due to ischemia represented a non-prespecified endpoint in the major ASPREE publication (McNeil, Wolfe et al., 2018). It was a composite of death from coronary heart disease (but not attributable to heart failure), MI (non-fatal) or ischemic stroke (fatal or non-fatal) (McNeil, Wolfe et al., 2018).

Outcomes were ascertained in the ASPREE study, prior to our data analysis. In the clinical trial, all potential CVD events (both fatal and non-fatal) were monitored. Source information was gathered from next-of-kin or other family member, such as documents from hospitals and medical centers, treating physicians, death certificates, other medical records, and hospital information. Where relevant, medical documentation was collected and sent to the ASPREE data management center, and presented to adjudicators for whom all cases were blinded. Inclusion of events were decided by international endpoint adjudication committees who considered all information, including relevant diagnostic tests (e.g., autopsy results, ECGs, biochemical markers, pathologic findings, and imaging—i.e., CT, MRI).

Confounders

Putative confounders associated with both optimism/pessimism and CVD in the literature (Rozanski et al., 2019) included self-reported age (70–74 years, 75–84 years, 85 years and older), gender (male or female), living situation (lives with other people or lives alone), level of education (12 years or less of education, more than 12 years of education); smoking status that was assessed by asking a question about the participant’s lifetime smoking history, with the possible responses being “current,” “former,” “never”; alcohol intake assessed by asking a question about lifetime alcohol use, with the possible responses also being “current,” “former,” or “never”; physical activity in a typical week (less physically active: rarely, never or does only light activity; more physically active: does moderate or vigorous activity), and body mass index (BMI), calculated from the objectively measured height and weight as the ratio of weight in kilograms divided by height in meters squared (kg/m2).

Statistical Analysis

Baseline characteristics of study participants were stratified by tertiles of optimism and pessimism, and presented as counts and percentages. Group difference in sociodemographic factors and health-related behaviors was assessed using χ2 tests for categorical variables, and t-tests for continuous variables.

The relationships of optimism and pessimism with CVD events and MACE were assessed using the Cox Proportional Hazards models with time-to-event analysis, and Hazard ratios (HR) and 95% confidence intervals (95% CI) are presented. Hazards of the components of the composite CVD measure were estimated for optimism and pessimism, with deaths from other reasons than the outcomes of interest as the censoring events. Entry was considered as the baseline completion of the LOT-R when participants were enrolled in ASPREE, and the endpoint was either the date on which the CVD event occurred, measured as days post randomization, or the date of the last data where adjudicators were confident that no CVD event had occurred.

Consecutive adjustments in the regression models were made for potential confounding variables associated with both optimism/pessimism and CVD that were identified from previous studies. To avoid the issue of multi-collinearity, we used Spearman rank correlations to test if any of the variables were intercorrelated (Kraemer, 2003). As correlation coefficients were all low (r < 0.30) (Supplemental Table S2) all the a priori putative confounders were included in the subsequent models.

Model one was unadjusted (crude model), and Model 2 was adjusted for baseline age, gender, living situation, level of education, smoking status, daily alcohol consumption, physical activity, and BMI.

Components of the CVD composite measure (fatal CHD, non-fatal MI, fatal and non-fatal stroke, hospitalization for heart failure) were evaluated in post-hoc analysis to better understand the association of optimism and pessimism with the separate CVD events in the study. For each component, HR and 95%CI was determined (see supplementary digital content, Supplemental Table S3). The proportional hazards assumption was tested for each Cox model, and it was met. Tests for interaction were performed, and based on multiplicative and additive interactions, age and gender did not modify the association between optimism/pessimism and CVD/MACE. (p > .05 for all models), and, therefore, the analyses were performed on a total study sample.

Competing risk regression, a modified survival analysis method, was used to assess the risk of fatal CHD, such that the regression accounted for competing events (i.e., death from another cause). The survival regression model based on cumulative incidence function (CIF) from Fine and Gray (1999) was used to assess the probability of death from CHD, while taking into account the risk of death from either cancer-related causes, major hemorrhage or other cause, by using the time-to-event data for the competing causes of death. Sub-distribution hazard ratios (SHR) and 95% CIs were determined and reported.

Randomization for ASPREE commenced in 2010, and ALSOP began in early 2012. Thus, for a small proportion of the ASPREE cohort who enrolled early, there was a difference in the timing of the collection of baseline ASPREE data and the completion of the LOT-R (in the ALSOP social baseline questionnaire) (J. J. McNeil et al., 2019). Therefore, we conducted sensitivity analysis to assess reverse causality by excluding participants with their first CVD event, or MACE, (or censored) within the first 6 months, and then within 1 year (supplemental Tables S4 and S5).

It is hypothetically plausible that optimism and pessimism may not have an independent association with CVD, and rather signal the absence of depression in our cohort. As such, additional sensitivity analysis was done to adjust for depression as a confounder. Additional sensitivity analyses were performed to explore whether optimism and pessimism impact CVD independently from one another.

All statistical analyses were done using Stata version 16.0 (StataCorp LLC, College Station Texas, USA).

Ethical Approval

The project was reviewed and approved by the Monash University Human Research Ethics committee, reference number: 21906. The ASPREE study complies with the Declaration of Helsinki, and was approved by multiple Institutional Review Boards. All participants provided informed written consent prior to taking part in the ASPREE and ALSOP studies.

Results

Of the total number of participants who completed the social baseline questionnaire (n = 12,896), 1245 individuals were excluded from the subsequent analysis because data were incomplete. Compared to participants for whom complete data were available, those with missing data tended to be older, female, higher in optimism and pessimism, live alone, have lower level of formal education, never smoke or consume alcohol, and be more physically active (Supplemental Table S2). The final study sample included 11,651 participants (53.3% females).

There were 495 participants who experienced an incident CVD event over the median 4.7 years of follow-up from the date of ASPREE randomization (for the sample of 11,651 participants) (IQR 3.6, 5.6), a rate of 9.6 events per 1000 person years, while the rate of MACE was 7.2 events per 1000 person years. There were 43 cases of fatal CHD over this time, a rate of 0.7 per 1000 person years. The rate of strokes (both fatal and non-fatal) was 3.9 events per 1000 person years, while there was a rate of non-fatal MI of 3.3 events per 1000 person years. Rates of hospitalization for heart failure were lower—1.8 events per 1000 person years.

At baseline, participants belonging to the highest tertile of optimism were more likely to be female, have more than 12 years of education, have never smoked, and be more physically active (Table 1). Age, living situation and BMI were similar across tertiles of optimism. Participants belonging to the highest tertile of pessimism were more likely to be older, have 12 or less years of formal education, smoke, be less physically active, be a former drinker or never drinking (Table 2). We report the Cronbach alphas for the analytic sample to be acceptable to good—0.66 (optimism subscale), 0.80 (pessimism subscale) and 0.74 (composite score).

Table 1.

Baseline Characteristics According to Tertiles of Optimism, n = 11,651.

Tertiles of optimism
T1 (lowest)
 T2
 T3 (highest)
(n = 3950) (n = 4781) (n = 2920) p-value
Age, Mean ± SD 75.0 ± 4.22 75.1 ± 4.29 75.1 ± 4.18 .75
Age, n (%)
 70–74 2391 (60.5) 2857 (59.8) 1716 (58.8) .44
 75–84 1432 (36.3) 1761 (36.8) 1117 (38.3)
 ≥85 127 (3.2) 163 (3.4) 87 (3.0)
Sex, n (%)
 male 1957 (49.5) 2239 (46.8) 1249 (42.8) <.001
 female 1993 (50.5) 2542 (53.2) 1671 (57.2)
Education level, n (%)
 ≤12 years 2423 (61.3) 2772 (58.0) 1558 (53.4) <.001
 >12 years 1527 (38.7) 2009 (42.0) 1362 (46.6)
Living situation, n (%)
 lives with others 2760 (69.9) 3418 (71.5) 2044 (70.0) .19
 lives alone 1190 (30.1) 1363 (28.5) 876 (30.0)
Smoking status, n (%)
 never 2087 (52.8) 2657 (55.6) 1725 (59.1) <.001
 current/former 1863 (47.2) 2124 (44.4) 1195 (40.9)
Alcohol intake, n (%)
 never 549 (13.9) 694 (14.5) 507 (17.4) <.001
 current 3180 (80.5) 3907 (81.7) 2276 (77.9)
 former 221 (5.6) 180 (3.8) 137 (4.7)
Physical activity, n (%)
 less active 1472 (37.2) 1567 (32.8) 872 (29.9) <.001
 more active 2479 (62.8) 3214 (67.2) 2048 (70.1)
BMI, Mean ± SD 27.9 ± 4.49 27.9 ± 4.47 27.9 ± 4.47 .69
CVD, n (%)
 yes 172 (4.4) 205 (4.3) 118 (4.0) .80
 no 3778 (95.6) 4576 (99.5) 2802 (57.0)
Fatal CHD, n (%)
 yes 19 (0.5) 13 (0.3) 11 (0.4) .28
 no 3931 (99.5) 4768 (99.7) 2909 (99.6)
Hospitalization for heart
Failure, n (%)
 yes 43 (1.1) 33 (0.7) 20 (0.7) .08
 no 3907 (98.9) 4748 (99.3) 2900 (99.3)
Non-fatal MI, n (%)
 yes 63 (1.6) 91 (1.9) 36 (1.2) .08
 no 3887 (98.4) 4690 (98.1) 2884 (98.8)
Stroke, n (%)
 yes 66 (1.7) 77 (1.6) 62 (2.1) .22
 no 3884 (98.3) 4704 (98.4) 2858 (97.9)
MACE, n (%)
 yes 121 (3.1) 161 (3.4) 91 (3.1) .69
 no 3829 (96.9) 4620 (96.6) 2829 (96.9)
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T1: tertile one, optimism sub scores 3–11; T2: tertile two, optimism sub scores 12–13; T3: tertile three, optimism sub scores 14–15; BMI: body mass index; CVD: cardiovascular disease; CHD: coronary heart disease; MI: myocardial infarction; MACE: major adverse cardiovascular events.

Table 2.

Baseline Characteristics According to Tertiles of Pessimism, n = 11,651.

Tertiles of pessimism
T1 (lowest)
 T2
 T3 (highest)
(n = 4904) (n = 2958) (n = 3789) p-value
Age, mean ± SD 74.9 ± 4.13 75.1 ± 4.16 75.3 ± 4.43 <.001
Age, n (%)
 70–74 3034 (61.9) 1740 (58.8) 2190 (57.8) <.001
 75–84 1732 (35.3) 1130 (3.8) 1448 (38.2)
 ≥85 138 (2.8) 88 (3.0) 151 (4.0)
Sex, n (%)
 male 2052 (41.8) 1509 (51.0) 1884 (49.7) <.001
 female 2852 (58.2) 1449 (49.0) 1905 (50.3)
Education level, n (%)
 ≤12 years 2337 (47.7) 1708 (57.7) 2708 (71.5) <.001
 >12 years 2567 (52.3) 1250 (42.3) 1081 (28.5)
Living situation, n (%)
 lives with others 3420 (69.7) 2150 (72.7) 2652 (70.0) .01
 lives alone 1484 (30.3) 808 (27.3) 1137 (30.0)
Smoking status, n (%)
 never 2870 (58.5) 1626 (55.0) 1973 (52.1) <.001
 current/former 2034 (41.5) 1332 (45.0) 1816 (47.9)
Alcohol intake, n (%)
 never 700 (14.3) 422 (14.3) 628 (16.6) <.001
 current 4023 (82.0) 2405 (81.3) 2935 (77.5)
 former 181 (3.7) 131 (4.4) 226 (6.0)
Physical activity, n (%)
 less active 1514 (30.9) 971 (32.8) 1425 (37.6) <.001
 more active 3390 (69.1) 1987 (67.2) 2364 (62.4)
BMI, mean ± SD 27.6 ± 4.30 29.9 ± 4.41 28.3 ± 4.71 <.001
CVD, n (%)
 yes 197 (4.0) 114 (3.9) 184 (4.9) .07
 no 4707 (96.0) 2844 (96.1) 3605 (95.1)
Fatal CHD, n (%)
 yes 15 (3.1) 12 (0.4) 16 (0.4) .63
 no 4889 (99.7) 2946 (99.6) 3773 (99.6)
Hospitalization for heart
Failure, n (%)
 yes 34 (0.7) 23 (0.8) 39 (1.0) .22
 no 4870 (99.3) 2935 (99.4) 3750 (99.0)
non-fatal MI, n (%)
 yes 75 (1.5) 43 (1.5) 72 (1.9) .27
 no 4829 (98.5) 2915 (98.5) 3717 (98.1)
Stroke, n (%)
 yes 82 (1.7) 46 (1.6) 77 (2.0) .28
 no 4822 (98.3) 2912 (98.4) 3712 (98.0)
MACE, n (%)
 yes 149 (3.0) 86 (2.9) 138 (3.6) .16
 no 4755 (97.0) 2872 (97.1) 3651 (96.4)
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T1: tertile one, pessimism sub scores 3–4; T2: tertile two, pessimism sub scores 5–8; T3: tertile three, pessimism sub scores 9–15; BMI: body mass index; CVD: cardiovascular disease; CHD: coronary heart disease; MI: myocardial infarction; MACE: major adverse cardiovascular events.

There was no association between optimism and CVD events or MACE (Table 3). Compared to those with lowest pessimism (T1), those with highest (T3) had a higher risk of CVD (HR (95%CI) = 1.23 (1.01, 1.51) (Table 3). However, after adjustment for the putative confounders, there was no association between pessimism and CVD.

Table 3.

Cox Proportional Hazards Regression for the Association of Optimism and Pessimism with CVDa and MACEb (n = 11,651).

Optimism
 Pessimism
HR (95% CI) p
 HR (95% CI) p
T2 versus T1 T3 versus T1 T2 versus T1 T3 versus T1
CVD events
 Model 1 0.98 (0.80–1.20) .82 0.92 (0.73–1.16) .48 0.97 (0.77–1.22) .76 1.23 (1.01–1.51) .04
 Model 2 1.03 (0.84–1.26) .78 1.02 (0.80–1.29) .89 0.87 (0.69–1.09) .23 1.03 (0.83–1.26) .80
MACE
 Model 1 1.09 (0.86–1.38) .46 1.01 (0.77–1.33) .94 0.96 (0.74–1.26) .78 1.22 (0.97–1.54) .09
 Model 2 1.15 (0.91–1.46) .23 1.12 (0.86–1.47) .41 0.86 (0.65–1.12) .25 1.02 (0.81–1.30) .85
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a

Composite CVD measure: fatal CHD, non-fatal MI, stroke, hospitalization for heart failure; n (events)—Optimism: T1 = 172; T2= 205; T3 = 118; Pessimism—T1 = 197; T2 = 114; T3 = 184.

b

MACE: CHD death, non-fatal MI, ischemic stroke; n (events)—Optimism: T1 = 121; T2 = 161; T3 = 91; Pessimism: T1 = 149; T2 = 86; T3 = 138; Model 1: crude model; Model 2: model 1 + age, sex, living situation, education level, alcohol intake, smoking status, physical activity, and BMI; CVD: cardiovascular disease events; MACE: Major adverse cardiovascular events; MI: myocardial infarction; T1: tertile one, optimism sub scores 3–11; T2: tertile two, optimism sub scores 12–13; T3: tertile three, optimism sub scores 14–15; T1: tertile one, pessimism sub scores 3–4; T2: tertile two, pessimism sub scores 5–8; T3: tertile three, pessimism sub scores 9–15. Numbers presented in bold indicate statistically significant association.

Analyses testing the association of optimism and pessimism with component measures indicate that those in the highest tertile of optimism were less likely to experience non-fatal MI (HR: 0.58, 95% CI: 0.37–0.89, p = 0.01), while those in the highest tertile of pessimism were more likely to experience fatal CHD (HR: 5.62, 95% CI: 1.44–22.02, p = 0.01) (Supplemental Table S3).

Sensitivity analysis that excluded CVD events (or censored) in the first 6 months post randomization were similar to main findings (Supplemental Tables S4 and S5). Similarly, our overall conclusions did not differ when inclusion was restricted to active participants after 1-year from randomization. The results of sensitivity analyses with depression as an additional covariate were similar to main findings across models (Supplemental Table S6 and S7). Supplemental Table S8 and S9 present that there was no association between optimism and pessimism and CVD events when included in the same model, which is consistent with analyses measuring optimism and pessimism as separate exposures. To further explore the role of confounding factors, and potential impact upon the association between optimism and pessimism and cardiovascular illness, we did additional analyses with a Cox model adjusting for confounders in a stepwise fashion (supplemental table S10 and S11). In doing so, we report that there is no association between either optimism or pessimism and CVD events. Sensitivity analyses also confirmed that in both crude and fully adjusted models which use a composite scale, combining the optimism and pessimism subscales, (Supplemental Table S12) there is no association between the composite measure and the primary outcomes of CVD events and MACE.

Discussion

Among 11,651 males and females aged 70 years and older living in Australia, participants of the ASPREE and ALSOP studies, we observed no association of optimism and pessimism with composite CVD or MACE. However, we did observe the association between greater pessimism and risk of fatal CHD as well as the association between greater optimism and lower risk of non-fatal MI.

Our results on the relationship between optimism and non-fatal MI are consistent with a study of 7942 adults in the UK Whitehall II study aged 39–63 years reporting that higher optimism is associated with less risk of non-fatal MI (Boehm et al., 2011). Some mechanisms underpinning this relationship may be the fact that individuals who are more optimistic are also more likely to engage in health promoting behaviors, such as abstaining from smoking and being physically active, which contribute to superior cardiac health (Boehm et al., 2018; Steptoe et al., 2006). Optimists are more likely to cope adaptively to everyday stressors, and it has thus been suggested that such individuals will have less hormonal and cardiovascular reactivity, which reduces the stresses placed upon the cardiac system (Matthews et al., 2004). Further, optimistic individuals have lower ambulatory blood pressure (Räikkonen et al., 1999), which is also beneficial for cardiovascular health.

While a study on 23,216 adults in Finland aged 20–54 years reported no significant association between optimism and risk of stroke (Nabi et al., 2010), others have observed that higher optimism was associated with less progression of carotid disease (Matthews et al., 2004), reduced risk of stroke (Kim et al., 2011), or reduced risk of deaths due to CVD related causes (Anthony et al., 2016; Giltay et al., 2004; Kim et al., 2017; Tindle et al., 2009) and risk of incident coronary heart disease or coronary heart disease related mortality (Tindle et al., 2009). Some of these studies measured a different outcome to that in our study, that is, CVD related mortality, and most examined optimism and pessimism on a single scale (when optimism and pessimism are considered as opposing ends of a unidimensional continuum). This may explain the difference in the study results considering that we researched optimism and pessimism as separate constructs. It has been suggested that when a unidimensional scale is used to assess optimism and pessimism, the association between positive health outcomes such as less risk of stroke (Kim et al., 2011) and higher degrees of optimism may mask the effect of low levels of pessimism (Serlachius et al., 2015).

Our findings of no relationship between pessimism and the composite CVD outcome after adjustment for potential confounders are similar to those of a US study where pessimism was positively associated with cardiovascular mortality among 876 older adults (mean age 74.1 years; p = 0.002), while no association was reported when covariates (age, gender, health-related behaviors and CVD risk factors) were accounted for in the regression model (Anthony et al., 2016). Our study adds to the available, but scarce, evidence by reporting the novel findings of no associations of pessimism with composite outcomes CVD and MACE in a cohort of older adults exclusively aged 70 years or older. While there is some evidence that health-related behaviors may underlie the mechanistic pathways in the association between psychosocial factors and CVD outcomes (e.g., Boehm et al., 2018; Steptoe et al., 2006) our results for the two primary outcome measures do not provide further supporting evidence of this.

As part of the post-hoc analyses, we observed the association between pessimism and fatal CHD, which was consistent with a previous study in older individuals (Pänkäläinen et al., 2016). There are several potential mechanisms relating pessimism to CVD outcomes. Individuals who are pessimistic tend to engage in perseverative thoughts, which can lead to higher physiological arousal—and arousal is thought to interrupt the usual restorative physiological processes (such as dipping of mean arterial pressure overnight), this way increasing the risk of CVD (Felt et al., 2020). Pessimism may result in cognitive effects such as catastrophic thinking, self-blame and defeatism—which may increase cortisol levels and activate the sympathetic nervous system, and these physiological changes may increase the risk of CVD (Das & O’Keefe, 2006). Higher pessimism is also associated with greater subclinical atherosclerosis (Matthews et al., 2004), increased levels of inflammatory markers (Roy et al., 2010) and decreased telomere length (Ikeda et al., 2014), all associated with increased risk of CVD. In addition, although based on limited evidence (Asimakopoulou et al., 2007), less pessimistic individuals, compared to more pessimistic ones, may engage in more health promoting behaviors, which may in turn be associated with lower risk of CVD. Examination of Table 2 (baseline characteristics of the participants) suggests that there are some unique differences in the likelihood of individuals being more optimistic and less pessimistic, and thus perhaps at less risk of certain cardiovascular events. Straightforward positive psychological interventions have been demonstrated to promote optimism and decrease pessimism in older adults (Ho et al., 2014), thus our findings imply that if such interventions are targeted to those most at risk, potentially the risk of specific CVD events may be reduced.

There are several limitations to the study. It should be considered that those individuals who volunteer for a long-term trial (such as ASPREE/ALSOP) differ from the general population in terms of various personality traits that may have an impact on study outcomes (Almeida et al., 2008). In other words, people who give their time to participate in research may be more optimistic and less pessimistic than others who do not—and we noted this is in our cohort. An additional limitation of this research is that our results may not be generalizable to a nationally representative sample of Australia. Unlike the relatively healthy adults making up our sample, according to 2020 data, 4.5% of older Australians live in residential aged care, and in 2018, 50% of adults aged 65 or older lived with a disability (AIHW, 2020). Furthermore, according to a systematic review of 45 studies, including more than 60 million older adults in 30 high income countries, a large proportion of older adults (66.1%, [IQR] = 54.4–76.6%) live with multimorbidity (Ofori-Asenso et al., 2019). Nevertheless, our demographic is somewhat representative of Australian older adults, of whom 75% report being in good, very good, or excellent health (42% rating their health as very good or excellent), 47% have 12 years or less education, and 53% identify as women (AIHW, 2020). We acknowledge that the null finding for both CVD and MACE could reflect the lack of clinically meaningful variation in the LOT-R sub scores (primary exposures) which had a skewed distribution, with optimism scores being negatively skewed and pessimism scores positively skewed. In addition, the generalizability of our findings may be limited, as the community-dwelling ALSOP participants were pre-dominantly white, and free of major physical disability, dementia and pre-existing CVD. However, the cohort was considered to be representative of adults aged 70 years and older living in Australia in relatively good health (J. J. McNeil et al., 2019). Our null finding may reflect the healthy cohort effect, such that those adults who reach 70 years in relatively good health may be less susceptible to CVD events compared to their less healthy counterparts. In addition, the very low number of CVD events may also have resulted in the null finding, and the inconsistent result for the association of optimism and pessimism with the components of the composite CVD measure. We also note the small number of CVD events in some categories, which may explain some of the lack of precision evidenced by wide CIs. We provide the number of events by tertile of optimism and pessimism in Table 3 (and supplemental Tables S3, S4 and S5), and acknowledge this limitation. We concede that our decision to exclude missing data (listwise deletion), is a limitation. Nevertheless, our analyses of proportion of missing data (0.43–6.25%), and that there is no specific pattern of missingness such that is co-occurring across variables leads us to believe our statistical power was preserved to explore the association of optimism and pessimism with CVD.

Despite the limitations, to the best of our knowledge, a particular contribution of our work is that it is the first larger study to comprehensively investigate the association between optimism and pessimism, as separate constructs, and carefully adjudicated CVD and MACE outcomes in a cohort of adults aged 70 years and older, which few previous studies have done. The data were analyzed (from an ASPREE substudy) from a clinical trial in which a large sample of older adults have participated, allowing for large-scale investigation of a number of factors associated with aging. Our population consisted of both males and females, and our composite measures covered a range of cardiovascular events which has been a limitation of some previous studies which have, for example, only measured one event type of CVD (Nabi et al., 2010) or CVD death (Giltay et al., 2004).

Implications

There are several implications for future research and clinical practice. First, our findings suggest that optimism and pessimism should be researched as separate constructs (Felt et al., 2020), because in our cohort the individuals with low optimism were not necessarily high in pessimism, which suggests these two constructs are different. This may especially be important for older adults over 70 years, as it has been argued that optimism decreases after age of 70 while pessimism increases (Chopik et al., 2015, 2020), and that optimism and pessimism become more independent of one another with aging (Herzberg et al., 2006; Robinson-Whelen et al., 1997).

Previous studies suggest that optimism and pessimism are modifiable (Malouff & Schutte, 2017; Plomin et al., 1992). Therefore, further research may reveal an opportunity to develop interventions designed to reduce pessimism and thus decrease risk of CVD for older adults. Evidence suggests that positive psychology interventions targeting optimism may be especially beneficial for individuals who are more pessimistic (Sergeant & Mongrain, 2014). However, there is little evidence on the efficacy of positive psychology interventions for older adults (Ho et al., 2014), and evidence is currently limited for interventions to modify pessimism (Dubois et al., 2012).

Our study also suggests that baseline characteristics (demographics and health-related behaviors) could potentially explain the apparent association between pessimism and cardiac outcomes in previous studies. This is important, as modifying health behaviors can reduce the risk of CVD. A positive psychology intervention delivered to 97 individuals hospitalized for acute coronary syndrome effectively increased self-reported health behaviors (including engaging in moderate or vigorous physical activity), but this intervention targeted optimism rather than pessimism (Celano et al., 2018). Preliminary results from an American study of cardiac health, however, did suggest that lower levels of pessimism are associated with less likelihood of smoking, and increased likelihood of exercising moderately and eating a more nutritious diet (Serlachius et al., 2015). Therefore, targeted interventions to decrease pessimism in older adults may also increase the likelihood that they will engage in healthy behaviors (such as abstaining from smoking, exercising regularly and eating a good quality diet), that in turn also may reduce CVD risk.

Conclusion

Our study of 11,651 participants is among the first to examine the separate associations of optimism and pessimism with incident CVD events and MACE in a population of adults aged 70 years and older. We observed no association of optimism or pessimism with incident composite CVD events or MACE, after adjustment for potential confounders. However, greater pessimism was associated with a greater risk of fatal coronary heart disease, while being more optimistic was associated with a lower risk of non-fatal myocardial infarction. The results of our study also support the argument of others that optimism and pessimism should be researched as separate constructs. We argue that this may particularly be important in older age due to changes in optimism and pessimism that occur as we age.

Supplementary Material

Supplementary Material

Funding

RFP is supported by an Australian Heart Foundation post-doctoral fellowship (101927), JR is supported by NHMRC Dementia Research Leader Fellowship (1135727). Supported by grants (U01AG029824 and U19AG062682) from the National Institute on Aging and the National Cancer Institute at the National Institutes of Health, by grants (334047 and 1127060) from the National Health and Medical Research Council of Australia, and by Monash University and the Victorian Cancer Agency.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical Approval

The project was reviewed and approved by the Monash University Human Research Ethics committee, reference number: 21906. The ASPREE study complies with the Declaration of Helsinki, and was approved by multiple Institutional Review Boards. All participants provided informed written consent prior to taking part in the ASPREE and ALSOP studies.

Supplemental Material

Supplemental material for this article is available online.

Data Availability

Data cannot be shared for legal and ethical reasons. Data cannot be shared publicly as data are part of a large ongoing observational cohort with a rigorous process to access data. Data are available from Monash University for researchers who meet the criteria (contact via https://aspree.org/aus/for-researchers; aspree@monash.edu).

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Supplementary Materials

Supplementary Material
NIHMS1878730-supplement-Supplementary_Material.pdf (330.6KB, pdf)

Data Availability Statement

Data cannot be shared for legal and ethical reasons. Data cannot be shared publicly as data are part of a large ongoing observational cohort with a rigorous process to access data. Data are available from Monash University for researchers who meet the criteria (contact via https://aspree.org/aus/for-researchers; aspree@monash.edu).

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