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. Author manuscript; available in PMC: 2021 Jul 1.
Published in final edited form as: Psychoneuroendocrinology. 2020 Apr 26;117:104686. doi: 10.1016/j.psyneuen.2020.104686

Objective and Subjective Socioeconomic Status Associated with Metabolic Syndrome Severity among African American Adults in Jackson Heart Study

Michelle I Cardel a, Yi Guo a, Mario Sims b, Akilah Dulin c, Darci Miller a, Xiaofei Chi a, Gregory Pavela d, Mark D DeBoer e, Matthew J Gurka a
PMCID: PMC7304382  NIHMSID: NIHMS1592767  PMID: 32361636

Abstract

Purpose:

To assess independent associations between objective socioeconomic status (OSS) and subjective social status (SSS) with metabolic syndrome (MetS) severity and indicators among African American (AA) adults in the Jackson Heart Study (JHS) at baseline (2000-2004) and eight-year follow-up (2009-2013).

Methods:

Participants included 1,724 AA adults from the JHS cohort (64.4% women; mean age 53.4 ± 11.8). Associations of OSS (annual household income and school years completed) and SSS (measured with MacArthur Scales) with 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, alcohol consumption, and depressive symptoms) at baseline and eight-year follow-up.

Principal Results:

Independent of OSS, demographic, psychosocial, and lifestyle factors, individuals with lower US-society SSS had more severe MetS at baseline. A significant interaction existed between sex and US-society SSS such that women with lower perceived social status had more severe MetS severity at baseline, and for every one unit increase in US-society SSS, MetS severity Z-score is estimated to decrease by 0.04. Components of MetS driving the relationship between US-society SSS and MetS severity at baseline were the inverse associations of SSS with glucose levels and the positive associations of SSS with HDL-C. Physical activity was independently associated with MetS severity at baseline, but not at eight-year follow-up.

Major Conclusions:

Though subjective and objective measures of social status are independently associated with cardiometabolic risk factors and MetS severity among AA adults, SSS may be a stronger predictor of MetS severity than OSS, particularly among women. SSS should be considered in conjunction with OSS when exploring social determinants of cardiometabolic health.

Keywords: socioeconomic status, social status, African Americans, Jackson Heart Study, metabolic syndrome, cardiometabolic health

1. Introduction

Objective socioeconomic status (OSS), typically measured using income and education, is inversely related to myriad risk factors for cardiovascular disease (CVD)(Kaplan and Keil, 1993). Though OSS is commonly used to assess social position, subjective social status (SSS), a measure that allows for self-assessment of perceived social rank, is hypothesized to better tap into the psychosocial consequences of relative position within social hierarchy. SSS is inversely associated with number of cardiovascular risk factors and tends to be more strongly, inversely associated with health status over time and psychosocial risk factors when compared to OSS (Adler et al., 2008; Adler et al., 2000; Goodman et al., 2003; Manuck et al., 2010; Wright and Steptoe, 2005). SSS has also been linked with self-rated health, depression, hypertension (with the exception of African American (AA) males)(Adler et al., 2008), obesity, and food insecurity (Cardel et al., 2018c; Goodman et al., 2003; Goodman et al., 2015). Among Jackson Heart Study (JHS) participants, SSS was also associated with depressive symptoms and insulin resistance among AA women (Subramanyam et al., 2012a). SSS may be more sensitive to race/ethnicity than OSS as it may uncover social circumstances involving racism or discrimination, particularly among AA, not captured with the OSS measure alone (Subramanyam et al., 2012a). Assessment of both objective and subjective measures of social standing may be particularly relevant among AA adults, as evidence suggests that for a given level of education and income, AAs experience lower economic and social returns relative to non-Hispanic whites (Braveman et al., 2005; Krieger, 1990). Thus, SSS may better capture the social and material implications of social rank among AA adults, especially when evaluating social determinants of health and cardiometabolic risk.

Metabolic syndrome (MetS) is a risk factor for the development of CVD and type 2 diabetes and is indicated by elevated triglyceride (TG) levels, central adiposity, fasting glucose, blood pressure, and reductions in high-density lipoprotein cholesterol (HDL-C) (Grundy et al., 2005). However, traditional MetS criteria, such as those used with the Adult Treatment Panel (ATP)-III, have noted limitations including their binary nature and discrepancies by race/ethnicity, potentially underestimating risk among AA (DeBoer, 2011; DeBoer et al., 2011; Walker et al., 2012). Previous analyses from the JHS have shown associations between OSS and hypertension (Glover et al., 2020), as well as perceived stress and incidence of hypertension (Spruill et al., 2019), one indicator of MetS.

While MetS is attributed in part to known lifestyle risk factors, OSS and SSS may also contribute to severity of MetS. However, the relationship between SSS and indicators of MetS after adjusting for known MetS risk factors (including OSS) is poorly understood, particularly among AA (Adler et al., 2008; Manuck et al., 2010; Ostrove et al., 2000). Moreover, an inverse association between SSS and hypertension has been found among AA women but not AA men (Adler et al., 2008), suggesting that the relationship between SSS and cardiovascular health may differ by sex. Thus, additional research is needed to investigate associations between both OSS and SSS with MetS indicators to determine how they may influence the development of poor cardiovascular health outcomes over time in the overall population and by sex.

In this analysis, data from the JHS were used to assess independent associations between OSS and SSS with MetS severity and MetS indicators in AA adults at baseline and eight years later. Given that we were interested in how AA adults perceive their rank within different contexts, two separate constructs of SSS were used, including SSS at the United States (US) society and community levels. OSS was assessed by education and income. We hypothesized that MetS severity would be inversely associated with OSS and SSS (US and community) at baseline and at follow-up. Given previous reports of sex-specific associations between SSS and cardiometabolic risk (Adler et al., 2008; Subramanyam et al., 2012b), we also examined sex differences in the association.

2. Methods

2.1. Data

JHS data were used from exam 1 (2000-2004) and exam 3 (2009-2013) to assess cross-sectional and longitudinal associations of OSS and SSS with MetS severity among AA adults. JHS is the largest cohort study to investigate CVD in the AA population at a single site. The study has been approved by the Institutional Review Board (IRB) of the University of Mississippi Medical Center, Tougaloo College, and Jackson State University, and all participants provided informed consent. At baseline, 5,301 participants ages 35-84 were recruited from Jackson, Mississippi and the tri-county regional area including Hinds, Madison, and Rankin counties (Fuqua et al., 2005; Taylor et al., 2005). At each visit, demographic and participant health information were collected including blood pressure, TG levels, glucose, cholesterol, waist circumference (WC), and self-reported age, sex, education, and income level using standardized protocols (Taylor et al., 2008; Taylor et al., 2005). Participants were fasting at each visit. Lifestyle risk factors were assessed in clinic and home interviews (Taylor et al., 2005). Participants included in the analytic sample were those in the JHS with both baseline and 8-year follow-up data (n=1,724).

2.2. Subjective Social Status (SSS)

SSS was assessed using the MacArthur Scale of SSS (Adler et al., 2000), a measure using pictorial depictions of a social ladder with two different referent points: 1) the entire US-society and 2) the participant’s community (Adler et al., 2000; Singh-Manoux et al., 2003; Subramanyam et al., 2012a). We elected to include measures of both the US-society and participant community because the two ladders represent different constructs. Whereas the US-society ladder generally solicits comparisons based on income, education, and occupation within the broader society as the reference, the community ladder generally solicits one’s own defined community as the reference (Adler et al., 2000; Singh-Manoux et al., 2003; Subramanyam et al., 2012a). Moreover, previous studies indicate that AA tend to report higher community SSS at a given US-referent SSS, supporting prior evidence that they are different constructs (Subramanyam et al., 2012a; Wolff et al., 2010). When assessing perceptions of social status within the US society, participants are asked to imagine that the ladder represents the place people occupy in American society. When assessing perceptions of social status within the community, participants are asked to imagine that the ladder represents the place people occupy in their community. In both instances, on each 10-rung ladder, the first (bottom) rung represents people who are the worst off—having the least money, least education, and worst job or no job. The tenth (top) rung represents people who are the best off—having the most money, most education, and most respected job. Participants are then asked to mark the place on each ladder best representing where they stand at present, with SSS scores derived from the rung selected. SSS was analyzed as a continuous variable (range 1-10).

2.3. Objective Socioeconomic Status (OSS)

OSS was measured using self-reported years of school completed and income level. Educational attainment was classified into five categories (less than high school, high school graduate, vocational school graduate, college graduate, and graduate/professional school completion). Income was dichotomously coded as an income <$25,000 per year versus an income of ≥$25,000 per year. This cutoff was selected because 2013 was the last year data were collected for this study. At that time, the US Department of Health and Human Services poverty guidelines reported that a family of four lived in poverty if the household income was ~$25,000 per year or less (Health and Services, 2016).

2.4. Depressive Symptoms

The Center for Epidemiologic Studies Depression (CES-D) 20-item scale was used to measure depressive symptoms and has been shown to have excellent psychometric properties among AA (Naughton and Wiklund, 1993). Participants rated the frequency of symptom occurrence, with scores ranging from 0 to 3. Scores were summed, and higher scores denote greater frequency of depressive symptoms. In our analyses, depressive symptoms were used as a continuous variable. However, given that CES-D was given as part of a take-home packet at the end of the baseline visit with instructions to mail back, it is only available for 60% of the total cohort.

2.5. MetS Classification and Z-score

Given that traditional MetS criteria, such as those used with the ATP-III, has noted limitations and potentially underestimates risk among AA (DeBoer, 2011; DeBoer et al., 2011; Walker et al., 2012), our group formulated a MetS severity Z-score, improving risk prediction for diabetes and coronary heart disease among individuals without diabetes (DeBoer et al., 2017; Gurka et al., 2017). MetS severity Z-score is our primary outcome (continuous) and was calculated using previously described research (Gurka et al., 2012; Gurka et al., 2014). Briefly, scores were determined using confirmatory factor analysis (CFA) of the five standard criteria of MetS (Grundy et al., 2005) for the purposes of assessing the weighted contribution of each component to a latent MetS “factor” on a sex- and race/ethnicity-specific basis. These MetS severity scores are presented as Z-scores (with 99.75% of values ranging from −3 to 3) of relative MetS severity with higher scores indicating greater MetS severity.

Our secondary outcomes included ATP-III MetS score (categorical) and the five components of MetS; WC, TG levels, systolic blood pressure (SBP), HDL-C, and glucose levels measured at baseline. These outcome measures were assessed in the JHS to determine whether participants were diagnosed with MetS (Grundy et al., 2005). To be diagnosed as having MetS, individuals are required to meet ≥3 of the following 5 criteria: concentration of TG ≥1.69 mmol/L (150 mg/dL), HDL-C <1.04 mmol/L (40 mg/dL) for males and <1.3 mmol/L (50 mg/dL) for females, WC ≥102 cm for males and ≥88 cm for females, glucose concentration ≥5.55 mmol/L (100 mg/dL), and SBP ≥130 mmHg or diastolic blood pressure (DBP) ≥85 mmHg; otherwise, individuals were classified as not having MetS (Grundy et al., 2005).

2.6. Covariates

Covariates included baseline age (continuous), sex, education, income level, depressive symptoms, and MetS lifestyle risk factors. As previously mentioned, education and income indicate OSS. Physical activity was assessed using the JHS Physical Activity Cohort (JPAC) survey (Dubbert et al., 2005) and nutrition status was assessed using 24-hour dietary recalls (Carithers et al., 2005). Both physical activity and nutrition status of each subject were categorized into tertiles of ideal, intermediate, or poor according to recommendations of the American Heart Association’s Life’s Simple 7 metrics for cardiovascular health status (Folsom et al., 2011). Smoking status and alcohol consumption were bivariate and indicated whether a participant currently smoked and consumed alcohol within the past 12 months. Results are displayed after adjustment for covariates using linear modeling for both US-level SSS and community-level SSS.

2.7. Statistical Analysis

Descriptive statistics (means and SD) are presented by age and by sex. Multivariable linear regression models were used to test whether community- and US-society SSS were associated with MetS severity and to test their association with each individual item of the MetS measure (WC, HDL-C, SBP, TG, and glucose). Two sets of regression models were analyzed: (1) baseline MetS as the dependent variable and (2) MetS score at eight-year follow-up as the dependent variable with baseline MetS included as a covariate. Two sets of logistic regression models were analyzed: (1) baseline ATP-III as the dependent variable and (2) ATP-III at eight-year follow-up as the dependent variable with baseline ATP-III included as a covariate. All models adjusted for age, sex, education, nutrition, physical activity, smoking status, alcohol consumption, and depressive symptoms.

3. Results

Participant characteristics are displayed in Table 1 for the overall analytic sample by sex and by age. While JHS was comprised of 5,301 participants, our analytic sample was 1,724, representing those individuals with both baseline measures (including all covariates of interest included in our final models) and eight-year follow-up data. The mean age was 53.4 ± 11.8 years and 64.4% of participants were female. Most participants (30.7%) completed vocational school as their highest level of education while 10.9% completed education less than high school. 70.9% of participants received a household income ≥$25,000 per year. Mean US-society SSS was 6.3 ± 2.1 and mean community SSS was 7.6 ± 2.0 for the total sample. Both US-society SSS and community SSS significantly increased with age. Neither SSS measure differed by sex. Results in Table 1 also display overall means of each MetS component of participants in the cohort. Mean WC indicating central adiposity was 99.8 ± 16.0 cm. Mean HDL-C levels indicated 51.9 ± 14.2 mg/dL. Mean SBP was 124.9 ± 16.6 mmHg. Mean TG level concentration was 102.5 ± 60.7 mg/dL. Mean glucose concentration was 95.9 ± 24.9 mg/dL. Mean MetS severity Z-score was 0.1 ± 0.9.

Table 1:

Participant characteristics for total sample and by sex and age

Overall Females Males p-valuea 20-44 45-64 65+ p-valueb
N 1724 1110 614 477 946 301
Demographics
 Age, Mean (SD) 53.4 (11.8) 53.6 (11.9) 52.9 (11.6) 0.2563 38.7 (5.1) 55.4 (5.9) 70.1 (4.0) <.0001
 Sex (% Female) 64.4 - - - 63.3 63.8 67.8 0.3934
Objective Social Status/Lifestyle factors
 Education (%)
  < High School Grad 10.9 10.5 11.7 0.0213 4.2 8.7 28.6 <.0001
  High School Grad 15.1 16.2 13.0 10.7 16.9 16.3
  Vocational School 30.7 31.3 29.8 43.4 28.6 17.3
  College Graduate 20.6 18.5 24.4 28.3 20.6 8.3
  Graduate/Prof 22.7 23.6 21.0 13.4 25.2 29.6
Household Income (%)
 <25k 29.1 34.8 18.7 <.0001 24.9 26.1 44.9 <.0001
 ≥25k 70.9 65.2 81.3 75.1 73.9 55.1
Subjective Social Status
 US-Society SSS 6.3 (2.1) 6.4 (2.1) 6.3 (2.0) 0.3834 6.0 (1.9) 6.5 (2.1) 6.4 (2.2) 0.0002
 Community SSS 7.6 (2.0) 7.6 (2.0) 7.6 (2.0) 0.5986 6.9 (2.2) 7.8 (1.9) 7.9 (1.9) <.0001
Current smoker (%)
 No 90.0 91.3 87.8 0.0211 89.9 88.1 96.3 0.0002
 Yes 10.0 8.7 12.2 10.1 11.9 3.7
Alcohol consumption (%)
 No 49.2 55.9 37.0 <.0001 38.8 48.3 68.4 <.0001
 Yes 50.8 44.1 63.0 61.2 51.7 31.6
Nutrition (%)
 Ideal health 1.2 1.3 1.1 0.1828 0.2 1.4 2.3 <.0001
 Intermediate health 37.4 38.9 34.5 27.3 39.9 45.5
 Poor health 61.4 59.8 64.3 72.5 58.8 52.2
Physical Activity (%)
 Ideal health 23.2 20.5 28.0 0.0020 27.9 23.2 15.9 <.0001
 Intermediate health 36.1 37.5 33.6 38.6 36.0 32.2
 Poor health 40.7 42.0 38.4 33.5 40.8 51.8
Total Depressive Symptoms Score, Mean (SD) 10.3 (7.5) 10.8 (7.7) 9.3 (6.9) <.0001 10.9 (7.6) 10.1 (7.7) 9.9 (6.5) 0.1136
Health Measures, Mean (SD)
 WC, cm 99.8 (16.0) 99.3 (16.2) 100.8 (15.7) 0.0640 98.9 (18.3) 100.1 (15.6) 100.5 (13.4) 0.3120
 HDL-C, mg/dL 51.9 (14.2) 55.2 (14.2) 45.9 (12.1) <.0001 49.5 (12.7) 52.0 (14.1) 55.5 (15.8) <.0001
 SBP, mmHG 124.9 (16.6) 124.0 (16.9) 126.6 (16.0) 0.0022 117.1 (13.9) 126.3 (16.0) 133.0 (17.4) <.0001
 TG, mg/dL 102.5 (60.7) 97.6 (51.8) 111.2 (73.4) <.0001 90.2 (63.0) 107.7 (61.8) 105.4 (49.9) <.0001
 Glucose, mg/dL 95.9 (24.9) 95.3 (24.7) 97.1 (25.3) 0.1541 88.6 (18.8) 98.6 (28.6) 99.3 (17.5) <.0001
 MetS Z-score 0.1 (0.9) 0.1 (1.0) 0.1 (0.9) 0.8824 −0.2 (0.9) 0.2 (1.0) 0.2 (0.8) <.0001
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a

t-test for continuous variables, chi-square tests for categorical variables

b

ANOVA for continuous variables, chi-square tests for categorical variables

Table 2 presents results of linear regression models testing the associations between community SSS, OSS, and MetS severity at baseline and eight years later, independent of demographic, psychosocial, and lifestyle factors. Age was significantly associated (p<0.0001) with MetS severity at baseline and follow-up. Both physical activity (intermediate vs poor and ideal vs poor; b=−0.116, p=0.0250; b=−0.154, p=0.0103, respectively) and education (graduate/professional school vs less than high school) (b=−0.180, p=0.0498) were inversely and significantly associated with baseline MetS severity, but not eight years later after controlling for baseline MetS severity. We did not observe a significant association between community SSS and MetS severity at baseline or eight years later, nor did we see a significant interaction between community SSS and sex. The only variables associated with MetS severity eight years later were baseline MetS severity and age (p<0.001). Depressive symptoms were not significantly associated with MetS severity at either time point.

Table 2.

Association between Community Subjective Social Status (SSS), Objective Social Status, and Metabolic Syndrome Severity at Baseline and 8-Years Later, Independent of Demographic, Psychosocial, and Lifestyle Factors, n=1,724

MetS Severity At Baseline MetS Severity 8-Years Later
Parameter Est SE t Value P Est SE t Value P
Baseline MetS Severity - - - - 0.762 0.020 38.81 <.0001
Community SSS −0.002 0.014 −0.11 0.9128 0.001 0.012 0.09 0.9299
Age 0.012 0.002 5.61 <.0001 −0.010 0.002 −5.40 <.0001
Male 0.151 0.182 0.83 0.4082 −0.182 0.148 −1.23 0.2186
Education: High School (HS)/Some college vs <HS −0.111 0.079 −1.40 0.1613 0.007 0.064 0.11 0.9129
Education: Graduate/Professional vs <HS −0.180 0.071 −1.39 0.0498 −0.040 0.074 −0.54 0.5889
Income >=25k vs < 25k −0.089 0.056 −1.58 0.1140 0.012 0.046 0.26 0.7975
Nutrition: Intermediate vs Poor 0.062 0.047 1.31 0.1909 −0.002 0.038 −0.05 0.9613
Nutrition: Ideal vs Poor 0.031 0.205 0.15 0.8782 −0.166 0.167 −1.00 0.3193
Physical Activity: Intermediate vs Poor −0.116 0.052 −2.24 0.0250 −0.040 0.042 −0.96 0.3382
Physical Activity: Ideal vs Poor −0.154 0.049 −2.57 0.0103 −0.089 0.049 −1.82 0.0689
Current smoker: yes vs no −0.092 0.077 −1.20 0.2309 0.065 0.062 1.04 0.2982
Alcohol Intake: yes vs no 0.051 0.047 1.09 0.2764 −0.018 0.038 −0.46 0.6454
Total Depressive Symptoms Score 0.006 0.003 1.90 0.0576 0.001 0.003 0.36 0.7166
Interaction: Community SSS*Male −0.017 0.023 −0.71 0.4749 0.014 0.019 0.73 0.4633
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Table 3 presents results of linear regression models testing the associations between US-society SSS, OSS, and MetS severity at baseline and eight years later, independent of demographic, psychosocial, and lifestyle factors. Covariates significantly associated (p<0.05) with MetS severity at baseline were similar, but not identical to those identified in the model with community SSS. Covariates significantly associated with MetS severity eight years later included baseline MetS severity, age (p<0.0001), and sex (p=0.0236). Physical activity (intermediate vs poor and ideal vs poor; b=−0.118, p=0.0229; b=−0.155, p=0.0098) was negatively associated with MetS at baseline, but not eight years later. We also observed a significant inverse association between self-reported US-society SSS and severity of MetS at baseline (b=−0.046, p=0.0007, but not eight years later, independent of demographic, psychosocial, and lifestyle factors. At baseline, we observed a significant interaction between US-society SSS and sex (b=0.046, p=0.0451). Depressive symptoms were not significantly associated with MetS severity at either time point. In Table 4, we present the coefficient for US-society SSS by sex. Among women, US-society SSS was inversely associated with MetS severity at baseline (SSS coefficient=−0.039, p=0.0046), but not follow-up. Among men, US-society SSS was not associated with MetS severity at baseline or at follow-up.

Table 3.

Association between US-Society Subjective Social Status, Objective Social Status, and Metabolic Syndrome Severity at Baseline and 8-Years Later, Independent of Demographic, Psychosocial, and Lifestyle Factors, n=1,724

MetS Severity At Baseline MetS Severity 8-Years Later
Parameter Est SE t Value P Est SE t Value P
Baseline MetS Severity - - - - 0.760 0.020 38.63 <.0001
US-Society SSS −0.046 0.013 −3.39 0.0007 −0.008 0.011 −0.70 0.4811
Age 0.012 0.002 5.93 <.0001 −0.009 0.002 −5.29 <.0001
Male −0.270 0.153 −1.77 0.0771 −0.282 0.124 −2.27 0.0236
Education: High School (HS)/Some college vs <HS −0.104 0.079 −1.32 0.1885 0.006 0.064 0.09 0.9316
Education: Graduate/Professional vs <HS −0.166 0.092 −1.81 0.0704 −0.045 0.075 −0.61 0.5438
Income >=25k vs < 25k −0.085 0.056 −1.51 0.1311 0.013 0.046 0.29 0.7700
Nutrition: Intermediate vs Poor 0.070 0.047 1.48 0.1397 −0.003 0.038 −0.07 0.9453
Nutrition: Ideal vs Poor 0.051 0.205 0.25 0.8020 −0.161 0.167 −0.97 0.3326
Physical Activity: Intermediate vs Poor −0.118 0.052 −2.28 0.0229 −0.041 0.042 −0.98 0.3272
Physical Activity: Ideal vs Poor −0.155 0.060 −2.58 0.0098 −0.086 0.049 −1.77 0.0768
Current smoker: yes vs no −0.080 0.076 −1.04 0.2968 0.063 0.062 1.01 0.3111
Alcohol Intake: yes vs no 0.050 0.047 1.05 0.2926 −0.019 0.038 −0.50 0.6160
Total Depressive Symptoms Score 0.005 0.003 1.69 0.0909 0.001 0.003 0.37 0.7125
Interaction: US-Society SSS*Male 0.046 0.023 2.01 0.0451 0.032 0.019 1.74 0.0829
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Table 4.

Coefficient for Subjective Social Status (US) by sex on Metabolic Syndrome Severity, n=1,724

Men Women
N SSS coefficient p-value N SSS coefficient p-value
MetS At Baseline 614 −0.001 0.9742 1110 −0.039 0.0046
MetS 8-Years Later 614 0.022 0.1548 1110 −0.012 0.2798
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Tables 5 and 6 indicate odds ratios of ATP-III MetS at baseline and at eight-year follow-up, including the same factors examined in the models of MetS severity (Tables 2 and 3), and including the interaction between the two SSS measures and sex. In Table 5 (which included community SSS), age (OR=1.027, p<0.0001) and depressive symptoms (OR=1.021, p=0.0047) were positively associated with ATP-III MetS score at baseline, but not at eight-year follow-up. Physical activity (ideal vs poor; b=0.668, p=0.0273) was positively associated with ATP-III MetS score at eight-year follow-up, but not at baseline. Table 6 displays odds ratios testing the association between US-society SSS, OSS, and ATP-III MetS score at baseline and at eight-year follow-up, including all demographic, psychosocial, and lifestyle factors. The significantly associated covariates with ATP-III MetS score in this analysis were the same as what was identified in the model with community SSS and thus, age (OR=1.029, p<0.0001) and depressive symptoms (OR=1.019, p=0.0103) at baseline, but not eight years later, as well as physical activity (ideal vs poor; OR=0.672, p=0.0319) at follow-up only.

Table 5.

Association between Community SSS, OSS, and ATP-III MetS at Baseline and 8-Years Later, Independent of Demographic, Psychosocial, and Lifestyle Factors, n=1,724

MetS At Baseline MetS 8-Years Later
Parameter OR 95% CI P OR 95% CI P
Baseline ATP-III MetS - - - 8.467 6.708 – 10.688 <.0001
Community SSS: at Sex = Male* 0.991 0.908 – 1.083 0.8486 0.971 0.884 – 1.067 0.5439
Community SSS: at Sex = Female* 1.030 0.966 – 1.099 0.3658 0.984 0.918 – 1.055 0.6579
Age 1.027 1.017 – 1.037 <.0001 1.008 0.997 – 1.019 0.1594
Education: High School (HS)/Some college vs <HS 0.796 0.563 – 1.125 0.4260 1.185 0.803 – 1.749 0.0610
Education: Graduate/Professional vs <HS 0.756 0.638 – 1.201 0.3108 0.855 0.544 – 1.346 0.1494
Income >=25k vs < 25k 0.882 0.715 – 1.066 0.3303 1.049 0.796 – 1.382 0.7343
Nutrition: Intermediate vs Poor 1.224 1.008 – 1.420 0.3518 1.056 0.837 – 1.334 0.0839
Nutrition: Ideal vs Poor 0.940 0.404 – 2.411 0.7306 0.391 0.125 – 1.226 0.0956
Physical Activity: Intermediate vs Poor 0.877 0.733 – 1.068 0.5462 0.821 0.637 – 1.058 0.9732
Physical Activity: Ideal vs Poor 0.879 0.628 – 0.988 0.6214 0.668 0.496 – 0.900 0.0273
Current smoker: yes vs no 0.947 0.701 – 1.217 0.7608 1.166 0.802 – 1.695 0.4202
Alcohol Intake: yes vs no 0.937 0.730 – 1.035 0.5562 1.018 0.806 – 1.285 0.8816
Total Depressive Symptoms Score 1.021 1.006 – 1.036 0.0047 0.997 0.982 - 1.013 0.7150
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*

Community SSS x Sex Interaction p-values: Baseline = 0.4829; 8-Years = 0.8161

Table 6.

Association between US-Society SSS, OSS, and ATP-III MetS at Baseline and 8-Years Later, Independent of Demographic, Psychosocial, and Lifestyle Factors, n= 1,724

MetS At Baseline MetS 8-Years Later
Parameter OR 95% CI P OR 95% CI P
Baseline ATP-III MetS - - - 8.400 6.653 – 10.605 <.0001
US-Society SSS: at Sex = Male* 1.014 0.928 – 1.107 0.7631 1.048 0.953 – 1.154 0.3333
US-Society SSS: at Sex = Female* 0.932 0.877 – 0.990 0.0217 0.933 0.873 – 0.998 0.0421
Age 1.029 1.019 – 1.039 <.0001 1.008 0.998 – 1.019 0.1338
Education: High School (HS)/Some college vs <HS 0.804 0.568 – 1.138 0.4202 1.194 0.808 – 1.764 0.0572
Education: Graduate/Professional vs <HS 0.783 0.521 – 1.177 0.3737 0.862 0.547 – 1.358 0.1565
Income >=25k vs < 25k 0.893 0.694 – 1.151 0.3829 1.045 0.793 – 1.377 0.7554
Nutrition: Intermediate vs Poor 1.235 0.997 – 1.529 0.3717 1.070 0.847 – 1.351 0.0866
Nutrition: Ideal vs Poor 0.976 0.384 – 2.478 0.7829 0.402 0.127 – 1.269 0.1053
Physical Activity: Intermediate vs Poor 0.874 0.691 – 1.105 0.5300 0.818 0.634 – 1.054 0.9825
Physical Activity: Ideal vs Poor 0.878 0.666– 1.156 0.6217 0.672 0.499 – 0.906 0.0319
Current smoker: yes vs no 0.964 0.679 – 1.367 0.8350 1.193 0.823 – 1.730 0.3511
Alcohol Intake: yes vs no 0.932 0.752 – 1.157 0.5248 1.013 0.802– 1.280 0.9114
Total Depressive Symptoms Score 1.019 1.004 – 1.034 0.0103 0.997 0.982 - 1.013 0.7209
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*

US-Society SSS x Sex Interaction p-values: Baseline = 0.1161; 8-Years = 0.0476

Linear regression analyses with each individual item of the MetS severity score as a dependent variable indicated that HDL-C and glucose levels (Supplemental Tables 4 and 5) were significantly associated with SSS. HDL-C at baseline was positively associated with US-society SSS (b=0.338, p=0.0356) and age (b=0.186, p<0.0001), independent of demographic, psychosocial, and lifestyle factors. Additionally, HDL-C was greater in females than males (b=−9.345, p<0.0001). Glucose levels at baseline were inversely associated with US-society SSS (b=−0.857, p=0.0038) and education (HS/some college vs <HS: b=−5.216, p=0.0127; graduate/professional vs <HS: b=−7.100, p=0.0035). Age (b=0.336, p<0.0001) and nutrition (intermediate vs poor: b=2.997, p=0.0168) were also significantly associated with increased glucose levels at baseline. Other measured components of MetS including WC, TG levels, and SBP were not significantly associated with SSS (Supplemental Tables 1-3).

4. Discussion

In this study, data from the JHS were used to assess independent associations of OSS and SSS with MetS severity and individual MetS indicators among AA adults at baseline and eight years later. To our knowledge, this is the first study to examine the influence of SSS on MetS severity in a large sample of AA adults. We present four important findings: (1) independent of OSS, demographic, psychosocial, and lifestyle factors, US-society SSS was associated with MetS severity at baseline in females, but not males, (2) there was a significant interaction between sex and US-society SSS, such that the sex-specific associations between SSS and baseline MetS severity were significantly different from each other, (3) components of MetS driving the relationship between US-society SSS and MetS severity at baseline were HDL-C and glucose levels, and community SSS was not associated with MetS severity at baseline or eight years later. Our data indicate that both OSS and SSS are independently associated with MetS severity among AA adults at baseline and that among women, US-society SSS is strongly predictive in that a 0.04 decrease in MetS severity Z-score occurs for every one-point incremental increase in US-society SSS after adjusting for OSS. These data adds to the growing body of evidence that perceived social rank can have significant implications on health. Along with assessing objective markers of OSS (e.g., income, education, insurance status, food insecurity, adverse childhood experiences), we also recommend including social status perceptions as an important social determinant of health. Assessment of SSS could lead to more precisely targeted and tailored approaches to policy and disease initiatives focused on those who report lower SSS.

Consistent with observations in this study as well as others (Shaked et al., 2016; Subramanyam et al., 2012a; Wolff et al., 2010), AA adults tend to report higher community SSS relative to their US-society SSS, with the average SSS in our study being 7.6 and 6.3 in relation to community and US-society, respectively. There were no differences in SSS by sex, but perceptions of social rank changed significantly with age, such that those who were older (ages 45-64 and 65+) saw themselves as higher ranking in both US-society and in their communities, when compared to younger counterparts (ages 20-44). One explanation for why community SSS was higher than US-society SSS is the community measure may allow for consideration of other constructs such as self-worth or self-esteem, rather than socioeconomic components alone (Wolff et al., 2010). This is important because AA tend to have higher self-esteem than whites (Wolff et al., 2010) and socioeconomic factors do not predict SSS scores for AA as well as they do for whites (Adler et al., 2008; Shaked et al., 2016). This may seem paradoxical given that AA are a marginalized population, but Shaked et al. (2016) concluded that AA adults possess higher self-esteem as a result of social identity theory, which highlights in-group versus out-group comparisons (Shaked et al., 2016). This is consistent with previous research our group has observed among low-income Hispanic Americans, also a marginalized group, who scored community SSS higher than US-society SSS (Cardel et al., 2018c). Among AA communities, a great deal of racial socialization messages and perceived social support exist, which are associated with increased resiliency (Brown, 2008). Thus, diet, physical activity, sleep, and other non-economic indicators of well-being may be salient for AA when assessing SSS (Goodin et al., 2010; Reitzel et al., 2013). However, given the observed relationship between US-society SSS and MetS severity, even after controlling for OSS factors of income and education, financial self-regard, as assessed by US-society SSS, may contribute unique explanatory power beyond traditional measures of income, while community SSS does not. US-society SSS may capture measures of wealth or perceived security not captured by income or education alone, such as lack of debt, savings accounts (or liquid assets), social capital, or financial support from relatives, all of which may ultimately affect health and, in particular, MetS. More research is needed to fully understand components determining how AA adults rank SSS and how these components might further vary by social, cultural, or environmental factors.

Individuals who placed themselves at lower US-society SSS had more severe MetS at baseline. Moreover, a significant interaction was observed between US-society SSS and sex, such that women with lower perceived social rank in US-society had worse MetS severity at baseline and for every one-point incremental increase in US-society SSS, there is a 0.04 decrease in MetS severity Z-score after adjusting for OSS markers among women. Sex differences in MetS severity outcomes among AA adults have been previously reported by our group (Cardel et al., 2018a; Gurka et al., 2016). Specifically, we observed that among women (but not men), depressive symptoms correlated with MetS severity (Gurka et al., 2016). We also previously reported that MetS severity risk increases at high stress levels for women, but at medium stress levels for men, suggesting differences in regulatory effects of sex hormones, fat deposition, stress responses, and coping styles between men and women (Cardel et al., 2018a). Taken together, this suggests sex differences in response to perceptions of low US-society SSS and related health outcomes are complicated and may reflect both biological and social factors, and the complex interplay between them (Cardel et al., 2018a).

To identify MetS factors driving the observed relationship between US-society SSS and MetS severity, we investigated the five individual components of MetS. HDL-C levels were positively associated and glucose levels were inversely associated with US-society SSS, independent of OSS, demographic, psychosocial, and lifestyle factors. Community SSS was not associated with MetS severity at baseline or eight years later, nor with baseline MetS components. These findings differ from those reported by Manuck and colleagues, which found an inverse relationship between community SSS and MetS among younger adults, even after adjustment for SES-related measures. Additionally, community SSS was associated with measures of MetS, including WC, TG, and HDL-C (Manuck et al., 2010). However, their sample was primarily comprised of white, middle-aged adults, and studies have consistently demonstrated differences in SSS and health parameters between AA and whites (Adler et al., 2008; Manuck et al., 2010; Shaked et al., 2016). We cannot compare our US-society SSS results with the Manuck findings because they did not measure US-society SSS, but given the relationships between US-society SSS with HDL-C and glucose persisted despite controlling for OSS, demographic, and lifestyle factors, it appears perceived standing in the US is independently associated with important MetS components.

Given that HDL-C below recommended guidelines and glucose levels above recommended guidelines is associated with excess calorie intake and sedentary behavior (Potenza and Mechanick, 2009), diet and physical activity may play a significant role in the relationship between SSS and unhealthy markers of MetS. In turn, the association between SSS, diet, and physical activity may be due to a number of factors, including differences in material conditions not otherwise captured by standard measures of socioeconomic status and better measured by SSS. A number of studies have examined a “curious conjecture”, that subordinate individuals with a threatened sense of energetic security (i.e., sense of security about one’s ability to acquire sufficient nutrition to sustain life) may be physiologically driven to consume excess calories and reduce expenditure to preserve energy stores in an attempt to buffer against true scarcity (Cardel et al., 2017; Dhurandhar, 2016; Kaiser et al., 2012; Lee and Cardel, 2018; Nettle et al., 2016). Experimental human models that manipulate acute social status lend some support to this idea by showing that being randomized to low social status is associated with excess calorie intake and dysregulation of satiety hormones (Bratanova et al., 2016; Cardel et al., 2016; Cheon and Hong, 2016). Thus, perceptions of low social status in society, as represented by US-society SSS, may engender behaviors encouraging the consumption of excess calories, either via modifying energy intake, physical activity, or both, and additional research is needed to examine the role of physical activity in energy balance as a response to low social status.

This study has many strengths, including the examination of associations of both OSS and SSS with MetS-related phenotypes at baseline and eight years later. We were also able to confirm that education status appears to eclipse race/ethnicity as a MetS determinant, consistent with work published by Scuteri and colleagues (Scuteri et al., 2008). Additionally, the data are from a well-characterized, large sample of AA and assess MetS severity in addition to changes in MetS longitudinally. There are limitations that warrant mention. The study was conducted in a single metropolitan area in Jackson, Mississippi, potentially limiting its generalizability to AA populations in other geographic regions. Further, we were not able to include an exhaustive set of variables with potential roles including individual clusters and inflammation (Scuteri et al., 2010; Scuteri et al., 2011; Scuteri et al., 2008). Missing data exists regarding depression scores for participants in the JHS and thus, this limits our sample size and does impact our power. Additional analyses using stress factors may also be necessary, though our group has previously published on the influence of psychosocial stressors on MetS severity (Cardel et al., 2018b). Alcohol intake was included as a covariate in all models, but included a bivariate variable assessing whether or not someone drinks alcohol. This does not provide insight into levels of alcohol consumed, which is a limitation given that moderate alcohol intake may benefit health, while excess intake is harmful to health. Finally, MetS severity is based on traditional MetS criteria and thus, may not be inclusive of all factors that influence it as well as other related disease states (Keita et al., 2014). MetS severity is used as a measure of cardiometabolic risk and is not the only way to measure cardiometabolic risk, so the outcomes of this analysis should be interpreted with caution.

5. Conclusions

In summary, female JHS participants who self-identified as having a low US-society SSS had more severe MetS at baseline independent of OSS, demographic, psychosocial, and lifestyle factors. Overall, MetS components driving this relationship were inverse associations between glucose levels with US-society SSS and positive associations between HDL-C levels with US-society SSS. Physical activity was independently associated with baseline MetS severity, but not eight years later. These data indicate independent associations between SSS and OSS with cardiometabolic risk factors and severity of MetS among AA adults. Implications of this research indicate that SSS and OSS may be of importance to cardiometabolic outcomes among AA adults, and support the use of both objective and subjective measures when exploring the role of social determinants of cardiometabolic health in clinical and interventional settings. Additional work is needed to characterize the mechanisms linking subjective and objective perceptions of social status to health outcomes in this population.

Supplementary Material

1

Highlights.

  • Lower perception of rank in US society showed greater MetS severity at baseline.

  • Social rank perception may be a stronger predictor of MetS severity in women relative to men.

  • Subjective social status is important to consider when exploring social determinants in health.

A

Funding: The Jackson Heart Study (JHS) is supported and conducted in collaboration with Jackson State University (HHSN268201800013I), Tougaloo College (HHSN268201800014I), the Mississippi State Department of Health (HHSN268201800015I) and the University of Mississippi Medical Center (HHSN268201800010I, HHSN268201800011I and HHSN268201800012I) contracts from the National Heart, Lung, and Blood Institute (NHLBI) and the National Institute for Minority Health and Health Disparities (NIMHD). The authors also wish to thank the staffs and participants of the JHS. 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 (UL1TR001427). Dr. Cardel is supported by the National Institutes of Health National Heart, Lung, and Blood Institute (R25HL126146 and K01HL141535). 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.

Footnotes

Declarations of interest: none

Conflicts of interest: none

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