Skip to main content
NCBI home page
The Journals of Gerontology Series B: Psychological Sciences and Social Sciences logoLink to The Journals of Gerontology Series B: Psychological Sciences and Social Sciences
. 2020 Aug 28;76(5):910–919. doi: 10.1093/geronb/gbaa106

Subjective Aging and Incident Cardiovascular Disease

Yannick Stephan 1,✉, Angelina R Sutin 2, Susanne Wurm 3, Antonio Terracciano 2
Editor: Amit Shrira
PMCID: PMC8063671  PMID: 32857131

Abstract

Objectives

Subjective aging, including subjective age and self-perceptions of aging (SPA), predicts health-related outcomes in older adults. Despite its association with cardiovascular risk factors, little is known about the association between subjective aging and the incidence of cardiovascular disease. Therefore, the present study examined whether subjective age and SPA are related to the incidence of heart conditions and stroke.

Methods

The sample comprises 10,695 participants aged 50–100 years from the Health and Retirement Study. Subjective age, SPA, demographic factors, and health-related behaviors, body mass index (BMI), hypertension, diabetes, and depressive symptoms were assessed at baseline. Self-reported physician diagnosis of heart conditions and stroke were assessed biennially over up to 9 years of follow-up.

Results

Controlling for demographic factors, an older subjective age and more negative SPA were related to a higher risk of incident heart conditions and stroke. Feeling older and holding negative SPA were associated with around 40% higher risk of experiencing heart conditions over time. An older subjective age and negative SPA were related to almost twofold and 30% higher risk of incident stroke, respectively. Health risk behaviors, BMI, hypertension, diabetes, and depressive symptoms accounted for part of the associations between subjective aging and heart diseases and stroke.

Conclusions

Consistent with the literature on subjective aging and cardiovascular risk factors, this large prospective study indicates that an older subjective age and negative SPA increase the risk of incident stroke and other cardiovascular diseases.

Keywords: Cardiovascular disease, Self-perceptions of aging, Stroke, Subjective age

Cardiovascular diseases (CVDs) are among the leading causes of death worldwide (Global Burden of Disease [GBD] 2017 Causes of Death Collaborators, 2018). Age is a major risk factor for CVD, with a higher prevalence of heart conditions and stroke among older adults (Benjamin et al., 2017). However, there is large variability in the aging process, which is in part captured by subjective aging. Subjective aging is an umbrella term that encompasses subjective age and self-perceptions of aging (SPA; Wurm et al., 2017). Subjective age refers to how old or young individuals feel relative to their chronological age, whereas SPA refer to perceived age-related changes in their overall functioning. Both subjective age and SPA are significant predictors of a wide range of health outcomes in old age (Westerhof et al., 2014; Westerhof & Wurm, 2018). Independent of chronological age, an older subjective age and more negative SPA predict a higher risk of incident hospitalization (Stephan et al., 2016; Sun et al., 2017), dementia (Levy et al., 2018; Stephan, Sutin, Luchetti et al., 2018), and both overall and cardiovascular mortality (Levy & Bavishi, 2018; Stephan, Sutin, & Terracciano, 2018). Recent research found that incident CVDs are predictive of an older subjective age and negative SPA (Wurm et al., 2019). However, whereas the impact of age stereotypes, which refer to societal views about aging and being old, on CVD has been found (Levy et al., 2009), no research has yet tested whether subjective aging is related to the incidence of CVD. Furthermore, existing research has focused on cardiovascular events without distinguishing between incident stroke and heart conditions. Therefore, the present study aims to extend existing knowledge by examining whether subjective aging predicts both incident stroke and heart conditions.

The association between subjective aging and health-related behaviors and health outcomes suggests a role of both subjective age and SPA in CVD. Subjective aging may contribute to CVD through multiple direct and indirect pathways that range from physiological dysfunction to psychosocial stressors. Indeed, an older subjective age and negative SPA are related to a range of CVD risk factors, including physical inactivity (Beyer et al., 2019; Wienert et al., 2016; Wurm, 2019), higher depressive symptoms (Gum & Ayalon, 2018; Rippon & Steptoe, 2018; Wurm & Benyamini, 2014), poor sleep quality (Stephan et al., 2017), higher concentrations of C-reactive protein (Levy & Bavishi, 2018; Stephan et al., 2015a), and higher levels of cortisol (Levy et al., 2016); all of these risk factors are associated with heart conditions and stroke (Grandner et al., 2012; Hare et al., 2014; Lee et al., 2012; Liu et al., 2014; Shlipak et al., 2005). In addition, feeling older and negative SPA are related to higher BMI (Levy & Slade, 2019; Stephan et al., 2019) and hypertension and diabetes (Demakakos et al., 2007), which are leading causes of CVD (Khan et al., 2018; Sowers et al., 2001). Subjective aging has also been found to shape vulnerability to stress and anxiety (Bellingtier & Neupert, 2018; Freeman et al., 2016; Shrira et al., 2018), which are strong contributors to CVD (Steptoe & Kivimäki, 2012).

A younger subjective age and positive SPA reflect physical and psychological resources to deal with the repercussions of stressful events (Bellingtier & Neupert, 2018; Hoffman et al., 2016; Shrira et al., 2018; Stephan et al., 2011). In contrast, individuals with an older subjective age and negative SPA hold fewer resources to protect their health and well-being from the deleterious effects of stress (Bellingtier & Neupert, 2018; Hoffman et al., 2016; Shrira et al., 2018; Stephan et al., 2011). Therefore, it is likely that this higher susceptibility to stress and anxiety may heighten the risk of heart conditions and stroke. In addition to behavioral, health, and biological pathways, subjective aging may predict the incidence of chronic diseases because it could reflect nonpathological physical and biological processes that may develop into worsening health over time (Stephan et al., 2015b; Thyagarajan et al., 2019).

Based upon a large longitudinal sample of middle-aged and older adults, the present study examined the relationship between subjective aging and the incidence of CVD. Building upon existing evidence for a link between subjective age, SPA, and cardiovascular risk factors (Beyer et al., 2019; Levy & Slade, 2018; Stephan et al., 2019; Wienert et al., 2016), it was hypothesized that an older subjective age and negative SPA are related to a higher likelihood of incident heart conditions and stroke. An additional purpose was to test the extent to which the association persisted controlling for cardiovascular risk factors (i.e., smoking, physical inactivity, diabetes, hypertension, depression, and BMI).

Method

Participants

Data were drawn from the Health and Retirement Study (HRS), a national longitudinal study of Americans aged 50 years and older and their spouses. A random half of HRS participants completed a questionnaire that included the subjective aging measures in 2008; the other half completed it in 2010. Data from both waves were combined as baseline. Data on heart conditions and stroke were collected every 2 years up to the 2016 wave. Individuals were included if they provided complete data on subjective aging (both subjective age and SPA) and demographic factors and if they had information on their medical status on at least one out of the two diseases at baseline, resulting in a sample of 12,102 participants. Within this sample, 11,990 individuals had information on heart conditions, 12,008 individuals had information on stroke, and 11,896 participants had information on both conditions. Analyses were conducted only among individuals who either did not have heart conditions or stroke at baseline or who only had one of the conditions at baseline. We excluded 491 participants who reported a diagnosis of both heart conditions and stroke, who were diagnosed with stroke but had missing data on heart conditions, or who were diagnosed with heart conditions but had missing data on stroke. The remaining sample (N = 11,611) was composed of individuals who were diagnosed as not suffering from at least one of the two CVDs at baseline. Specifically, this sample was composed of 8,709 individuals who did not have a heart condition diagnosis and 11,180 who did not have a stroke diagnosis. Among these participants, 8,278 individuals did not have either diagnosis. Within this baseline sample, 858 individuals were excluded because they did not have information about either heart conditions or stroke at follow-up, resulting in a sample of 10,785 individuals with information on at least one CVD diagnosis at follow-up. Among individuals without heart conditions at baseline, 8,175 had follow-up heart conditions information, and among those without stroke at baseline, 10,413 had information about stroke at follow-up. With 90 outliers on subjective age (i.e., individuals with scores 3 SDs above or below the mean) removed, a total of 10,695 participants were included in the present study.

Measures

Subjective age

Subjective age was assessed using the following item: “Many people feel older or younger than they actually are. What age do you feel?” Participants were asked to report the age they felt in years. In line with existing research (Stephan, Sutin, & Terracciano, 2018), a proportional discrepancy score was computed by subtracting chronological age from felt age and then divided by chronological age. A positive value represented an older subjective age whereas a negative value corresponded to a younger subjective age.

Self-perceptions of aging

The five-item Attitudes Toward Own Aging (Lawton, 1975) scale was used to assess SPA. Participants were asked to answer five items that assessed their personal experience and evaluation of age-related changes. An example item is “I have as much pep as I had last year.” Answers were rated on a scale from 1 (strongly disagree) to 6 (strongly agree). Sum scores ranged from 5 to 30, with higher scores indicating more positive SPA.

Cardiovascular diseases

Heart conditions and stroke were assessed using participants’ reported physician diagnosis. Specifically, two separate questions asked participants to indicate whether a physician ever told them that they had a heart condition (heart attack, coronary heart disease, angina, congestive heart failure, or other heart problems) and ever told them that they had a stroke. In the questionnaire, a physician was defined as a specialist, such as cardiologist, osteopath, dermatologist, psychiatrist, or ophthalmologist, as well as family doctor, internist, and physician’s assistant. Answers were given using a yes/no format.

Covariates

Demographic factors included age, sex, education, race, and ethnicity. In additional analyses, baseline smoking, physical inactivity, body mass index (BMI), hypertension, diabetes, and depressive symptoms were also included as covariates. Current or former smokers were coded as 1 and never smokers were coded as 0. The frequency of vigorous and moderate activities was measured in each case using a scale from 1 (more than once a week) to 4 (hardly ever or never). Physical inactivity was computed as the mean of these two items. Objective measurements of weight and height were used to derive BMI as kg/m2. Two questions asked participants whether a physician ever told them that they had high blood pressure or hypertension and whether a physician ever told them that they had diabetes or high blood sugar. Depressive symptoms were measured using the eight-item version of the Center for Epidemiologic Studies-Depression scale (Wallace et al., 2000).

Data Analysis

Cox proportional hazard models were used to test whether subjective aging was associated with the risk of CVD for a period of 9 years. Separate analyses were first conducted with subjective age or SPA entered as the predictor of time to incidence (in years), controlling for age, sex, education, race, and ethnicity. Subjective age was categorized as younger subjective age (felt age lower than chronological age), no discrepancy (felt age equal to chronological age), and older subjective age (felt age higher than chronological age). Based upon existing research (Levy & Slade, 2019), SPA was categorized as negative SPA (equal to or lower than a score of 15) and positive SPA (score greater than 15). The categorical scale directly contrasts negative subjective aging (i.e., an older subjective age and negative SPA) to positive subjective aging (i.e., a younger subjective age or the same age, and positive SPA) to provide a clear test of whether subjective aging is related to the risk of CVD.

The same analysis was conducted with both subjective age and SPA included simultaneously as predictors. Participants who did not develop the diseases were censored at the last available assessment. Additional analysis included smoking, physical inactivity, BMI, hypertension, diabetes, and depressive symptoms as covariates. Separate analyses were conducted for heart conditions and stroke. The proportional hazard assumption was met in each analysis.

Several sensitivity analyses were conducted. All analyses controlled for demographic factors. First, Cox regressions were conducted to test whether the relationship between subjective aging and heart conditions persisted controlling for baseline and incident stroke and whether the relationship between subjective aging and stroke persisted controlling for baseline and incident heart conditions. Second, we examined the link between subjective aging and CVD using continuous measures of subjective age and SPA. Third, to mitigate the option of potential reverse causality, we repeated the analyses excluding the cases that occurred in the first 2 years of follow-up to address the potential of reverse causality.

Results

Descriptive statistics for the full sample are presented in Table 1. In the total sample, 77.32% of participants (N = 8,269) felt younger than their chronological age, 13.28% (N = 1,420) felt their age, and 9.41% (N = 1,006) felt older than their chronological age. Furthermore, 79.97% (N = 8,553) had positive SPA and 20.03% (N = 2,142) had negative SPA. Over a median follow-up of 6 years, 16.01% (N = 1,299) reported being diagnosed with a heart condition (range: 1–9 years, 48,237 person years) and 5.41% (N = 559) reported being diagnosed with stroke (range: 1–9 years, 63,039 person years).

Table 1.

Descriptive Statistics for the Sample

Total sample Younger subjective age Same age Older subjective age Positive SPA Negative SPA
Variables M/% SD M/% SD M/% SD M/% SD M/% SD M/% SD
Age (years) 69.14 9.36 69.21 9.22 70.31 9.62 66.93 9.79 68.70 9.12 70.88 10.08
Sex (% women) 59% — 60% 56% 56% 59% — 61% —
Education 12.85 2.96 13.09 2.86 12.15 3.12 11.94 3.42 13.05 2.92 12.08 3.13
Race (% white) 84% — 85% — 83% — 81% — 84% — 83% —
Ethnicity (% Hispanic) 8% 8% — 9% — 11% — 7% — 11% —
Subjective age −0.16 0.16 −0.21 0.12 0.00 0.00 0.10 0.10 −0.18 0.14 −0.07 0.16
Self-perceptions of aging 20.21 5.48 21.19 5.09 18.11 5.26 15.16 5.29 22.21 3.99 12.23 2.64
Smoking (% current/former) 52% — 52% — 53% — 58% — 52% — 54% —
Physical inactivity 2.57 1.08 2.48 1.07 2.83 1.06 3.02 0.98 2.46 1.07 3.02 1.00
Depressive symptoms 1.24 1.84 1.03 1.65 1.54 1.90 2.63 2.48 0.90 1.48 2.66 2.40
BMI 29.48 5.91 29.19 5.73 30.07 6.35 31.17 6.50 29.35 5.76 30.04 6.49
Hypertension 61% — 59% — 67% — 69% — 59% — 68% —
Diabetes 21% — 19% — 28% — 31% — 20% — 19% —
Follow-up heart conditionsa 16% — 16% — 17% — 19% — 15% — 20% —
Follow-up strokea 5% — 5% — 6% — 8% — 5% — 7% —
Open in a new tab

Notes: BMI = body mass index; SPA = self-perceptions of aging. Total sample: N = 10,695.

aThe number differs due to missing data: heart conditions: N = 8,112; stroke: N = 10,325.

The main hypotheses of the study were addressed by Models 1 and 3 in Table 2. Models 2 and 4 in Table 2 test the follow-up question of whether behavioral and health variables are able to explain the main associations. Controlling for demographic factors, Cox regression revealed that both an older subjective age and negative SPA were related to a higher risk of incident heart conditions (Table 2). Specifically, the results suggest that feeling older and holding negative SPA were associated with around 40% higher risk of experiencing heart conditions over time (Table 2, Models 1 and 3). In follow-up analyses that included smoking, physical inactivity, BMI, hypertension, diabetes, and depressive symptoms as additional covariates (Table 2, Models 2 and 4), feeling older and having negative SPA remained associated significantly with a higher risk of heart conditions. Further analyses included both subjective age and negative SPA (see Model 5). These analyses revealed that both an older subjective age and negative SPA were significantly related to a higher risk of heart conditions (Model 5, Table 2). The association between negative SPA and incident heart conditions remained significant when additional covariates were included (Model 6, Table 2). In Model 6, the effect of subjective age was reduced to nonsignificance, suggesting that health behaviors and conditions account for part of the association between feeling older and the risk of heart conditions.

Table 2.

Cox Regression Predicting Risk of Heart Conditions

Predictor Model 1 Model 2a Model 3 Model 4 Model 5 Model 6
Hazard ratios (95% CI)
Age 1.05 (1.04–1.05)*** 1.04 (1.04–1.05)*** 1.04 (1.04–1.05)*** 1.04 (1.03–1.05)*** 1.04 (1.04–1.05)*** 1.04 (1.04–1.05)***
Sex 1.28 (1.15–1.43)*** 1.23 (1.08–1.40)** 1.30 (1.17–1.45)*** 1.24 (1.09–1.41)** 1.29 (1.16–1.45)*** 1.23 (1.08–1.40)**
Race 1.15 (0.98–1.34) 1.35 (1.12–1.62)** 1.15 (0.98–1.34) 1.35 (1.13–1.62)** 1.15 (0.98–1.34) 1.34 (1.12–1.61)**
Ethnicity 0.80 (0.64–1.00)* 0.81 (0.64–1.04) 0.78 (0.63–0.98)* 0.80 (0.63–1.02) 0.79 (0.63–0.98)* 0.81 (0.63–1.03)
Education 0.98 (0.96–1.00)* 0.99 (0.97–1.01) 0.98 (0.96–1.00)* 0.99 (0.97–1.01) 0.98 (0.96–1.00) 0.99 (0.97–1.01)
Same subjective agea 1.10 (0.93–1.29) 1.03 (0.85–1.24) 1.05 (0.89–1.24) 1.00 (0.83–1.21)
Older subjective agea 1.44 (1.19–1.73)*** 1.28 (1.03–1.60)* 1.29 (1.07–1.57)** 1.21 (0.96–1.51)
Negative SPA 1.37 (1.21–1.57)*** 1.29 (1.10–1.52)** 1.31 (1.14–1.50)*** 1.26 (1.07–1.49)**
Smoking 1.12 (0.99–1.27) 1.12 (0.99–1.28) 1.12 (0.99–1.28)
Physical inactivity 1.06 (1.00–1.13) 1.06 (1.00–1.13) 1.06 (0.99–1.13)
BMI 1.01 (1.00–1.02)* 1.01 (1.00–1.02)* 1.01 (1.00–1.02)*
Hypertension 1.46 (1.27–1.68)*** 1.47 (1.27–1.68)*** 1.46 (1.27–1.68)***
Diabetes 1.31 (1.13–1.53)*** 1.31 (1.13–1.53)*** 1.31 (1.13–1.52)***
Depressive symptoms 1.05 (1.01–1.09)** 1.04 (1.00–1.07) 1.03 (0.99–1.07)
Open in a new tab

Notes: BMI = body mass index; CI = confidence interval; SPA = self-perceptions of aging. Sample size for the model N = 8,112.

aYounger subjective age is the reference group.

*p < .05, **p < .01, ***p < .001.

Consistent with the hypothesis, both subjective age and SPA were associated with the risk of stroke (Table 3). An older subjective age and negative SPA were related to almost twofold and 30% higher risk of incident stroke, respectively (Table 3, Models 1 and 3). These relationships persisted when additional covariates were included (Table 3, Models 2 and 4). When considered simultaneously, only feeling older remained significantly related to the risk of incident stroke (see Table 3, Model 5). The association also remained significant after the inclusion of the additional covariates (see Table 3, Model 6).

Table 3.

Cox Regression Predicting Risk of Stroke

Predictor Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
Hazard ratios (95% CI)
Age 1.06 (1.05–1.07)*** 1.07 (1.05–1.08)*** 1.06 (1.05–1.07)*** 1.06 (1.05–1.08)*** 1.06 (1.05–1.07)*** 1.07 (1.05–1.08)***
Sex 1.07 (0.91–1.27) 1.08 (0.89–1.32) 1.10 (0.93–1.30) 1.10 (0.91–1.34) 1.08 (0.91–1.28) 1.08 (0.89–1.32)
Race 0.80 (0.64–1.00) 0.88 (0.69–1.14) 0.80 (0.64–0.99) 0.89 (0.69–1.14) 0.80 (0.64–1.00) 0.88 (0.69–1.14)
Ethnicity 0.97 (0.70–1.35) 0.96 (0.67–1.39) 0.96 (0.69–1.33) 0.95 (0.66–1.37) 0.97 (0.70–1.34) 0.96 (0.67–1.39)
Education 0.98 (0.95–1.01) 1.00 (0.97–1.04) 0.98 (0.95–1.00) 1.00 (0.97–1.03) 0.98 (0.95–1.01) 1.00 (0.97–1.04)
Same subjective agea 1.30 (1.03–1.64)* 1.17 (0.90–1.52) 1.26 (1.00–1.60) 1.15 (0.88–1.51)
Older subjective agea 1.91 (1.48–2.46)*** 1.51 (1.11–2.06)* 1.80 (1.38–2.35)*** 1.48 (1.08–2.03)*
Negative SPA 1.32 (1.08–1.60)** 1.15 (0.91–1.46) 1.16 (0.94–1.42) 1.09 (0.85–1.38)
Smoking 1.35 (1.11–1.64)** 1.35 (1.11–1.64)** 1.35 (1.11–1.64)**
Physical inactivity 1.05 (0.95–1.15) 1.05 (0.96–1.16) 1.05 (0.95–1.15)
BMI 1.00 (0.98–1.01) 1.00 (0.98–1.01) 1.00 (0.98–1.01)
Hypertension 1.44 (1.16–1.79)** 1.45 (1.17–1.81)** 1.44 (1.16–1.79)**
Diabetes 1.36 (1.09–1.69)** 1.37 (1.10–1.71)** 1.36 (1.09–1.69)**
Depressive symptoms 1.09 (1.04–1.14)** 1.09 (1.04–1.15)** 1.08 (1.03–1.14)**
Open in a new tab

Notes: BMI = body mass index; CI = confidence interval; SPA = self-perceptions of aging. Sample size for the model N = 10,325.

aYounger subjective age is the reference group.

*p < .05, **p < .01, ***p < .001.

Sensitivity analyses revealed that the relationship between an older subjective age and negative SPA and the risk of heart conditions (hazard ratio [HR]Subjective age = 1.38, 95% confidence interval [CI] 1.14–1.66, p < .01; HRSPA = 1.33, 95% CI 1.16–1.52, p < .001) and stroke (HRSubjective age = 1.80, 95% CI 1.39–2.33, p < .001; HRSPA = 1.22, 95% CI 1.00–1.49, p < .05) persisted controlling for the diagnosis of heart conditions and stroke, respectively, at baseline. The same pattern of relationships between feeling older and negative SPA and the risk of heart conditions (HRSubjective age = 1.35, 95% CI 1.11–1.66, p < .01; HRSPA = 1.36, 95% CI 1.19–1.57, p < .001) was observed when incidence of stroke was controlled. When incidence of heart conditions was controlled, the link between an older subjective age and stroke persisted (HRSubjective age = 1.70, 95% CI 1.20–2.42, p < .01) whereas the association between SPA and stroke was reduced to nonsignificance (HRSPA = 1.13, 95% CI 0.87–1.48, p = .35). Furthermore, the association between subjective age and SPA and heart conditions (HRSubjective age = 1.09, 95% CI 1.03–1.15, p < .01; HRSPA = 0.83, 95% CI 0.78–0.87, p < .001) or stroke (HRSubjective age = 1.14, 95% CI 1.04–1.24, p < .01; HRSPA = 0.82, 95% CI 0.75–0.89, p < .001) was also apparent when continuous measures were used. Finally, additional analyses examined whether the association between subjective age and CVD was explained by reverse causality by excluding the cases that occurred in the first 2 years of follow-up. The overall pattern was unchanged: feeling older and negative SPA were related to higher risk of heart conditions (HRSubjective age = 1.51, 95% CI 1.23–1.84, p < .001; HRSPA = 1.38, 95% CI 1.20–1.59, p < .001) and stroke (HRSubjective age = 1.96, 95% CI 1.50–2.57, p < .001; HRSPA = 1.30, 95% CI 1.05–1.60, p < .05). There was no evidence of interaction between subjective age and SPA in the prediction of CVD.

Discussion

The present study examined the association between subjective aging and incident CVD in a large longitudinal sample of middle-aged and older adults. As expected, the results revealed that an older subjective age and negative SPA are related to a higher incidence of both heart conditions and stroke for a 9-year period, controlling for demographic factors and modifiable risk factors for CVD. To the best of our knowledge, this is the first study to identify an association between subjective age, SPA, and incident CVD. It expands on existing research that has found that age stereotypes predict CVD (Levy et al., 2009) by showing that other self-rated views on aging, such as subjective age and SPA, contribute to these conditions. In addition, the study extends evidence that incident CVD predicts subjective aging (i.e., negative changes in SPA and subjective age; Wurm et al., 2019), by providing new evidence that subjective aging also predicts incident CVD, which suggests a vicious cycle between subjective aging and cardiovascular health. Given that CVDs are among the leading causes of death and disability across the globe (GBD 2017 Causes of Death Collaborators, 2018), the higher incidence of CVD may be a key mechanism between feeling older or negative SPA, respectively, and the increased risk of cognitive impairment and dementia (Levy et al., 2018; Stephan, Sutin, Luchetti et al., 2018), functional limitations (Rippon & Steptoe, 2018; Wurm & Benyamini, 2014), hospitalization (Stephan et al., 2016; Sun et al., 2017), and mortality (Levy et al., 2002; Stephan, Sutin, & Terracciano, 2018).

The association between subjective aging and the incidence of CVD may be explained by several behavioral, biological, and psychological factors. Indeed, the present study found that physical inactivity, smoking, BMI, hypertension, diabetes, and mental health partially accounted for the link between feeling older and negative SPA and a higher risk of both heart conditions and stroke. This finding suggests that the association between subjective aging and incident CVD is mediated in part by their relationship with physical inactivity, smoking, obesity, blood pressure, diabetes, and depressive symptoms. Such a model is consistent with existing evidence of an association between an older subjective age or negative SPA, respectively, and lower physical activity (Beyer et al., 2019; Wienert et al., 2016), obesity (Levy & Slade, 2019; Stephan et al., 2019), hypertension and diabetes (Demakakos et al., 2007), and higher depressive symptoms over time (Gum & Ayalon, 2018; Rippon & Steptoe, 2018; Wurm & Benyamini, 2014) that are robust predictors of cardiovascular disease. Other variables may also operate in this context. In particular, feeling older and negative SPA have been related to physiological factors known to increase cardiovascular risks, such as systemic inflammation and a higher concentration of cystatin C (Levy & Bavishi, 2018; Stephan et al., 2015a). Stress may also explain part of the link between subjective aging and CVD. Indeed, individuals with an older subjective age and negative SPA may be more vulnerable to the deleterious effect of stress and anxiety exposure (Freeman et al., 2016; Shrira et al., 2018) leading to a higher risk of a cardiovascular event.

When considered together in the same analysis, subjective age and SPA were differentially related to the incidence of either heart conditions or stroke. In particular, when both aspects of subjective aging were included, the link between subjective age and the incidence of heart conditions was reduced whereas the contribution of negative SPA remained almost the same. One possibility is that negative SPA may account for the association between feeling older and higher incidence of heart conditions. This assumption is consistent with recent evidence for a mediating role of perception of age-related changes in the relationship between an older subjective age and worse functional health (Brothers et al., 2017). Individuals who feel older may experience more negative age-related changes, such as a loss of energy, that may be indicative of a higher likelihood of heart conditions.

In contrast, subjective age was a better predictor of incident stroke than SPA. This finding suggests that subjective age may be more strongly related to abrupt health events than the SPA. As a whole, biological, behavioral, and health-related factors may explain this association. For example, an older subjective age is related to biological dysfunction and lower respiratory and pulmonary function (Stephan et al., 2015b), everyday physical problems, such as pain, physical limitations, or fatigue (Barrett & Gumber, 2020), physical inactivity (Wienert et al., 2016), anxiety (Stephan et al., 2017), and stress (Shrira et al., 2016), and these factors may contribute to a higher risk of stroke. However, there are two different theoretical explanations for how these factors operate in the association between subjective age and CVD. First, a causal model suggests that subjective age may predict stroke through its influence on biological, behavioral, and health-related factors. A second explanation is based upon the conceptualization of subjective age as a biopsychosocial marker of aging. In this case, subjective age is the outcome and reflects worse biological functioning, physical and mental health which may convert into stroke over time. This conceptualization suggests that the assessment of subjective age is easy to administer and noninvasive marker of individuals’ risk for stroke over time. The sensitivity of subjective age to stroke-related factors adds to the correlates of a range of behavioral, biological, and health factors implicated in stroke risk that could explain why feeling older is more strongly associated with stroke risk than negative SPA.

The present study has several strengths, including the large sample of middle-aged and older adults, and a follow-up period of up to 9 years. Among the limitations of this study was the use of participants’ self-reported diagnosis. For example, with this approach, we missed CVD that resulted in the deaths of participants. In addition, the severity of CVD was not assessed. Ideally, future research should use objective medical records including causes of death to track the incidence of CVD. Although the link between subjective aging and CVD persisted when cases occurring in the first 2 years following baseline assessment were excluded, reverse causation could explain part of this association. Indeed, individuals may feel older than their age and perceive their aging process more negatively because they experience undiagnosed or unreported cardiovascular conditions, leading to biased associations with future risk of heart conditions and stroke. This study tested whether subjective aging predicts incident CVD, but incident CVD may also shape subjective aging (Wurm et al., 2019). More research is needed to test for the reciprocal relationships between subjective aging and heart conditions and stroke. Furthermore, more research is needed to test whether specific facets of subjective age (e.g., subjective physical age) or specific domains of SPA (e.g., perceiving aging as associated with physical losses or ongoing development; Wurm et al., 2007) may be specifically related to the development of CVD.

In summary, the present study revealed that subjective aging is related to the incidence of CVD in middle and older adulthood and suggests that how old someone feels and how individuals perceive their aging process are important markers of cardiovascular health in old age, beyond chronological age. From a practical perspective, the inclusion of subjective aging assessment may enrich the identification and monitoring of individuals at risk of CVD incidence, which may be targeted by preventive interventions. In addition, subjective aging has been shown to be modifiable (Beyer et al., 2019; Dutt & Wahl, 2017). Therefore, targeted interventions may be directed toward individuals with older subjective age and also those who have negative perceptions of their aging process in order to promote favorable health-related outcomes over time.

Funding

None declared.

Conflict of Interest

None declared.

Acknowledgments

The Health and Retirement Study (HRS) is funded by the National Institute on Aging (NIAU01AG009740) and conducted by the University of Michigan. HRS was approved by the University of Michigan Institutional Review Board. HRS data are available at http://hrsonline.isr.umich.edu/index.php

References

  1. Barrett, A E, & Gumber, C. (2020). Feeling old, body and soul: The effect of aging body reminders on age identity. The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 75(3), 625–629. doi: 10.1093/geronb/gby085 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Bellingtier, J. A., & Neupert, S. D. (2018). Negative aging attitudes predict greater reactivity to daily stressors in older adults. The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 73(7), 1155–1159. doi: 10.1093/geronb/gbw086 [DOI] [PubMed] [Google Scholar]
  3. Benjamin, E J, Blaha, M J, Chiuve, S E, Cushman, M, Das, S R, Deo, R, de Ferranti, S. D., Floyd, J., Fornage, M., Gillespie, C., Isasi, C. R., Jiménez, M. C., Jordan, L. C., Judd, S. E., Lackland, D., Lichtman, J. H., Lisabeth, L., Liu, S., Longenecker, C. T., Mackey, R. H., …. American Heart Association Statistics Committee and Stroke Statistics Subcommittee . (2017). Heart disease and stroke statistics—2017 update: A report from the American Heart Association. Circulation, 135(10), e146–e603. doi: 10.1161/CIR.0000000000000485 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Beyer, A K, Wiest, M, & Wurm, S. (2019). There is still time to be active: Self-perceptions of aging, physical activity, and the role of perceived residual lifetime among older adults. Journal of Aging and Physical Activity, 27(4), 807–815. doi: 10.1123/japa.2018-0380 [DOI] [PubMed] [Google Scholar]
  5. Brothers, A, Miche, M, Wahl, H W, & Diehl, M. (2017). Examination of associations among three distinct subjective aging constructs and their relevance for predicting developmental correlates. The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 72(4), 547–560. doi: 10.1093/geronb/gbv085 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Demakakos, P, Gjonca, E, & Nazroo, J. (2007). Age identity, age perceptions, and health: Evidence from the English Longitudinal Study of Ageing. Annals of the New York Academy of Sciences, 1114, 279–287. doi: 10.1196/annals.1396.021 [DOI] [PubMed] [Google Scholar]
  7. Dutt, A J, & Wahl, H W. (2017). Feeling sad makes us feel older: Effects of a sad-mood induction on subjective age. Psychology and Aging, 32(5), 412–418. doi: 10.1037/pag0000179 [DOI] [PubMed] [Google Scholar]
  8. Freeman, A T, Santini, Z I, Tyrovolas, S, Rummel-Kluge, C, Haro, J M, & Koyanagi, A. (2016). Negative perceptions of ageing predict the onset and persistence of depression and anxiety: Findings from a prospective analysis of the Irish Longitudinal Study on Ageing (TILDA). Journal of Affective Disorders, 199, 132–138. doi: 10.1016/j.jad.2016.03.042 [DOI] [PubMed] [Google Scholar]
  9. Global Burden of Disease 2017 Causes of Death Collaborators . (2018). Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: A systematic analysis for the Global Burden of Disease Study 2017. The Lancet, 392(10159), 1736–1788. doi: 10.1016/S0140-6736(18)32203-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Grandner, M A, Jackson, N J, Pak, V M, & Gehrman, P R. (2012). Sleep disturbance is associated with cardiovascular and metabolic disorders. Journal of Sleep Research, 21(4), 427–433. doi: 10.1111/j.1365-2869.2011.00990.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Gum, A M, & Ayalon, L. (2018). Self-perceptions of aging mediate the longitudinal relationship of hopelessness and depressive symptoms. International Journal of Geriatric Psychiatry, 33(4), 591–597. doi: 10.1002/gps.4826 [DOI] [PubMed] [Google Scholar]
  12. Hare, D L, Toukhsati, S R, Johansson, P, & Jaarsma, T. (2014). Depression and cardiovascular disease: A clinical review. European Heart Journal, 35(21), 1365–1372. doi: 10.1093/eurheartj/eht462 [DOI] [PubMed] [Google Scholar]
  13. Hoffman, Y S, Shrira, A, Cohen-Fridel, S, Grossman, E S, & Bodner, E. (2016). Posttraumatic stress disorder symptoms as a function of the interactive effect of subjective age and subjective nearness to death. Personality and Individual Differences, 102, 245–251. doi: 10.1016/j.paid.2016.07.017 [DOI] [Google Scholar]
  14. Khan, S S, Carnethon, M R, & Lloyd-Jones, D M. (2018). The obesity paradigm and lifetime risk of cardiovascular disease—Reply. JAMA Cardiology, 3(9), 896–897. doi: 10.1001/jamacardio.2018.1840 [DOI] [PubMed] [Google Scholar]
  15. Lawton, M P. (1975). The Philadelphia Geriatric Center Morale Scale: A revision. Journal of Gerontology, 30(1), 85–89. doi: 10.1093/geronj/30.1.85 [DOI] [PubMed] [Google Scholar]
  16. Lee, I M, Shiroma, E J, Lobelo, F, Puska, P, Blair, S N, & Katzmarzyk, P T; Lancet Physical Activity Series Working Group . (2012). Effect of physical inactivity on major non-communicable diseases worldwide: An analysis of burden of disease and life expectancy. Lancet (London, England), 380(9838), 219–229. doi: 10.1016/S0140-6736(12)61031-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Levy, B R, & Bavishi, A. (2018). Survival advantage mechanism: Inflammation as a mediator of positive self-perceptions of aging on longevity. The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 73(3), 409–412. doi: 10.1093/geronb/gbw035 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Levy, B R, Moffat, S, Resnick, S M, Slade, M D, & Ferrucci, L. (2016). Buffer against cumulative stress: Positive age self-stereotypes predict lower cortisol across 30 years. GeroPsych: The Journal of Gerontopsychology and Geriatric Psychiatry, 29(3), 141–146. doi: 10.1024/1662-9647/a000149 [DOI] [Google Scholar]
  19. Levy, B R, Slade, M D, Kunkel, S R, & Kasl, S V. (2002). Longevity increased by positive self-perceptions of aging. Journal of Personality and Social Psychology, 83(2), 261–270. doi: 10.1037//0022-3514.83.2.261 [DOI] [PubMed] [Google Scholar]
  20. Levy, B R, Slade, M D, Pietrzak, R H, & Ferrucci, L. (2018). Positive age beliefs protect against dementia even among elders with high-risk gene. PLoS One, 13(2), e0191004. doi: 10.1371/journal.pone.0191004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Levy, B R, & Slade, M D. (2019). Positive views of aging reduce risk of developing later-life obesity. Preventive Medicine Reports, 13, 196–198. doi: 10.1016/j.pmedr.2018.12.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Levy, B R, Zonderman, A B, Slade, M D, & Ferrucci, L. (2009). Age stereotypes held earlier in life predict cardiovascular events in later life. Psychological Science, 20(3), 296–298. doi: 10.1111/j.1467-9280.2009.02298.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Liu, Y, Wang, J, Zhang, L, Wang, C, Wu, J, Zhou, Y, ... Zhao, X. (2014). Relationship between C-reactive protein and stroke: A large prospective community based study. PLoS One, 9(9), e107017. doi: 10.1371/journal.pone.0107017 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Rippon, I, & Steptoe, A. (2018). Is the relationship between subjective age, depressive symptoms and activities of daily living bidirectional? Social Science & Medicine (1982), 214, 41–48. doi: 10.1016/j.socscimed.2018.08.013 [DOI] [PubMed] [Google Scholar]
  25. Shlipak, M G, Sarnak, M J, Katz, R, Fried, L F, Seliger, S L, Newman, A B, … Stehman-Breen, C. (2005). Cystatin C and the risk of death and cardiovascular events among elderly persons. The New England Journal of Medicine, 352(20), 2049–2060. doi: 10.1056/NEJMoa043161 [DOI] [PubMed] [Google Scholar]
  26. Shrira, A., Palgi, Y., Ben-Ezra, M., Hoffman, Y., & Bodner, E. (2016). A youthful age identity mitigates the effect of post-traumatic stress disorder symptoms on successful aging. American Journal of Geriatric Psychiatry, 24, 174–175. doi: 10.1016/j.jagp.2015.07.006 [DOI] [PubMed] [Google Scholar]
  27. Shrira, A, Palgi, Y, Hoffman, Y, Avidor, S, Bodner, E, Ben-Ezra, M, & Bensimon, M. (2018). Subjective age as a moderator in the reciprocal effects between posttraumatic stress disorder symptoms and self-rated physical functioning. Frontiers in Psychology, 9, 1746. doi: 10.3389/fpsyg.2018.01746 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Sowers, J R, Epstein, M, & Frohlich, E D. (2001). Diabetes, hypertension, and cardiovascular disease: An update. Hypertension (Dallas, Texas: 1979), 37(4), 1053–1059. doi: 10.1161/01.hyp.37.4.1053 [DOI] [PubMed] [Google Scholar]
  29. Stephan, Y, Caudroit, J, & Chalabaev, A. (2011). Subjective health and memory self-efficacy as mediators in the relation between subjective age and life satisfaction among older adults. Aging & Mental Health, 15(4), 428–436. doi: 10.1080/13607863.2010.536138 [DOI] [PubMed] [Google Scholar]
  30. Stephan, Y, Sutin, A R, & Terracciano, A (2015a). Younger subjective age is associated with lower C-reactive protein among older adults. Brain, Behavior, and Immunity, 43, 33–36. doi: 10.1016/j.bbi.2014.07.019 [DOI] [PubMed] [Google Scholar]
  31. Stephan, Y, Sutin, A R, & Terracciano, A (2015b). How old do you feel? The role of age discrimination and biological aging in subjective age. PLoS One, 10(3), e0119293. doi: 10.1371/journal.pone.0119293 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Stephan, Y, Sutin, A R, & Terracciano, A. (2016). Feeling older and risk of hospitalization: Evidence from three longitudinal cohorts. Health Psychology, 35(6), 634–637. doi: 10.1037/hea0000335 [DOI] [PubMed] [Google Scholar]
  33. Stephan, Y, Sutin, A R, Bayard, S, & Terracciano, A. (2017). Subjective age and sleep in middle-aged and older adults. Psychology & Health, 32(9), 1140–1151. doi: 10.1080/08870446.2017.1324971 [DOI] [PubMed] [Google Scholar]
  34. Stephan, Y, Sutin, A R, Luchetti, M, & Terracciano, A. (2018). Subjective age and risk of incident dementia: Evidence from the National Health and Aging Trends survey. Journal of Psychiatric Research, 100, 1–4. doi: 10.1016/j.jpsychires.2018.02.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Stephan, Y, Sutin, A R, & Terracciano, A. (2018). Subjective age and mortality in three longitudinal samples. Psychosomatic Medicine, 80(7), 659–664. doi: 10.1097/PSY.0000000000000613 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Stephan, Y, Sutin, A R, & Terracciano, A (2019). Subjective age and adiposity: Evidence from five samples. International Journal of Obesity (2005), 43(4), 938–941. doi: 10.1038/s41366-018-0179-x [DOI] [PubMed] [Google Scholar]
  37. Steptoe, A, & Kivimäki, M. (2012). Stress and cardiovascular disease. Nature Reviews. Cardiology, 9(6), 360–370. doi: 10.1038/nrcardio.2012.45 [DOI] [PubMed] [Google Scholar]
  38. Sun, J K, Kim, E S, & Smith, J. (2017). Positive self-perceptions of aging and lower rate of overnight hospitalization in the US population over age 50. Psychosomatic Medicine, 79(1), 81–90. doi: 10.1097/PSY.0000000000000364 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Thyagarajan, B, Shippee, N, Parsons, H, Vivek, S, Crimmins, E, Faul, J, & Shippee, T. (2019). How does subjective age get “under the skin”? The association between biomarkers and feeling older or younger than one’s age: The Health and Retirement Study. Innovation in Aging, 3(4), igz035. doi: 10.1093/geroni/igz035 [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Wallace, R, Herzog, A R, Ofstedal, M B, Steffick, D, Fonda, S, & Langa, K. (2000). Documentation of affective functioning measures in the Health and Retirement Study. Survey Research Center, University of Michigan. [Google Scholar]
  41. Westerhof, G J, Miche, M, Brothers, A F, Barrett, A E, Diehl, M, Montepare, J M, … Wurm, S. (2014). The influence of subjective aging on health and longevity: A meta-analysis of longitudinal data. Psychology and Aging, 29(4), 793–802. doi: 10.1037/a0038016 [DOI] [PubMed] [Google Scholar]
  42. Westerhof, G J, & Wurm, S (2018, online first). Subjective aging and health. In Knight B G & Wahl H-W (Eds.), Oxford research encyclopedia of psychology and aging (pp. 1–30). Oxford University Press. [Google Scholar]
  43. Wienert, J, Kuhlmann, T, Fink, S, Hambrecht, R, & Lippke, S. (2016). Testing principle working mechanisms of the health action process approach for subjective physical age groups. Research in Sports Medicine (Print), 24(1), 67–83. doi: 10.1080/15438627.2015.1126277 [DOI] [PubMed] [Google Scholar]
  44. Wurm, S, & Benyamini, Y. (2014). Optimism buffers the detrimental effect of negative self-perceptions of ageing on physical and mental health. Psychology & Health, 29(7), 832–848. doi: 10.1080/08870446.2014.891737 [DOI] [PubMed] [Google Scholar]
  45. Wurm, S, Diehl, M, Kornadt, A E, Westerhof, GJ, & Wahl, H-W. (2017). How do views on aging affect health outcomes in adulthood and late life? Explanations for an established connection. Developmental Review, 46, 27–43. doi: 10.1016/j.dr.2017.08.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Wurm, S, Tesch-Römer, C, & Tomasik, M J. (2007). Longitudinal findings on aging related cognitions, control beliefs, and health in later life. The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 62(3), 156–164. doi: 10.1093/geronb/62.3.P156 [DOI] [PubMed] [Google Scholar]
  47. Wurm, S, Wiest, M, Wolff, J K, Beyer, A K, & Spuling, S M. (2019). Changes in views on aging in later adulthood: The role of cardiovascular events. European Journal of Ageing. doi: 10.1007/s10433-019-00547-5 [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from The Journals of Gerontology Series B: Psychological Sciences and Social Sciences are provided here courtesy of Oxford University Press

RESOURCES