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. Author manuscript; available in PMC: 2015 Nov 1.
Published in final edited form as: J Adolesc Health. 2014 Jul 22;55(5):678–683. doi: 10.1016/j.jadohealth.2014.05.018

Positive Attributes Protect Adolescents from Risk for the Metabolic Syndrome

Aimee J Midei 1, Karen A Matthews 1
PMCID: PMC4209330  NIHMSID: NIHMS606481  PMID: 25060290

Abstract

Purpose

Risk for cardiovascular disease develops as early as adolescence. The primary objective of the present study is to identify whether low levels of positive and high levels of negative emotions and attitudes are associated with the combination of cardiovascular risk factors known as the metabolic syndrome.

Methods

Participants were 239 healthy adolescents (57% black, 53% female, mean age = 15.7) from a low to middle class community. They completed measures of negative and positive emotions and attitudes, which were factor-analyzed and yielded two factors. Positive Attributes included general positive affect, optimistic attitudes, subjective social status, and self-esteem. Negative Emotions included cynical attitudes, depressive symptoms, trait anger, and general negative affect. Components of the metabolic syndrome (waist circumference, glucose, blood pressure, triglycerides, and high-density lipoprotein cholesterol) were standardized and averaged to create a metabolic syndrome composite risk score.

Results

Linear regression analyses showed that the Positive Attributes factor was inversely associated with metabolic syndrome composite risk score, p < .01. The relationship remained significant after adjusting for age, sex, race, socioeconomic status, physical activity, smoking, and body mass index percentile. The Negative Emotion factor was unrelated to metabolic risk score.

Conclusion

Adolescents with more positive attributes had lower metabolic syndrome risk scores. This study emphasizes the importance of the development of psychosocial resources during the adolescent transition for potentially reducing future cardiovascular risk.

Keywords: adolescents, metabolic syndrome, negative emotions, protective factors

Introduction

Risk factors for cardiometabolic diseases are not uncommon in adolescence and predict subclinical cardiovascular disease in adulthood. In the National Health Administration Examination Survey (NHANES) study, for example, 6% of female adolescents and 20% of male adolescents had high fasting blood glucose (≥ 100 mg/dl). 1 Combining blood pressure (BP) data from 11 studies and a total of 58,698 children and adolescents, up to 9.8% of children and adolescents had systolic hypertension, and up to 7.1% had diastolic hypertension.2 BP at age 13 predicted adulthood BP at age 24, in addition to elevated lipids and glucose.3 Autopsy studies of young adults who died from traumas reported a linear relationship between number of cardiometabolic risk factors and intima surface covered with fatty streaks in the aorta: 0, 1, 2, and 3/4 risk factors had, respectively, 19.1%, 30.3%, 37.9%, and 35.0% of the intimal surface covered.4 Similarly, greater the number of risk factors (cigarette smoking, elevated lipids, BP, and body mass index) in adolescence was linked with greater carotid intima medial thickness in both men and women in adulthood.5 A cluster of risk factors in adolescents was associated with reduced carotid artery elasticity and increased stiffness.6;7 The metabolic syndrome, a combination of elevated BP, triglycerides, waist circumference, glucose, and low high density lipoprotein levels (HDL-C), in childhood and adolescence predicted cardiovascular disease in adulthood.8

Few investigations have examined the psychosocial correlates of clustering of cardiovascular risk factors in adolescents, in contrast to the burgeoning literature in adulthood on the metabolic syndrome.9 One study of 37 boys found that trait anxiety, but not perceived stress or depressive symptoms, was related to higher metabolic risk scores, defined as standardizing and summing waist circumference, mean arterial blood pressure, hemoglobin A1c, and HDL-C.10 This study is limited because of its small sample size of boys only (no race reported) and simple correlation analyses. Räikkönen et al.11 reported that high hostility predicted participants who were classified with the metabolic syndrome three years later, compared to individuals who did not have the metabolic syndrome at either visit. Metabolic syndrome was defined as having two or more cardiometabolic risk factors above the 75th percentile distributions based on age, sex, and race. The sample was comprised of 134 children and adolescents and the psychosocial variables were limited to components of hostility. Another study of 122 adolescent females at risk for depression found that more negative social interactions throughout the day predicted increasing metabolic risk across 2 years, although they were unrelated to baseline metabolic risk. Metabolic risk was defined by standardizing and averaging the risk factors that constitute the metabolic syndrome.12 The Dunedin Study reported that children who were socially isolated and rejected were at elevated cardiovascular risk as young adults, defined as having at least three of six cardiovascular risk factors (overweight, low HDL-C, high BP, high cholesterol, high glycosolated hemoglobin, low maximum oxygen consumption).13 In the Cardiovascular Risk in Young Finns Study, depressive symptoms at age 12 predicted the metabolic syndrome defined by standard National Cholesterol Education Program guidelines among women, but not men, 20 years later.14 In the aggregate, these studies suggest that negative psychosocial characteristics in youth are associated with a clustering of cardiovascular risk factors, but the studies did not test the same negative characteristics so there was no opportunity for replication. Furthermore, metabolic risk was defined in various ways across studies.

It has become increasingly clear that positive emotions and attitudes can have a strong protective influence on cardiovascular risk in adults, and these effects can be independent of negative emotions and attributes.15;16 With regard to the influence of positive emotions and attributes on cardiometabolic risk factors in youth, we know of only three relevant studies. In the Holmes et al.10 study, higher school-related and sport-related self-esteem among boys was related to lower metabolic risk. In the social interaction study of adolescent females at risk for depression, more positive social interactions throughout the day were not associated with metabolic risk.12 In the Princeton School Study of black and white teenagers, optimistic attitudes were associated with high levels of HDL-C and low levels of insulin and triglycerides (blacks only).17 This paper did not report the association with the metabolic syndrome or with the total number of elevated risk factors. In sum, high self-esteem and optimism were related to low metabolic risk. However, similar to the studies regarding negative psychosocial characteristics, there was no opportunity for replication as each study measured different positive characteristics.

Adolescence is a unique developmental period not only from the perspective of cardiovascular risk but also because of the psychological and social challenges it presents. Developing a sense of competency, autonomy, and relatedness to others during adolescence is critical to a life of growth, integrity, and wellbeing.18;19 Adolescents must meet the demands of school and work, fostering a sense of competency; they must develop their own sense of values and unique identity to have a sense of autonomy; and they must form satisfying and enduring relationships within and outside of the family in an effort to relate to others. To the extent that adolescents feel positive about themselves, believe they are worthwhile, and are optimistic about their future and generally happy, they may be protected from adverse changes in cardiovascular risk that co-occur with the profound changes associated with maturation.

The aims of the present study are to test whether healthy black and white adolescents who have elevated metabolic syndrome risk profiles have higher negative and lower positive emotions and attitudes. The current study adds to the small adolescent literature in a number of key ways. First, it developed indices of negative and positive characteristics based on factor analysis rather than examining individual characteristics, thereby reducing Type I error. The characteristics were selected based on the large literature on the metabolic syndrome in adults. Given the sparse literature on metabolic risk in adolescents, additional characteristics were selected based on theories of successful adolescent development. Finally, the study evaluated whether the relationships were stronger in blacks or whites and males or females.

Method

Participants

Participants were 250 (47% male and 43% white) healthy students enrolled in a public high school near Pittsburgh, PA. This high school served about 500 students (42% black, 56% white, and 2% other) and 63% were eligible for free or reduced lunch, compared to 26% statewide. In the three years of the study, the high school graduated 83%; district performance was ranked as 111 out of 123 high schools in western Pennsylvania. This school was selected because it was racially integrated and served a lower to middle SES community, maximizing the potential for SES to be similar for black and white students. Participants were recruited from health classes for a research study designed to measure stress and risk factors for cardiovascular disease. The University of Pittsburgh Institutional Review Board approved the research protocol. Participants provided written informed consent prior to any research procedures and a parent or guardian provided consent for students under the age of 18. Parents reported whether their children met inclusion criteria: free of cardiovascular or kidney disease, and no medications for emotional problems, diabetes, high blood pressure, or those that affect the cardiovascular system or normal sleep. Sixteen students who were screened were ineligible to participate due to taking medications, and seven students signed consent but did not actively enroll in the study.

Overview of Procedure

Protocol was conducted at the high school and lasted for about one week. Staff measured height, weight, waist and hip circumference. Two resting blood pressures were taken while the participant was seated and had rested for five minutes. On a separate day, participants had a venous blood draw in a recumbent position after an eight-hour fast. They completed a battery of psychosocial questionnaires accessed from a study website. After completion of all parts of the protocol, which also included a week of actigraphy and diary to assess sleep patterns and ambulatory blood pressure for 48 hours, participants were paid $100. A follow-up report of the student’s blood pressure, sleep, anthropometric, and lipid levels was sent to the student and the student’s parent/guardian.

Standardized Questionnaire Assessments of Negative and Positive Characteristics

Questionnaires were selected based on the available literature on metabolic syndrome and theories of successful adolescent development. We selected seven measures: depressive symptoms, usual angry feelings, hostile attitudes toward others, global positive and negative affect, self-esteem, optimism, and subjective social status relative to peers.

Depressive symptoms were assessed using the 20-item Center for Epidemiological Studies Depression scale (CES-D).20 Participants rate the frequency of experiencing each symptom in the past week, ranging from 1 (less than one day) to 4 (five to seven days). A sample item was “I was bothered by things that usually don’t bother me.” Higher scores indicated greater depressive symptoms. Cronbach’s alpha coefficient for the CES-D in this sample was 0.85.

Anger was measured using the Spielberger Trait Anger Scale,21 which consists of 10 items related to the frequency with which the emotion of anger is generally experienced in relation to situations and interactions with others. Participants characterized how they generally felt, ranging from a 1 (almost never) to 4 (almost always). Sample items were, “I have a fiery temper” and “When I get frustrated, I feel like hitting someone.” Higher scores indicate greater trait anger. Cronbach’s alpha for trait anger in this sample was 0.87.

Cynicism was assessed by 12 items from the Cook-Medley Hostility Scale.22 Participants designated if they believed a statement to be true or false about the ways people behave. Sample items include, “It is safer to trust nobody” and “I think most people would lie to get ahead.” Higher scores indicate greater cynicism and the Cronbach’s alpha in this sample was 0.55.

The Positive and Negative Affect Schedule (PANAS)23 consisted of 10 items each measuring global positive and negative dispositional affect. Participants were asked to indicate how much they feel each affect in general ranging from 1 (not at all) to 5 (extremely). Cronbach’s alpha for negative affect was 0.85 and for positive affect was 0.82.

Self-esteem was measured with 10 items from the Rosenberg Self-Esteem Scale.24 Students characterized their agreement with statements regarding perceptions of self-worth using a scale ranging from 1 (strongly disagree) to 4 (strongly agree). A sample item is, “I feel that I am a person of worth, at least on an equal basis with others.” Higher scores are indicative of higher self-esteem. Cronbach’s alpha in the present sample was 0.84.

Optimism was measured using the 6-item Life Orientation Test-Revised (LOT-R).25 Participants characterized their agreement with each item using a scale ranging from 0 (strongly disagree) to 4 (strongly agree), with 2 being a neutral response. A sample optimism item is, “In uncertain times, I usually expect the best.” The LOT-R overall score ranges from 0–24 and higher scores indicate greater pessimism. The LOT-R showed moderate reliability; the Cronbach’s alpha coefficient was 0.60.

Subjective social status relative to peers was measured using the MacArthur Scale of Subjective Social Standing (modified for adolescents) that was developed as a measure of people’s perceptions of their placement in the social hierarchy.26 Using a picture of a ladder with 9 rungs, adolescents indicated where they rank relative to other students in the school based on popularity, grades, respect, etc. The youth version of the MacArthur Scale is appropriate for those grades 7 and above or children aged 12 and older. The ladder measure has been correlated with other biological measures in adolescent samples.27;28

Principal components analysis with orthogonal varimax rotation was conducted on the scale scores from the above questionnaires. The Kaiser-Meyer-Olkin measure verified the sampling adequacy for the analysis, KMO = 0.72. Barlett’s test of sphericity, χ2 (28) = 499.45, p < .01, indicated that correlations between measures were sufficiently large. Two components had eigenvalues over Kaiser’s criterion of 1 and in combination explained 55.5% of the variance. Four measures (CES-D, PANAS Negative Affect, Spielberger Trait Anger, and Cook-Medley Cynicism) loaded > .55 on the first factor labeled Negative Emotions, and four measures [PANAS Positive Affect, Rosenburg Self-Esteem, Optimism (reversed LOT-R), and the Subjective Social Standing ladder] loaded > .61 on the second factor, labeled Positive Attributes. Each score was standardized and averaged to form composite scores. Finally, the composite scores were re-standardized based on the full sample distribution to facilitate interpretation of the results.

Metabolic Syndrome Risk Factors

Fasting blood samples were obtained and serum was separated by refrigerated centrifuge. Serum was then aliquoted and stored at −70°C until assay at the Heinz Lipid Laboratory at the University of Pittsburgh. Each run included duplicate samples, standardization, and control sera. Triglycerides were determined using enzymatic methods and the lab coefficient of variation between runs was 1.7%. HDL-C was determined after selective precipitation by heparin/manganese chloride and removal by centrifugation of very low density and low density lipoprotein. The lab coefficient of variation between runs was 2.1%. Glucose was assessed using enzymatic-coupled reactions and the lab coefficient of variation between runs was 1.8%. Waist circumference was taken at the point of natural bend of the waist under clothing and after two forced exhalations. Resting systolic and diastolic BP was measured using an automated monitor (Spacelabs Healthcare Model #90217 Ultralite) following a five-minute rest period. Appropriately sized cuffs were selected by measuring the circumference of the non-dominant arm at its largest point. Two BP measurements were taken at 1-minute intervals, and the mean of the two values were used for the data analysis. Mean arterial pressure (MAP) was calculated with the following formula: (SBP-DBP/3) + DBP.

Previous research has suggested that the metabolic syndrome can be calculated as a continuous score representing a composite risk factor index in samples of healthy children and adolescents.29 We computed a composite risk factor index on components that align with adult criteria: waist circumference, HDL-C, triglycerides, fasting blood glucose, and MAP. MAP was used so that only one blood pressure variable (rather than two variables) would load into the calculation. Scores on each component were converted to z-scores. HDL-C was multiplied by −1 because it is inversely related to metabolic risk. Waist circumference and HDL-C were standardized within gender (because of adult criteria). Composite risk for metabolic syndrome was then calculated by averaging the z-scores across the five components. Finally, the metabolic syndrome risk factor index was re-standardized based on the distribution of scores in the full sample to facilitate interpretation of the results. Higher scores indicate worse metabolic syndrome risk.

Covariates

Age (range = 14–19), sex (0 = male, 1 = female), and race (0 = white, 1 = black) were determined by self-report. Socioeconomic status (SES) was measured by using the highest years of education attained by either parent, which was reported during an interview with the parent/caregiver. Physical activity was measured with the item, “How many days in the past seven days were you physically active for a total of at least 60 minutes?” Smoking was measured with the item, “During the past 30 days, how many cigarettes have you smoked?” Body mass index (BMI) was used as a measure of overall obesity and was calculated as weight (kg)/height (m2). Weight was measured without shoes, and in light indoor clothing, using a Tanita digital scale to the 1/10 of a pound. Height was measured without shoes using a stadiometer. We used the age- and sex-specific BMI growth charts from the Center of Disease Control and Prevention30 to categorize participants into BMI percentiles. Age, sex, race, SES, physical activity, smoking, and BMI percentile (continuous) were included as covariates in adjusted models.

Statistical Analysis

Data was checked for normality. The total analytic sample numbered 239 because two individuals had extremely high BMI (> 4 SDs), one had extremely high triglycerides (> 4 SDs), two were missing blood draw, four were missing questionnaire data, one subject was pregnant, and one individual was missing blood pressure data. Three subjects’ parents did not report on socioeconomic status; thus, the sample numbered 236 in models with covariates. Independent samples t-tests and Pearson chi-square tests of independence were used to examine race differences on metabolic syndrome risk factors and covariates. Univariate linear regressions were conducted to assess the relationship between psychosocial factor scores, taken separately, and the metabolic syndrome composite risk factor index. Multivariate linear regressions followed with age, sex, race, SES, physical activity, smoking, and BMI percentile as covariates. A third multivariate linear regression analysis included both psychosocial factors (Positive Attributes and Negative Emotions) and covariates in the same model. To examine if associations differed by race or sex, we created interaction terms between psychosocial variables and race or sex as predictors of metabolic syndrome composite score and adjusted for covariates. Exploratory analyses were conducted to examine whether specific measures (z-scored) within the factor variables accounted for significant relationships.

Results

Participant Characteristics

Table 1 shows sample characteristics for the full sample and separated by race. The sample was about half female and half black. White adolescents had unhealthier values for triglycerides and HDL-C. Whites also smoked more cigarettes and had lower SES, as measured by parental education, compared to black adolescents.

Table 1.

Sample characteristics

Full Sample Blacks Whites
N 239 135 104
Mean age 15.7 15.8 15.6
% Female 53 52 55
% Parents ≤ high school education a 59 52 68
Mean (SD) days of exercise in last 7 days 3.5 (2.3) 3.8 (2.4) 3.2 (2.1)
% Smoked cigarettes in the last 30 days b 26 25 49
% Overweight or obese (BMI ≥ 85th percentile) 57 60 54
Mean (SD) WC, centimeters 79.5 (14.0) 79.1 (13.5) 80.0 (14.6)
Mean (SD) HDL-C, mg/dl c 51.6 (11.6) 53.4 (11.6) 49.3 (11.3)
Mean (SD) Triglycerides, mg/dl d 77.6 (39.5) 65.7 (27.8) 93.0 (46.7)
Mean (SD) Glucose, mg/dl 87.7 (8.8) 87.8 (8.2) 87.5 (9.6)
Mean (SD) SBP, mmHg 125.4 (11.7) 125.6 (11.4) 125.2 (12.3)
Mean (SD) DBP, mmHg 73.5 (8.6) 73.7 (8.4) 73.1 (8.9)
Mean (SD) MAP, mmHg 90.1 (8.2) 90.3 (7.9) 89.9 (8.6)
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Notes: SD = standard deviation, N = number of subjects, SBP = systolic blood pressure, DBP = diastolic blood pressure, MAP = mean arterial pressure

a

Whites were more likely to have parents with a high school education or less [χ2 (2, N = 236) = 6.75, p < .01].

b

Whites were more likely to smoke in the past 30 days compared to blacks [χ2 (1, N = 239) = 4.98, p < .05].t (237) = 2.86, p < .01].

c

Whites had lower HDL-C (i.e., less healthy) compared to blacks [t (237) = -2.75, p < .01].

d

Whites had higher triglycerides compared to blacks [t (237) = 5.64, p < .01].

Metabolic Syndrome Risk and Psychosocial Factors

Linear regressions showed that Positive Attributes was significantly and inversely associated with metabolic syndrome composite scores (B = −0.23, SE = .06, p < .001) and remained significant when controlling for age, sex, race, SES, physical activity, smoking, and BMI percentile (B = −0.17, SE = .06, p < .01). The univariate model found that Positive Attributes explained 5.1% of the variance in metabolic syndrome risk profiles, and the fully adjusted model accounted for 26.1% of the variance in metabolic risk profiles.

Negative Emotion index was not related to metabolic syndrome composite scores in univariate analyses (B = −.004, SE = .07, p = .96) or adjusted models (B = −0.03, SE = .06, p = .65). When both Positive Attributes and Negative Emotions were included in the same model with covariates, Positive Attributes continued to be significantly associated with lower metabolic syndrome composite risk scores (see Table 2). Significant covariates of elevated metabolic syndrome scores were being male, white, low parental education, and high BMI percentile.

Table 2.

Results from the linear regression model with psychosocial factors predicting the metabolic syndrome composite score, with covariates

Independent Variables Metabolic Syndrome Composite Score (Z-scored)
B, SE p value
Positive Attributes (Z-scored) −0.18 (.06) < .01
Negative Emotions (Z-scored) −0.08 (.06) .23
Age, years 0.01 (.05) .85
Sex (0 = male, 1 = female) −0.39 (.12) < .01
Race (0 = white, 1 = black) −0.34 (.12) < .01
SES, highest years of education for either parent −0.07 (.04) < .05
Physical activity, # of physically active days in past week −0.04 (.03) .19
Smoked cigarettes in the last 30 days (Y/N) 0.01 (.03) .81
BMI percentile 0.02 (.003) < .001
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Note: SE = standard error, SES = socioeconomic status

We examined interactions terms in linear regressions to test for differences by race or sex. The relationship between Positive Attributes and metabolic syndrome composite risk scores did not vary by race or sex (ps ≥ .56). Similarly, there were no significant interactions between Negative Emotions and race or sex (ps ≥ .17).

Of the Positive Attributes, all four measures were significant and inversely associated with the metabolic syndrome composite risk score in univariate linear regression models, including positive affect (B = −0.17, SE = .06, p < .01), self-esteem (B = −0.13, SE = .06, p < .05), optimism (B = −0.14, SE = .06, p = .03), and subjective social standing (B = −0.18, SE = .06, p < .01). In fully adjusted models, positive affect (p = .02) and subjective social standing (p = .02) remained significant predictors of metabolic syndrome risk.

Discussion

The present study aimed to test whether those with higher levels of negative emotions and lower levels of positive attributes had elevated metabolic syndrome risk profiles in a sample of black and white adolescents. In contrast with previous adolescent literature finding a link between negative emotions (trait anxiety and hostility) and metabolic syndrome risk,10;11 the present study did not show an association. Such an association is not always obtained as previous reports did not find a relationship with depressive symptoms or perceived stress (cross-sectionally).10;12 Lower SES is consistently associated with higher levels of negative emotions in adults.31 Our sample is unique in that the adolescents were from a low to middle class community. Perhaps the influence of negative emotions is masked by the influence of lower and restricted range of SES in this sample. Given the small literature in adolescents and the larger literature in adults showing negative emotions, especially depression, being related to risk for metabolic syndrome, it is important to conduct further investigations of negative emotions in adolescent samples.

In contrast to the results for negative emotions, our results did show that positive attributes were inversely related to metabolic syndrome composite risk scores. Adolescents with more positive attributes had lower metabolic syndrome risk profiles. Neither statistical adjustments for health behaviors, BMI percentile, and parental education nor adjustments for negative emotions altered the results. The effects were similar in males and females and blacks and whites. Recall that the distributions for waist circumference and HDL-C were standardized within girls and boys separately.

Our findings dovetail with theoretical perspectives about successful adolescent development.18 To effectively traverse the adolescent transition, it is important to develop a sense of competency and feelings of self-worth, to have positive expectations about the future and be generally happy. From our theoretical perspective, these characteristics form the basis of a set of resources, which we label reserve capacity, to deal with the inevitable life stressors and challenges that occur during the adolescent period.31 Stressors and challenges are particularly likely in lower SES communities and families, like those in our study. Thus, positive attributes may be important in facilitating adolescents making better health behavior choices and diminishing sympathetic-nervous-system and hypothalamic-pituitary-adrenocortical responses to daily stressors and challenges, thereby delaying early indicators of cardiovascular disease progression.

It is instructive to place our sociodemographic findings in the context of the NHANES 2001 – 2006 data.32 Using clinical cutoffs for components of the metabolic syndrome, a greater proportion of white adolescents in NHANES had the metabolic syndrome and specifically the components of low HDL-C and high triglycerides, compared to black adolescents. Similarly, in our sample, white adolescents had higher overall metabolic syndrome scores and specifically the components of lower HDL-C and higher triglyceride levels than blacks. In NHANES samples and in the present study, there were no differences for BP.

Strengths of the current study are that we included an extensive assessment of psychological health in adolescence, measured with validated questionnaires. Additionally, we used a continuous and composite score of metabolic syndrome risk, which may be more appropriate for samples of children and adolescents.29 The study sample was also diverse in composition. A limitation of the present study is the inability to test directionality of the relationships because of the cross-sectional design. It is possible that a third common factor, such as a common underlying genetic or epigenetic component, may be driving both levels of positive attributes and metabolic syndrome risk. A future investigation, with several periods of measurement, could examine the stability of psychosocial attributes and metabolic syndrome risk, as well as how changes in each co-vary.

One important implication of our findings is improving the understanding of the pathogenesis of cardiovascular disease. Just as research shows a link between psychosocial variables and the metabolic syndrome in adulthood,9 this relationship appears to be relevant even in the adolescent years. Adolescents may benefit from an intervention that enhances positive attributes and skills, as opposed to focusing solely on reducing negative emotional characteristics. Intervention during adolescence may be a critical period in which to alter the negative health trajectory facing adolescents with high cardiovascular risk.

Implications and contribution.

Similar to studies demonstrating a link between psychosocial variables and the metabolic syndrome in adulthood, this relationship appears to be present even during adolescence. Positive attributes, particularly positive affect and high social status relative to peers, are associated with lower metabolic syndrome risk.

Acknowledgments

Funding source: This work was supported by National Institutes of Health HL025767. Portions of the data were presented at the American Psychosomatic Society Annual Meetings, 2011, 2013.

Footnotes

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