Abstract
Introduction
Using Jackson Heart Study (JHS) data, we assessed the association between perceived psychosocial stressors and metabolic syndrome (MetS) severity in African American adults.
Methods
Participants included 3,870 African American JHS participants aged 21 to 95 years (63.1% women; mean age 53.8± 13.0). Psychosocial stressors assessed included: major life events (MLEs); global stress; and weekly stress inventory. Each stress measure was classified into tertiles (low, medium, and high). Associations of psychosocial stressors with a sex- and race/ethnic-specific MetS severity Z-score were examined after adjustment for demographics and MetS risk factors (i.e., nutrition, physical activity, smoking status, and alcohol consumption).
Results
Independent of lifestyle factors, participants who reported high (versus low) perceived global stress and MLEs had significantly greater MetS severity (p=0.0207 and p=0.0105, respectively). Weekly stress was not associated with MetS severity. Compared to men, women reported significantly higher global stress and MLEs (p<0.0001). A significant interaction between sex and MLEs (p=0.0456) demonstrated men significantly increased their MetS severity at medium levels of stress, whereas women’s MetS severity was significantly increased at high levels of MLEs.
Conclusions
In the total sample, higher reported global stress and MLEs were associated with increased risk of MetS severity, while weekly stress was not. Men’s and women’s stress responses to MLEs were differentially associated with MetS severity, with male MetS severity increasing significantly at lower levels of MLEs relative to women’s MetS severity. These data may have implications for targeting stress-related factors in interventions to improve cardiometabolic health in African American adults.
Keywords: stress, metabolic syndrome, Jackson Heart Study, African Americans, adults, cardiovascular health
1. Introduction
Metabolic syndrome (MetS) is a risk factor for the development of cardiovascular disease (CVD) and type 2 diabetes. Individuals with MetS are twice as likely to develop CVD (Gami et al., 2007; Mottillo et al., 2010) and up to 5 times more likely to develop type 2 diabetes (Ford et al., 2008). Common features of MetS include abdominal adiposity, hypertension, hyperglycemia, and dyslipidemia (Grundy et al., 2005a). In 2012, a nationally representative sample demonstrated the prevalence of MetS in the U.S. was 34.7%, with slightly higher rates among African Americans (AA; 35.5%) than the general population (Aguilar et al., 2015). These rates are consistent with previously published MetS prevalence in the Jackson Heart Study (JHS) with 28.3–36.4% of participants having MetS (Gurka et al., 2016).
While development of MetS is attributed to known risk factors (e.g., poor diet, physical inactivity, smoking, low education) (Cameron et al., 2004; Irwin et al., 2002), adverse psychosocial factors may also contribute to MetS development and severity. Previously published JHS work indicated AA women with depression had worse MetS severity over an 8-year period relative to AA women who were not depressed (Gurka et al., 2016). Additionally, chronic stress has been identified as a possible risk factor for MetS, as it has been posited that psychosocial stress and neuroendocrine activation exert causal effects on MetS development (Björntorp, 1996; Hjemdahl, 2002; Kaur, 2014; Rosmond, 2005). For example, the “Bjorntorp hypothesis” states that chronic stress can activate the HPA axis, which increases cortisol levels leading to an increase in visceral fat deposition, which in turn promotes development of MetS (Björntorp, 1996, 2001). Yet, our group and others have demonstrated that AA tend to have less visceral adiposity relative to their non-Hispanic white counterparts (Cardel et al., 2011; Wagner and Heyward, 2000). Thus, there may be additional factors driving development of MetS in AA beyond that of excess visceral adiposity. The “Weathering Hypothesis” suggests that the health of AA deteriorates prematurely relative to non-Hispanic whites as a result of chronic exposure to social and environmental risk factors (Das, 2013; Thorpe et al., 2016). However, limited research has been conducted investigating the influence of psychosocial stressors on MetS outcomes in large samples of AA. Additionally, most research has focused on development or incidence, rather than severity, of MetS resulting from psychosocial stressors.
Thus, this study used JHS data to examine the associations of psychosocial stressors with severity of MetS among AA adults and whether relationships differed by sex. The hypothesis was that AA adults, particularly women, would have a higher MetS severity and that these relationships would be associated with psychosocial stressors.
2. Methods
2.1 Study Population
The JHS is a large, population-based cohort that investigates the etiology of CVD and related risk factors in AA. Between 2000–2004, 5,306 participants between the ages of 21–95 were recruited from the Jackson, Mississippi metropolitan area (Taylor et al., 2005). Three clinical examinations were conducted between 2000 and 2013 (exam 1 (baseline): 2000–2004; exam 2: 2005–2008; exam 3: 2009–2013). The Institutional Review Board (IRB) of the University of Mississippi Medical Center, Tougaloo College, and Jackson State University approved the study and all participants provided informed consent. In this cross-sectional study, data were utilized from exam 1 (2000–2004). Exam 1 included collection of baseline information through interviews in home and clinic settings. Questionnaires included inquiries about education, income, and lifestyle elements including physical activity, smoking status, alcohol consumption, and diet (Taylor et al., 2005). Exclusion criteria were presence of diabetes at baseline (n=1,233) and missing MetS severity score at exam 1 (n=203), resulting in a sample size of 3,870 for this study.
2.2 Psychosocial Stress Measures
Three psychosocial stress measures were included in this study: the Global Perceived Stress Scale (GPSS), Major Life Events (MLEs), and the Weekly Stress Inventory (WSI). The GPSS was given to participants in the baseline clinic examination, MLEs were determined through a telephone interview at the first annual follow-up, and the WSI was given to participants at the end of the baseline clinic examination (Gebreab et al., 2012).
The GPSS, a scale created specifically for the JHS cohort, consists of 8 domains assessing chronic stressors (i.e., employment, relationships, legal and medical issues, racism and discrimination, basic needs, etc.) throughout a 12-month period (Payne et al., 2005). Each domain is assessed using a 4-point scale of options ranging from “not stressful” to “very stressful” (0–3) with total scores varying between 0–24 (Payne et al., 2005). This scale was adapted from standardized stress scales including the Survey of Recent Life Experiences (Kohn and Macdonald, 1992), Perceived Stress Scale (Cohen et al., 1983), and Life Events Scale (Sarason et al., 1978). Inter-item reliability was satisfactory (Cronbach’s α=0.72).
MLEs were assessed for the past 12 months through the use of binary responses (yes/no) to an 11-item questionnaire (Holmes and Rahe, 1967). Items assessed include: 1) serious personal illness; 2) being a victim of physical assault; 3) being a victim of robbery/home burglary; 4) losing a loved one to violent behavior; 5) experience of gunfire at home/neighborhood; 6) death of a close friend/relative; 7) major illness/injury of a close friend/relative; 8) moving to a worse residence/neighborhood; 9) losing a job; 10) being forced into retirement when you did not want to; 11) experience of divorce/separation from a spouse. Total points possible range from 0–11 with 0 indicating no MLEs were experienced in the past 12 months and 11 indicating that all MLEs listed were experienced in the past 12 months. Cronbach’s alpha was not calculated as this measure is considered an index and not a true scale.
The WSI includes 87 items and was developed to report minor, daily stressful encounters and the magnitude of those encounters over the past week using an 8-point response scale ranging from “not stressful” to “extremely stressful” (0–7) (Brantley et al., 1987). Examples of these minor stressors include financial challenges, work-related tasks, transportation issues, relationships, household responsibilities, and leisurely activities. The score was determined by the number of minor stressors encountered (0–87). Cronbach’s alpha was 0.97.
2.3 MetS Classification and Z-score
At exam 1, MetS was defined using the adult ATP-III criteria (Grundy et al., 2005b). To be classified as having MetS, participants had to meet ≥3 of the following 5 criteria: concentration of triglycerides ≥1.69 mmol/L (150 mg/dL), HDL-C <1.04 mmol/L (40 mg/dL) for men and <1.3 mmol/L (50 mg/dL) for women, waist circumference ≥102 cm for men and ≥88 cm for women, glucose concentration ≥5.55 mmol/L (100 mg/dL), and systolic BP ≥130 mmHg or diastolic BP ≥85 mmHg (Grundy et al., 2005b).
MetS severity Z-score was calculated using formulas previously published (Gurka et al., 2012; Gurka et al., 2014). Briefly, these scores were determined with a confirmatory factor analysis (CFA) of the 5 standard components of MetS (described above (Grundy et al., 2005b)) to determine the weighted contribution of each of these components to a latent MetS “factor” on a sex- and race/ethnicity-specific basis. CFA was conducted on data from the National Health and Nutrition Examination Survey for adults ages 20–64 years (Gurka et al., 2014) divided into 6 sub-groups based on sex and self-identified race/ethnicity including: non-Hispanic white, non-Hispanic black, and Hispanic. For each of these 6 population sub-groups, loading coefficients for the 5 MetS components were determined to load on a single MetS factor and used to generate equations to calculate a standardized MetS severity score for each sub-group (found at http://mets.health-outcomes-policy.ufl.edu/calculator/). These MetS severity scores are Z-scores (with 99.75% of values ranging from −3 to 3) of relative MetS severity on a sex- and race/ethnicity-specific basis, with higher scores indicating worse MetS severity.
2.4 Covariates
Self-reported covariate measures included baseline age (continuous), sex, education, and income. Education was categorized by years of schooling completed: less than high school (<HS), high school graduate or GED equivalency through 1–3 years of college (HS4-C 1–3), and college graduate or more (C4+ years). Income was divided into 4 categories based on family size, US Census poverty levels, and year of baseline clinic visit (2000–2004): poor (less than federal poverty level), lower-middle (1–1.5 times the federal poverty level), upper-middle (more than 1.5, but less than 3.5 times the federal poverty level), and affluent (3.5 or more times the federal poverty level). Risk factors for development of MetS, including nutrition, physical activity, smoking status, and alcohol consumption were included as covariates. Both physical activity and nutrition status of each participant were classified into tertiles of ideal, intermediate, or poor based on recommendations of the American Heart Association’s Life’s Simple 7 cardiovascular health status metrics (Folsom et al., 2011). With consideration that some of these covariates could mediate psychosocial stress levels, results are shown before and after adjustment for the covariates using linear modeling in 3 different models.
2.5 Statistical Analysis
Descriptive statistics are presented by age and sex. Chi-square tests and t-tests (by sex)/ANOVA (by age category) were used to compare groups by categorical and continuous variables, respectively. Each stress measure was classified into tertiles indicating low, medium, and high stress of each participant, and mean MetS z-scores were compared across the 3 stress tertile groups. Multivariable linear regression was used to compare mean MetS z-scores across the stress tertiles with pre-determined sets of sequential adjustments. Model 1 adjusted for age and sex; model 2 adjusted for model 1 covariates plus education (<HS/HS-some college/college graduate); model 3 adjusted for model 2 covariates + nutrition (poor heath/other), physical activity (poor/intermediate/ideal health), smoking status (current smoker/other), and alcohol consumption (number of drinks per week). These models were used to estimate the main effect of stress on MetS severity; additional Model 3 was separately fit to explore interactions between sex and age category. Prevalence of ATP-III MetS was also estimated and compared across tertiles of the 3 stress measures. Each analysis was performed based on all available data, excluding observations with missing data.
3. Results
3.1 Sample Characteristics
Table 1 includes participant characteristics for the overall sample, stratified by sex and age. Data were evaluated from 3,870 participants (63.1% women; mean age 53.8 years) in the JHS. A large proportion of participants were identified as having poor health in the nutritional (60.3%) and physical activity (46.2%) categories. Further, 13.3% of participants reported being current cigarette smokers.
Table 1.
Participant characteristics overall, by sex and by age
| Overall | By Sex | By Age | ||||||
|---|---|---|---|---|---|---|---|---|
| Women | Men | p-value2 | 21–44 | 45–64 | 65+ | p-value3 | ||
| N | 3870 | 2441 | 1429 | 1087 | 1965 | 818 | ||
| Demographics | ||||||||
| Age, Mean (SD) | 53.8 (13.0) | 54.2 (13.0) | 53.1 (13.0) | 0.0136 | 38.2 (5.7) | 55.0 (5.9) | 71.6 (5.1) | <.0001 |
| Sex (% Women) | 63.1 | - | - | - | 61.7 | 62.8 | 65.5 | 0.2211 |
| S ES/Life style fac to rs | ||||||||
| Education (%) | ||||||||
| < High School | 15.4 | 14.9 | 16.2 | 0.5026 | 3.7 | 11.7 | 39.8 | <.0001 |
| High School 4 – College 3 | 49.8 | 50.4 | 48.8 | 60.7 | 49.3 | 36.4 | ||
| College 4+ | 34.8 | 34.7 | 35.0 | 35.6 | 39.0 | 23.8 | ||
| Income (%) | ||||||||
| Poor | 14.0 | 16.6 | 9.6 | <.0001 | 16.4 | 10.3 | 19.5 | <.0001 |
| Lower-middle | 23.3 | 24.9 | 20.6 | 19.3 | 19.7 | 37.0 | ||
| Upper-middle | 29.9 | 30.8 | 28.2 | 36.4 | 29.5 | 21.9 | ||
| Affluent | 32.9 | 27.7 | 41.7 | 27.9 | 40.5 | 21.6 | ||
| Cigarette smoking (AHA categorization) (%) | ||||||||
| Never smoked/quit ≥ 12 | 85.5 | 88.4 | 80.6 | <.0001 | 84.6 | 84.0 | 90.4 | <.0001 |
| month ago | ||||||||
| Quit < 12 month ago | 1.2 | 1.2 | 1.2 | 1.9 | 1.0 | 0.8 | ||
| Current smoker | 13.3 | 10.5 | 18.2 | 13.6 | 15.0 | 8.8 | ||
| Alcohol consumption | ||||||||
| Alcohol drinking in the past 12 months (%) | 49.1 | 41.9 | 61.5 | <.0001 | 63.7 | 49.4 | 29.3 | <.0001 |
| Average number of drinks per week, Mean (SD) | 1.8 (5.8) | 0.7 (3.4) | 3.5 (8.2) | <.0001 | 2.4 (7.1) | 1.8 (5.7) | 0.8 (3.4) | <.0001 |
| Nutrition (AHA categorization) (%) | ||||||||
| Ideal health | 0.8 | 0.9 | 0.6 | 0.0051 | 0.2 | 0.8 | 1.5 | <.0001 |
| Intermediate health | 38.9 | 40.8 | 35.5 | 28.8 | 40.9 | 46.6 | ||
| Poor health | 60.3 | 58.3 | 63.8 | 71.0 | 58.2 | 51.9 | ||
| Physical Activity (AHA categorization) (%) | ||||||||
| Ideal health | 21.0 | 18.2 | 25.8 | <.0001 | 26.2 | 20.8 | 14.6 | <.0001 |
| Intermediate health | 32.8 | 34.3 | 30.1 | 38.2 | 32.3 | 26.7 | ||
| Poor health | 46.2 | 47.5 | 44.1 | 35.6 | 46.9 | 58.8 | ||
| Stressor Scores, Mean (SD) | ||||||||
| Global Stress | 5.2 (4.4) | 5.6 (4.5) | 4.6 (4.2) | <.0001 | 6.6 (4.6) | 5.3 (4.3) | 3.1 (3.5) | <.0001 |
| Weekly stress | 83.7 (81.2) | 86.1 (81.3) | 79.5 (80.9) | 0.06344 | 105.0 (89.4) | 79.8 (77.1) | 55.1 (64.7) | <.0001 |
| Median (IQR) | 56 (28, 111.5) | 59 (28.5, 113) | 51 (25, 108) | 75 (41, 143) | 53 (27, 106) | 32 (18, 65) | ||
| Major Life Events1 | 1.3 (1.2) | 1.4 (1.2) | 1.2 (1.1) | <.0001 | 1.3 (1.3) | 1.4 (1.2) | 1.2 (1.1) | 0.0904 |
| Cumulative Stress Score | 6.1 (1.7) | 6.3 (1.7) | 5.9 (1.6) | <.0001 | 6.6 (1.6) | 6.1 (1.7) | 5.4 (1.5) | <.0001 |
| Health Measures, Mean (SD) | ||||||||
| BMI | 31.1 (7.1) | 32.1 (7.5) | 29.3 (6.0) | <.0001 | 31.8 (8.0) | 31.2 (6.9) | 29.8 (6.1) | <.0001 |
| Waist Circumference | 98.5 (15.6) | 98.0 (16.1) | 99.4 (14.8) | 0.0057 | 97.3 (17.2) | 98.9 (15.2) | 99.0 (14.4) | 0.0138 |
| SBP | 126.4 (16.8) | 125.7 (17.0) | 127.6 (16.3) | 0.0006 | 118.5 (13.2) | 127.3 (15.8) | 134.7 (18.6) | <.0001 |
| DBP | 76.2 (8.7) | 74.9 (8.5) | 78.5 (8.6) | <.0001 | 75.7 (8.6) | 77.5 (8.3) | 73.7 (9.0) | <.0001 |
| Triglycerides | 99.8 (66.4) | 94.2 (51.7) | 109.4 (85.0) | <.0001 | 89.4 (60.4) | 104.3 (74.0) | 102.9 (51.4) | <.0001 |
| HDL | 52.4 (14.8) | 55.8 (14.8) | 46.5 (12.8) | <.0001 | 49.8 (13.1) | 52.5 (14.9) | 55.3 (16.0) | <.0001 |
| Glucose | 90.4 (8.9) | 89.8 (9.1) | 91.5 (8.6) | <.0001 | 86.9 (7.7) | 91.2 (9.0) | 93.2 (8.9) | <.0001 |
| ATP-III MetS Status (%) | 21.5 | 22.7 | 19.5 | 0.0222 | 13.2 | 23.7 | 27.4 | <.0001 |
| MetS severity score Z-score | −0.070 (0.72) | −0.072 (0.73) | −0.064 (0.70) | 0.7292 | −0.253 (0.76) | −0.016 (0.70) | 0.046 (0.67) | <.0001 |
Boldface indicates statistical significance (p<0.05).
Collected at the first annual follow-up interview
t-test for continuous variables, chi-square tests for categorical variables
ANOVA for continuous variables, chi-square tests for categorical variables
p=0.0083 by Wilcoxon rank sum test
When stratifying by age, young people (ages 21–44) reported significantly more daily stress as measured by the WSI with median scores of 75 (interquartile range (IQR) 41, 143) compared to median scores of 53 (IQR 27, 106) for those ages 45–64 and 32 (IQR 18, 65) for those ages 65+ (p<0.0001). Young people also reported significantly more global stress (p<0.0001) as measured by the GPSS, where the mean score for ages 21–44 was 6.6 (± 4.6) while the mean score for ages 65+ was 3.1 (± 3.5).
When stratified by sex, women reported having significantly more global stress and MLE than men (p<0.0001). Global stress for women averaged 5.6 (± 4.5) while the average global stress score for men was 4.6 (± 4.2). MLEs were reported at 1.4 (± 1.2) for women and 1.2 (± 1.1) for men. The WSI median scores were 59 (IQR 28.5, 113) for women and 51 (IQR 25, 108) for men.
Prevalence of ATP-III MetS was 21.5% for the entire sample. Women (22.7%) and those in the older age group (27.4%) exhibited a higher prevalence of ATP-III MetS than men (19.5%) and those in the lowest age group (13.2%), respectively, with a significant increase by age (p<0.0001). MetS severity Z-scores also showed significant increases by age (p<0.0001).
3.2 Relationship between Baseline Psychosocial Stressors, ATP-III MetS Status, and MetS Severity
In unadjusted models (Table 4), significant associations of increased MLEs and perceived global stress with MetS severity were observed, with individuals with high MLEs exhibiting higher mean MetS severity (0.006 [95% confidence interval (CI) −0.053, 0.064]) compared to those with low levels of MLEs (−0.100 [CI −0.130, −0.071]; p=0.0016). Adjustment for potential confounders (age, sex, education, nutrition, physical activity, smoking status, and alcohol consumption) did not attenuate relationships between MetS severity, global, and MLE stress. WSI was not associated with MetS severity.
Table 4.
Linear Models of MetS Severity at Visit 1 (Overall)
| Model 1 | Model 2 | Model 3 | ||||
|---|---|---|---|---|---|---|
| Stressor | Mean Z-score (95% CI)2 | p-value3 | Mean Z-score (95% CI) | p-value | Mean Z-score (95% CI) | p-value |
| Global Stress | ||||||
| Low (n = 1633, 1.31 ± 1.18) | −0.089 (−0.125, −0.053) | -- | −0.091 (−0.127, −0.056) | -- | −0.095 (−0.134, −0.056) | -- |
| Medium (n = 1134, 5.36 ± 1.09) | −0.092 (−0.133, −0.050) | 0.9278 | −0.085 (−0.126, −0.044) | 0.8115 | −0.061 (−0.106, −0.017) | 0.2530 |
| High (n = 1076, 11.04 ± 2.98) | −0.036 (−0.079, 0.008) | 0.0683 | −0.038 (−0.081, 0.005) | 0.0673 | −0.022 (−0.070, 0.025) | 0.0207 |
| Weekly Stress | ||||||
| Low (n = 741, 18.8 ± 10.1) | −0.088 (−0.139, −0.037) | -- | −0.088 (−0.139, −0.038) | -- | −0.093 (−0.148, −0.038) | -- |
| Medium (n = 744, 58.1 ± 14.6) | −0.094 (−0.144, −0.043) | 0.8899 | −0.085 (−0.135, −0.035) | 0.9323 | −0.096 (−0.149, −0.042) | 0.9519 |
| High (n = 731, 175.7 ± 79.1) | −0.082 (−0.133, −0.030) | 0.8557 | −0.090 (−0.141, −0.038) | 0.9691 | −0.095 (−0.152, −0.038) | 0.9691 |
| Major Life Events1 | ||||||
| Low (n = 2184, 0.50 ± 0.50) | −0.100 (−0.130, −0.071) | -- | −0.099 (−0.129, −0.070) | -- | −0.090 (−0.123, −0.058) | -- |
| Medium (n = 861, 2.0 ± 0) | −0.060 (−0.107, −0.013) | 0.1567 | −0.057 (−0.104, −0.010) | 0.1387 | −0.050 (−0.101, 0.001) | 0.1797 |
| High (n = 556, 3.5 ± 0.75) | 0.006 (−0.053, 0.064) | 0.0016 | −0.005 (−0.064, 0.054) | 0.0049 | 0.003 (−0.061, 0.067) | 0.0105 |
Low=first tertile; medium=second tertile; high=third tertile
Model 1 covariates: Individual stress score (by tertile), age, sex; Model 2 covariates: Model 1 covariates + education (<hs/hs-some college/college graduate); Model 3 covariates: Model 2 covariates + nutrition (poor heath/other), physical activity (poor/intermediate/ideal health), smoking status (current smoker/other), alcohol consumption (number of drinks per week)
Boldface indicates statistical significance (p<0.05).
Collected at the first annual follow-up interview
Calculated at median values of continuous covariates and observed marginal distribution of categorical covariates
Comparing to the “low” stress group
Tables 2 and 3 present associations of each stress variable with MetS severity and prevalence of ATP-III MetS stratified by sex. Table 2 shows a significant interaction between sex and stress levels for both weekly stress (p=0.0020) and MLEs (p=0.0456). Mean Z-scores for MLEs among women approached significance at p=0.0676 in the highest tertile (compared to the lowest tertile), suggesting potentially higher MetS severity for women with high MLEs. Mean Z-scores for MLEs among men were significantly greater in the medium (versus low) tertile (p=0.0057). This suggests a potential higher threshold for MetS severity among women as compared to men in response to MLE stress. However, this is an associative relationship and causality cannot be inferred. Table 3 indicates that the prevalence of ATP-III MetS by sex was not significant for all 3 measures including perceived global stress, weekly stress, and MLEs.
Table 2.
Linear Models of MetS Severity at Visit 1, by Sex (Model 3)
| Men | Women | ||||||
|---|---|---|---|---|---|---|---|
| Stressor | N | Mean Z-score (95% CI)2 | p-value3 | N | Mean Z-score (95% CI) | p-value | p-value for Sex*Stressor Interaction |
| Global Stress | 0.0836 | ||||||
| Low | 598 | −0.065 (−0.126, −0.048) | -- | 824 | −0.11 (−0.158, −0.059) | -- | |
| Medium | 341 | −0.0026 (−0.079, 0.074) | 0.1993 | 656 | −0.10 (−0.155, −0.046) | 0.8307 | |
| High | 257 | −0.0067 (−0.095, 0.082) | 0.2798 | 655 | −0.036 (−0.091, 0.019) | 0.0580 | |
| Weekly Stress | 0.0020 | ||||||
| Low | 242 | −0.048 (−0.140, 0.044) | -- | 401 | −0.12 (−0.185, −0.048) | -- | |
| Medium | 225 | 0.030 (−0.063, 0.122) | 0.2289 | 444 | −0.16 (−0.227, −0.097) | 0.3493 | |
| High | 196 | −0.153 (−0.253, −0.052) | 0.1284 | 415 | −0.064 (−0.135, 0.0036) | 0.2912 | |
| Major Life Events1 | 0.0456 | ||||||
| Low | 719 | −0.084 (−0.137, −0.030) | -- | 1180 | −0.095 (−0.135, −0.054) | -- | |
| Medium | 235 | 0.061 (−0.030, 0.152) | 0.0057 | 526 | −0.102 (−0.162, −0.042) | 0.8349 | |
| High | 143 | 0.030 (−0.086, 0.146) | 0.0754 | 325 | −0.014 (−0.091, 0.062) | 0.0676 |
Low=first tertile; medium=second tertile; high=third tertile
Model 3 covariates: Individual stress score (by tertile), age, education (<hs/hs-some college/college graduate), nutrition (poor heath/other), physical activity (poor/intermediate/ideal health), smoking status (current smoker/other), alcohol consumption (number of drinks per week) Boldface indicates statistical significance (p<0.05).
Collected at the first annual follow-up interview
Calculated at median values of continuous covariates and observed marginal distribution of categorical covariates
Comparing to the “low” stress group
Table 3.
Prevalence of ATP-III MetS at Visit 1, by Sex (Unadjusted)
| Men | Women | ||||||
|---|---|---|---|---|---|---|---|
|
| |||||||
| n/N | % (95% CI)2 | p-value3 | n/N | % (95% CI) | p-value | p-value for Sex*Stressor Interaction4 | |
| Global Stress | 0.8196 | 0.0670 | 0.2084 | ||||
| Low | 131/694 | 18.9 (16.0, 22.0) | 232/939 | 24.7 (22.0, 27.6) | |||
| Med | 81/399 | 20.3 (16.5, 24.6) | 165/735 | 22.5 (19.5, 25.6) | |||
| High | 66/329 | 20.1 (15.9, 24.8) | 149/747 | 20.0 (17.1, 23.0) | |||
| Weekly Stress | 0.3045 | 0.2067 | 0.1835 | ||||
| Low | 55/295 | 18.6 (14.4, 23.6) | 102/446 | 22.9 (19.1, 27.1) | |||
| Med | 52/255 | 20.4 (15.6, 25.9) | 89/489 | 18.2 (14.9, 21.9) | |||
| High | 38/250 | 15.2 (11.0, 20.3) | 97/481 | 20.2 (16.7, 24.0) | |||
| Major Life Events1 | 0.2340 | 0.4282 | 0.2037 | ||||
| Low | 157/852 | 18.4 (15.9, 21.2) | 301/1332 | 22.6 (20.4, 24.9) | |||
| Med | 64/277 | 23.1 (18.3, 28.5) | 126/584 | 21.6 (18.3, 25.1) | |||
| High | 35/178 | 19.7 (14.1, 26.3) | 95/378 | 25.1 (20.8, 29.8) | |||
Low=first tertile; medium=second tertile; high=third tertile
Collected at the first annual follow-up interview
Clopper-Pearson (Exact) confidence limits
Chi-square test
Calculated based on logistic regression models log-likelihood statistics for type 3 analysis
Table 5 describes the prevalence of ATP-III MetS with all 3 stress measures. Neither perceived global stress, weekly stress, nor MLEs were related to ATP-III. Table 6 shows the impact of stressors on MetS severity, by age. In this table, none of the stress measures were significantly associated with MetS severity.
Table 5.
Prevalence of ATP-III MetS at Visit 1 (Overall; unadjusted)
| n | % (95% CI)2 | p-value3 | |
|---|---|---|---|
| Global Stress | 0.3668 | ||
| Low (n = 1633, 1.31 ± 1.18) | 363 | 22.2 (20.2, 24.3) | |
| Med (n = 1134, 5.36 ± 1.09) | 246 | 21.7 (19.3, 24.2) | |
| High (n = 1076, 11.04 ± 2.98) | 215 | 20.0 (17.6, 22.5) | |
| Weekly Stress | 0.3720 | ||
| Low (n = 741, 18.8 ± 10.1) | 157 | 21.2 (18.3, 24.3) | |
| Med (n = 744, 58.1 ± 14.6) | 141 | 19.0 (16.2, 22.0) | |
| High (n = 731, 175.7 ± 79.1) | 135 | 18.5 (15.7, 21.5) | |
| Major Life Events1 | 0.4353 | ||
| Low (n = 2184, 0.50 ± 0.50) | 458 | 21.0 (19.3, 22.7) | |
| Med (n = 861, 2.0 ± 0) | 190 | 22.1 (19.3, 25.0) | |
| High (n = 556, 3.5 ± 0.75) | 130 | 23.4 (20.0, 27.1) |
Collected at the first annual follow-up interview
Calculated at median values of continuous covariates and observed marginal distribution of categorical covariates
Comparing to the “low” stress group
Table 6.
Linear Models of MetS Severity at Visit 1, by Age (Model 3)
| 21–44 Year | 45–64 Years | 65+ Years | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| N | Mean Z-score (95% CI)2 | p-value3 | N | Mean Z-score (95% CI) | p-value | N | Mean Z-score (95% CI) | p-value | p-value for Age*Stress Interaction | |
| Global Stress | 0.1738 | |||||||||
| Low | 312 | −0.28 (−0.37, −0.19) | -- | 795 | −0.020 (−0.073, 0.033) | -- | 526 | 0.060 (−0.002, 0.122) | -- | |
| Medium | 343 | −0.28 (−0.37, 0.20) | 0.9508 | 611 | 0.029 (−0.030, 0.088) | 0.2204 | 180 | −0.019 (−0.125, 0.086) | 0.2002 | |
| High | 426 | −0.19 (−0.27, −0.11) | 0.1435 | 549 | −0.000 (−0.063, 0.063) | 0.6339 | 101 | 0.144 (0.002, 0.286) | 0.2885 | |
| Weekly Stress | 0.8686 | |||||||||
| Low | 155 | −0.27 (−0.39, −0.14) | -- | 385 | −0.018 (−0.093, 0.057) | -- | 201 | 0.045 (−0.056, 0.146) | ||
| Medium | 250 | −0.33 (−0.42, −0.23) | 0.4468 | 388 | −0.012 (−0.084, 0.061) | 0.8992 | 106 | −0.014 (−0.147, 0.119) | 0.4904 | |
| High | 306 | −0.31 (−0.39, −0.21) | 0.6530 | 359 | −0.017 (−0.095, 0.061) | 0.9798 | 66 | −0.060 (−0.231, 0.111) | 0.2940 | |
| Major Life Events1 | 0.0573 | |||||||||
| Low | 608 | −0.25 (−0.32, −0.19) | -- | 1096 | −0.029 (−0.074, 0.016) | -- | 480 | 0.022 (−0.043, 0.086) | -- | |
| Medium | 238 | −0.31 (−0.42, −0.21) | 0.3463 | 435 | 0.049 (−0.020, 0.119) | 0.0573 | 188 | 0.102 (−0.000, 0.205) | 0.1917 | |
| High | 160 | −0.13 (−0.26, 0.0038) | 0.0894 | 307 | 0.017 (−0.066, 0.099) | 0.3358 | 89 | 0.116 (−0.042, 0.274) | 0.2789 |
Low=first tertile; medium=second tertile; high=third tertile
Model 3 covariates: Individual stress score (by tertile), sex, education (<hs/hs-some college/college graduate), nutrition (poor heath/other), physical activity (poor/intermediate/ideal health), smoking status (current smoker/other), alcohol consumption (number of drinks per week)
Collected at the first annual follow-up interview
Calculated at median values of continuous covariates and observed marginal distribution of categorical covariates
Comparing to the “low” stress group
4. Discussion
This study investigated the relationships between psychosocial stressors (global stress, weekly stress, and MLEs) and the severity of MetS among AA adults. To our knowledge, this is the first study to examine the influence of psychosocial stressors on MetS severity in a large sample of AA. We found partial support for associations between stress and MetS: individuals with high (versus low) perceived global stress and MLEs had significantly greater MetS severity. Additionally, women reported higher global and MLE stress than men, but MetS severity was significantly higher at medium levels of stress in men, whereas women’s MetS severity was only significantly higher at high levels of MLEs. These data indicate differences both in reported stress of AA men and women and suggests a potential differential physiologic response to this stress. However, these relationships are derived from cross-sectional data and causality cannot be inferred. Thus, future research should be conducted to characterize sex-specific physiologic responses to perceived psychosocial stressors on MetS severity.
High global stress and MLEs were positively associated with MetS severity, independent of demographic and lifestyle factors known to contribute to MetS (Cameron et al., 2004; Irwin et al., 2002). Given that global stress and MLEs were significantly related to MetS severity, yet weekly stress was not, this suggests that both the level and type of stress are important for predicting MetS severity in AA adults. Specifically, high levels of chronic stress, as reflected by perceived global stress and MLEs, may be significantly associated with MetS severity, whereas daily stressors captured by the WSI appear to not be associated with MetS severity. This builds on a prospective study conducted primarily in non-Hispanic white women in the U.S. reporting that stressful life events at baseline resulted in increased risk for developing MetS over 15 years of follow-up (Räikkönen et al., 2007). Further, a large study (n=1,099) completed in a Dutch population ages 50–75 also found that men and women who reported a greater number of stressful life events had a higher risk of developing MetS during 6.5 years of follow-up (Rutters et al., 2015). However, when looking at more objective measures of stress, such as salivary cortisol, no relationship was found between level or diurnal pattern of salivary cortisol output in the Multi-Ethnic Study of Atherosclerosis (MESA) study, which included African Americans (DeSantis et al., 2011).
We also observed a significant interaction between sex and MLEs on MetS severity. Others have proposed that the ability to adapt to chronic stress may differ according to sex, and may be influenced by the regulatory effects of sex hormones (Pasquali, 2012). Specifically, alterations in sex hormones, particularly androgens, are associated with different patterns of fat deposition and distribution between men and women. Given that men tend to distribute their adiposity to abdominal and visceral regions, whereas women usually deposit fat in subcutaneous and gluteofemoral regions (Pasquali, 2006, 2012; Pasquali et al., 2008), sex differences in adiposity may influence MetS severity. Additionally, a stressful environment may lead to visceral fat accumulation as a result of chronic hypercortisolism (Kaur, 2014) and activate central pathways that stimulate the adrenals to release glucocorticoids. This process can mediate a pathogenetic role in the development and severity of MetS by leading to increased visceral adiposity, dyslipidemia, and hypertension (Rosmond, 2005). Beyond physiological sex differences, sex differences have also been cited in stress and coping styles. For example, women report more stress than men, but their coping style is more emotion-focused (Matud, 2004). How this plays out in terms of health outcomes is paradoxical in that women have lower rates of mortality, yet report higher levels of depression, psychiatric disorders, distress, and chronic illnesses than men (Denton et al., 2004). Thus, it is likely that sex differences in stress response and related health outcomes are complicated and reflect both biological and social factors, and the interplay between them. Further research is needed to confirm our observed associations and examine potential sex and chronic stress interactions in other populations.
Interestingly, when examining MetS prevalence using ATP-III definitions, psychosocial stressors were not associated with MetS in the overall sample or by sex or age stratifications. This is likely a reflection that MetS classification using the adult ATP-III criteria only takes into account the 5 physiological endpoints that define MetS and does not take into account factors that influence development of MetS including sex, race/ethnicity, and age (Cameron et al., 2004; Irwin et al., 2002). This suggests that our MetS severity Z-score may be a more relevant measure than using ATP-III criteria alone, as it allows for a weighted contribution of each of these 5 clustered components to a latent MetS “factor” on a sex- and race/ethnicity-specific basis.
4.1. Limitations
This study has many strengths including the assessment of multiple psychosocial stressors, demographic and lifestyle factors, and MetS-related variables. It also includes a well-characterized, large sample of AA and assesses MetS severity in addition to incidence of MetS. However, there are also some limitations that warrant discussion. First, only baseline measures of psychosocial stress (GPSS, MLE, and WSI) were obtained and thus, this study was unable to track for changes over time. The assessment of MLEs over the past 12 months may be subject to recall bias compared to the stress measurements that were used to determine current global and weekly stress, which were more acute measures. Additionally, perceived impact (whether negative or positive) of each MLE was not assessed as it was for global and weekly stress. For example, a MLE such as a divorce may be perceived as a positive event (Hollis et al., 1990). Further, the study was conducted in a single metropolitan area in Jackson, Mississippi, potentially limiting its generalizability to AA populations in other geographic regions.
5. Conclusions
In summary, psychosocial stressors were associated with MetS severity, with the strongest evidence displayed for MLEs impacting MetS severity. Medium levels of MLEs were associated with MetS severity in men, whereas stress from MLEs was not significantly associated in women until high levels were considered. Psychosocial stressors may be a point of intervention among AA for decreasing MetS severity and reducing health consequences and MetS risk.
Highlights.
High global stress is related to significantly greater MetS severity
High major life event stress was related to significantly greater MetS severity
Women report higher global and life event stress than men
Men significantly increase their MetS severity at medium levels of stress
Women significantly increase their MetS severity at high levels of stress
Acknowledgments
Funding: This work was supported by the National Institutes of Health National Heart, Lung, and Blood Institute (R01HL120960) and the National Center For Advancing Translational Sciences of the National Institutes of Health (UL1TR001427). The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.
The Jackson Heart Study (JHS) is supported and conducted in collaboration with Jackson State University (HHSN268201300049C and HHSN268201300050C), Tougaloo College (HHSN268201300048C), and the University of Mississippi Medical Center (HHSN268201300046C and HHSN268201300047C) contracts from the National Heart, Lung, and Blood Institute (NHLBI) and the National Institute for Minority Health and Health Disparities (NIMHD). The authors wish to thank the staff and participants of the JHS. Special thanks to Darci Miller for her careful review of the manuscript.
Footnotes
Financial disclosure: No financial disclosures were reported by the authors of this paper.
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