Cumulative Psychosocial Stress and Ideal Cardiovascular Health in Older Women: Data by Race/Ethnicity

Abstract

Background:

Research implicates acute and chronic stressors in racial/ethnic health disparities, but the joint impact of multiple stressors on racial/ethnic disparities in cardiovascular health is unknown.

Methods:

In 25,062 women (N: White: 24,053; Hispanic: 256; Black: 440; Asian: 313) participating in the Women’s Health Study (WHS) follow-up cohort, we examined the relationship between cumulative psychosocial stress (CPS) and ideal cardiovascular health (ICH), as defined by the American Heart Association Strategic 2020 goals. This health metric includes smoking, body mass index, physical activity, diet, blood pressure, total cholesterol and glucose, with higher levels indicating more ideal cardiovascular health and less cardiovascular risk (score range: 0–7). We created a CPS score which summarized acute (e.g. negative life events) and chronic stressors (e.g. work, work-family spillover, financial, discrimination, relationship and neighborhood) and traumatic life event stress reported on a stress questionnaire administered in 2012–2013 [score range 16–385, higher scores indicating higher levels of stress)].

Results:

White women had the lowest mean CPS scores (White: 161.7 ± 50.4; Hispanic: 171.2 ± 51.7; Black: 172.5 ± 54.9; Asian: 170.8 ± 50.6; p _overall <0.01). Mean CPS scores remained higher in Hispanic, Black and Asian women compared to White women after adjusting for age, socioeconomic status (SES: income and education) and psychological status (depression and anxiety) [p_each <0.01]. Mean ICH scores varied by race/ethnicity (p < 0.01), and were significantly lower in Black women and higher in Asian women when compared to White women (β coefficient and 95% Confidence Interval (CI): Hispanics −0.02: −0.13, −0.09; Blacks −0.34: −0.43, −0.25; Asians 0.34: 0.24, 0.45); control for SES and CPS did not change these results. Interactions between CPS and race/ethnicity in ICH models were not significant.

Conclusions:

Both cumulative psychosocial stress and ideal cardiovascular health varied by race/ethnicity. ICH remained worst in Blacks and better in Asians compared to Whites, despite taking into account socioeconomic factors and cumulative psychosocial stress.

INTRODUCTION

Cardiovascular disease (CVD) is a leading cause of death for every racial/ethnic group in the US, and accounts for much of the excess premature mortality among Blacks when compared to Whites.¹ Several decades of research have sought to unpack the mechanisms through which race/ethnicity impacts traditional modifiable risk factors for CVD, such as hypertension, elevated cholesterol, poor diet and low physical activity, with the aim of targeting cardiovascular prevention programs to reduce differences in CVD outcomes.² Although psychosocial stress is a known risk factor for CVD including myocardial infarction,^{3, 4} much of the work related to the latter in different racial/ethnic groups is limited to single domains of stress, such as discrimination or to general perceived stress. Thus, almost no data exist pertaining to the relationship of a combination of acute and chronic stressors (cumulative psychosocial stress; CPS) and race/ethnicity or to CVD health resulting in significant gaps in the literature in these regards. Indeed, individuals typically experience a combination of stressors and the examination of single domains of stress likely do not accurately capture the impact of cumulative stress over time. Moreover, whether the association between CPS and CVD varies based on race/ethnicity is unknown.

Psychosocial stress can result from multiple sources including trauma, interpersonal relationships, employment and neighborhood environment, potentially resulting in physiological consequences including dysregulation of the inflammatory, neuro-hormonal and autonomic nervous systems.^{5, 6} Psychosocial stress associated with social inequalities is arguably disproportionately experienced by racial/ethnic minorities living in the United States (U.S).^{7, 8} For example, job instability and financial strain are associated with increased serum C-reactive protein concentration in Mexicans living in the US.⁹ Additionally, everyday discrimination is associated with increased serum biomarkers of endothelial dysfunction and blood pressure.^6,10 These aforementioned forms of psychosocial stress in turn may be potential mechanisms by which racial/ethnic disparities in CVD risk occur.^7,10–12

Ideal cardiovascular health (ICH) is a metric supported by the American Heart Association (AHA) 2020 Impact Goals to improve the cardiovascular health of all Americans by 20%, in which a higher score is associated with a more favorable cardiovascular profile.¹³ More than a mere tally of the absence of 7 lifestyle-related risk factors for CVD, including tobacco use, blood pressure, cholesterol, fasting glucose, weight, physical activity, and diet, ICH was created to take into account both behavioral and clinical risk factors in order to be used both in research and clinical practice as a pragmatic tool to empower patients to reduce their CVD risk. To date, emerging data indicate an inverse association of ICH with incident myocardial infarction, heart failure, stroke and cardiovascular mortality in men and women.^{14, 15} Although women live longer than men, black women in particular do not achieve as much of the cardiovascular benefit associated with sex as women of other races/ethnicities.^16,17 Although lower SES regardless of race/ethnicity is associated with poor cardiovascular health, differences in cardiovascular health outcomes by race/ethnicity are not fully explained by SES differences.¹⁸ Given that psychosocial stress is as important a risk factor for CVD as traditional risk factors such as smoking and dyslipidemia, and that psychosocial stressors might be differentially associated with heightened cardiovascular risk based on race/ethnicity and culture ³,¹⁹, we sought 1) to assess the relationship between cumulative psychosocial stress and race/ethnicity and 2) to evaluate the impact of cumulative psychosocial stress on any observed ICH-race/ethnicity relationship in women participating in the Women’s Health Study.^{14, 20, 21}

METHODS

Data Availability

The data will not be made available to other researchers for purposes of reproducing results. However, we highly encourage collaboration and contacting the corresponding author regarding sharing of methods and other information.

Study Population

We utilized participants from the follow-up cohort of the Women’s Health Study (WHS), a completed randomized clinical trial of the effect of low dose aspirin, Vitamin E and beta carotene in the primary prevention of cancer and CVD.²² Female health professionals age 45 years and older in the United States were invited to participate in the trial (N=39,876). Study randomization began in April 1993 and follow-up for the clinical trial ended in March 2004. After trial conclusion, consenting participants from the trial were recruited into an observational cohort, starting in 2005 (N= 33,796). Follow-up questionnaires were conducted every 6 months during the first year, and every year starting in year 2 to assess self-reported sociodemographic information and health outcomes. In 2012–2013, participants in the WHS observational cohort with no history of CVD were invited to participate in this stress cohort. A total of 25,335 participants were willing and eligible, and provided informed consent for the stress study. Women with complete data on race/ethnicity, cumulative psychosocial stress, and ICH metrics were included in this analysis (N=25,062); 193 women without complete race/ethnicity, stress and ICH data were excluded. Due to the small sample size of American Indian women (N=49) and women who reported their race/ethnicity as other (N=31), we do not present these data. Therefore, 273 women were excluded representing 1.1 % of this stress cohort. The distributions of available baseline characteristics were similar in the excluded group compared to women in this analysis (data not shown). This study was approved by the Institutional Review Boards of Brigham and Women’s Hospital and the University of California, San Francisco.

Assessment of Cumulative Psychosocial Stress

Details of the WHS stress follow-up study are previously detailed.²³ A mailed written questionnaire to evaluate acute and chronic psychosocial stressors was completed by each participant. Acute stress domains (reported as yes or no) included items regarding negative events in the past 5 years (e.g. fired from a job, moving to a worse neighborhood, unemployment) and traumatic life events (e.g. life-threatening illness or death of child/spouse, physical attack/assault victim). Chronic stress domains included work stress (e.g unable to express work creativity, lack of decision authority, monotony or excessive work, conflicting demands, job insecurity), work-family conflict (e.g too stressed out to participate in activities with family/others), financial stress (e.g inadequate funds, difficulty paying bills), intimate partner stress (e.g relationship happiness, partner demands, conflict resolution ), neighborhood stress (e.g safety, community member trust/support) and everyday discrimination (e.g less respect, poor service, treated as unintelligent/dangerous). These chronic stress domains were assessed using 4 or 5 option Likert-style responses depending on the domain.²³ Weights were assigned to each of the 8 domains comprising the cumulative stress score based on the reciprocal of the standard deviation of the scores for questions in each domain. The 8 domain specific weighted scores were then added to create the cumulative stress score (CPS; range 16–385), with higher values representing higher stress.

Assessment of Ideal Cardiovascular Health

We created an ICH score using the AHA Strategic 2020 Impact Goals, which captures an index of ideal cardiovascular health consisting of 7 health behaviors and factors. ICH is defined as: body mass index (BMI) < 25 kg/m2; ≥150 min/week of moderate physical activity; a healthy diet pattern including sufficient amounts of fruits and vegetables; optimal blood pressure (<120/ <80 mmHg); fasting glucose <100 mg/dL; total cholesterol <200 mg/dL; and never smoking or smoking cessation for more than 12 months.¹³ ICH was determined for each participant in WHS using self-reported data collected within one year of stress study baseline in 2011–2012 due to WHS followup data collection schedule. The accuracy of self-reported health conditions in WHS, including blood pressure, diabetes and weight, is greater than 90%.^24–27 Diet information was collected in a self-administered food frequency questionnaire administered in 2004. Missing values for total cholesterol were imputed using the value from the data collection period immediately preceding the 2011–2012 follow-up assessment (i.e 2010–2011).

The definition of each component of ICH is consistent with the AHA definition, with the following modifications to accommodate the methodology of WHS (Table 1):

1. Physical activity: Ideal- moderate physical activity ≥150 minutes per week, intermediate- 1–150 minutes per week, poor- <1 minute per week;

2. Diet: The diet metric is composed of five components consistent with a Dietary Approaches to Stop Hypertension (DASH) diet: fruits and vegetables, fish, fiber-rich whole grains, sodium, and sugar-sweetened beverages. In this analysis, each component of the DASH diet was assessed by 25^th or 75^th percentiles for the WHS cohort. Participants were classified as ideal if they reported fruits and vegetables consumption above the 75^th percentile, fish intake above the 75^th percentile, sodium intake below the 25^th percentile and sugar-sweetened beverages below the 25^th percentile. Fiber-whole grains consumption was divided into whole grains intake and fiber intake, and each received a score of 0.5 above the 75^th percentile. Diet was rated according to the number of dietary components that met the criteria for ideal: ideal: 4–5; intermediate: 2–3; poor: 0–1; Glycemia: ideal- no self-report of type 2 Diabetes Mellitus (diabetes), poor- self-report of diabetes consistent with the definitions used in the AHA 2020 goals.¹³

Table 1:

Definition of Poor, Intermediate and Ideal Cardiovascular Health in the Women’s Health Stress Study

	Ideal Cardiovascular Health
	Poor	Intermediate	Ideal
Health Behaviors
Smoking	Current	Former	Never
Weight/ BMI	≥30 kg/m2	25 – < 30 kg/m2	< 25 kg/m2
Physical Activity	Moderate physical activity less than 1 minute per week	Moderate physical activity between 1 – 149 minutes per week	Moderate physical activity greater than or equal to 150 minutes per week
Diet	0–1 Components	2–3 Components	4–5 Components
a. Fruits and Vegetables (Above 75th percentile)   b. Fish (Above 75th percentile)   c. Sodium (Below 25th percentile)   d. Sugar Sweetened Beverages (Below 25th percentile)   e. Fiber-Rich Whole Grains: Fiber ((Above 75th percentile); Whole Grains (Above 75th percentile)
Health Factors
Blood Pressure	SBP ≥ 140 mmHg or DBP ≥ 90 mmHg	SBP 120–139 mmHg or DBP 80–89 mmHg	< 120/80 mmHg
Total Cholesterol	≥ 240 mg/dL	200–239 mg/dL	< 200 mg/dL
Glycemia/ Fasting Plasma Glucose	Positive Type 2 Diabetes Diagnosis	N/A	No History of Type 2 Diabetes

For each component of ICH, participants were given a score of 1 for ideal classification, a score of 0.5 for intermediate, and a score of 0 for poor. The scores for the 7 metrics were summed to give a total ICH score ranging between 0 and 7, with 7 meaning ideal risk factor category for all components. This continuous ICH score was categorized into 3 groups: low (scores 0 – 3), intermediate (scores 3.5 – 5.5) and high (scores 6 – 7).

Covariates

Age, race/ethnicity, education level and annual household income (income) were self-reported. Other conditions included in the analyses include: obesity/overweight (normal <25.0 kg/m², overweight 25.0 – less than 30.0 kg/m², and obese ≥30.0 kg/m²; Asians: normal <23.0 kg/m², overweight 23.0 – less than 27.0 kg/m², and obese ≥27.0 kg/m²), hypertension history, hypercholesterolemia and alcohol use (<1 glass/day versus ≥1 glass/day).^28,29

Physical activity was evaluated by self-report at initiation of the WHS and is updated every 2–3 years with questions based on the College Alumni Health Study for which reliability and validity has been extensively investigated.^30,31 Ascertained data includes information about usual pattern of stair climbing and walking and average time weekly doing leisure time activities (e.g walking/jogging, aerobic exercise, dance, swimming). Blood pressure was self-reported using the following criteria from the annual WHS follow-up questionnaire: 1) physician diagnosis of hypertension; 2) initiation of blood pressure lowering medication; 3) systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg. Validation of self-report of hypertension in WHS is 96%.²⁵

Participants completed a validated, reproducible 131 item semi-quantitative food frequency questionnaire prior to WHS randomization and in 2004 to assess dietary intake.³² Women responded to questions that inquired about frequency of consumption of the following foods: fruits and vegetables (includes fruit juices and excludes potatoes), fish (e.g canned tuna, shrimp/lobster, dark meat fish, breaded fish), fiber (e.g dark bread, brown rice, oatmeal, grains), sugar sweetened beverages (e.g carbonated beverage with caffeine and sugar, punch, lemonade) and sodium. Responses were on a 9 point-scale ranging from never/less than once/monthly to ≥ 6 times/day. Due to skewedness related to food consumption distribution, food intake was treated both as continuous and dichotomous variables (i.e cut-points were for fruits and vegetables ≥ 4.5 cups/day, fish ≥ two 3.5 oz servings/week, fiber rich whole grains ≥ three 1-oz equivalent servings/day, sugar sweetened beverages ≤ 450kcal (36 oz)/week, sodium <1500 mg/day). Total caloric intake (kcal/day) was a continuous variable.³³

Lipid levels were initially obtained via blood from WHS participants prior to randomization and by self-report. Thereafter, h/o hypercholesterolemia is self-reported on annual follow-up questionnaires. The reliability of self-report is extremely high and correlates well with cardiovascular disease risk. ³⁴ Self-reported Type 2 diabetes (diabetes) is also collected on the annual WHS follow-up questionnaire and validated using American Diabetes Association criteria (Positive Predictive Value for validation is 91%).²⁴ Finally, self-reported weight correlates strongly (r=0.96) with directly measured weight.²⁷ Psychological status including depressed mood (e.g., feeling downhearted/blue/in the dumps) and anxiety (e.g., nervousness, feeling calm/peaceful) were assessed by the stress questionnaire.

Statistical Analyses

Baseline characteristics are reported by race/ethnicity as means and medians; significance testing was performed using ANOVA or Kruskal Wallis and Chi-square. CPS is reported as median and associated 25^th and 75^th interquartile range based on race/ethnicity. To compare CPS by race/ethnicity, we used linear regression analyses and report the beta-coefficients (referent group: whites). Linear regression models assessed the relationship between race/ethnicity as follows: Model 1: unadjusted; Model 2: age-adjusted; Model 3: Model 2 + SES (income and education); Model 4: Model 3 + psychological status (depression and anxiety symptoms); Model 5: Model 4 + hypertension, BMI, smoking, alcohol use, and physical activity.

The relationship between race/ethnicity and ICH (continuous variable) was examined by linear regression: Model 1: unadjusted; Model 2: age-adjusted; Model 3: age + CPS; Model 4: Model 3+ SES (education, income); Model 5: Model 4+ psychological status. We also performed mediation analyses using CAUSALMED procedure in SAS to understand the effect of cumulative stress on racial/ethnic differences in ICH. We also examined the individual components of the ICH and CPS scores by race/ethnicity. Pearson correlation coefficients between CPS and ICH were also calculated. The proportional odds assumption and models of unequal slopes for race/ethnicity were performed. A two-tailed p-value < 0.05 indicated statistical significance. Analyses used SAS® 9.4 (SAS Institute Inc., Cary, NC, USA).

RESULTS

Among the participating 25,062 women [White (n=24,053); Hispanic (n=256); Black (n=440); Asian (n=313)], overall mean age at the time of the stress questionnaire was 72.2 ± 6.0 years old. Compared to White women, Hispanic women had lower educational attainment and income, higher prevalent diabetes and hypercholesterolemia, higher BMI, and less current smoking; Black women had lower income, more diabetes and hypertension, higher BMI and more current smokers (Table 2). Asian women had higher educational attainment and income, more diabetes, lower BMI and current smoking. White women had more prevalent alcohol use than women of other racial/ethnic groups.

Table 2:

Sociodemographic Characteristics and Cardiometabolic Risk Factors of Participants in the Women’s Health Stress Study by Race/Ethnicity

	White	Hispanic	Black	Asian	p-value overall
Sample Size, N	N = 24053	N = 256	N = 440	N = 313
Age (years), median (IQR)	70.9 (67.3 – 75.8)	70.4 (67.2 – 75.1)	71.5 (68.0 – 75.4)	71.1 (67.8 – 74.6)	0.56
Education, N (%)					<0.001
Less than College (< Bachelor’s Degree)	50.8%	55.5%	50.6%	20.9%
College or More (≥ Bachelor’s Degree)	45.1%	44.5%	49.4%	79.1%
Household Income, N (%)					<0.001
Less than $50,000	40.3%	46.4%	45.6%	15.6%
$50,000 or More	57.2%	53.6%	54.4%	84.4%
Type 2 Diabetes, (%)	9.8%	19.5%	23.0%	19.5%	<0.001
Current Hypertension, N (%)	69.8%	70.3%	88.4%	70.9%	<0.001
Current Hypercholesterolemia (>240mg/dL), N (%)	73.6%	79.3%	73.3%	79.2%	0.02
Current BMI (kg/m2), median (IQR)	25.8 (23.0 – 29.7)	26.5 (23.4 – 30.1)	28.3 (25.7 – 32.1)	23.0 (21.1 – 25.6)	<0.001
Current BMI, N (%)					<0.001
< 25.0	42.7%	38.0%	19.3%	71.3%
25.0 – <30.0	34.0%	35.7%	43.4%	21.7%
≥30.0	23.3%	26.3%	37.3%	7.0%
Smoking, N (%)					<0.001
Never	49.2%	62.5%	51.9%	77.3%
Past	46.1%	34.0%	42.4%	20.8%
Current	4.8%	3.5%	5.7%	1.9%
Alcohol, N (%)					<0.001
<1 glass/ day	84.6%	93.4%	95.0%	94.9%
>=1glass/day	15.5%	6.6%	5.0%	5.1%
Current METs (hrs/wk), mean (±SD)	17.5 ± 16.5	16.3 ± 18.1	16.1 ± 17.5	21.7 ± 17.5	<0.001
Depression Score, mean (± SD)	5.5 ± 2.1	5.7 ± 2.6	5.3 ± 2.0	5.7 ± 2.0	0.01
Anxiety Score, mean (± SD)	4.4 ± 1.6	4.4 ± 1.8	4.0 ± 1.5	4.4 ± 1.6	<0.001

Figure 1 displays CPS scores (mean, median and interquartile range) by race/ethnicity. Overall, non-Whites had higher CPS scores than Whites. Specifically, mean CPS scores were lowest for White women (161.7 ±50.4). Black women had the highest mean CPS score (172.5 ±54.9), followed by Hispanic women (171.2 ±51.7) and then Asian women (170.8 ±50.6). Table 3 shows the results of linear regression analyses of CPS by race/ethnicity (White women= referent). After adjusting for potential confounders, Black (β = 0.08, 95% CI 0.06–0.10), Hispanic (β = 0.05, 95% CI 0.03–0.08) and Asian (β = 0.04, 95% CI 0.02–0.07) women reported higher CPS than White women (all p <0.001). Table 4 shows the relationship between the individual stressors and ICH by race/ethnicity. These results reveal that the impact of each stress domain on ICH is relatively similar in magnitude in Blacks and Asians. The effect of individual stressor domains in Hispanics was negligible and not statistically significant.

Figure 1: Cumulative Psychosocial Stress (CPS) Score by Race/Ethnicity in the Women’s Health Stress Study.

Mean (♦) and median cumulative stress scores and associated interquartile range (IQR) according to race/ethnic group among participants in the WHS Stress Study. P Value across race/ethnicity groups < 0.001

Table 3:

Comparison of Cumulative Psychosocial Stress (CPS) Scores by Race/Ethnicity in the Women’s Health Stress Study

Model	Hispanic	Black	Asian
Sample Size, N	N = 256	N = 440	N = 313
Model 1: Unadjusted	6.7% (3.9, 9.6) P < 0.001	7.7% (5.6, 9.9) P < 0.001	2.4% (−0.03, 4.9) P = 0.05
Model 2	6.4% (3.7, 9.0) P < 0.001	7.4% (5.3,9.4) P < 0.001	2.5% (0.007,4.8) P = 0.04
Model 3	6.1% (3.4,8.7) P < 0.001	7.4% (5.3,9.5) P < 0.001	4.8% (2.4, 7.3) P < 0.001
Model 4	5.5% (3.1, 7.8) P < 0.001	9.5% (7.6,11.3) P < 0.001	4.0% (1.8, 6.2) P < 0.001
Model 5: Fully Adjusted	5.4% (3.1, 7.8) P < 0.001	8.2% (6.1, 10.1) P < 0.001	4.3% (2.1, 6.5) P < 0.001

Percent differences from White women (reference), 95% Confidence Interval and P value.

Model 1: Unadjusted

Model 2: Age

Model 3: Model 2 + Income + Education

Model 4: Model 3 + Depression/Anxiety

Model 5: Model 4 + Hypertension + Smoking + Alcohol Use + METs + BMI

Table 4:

Ideal Cardiovascular Health in Relation to Individual Psychosocial Stress Domains by Race/ethnicity

	Race/Ethnicity
	White	Hispanic		Black		Asian
Individual Stressor	β (SE)	β (SE)	P-value	β (SE)	P-value	β (SE)	P-value
Work stress	1.00	−0.08 (0.06)	0.16	−0.41 (0.04)	<0.01	0.41 (0.05)	<0.01
Work-Family Stress	1.00	−0.08 (0.06)	0.18	−0.43 (0.04)	<0.01	0.43 (0.05)	<0.01
Financial Stress	1.00	−0.05 (0.06)	0.38	−0.35 (0.04)	<0.01	0.38 (0.05)	<0.01
Traumatic events	1.00	−0.07 (0.06)	0.24	−0.42 (0.04)	<0.01	0.41 (0.05)	<0.01
Negative life events (past 5 years)	1.00	−0.07 (0.06)	0.24	−0.41 (0.04)	<0.01	0.42 (0.05)	<0.01
Discrimination Stress	1.00	−0.07 (0.06)	0.23	−0.39 (0.04)	<0.01	0.44 (0.05)	<0.01
Relationship Stress	1.00	−0.06 (0.06)	0.31	−0.36 (0.04)	<0.01	0.44 (0.05)	<0.01
Neighborhood Stress	1.00	−0.04 (0.06)	0.47	−0.38 (0.04)	<0.01	0.43 (0.05)	<0.01

β =Beta-Coefficient, SE=Standard Error, White women = reference

As shown in Figure 2, Mean ICH score was the highest in Asian (5.0 ±0.9), followed by White (4.6 ±0.9), Hispanic (4.5 ±1.0) and Black (4.1 ±1.0) women. Black women had the highest proportion of participants with low ICH scores (19.1%), i.e. lowest cardiovascular health, and the lowest percentage of participants with high ICH scores (3.9%) (Supplemental Table 1). Asian women had the lowest percentage of participants with low ICH scores (4.8%) and the highest percentage of participants with high ICH scores (19.2%), i.e. with ideal cardiovascular health. The odds of having ideal ICH classification (ICH score= 6–7) vs. poor ICH classification (ICH score= 0–3) was significantly decreased for Black women compared to White women (odds ratio [OR] =0.46, 95% CI 0.28, 0.75) after adjusting for age, CPS and SES (Supplemental Table 1). Asian women were two times more likely than White women to have ideal vs. poor ICH (OR=2.21, 95% CI 1.65, 2.98).

Figure 2: Ideal Cardiovascular Health Score by Race/Ethnicity in the Women’s Health Study.

Mean (♦) and median ideal cardiovascular health scores and associated interquartile range (IQR) according to race/ethnic group among participants in the WHS Stress Study. P Value < 0.001

We also observed that in all race/ethnicity groups, physical activity was the ICH metric with the largest proportion of women categorized as ideal, with a range from 73.8% to 88.6% (Supplemental Table 2). The BMI component of the ICH score had the widest range of percentage of participants meeting the criteria for ideal classification, ranging from 19.3% in Black women to 71.3% in Asian women. Asian women had the highest percentage of participants meeting the criteria for ideal for the greatest number of individual components of the ICH score. When considering the individual components of ICH (i.e odds for ideal vs poor component), the odds of absence of diabetes (ideal) was lower in Hispanics (OR=0.49, 95% CI 0.36, 0.67), Blacks (OR=0.42, 95% CI 0.34, 0.53) and Asians (OR=0.45, 95% CI 0.34, 0.60) compared to Whites. Additionally in Asians, the odds of other ideal ICH components were significantly higher (e.g never smokers, OR =3.92, 95% CI 1.72, 8.86) compared to Whites, besides total cholesterol. The odds of ideal vs. poor blood pressure was significantly lower in Blacks (OR= 0.61, 95% CI 0.44, 0.86) compared to Whites.

Table 5 shows results of linear regression analyses of ICH according to race/ethnicity. As previously noted, compared to White women, Black women and Hispanic women had lower ICH scores and Asian women had higher ICH scores (Table 3). These racial/ethnic differences persisted and remained statistically significant despite adjustment for CPS (model 3) and additionally for SES (model 4), except among Hispanics. In age-adjusted models, among blacks compared to whites, approximately 12.7% of ICH was mediated by CPS (p < 0.001). No significant associations were noted in Hispanics (p=0.27) and Asians (p =0.06). The overall correlation between ICH and the CPS score was small (r=−0.06, P<0.001).

Table 5:

β Coefficients of Ideal Cardiovascular Health Score by Race/Ethnicity (Reference = White women)

	Hispanic	Black	Asian
Sample Size, N	N = 256	N = 440	N = 313
Model 1	−0.07 (−0.18, −0.05) P = 0.26	−0.37 (−0.45, −0.28) P < 0.01	0.42 (0.32, 0.52) P < 0.01
Model 2	−0.06 (−0.18, −0.05) P = 0.27	−0.37 (−0.45, −0.28) P < 0.01	0.42 (0.31, 0.52) P < 0.01
Model 3	−0.03 (−0.14, 0.09) P =0.65	−0.32 (−0.40, −0.23) P <0.01	0.43 (0.33, 0.56) P < 0.01
Model 4	−0.02 (−0.13, 0.09) P = 0.72	−0.33 (−0.42, −0.24) P < 0.01	0.35 (0.24, 0.45) P < 0.01
Model 5	−0.02 (−0.13, 0.09) P = 0.72	−0.34 (−0.43, −0.25) P < 0.01	0.34 (0.24, 0.45) P < 0.01

Beta-Coefficient, 95% Confidence Interval, and P Value.

Model 1: Unadjusted

Model 2: Age

Model 3: Model 2 + Cumulative Psychosocial Stress

Model 4: Model 3 + Education + Income

Model 5: Model 4 + Depression/Anxiety

Reference = White Women.

Negative values indicate lower ideal cardiovascular health

DISCUSSION

In this cross-sectional study of older women participating in the Women’s Health Study, both CPS and ICH varied by race/ethnicity. White women had lower CPS scores than other women. Black women had the highest CPS and the lowest ICH scores. Asian women had the highest ICH scores and were more likely categorized as having ideal cardiovascular health compared to White women. The observed racial/ethnic differences in ICH persisted after adjustment for CPS or SES between. These data suggest that the mechanisms by which racial/ethnic differences in cardio-metabolic risk in this cohort likely occur through multiple pathways beyond SES and measured acute and chronic stressors. Given that racial/ethnic heterogeneity exists in all major groups discussed in this paper and is primarily a social construct that serves as a surrogate for other individual and societal variables that might affect health behaviors and health outcomes, our analysis significantly adds to existing literature by additionally examining the impact of cumulative stress on ICH. In future research, it will be important to evaluate whether alternative modes to assess stress can be of additional value for understanding the association between race/ethnicity and cardiovascular health.

While the prevalence of ICH was higher in our study compared to other cohorts, the racial/ethnic differences in ICH were similar to that observed in other cohorts.^{20,21, 35} NHANES 2003–2008 data demonstrated a prevalence of ICH in women age ≥ 65 years of less than 2%, which is considerably less than what was reported for each of the race/ethnicity groups in our study.³⁵ However, the participants of WHS were health professionals, and thus have a relatively higher educational attainment than other cohorts and likely higher exposure to information on healthy behaviors, which may account for the higher prevalence of ICH. However, despite the overall increased prevalence of ICH in WHS, racial/ethnic differences in ICH remain. In other cohorts, despite the considerable heterogeneity in the manner in which the components of ICH have been defined and measured, particularly in diet, the pattern of worse ICH in Blacks is a recurrent observation. In examining the NHANES (2003–2008) data by race/ethnicity, Black women aged ≥ 65 years had the lowest prevalence of ideal classification in the areas of tobacco, BMI, diet and blood pressure, while Mexican American women of the same age group had the lowest prevalence of ideal physical activity and fasting glucose.³⁵ Of note, Asian American women were not included in many of the studies of ICH with the exception of a study from the Behavioral Risk Factor Surveillance System (BRFSS). In an analysis of BRFSS 2009 data, patterning in overall ICH scores by race/ethnicity was similar to our study with Asians having the highest prevalence of ICH, followed by Whites, Hispanics and Blacks.²⁰ Importantly, in this analysis we used recommended cut-points for Asian women who tend to have higher CVD risk at lower BMI.^{28, 29} ICH in Hispanics differs by national background as observed in the Northern Manhattan Study in which Caribbean Hispanics had the lowest prevalence of ICH and the lowest prevalence of ideal classification in the areas of BMI and blood pressure.¹⁴

In our data herein, ICH varied by race/ethnicity despite taking into account CPS and SES. On one hand, the latter is surprising since the CPS scores are statistically different by race/ethnicity and previous work from this cohort indicates robust socioeconomic diversity linked to CVD outcomes despite the fact that the WHS participants are female health professionals.³⁶ Despite the latter, overlapping confidence intervals between CPS by race/ethnicity and the likelihood that racial/ethnic differences in ICH in women likely occur through multiple mechanisms including genetic but more likely environmental, behavioral and social factors may have impacted the findings in this cohort of health professionals.^{7, 37} For example, characteristics of neighborhood physical and social environment, such as walkability and safety, are associated with hypertension and obesity prevalence.³⁸Neighborhood characteristics also influence cardiovascular health behaviors.^37–43 Indeed, the ICH metric is comprised of both cardio-metabolic risk factors and health behaviors, each of which might have different upstream social determinants, including cultural practices that influence food choices and leisure-time physical activity. While the CPS measurement herein included neighborhood stressors, it is possible that the magnitude of the range in the neighborhood stress score for these female health professionals might be different than that noted in the general population. Despite the latter, the ability to capture multiple domains of potential stressors in this well phenotyped cohort is a significant addition to the current literature. Certainly, previous WHS data about race/ethnicity and inflammation was one of the first published studies about racial/ethnic differences in high-sensitivity C-reactive protein and has remained generalizable over time to other cohorts and to the general population.⁴⁴

Despite the preceding, limitations of this study merit discussion. First, these data are cross-sectional. Stress due to medical problems was omitted from the CPS assessment for this analysis in order to help mitigate the potential for reverse causality. Second, participants in WHS are older health care female professionals, and thus similar analyses in other populations including in men and younger individuals is needed. Health behaviors of female health professionals might differ from those of other populations. For example, as noted physical activity levels tend to be greater among participants in the WHS, albeit this would tend to underestimate any observed differences noted in this analysis herein. Third, the stressors measured in the stress questionnaire are self-reported. However, the perceived experience of psychosocial stress likely represents the actual stress burden of the participant as it is an individual’s perception of a stressor and response to the latter that influences their physiological response or health outcome via inflammatory, neurohormonal and autonomic regulatory systems.⁵ Additionally, although WHS is a mailed survey and other variables such as hypertension and diabetes are self-reported, the validity of these self-reported variables within WHS has had greater than 90% accuracy with physician-diagnosis.^24–27 Weight as a self-reported variable has been validated in other cohorts.⁴⁵ Fourth, approximately 42% and 35% of variables related to work and relationship were missing likely due to many of the women being older retirees. However, performance of sensitivity analyses revealed that our results without missing are similar. Fifth, the dietary questionnaire (2004) was conducted 7 years prior to the stress questionnaire (2012–2013), and thus dietary patterns of these women could have changed over time. We are unable to correct for this limitation but note that WHS has several published manuscripts utilizing these same diet data that accurately predict disease risk.^46–48 Finally, we cannot account for unmeasured confounders.

In conclusion, these data show that although ICH varies by race/ethnicity among female health professionals participating in the Women’s Health Study, the association between race/ethnicity and ICH was un-attenuated by our joint assessment of acute and chronic stressors nor by SES as measured by income and education. Our results are intriguing and suggest that other pathways likely contribute to racial/ethnic differences in ICH within WHS. Additionally, it is uncertain whether our findings are cohort specific and thus similar work in other populations is required. To the best of our knowledge, data regarding this topic remain sparse. Future work must include prospective analyses about the interplay between race/ethnicity, CPS and CVD risk as both behavior at the individual level and policy interventions intended to reduce CVD risk currently do not incorporate psychosocial stressors.

CONCLUSIONS

In a cohort of older women, lifetime stress as defined by acute and chronic stressors and ICH varied by race/ethnicity. Cumulative psychosocial stress and socioeconomic status did not account for the racial/ethnic differences in ICH. These data support the need for additional work that addresses the joint impact of multiple social determinants of health, such as psychosocial stress, on CVD in diverse populations.

Clinical Perspective.

What is new?

• Cumulative psychological stress and socioeconomic status were evaluated as potential explanations for racial/ethnic differences in ideal cardiovascular health among older women.

• Our results show that these factors did not explain the racial/ethnic differences noted in ideal cardiovascular health among older female health professionals.

• Stressors were jointly evaluated and included both acute (e.g life events) and chronic (e.g job, financial, work-family conflict, neighborhood) sources of stress.

What are the clinical applications?

• Psychosocial stressors are social determinants of health that likely have different prevalence according to race/ethnicity.

• Clinicians should incorporate psychosocial stressors in their assessment of patients as they might help to better target cardiovascular care particularly since different patients will have wide variability in socioeconomic status, a potential source of stress.

• This analysis utilized a psychosocial stress questionnaire with potential clinical utility due in part to its succinct but comprehensive components.