Physical Activity, Stress, and Metabolic Risk Score in 8- to 18-Year-Old Boys

Holmes, Megan E.; Eisenmann, Joey C.; Ekkekakis, Panteleimon; Gentile, Douglas A.

doi:10.1123/jpah.5.2.294

Cited by 28 publications

(19 citation statements)

References 56 publications

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“…34 Studies in children show conflicting results, 23 and are limited in number, sample size, and scope of parameters studied (e.g. to a single serum cortisol sample 18,22 or to questionnaire data alone 19,35 ). For example, school-related stressful events were positively associated with visceral and subcutaneous adipose tissue in peri-pubertal Latino girls with high CAR, and not in girls with low CAR, 20 but laboratory assessment for MetS was not performed.…”

Section: Discussionmentioning

confidence: 99%

Salivary Cortisol does not Correlate with Metabolic Syndrome Markers or Subjective Stress in Overweight Children

et al. 2018

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Objective Being overweight is a risk factor for metabolic syndrome in children, but not all overweight children develop metabolic syndrome. Cortisol excess from chronic psychological stress has been proposed as an independent risk factor for metabolic syndrome in this already at-risk population. The present study assesses the relationship of biochemical and body composition radiographic markers of metabolic syndrome to salivary cortisol and self-report of chronic psychological stress in a cohort of overweight children. Methods This cross-sectional study took place in a multi-disciplinary pediatric obesity clinic at a tertiary care hospital, and involved fifteen children with BMI at or above the 85th percentile for age and sex, 10 of whom provided salivary cortisol samples. The main outcomes measured were salivary bedtime cortisol, first-waking cortisol, and cortisol awakening response (CAR–the rise in cortisol in the first half hour after waking); fasting serum triglycerides, HDL cholesterol, glucose and insulin for HOMA-IR; the ratio of abdominal fat to total body fat by DXA scan; and scores of validated stress and bullying questionnaires (PANAS-C, PSS, and SEC-Q). Results In this pilot study, no correlation was found between salivary cortisol measures and questionnaire scores of subjective stress or bullying, and no correlation was found between any of these measures and markers of metabolic syndrome (dyslipidemia, insulin resistance, increased abdominal fat). Conclusions These results suggest that measures of psychological stress, whether biochemical or subjective, do not appear to predict risk of metabolic syndrome in overweight children. While ease of collection and demonstrated utility both in detection of pediatric Cushing disease and in adult psychological research make salivary cortisol assessment an attractive clinical tool, further investigation into the value of salivary measures in pediatric stress research is needed.

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Section: Discussionmentioning

confidence: 99%

Salivary Cortisol does not Correlate with Metabolic Syndrome Markers or Subjective Stress in Overweight Children

et al. 2018

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“…19 Holmes et al developed a MetS risk zscore based on blood pressure, HDL-C, hemoglobin A1c, and waist circumference in 37 boys. 42 PA was estimated from 4-days of accelerometry. The correlations between total, moderate, vigorous PA and the MetS score were low (r~-0.09 to -0.13), but in a favorable direction.…”

Section: Habitual Physical Activitymentioning

confidence: 99%

The Influence of Exercise on Metabolic Syndrome in Youth: A Review

McMurray

Andersen

2009

American Journal of Lifestyle Medicine

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This file was dowloaded from the institutional repository Brage NIH -brage.bibsys.no/nih McMurray, R. G., Andersen, L. B. (2010). The influence of exercise on metabolic syndrome in youth : a review. American Journal of Lifestyle Medicine, 4(2), 176-186.Dette er siste tekst-versjon av artikkelen, og den kan inneholde ubetydelige forskjeller fra forlagets pdf-versjon. Forlagets pdf-versjon finner du på sagepub.com: http://dx.doi.org/10.1177/1559827609351234This is the final text version of the article, and it may contain insignificant differences from the journal's pdf version. used growth curve modeling to develop age and sex-specific criteria for MetS in youth based on the accepted criteria for adults. This approach is logical because the risk factors have a propensity to track from childhood through adulthood and the adult risk factor cut-points are clearly associated with the development of cardiovascular disease. 13 The most biologically meaningful approach may be to select the children where risk factors were not independently distributed, as done by Andersen et al. in 2003. 14 Another approach used in publication from the European Youth Heart Study (EYHS) is to develop an age and sex-specific metabolic risk score based on z-scores for each of the MetS characteristics. 15--17 The authors argue that since there is no accepted definition of MetS in children, the z-score provide a continuous score which may be more appropriate for investigating associations. Dichotomization of each variable causes reduction in the information and therefore the diagnostic value. One system used a standardized score developed as a sum each of seven criteria (insulin, glucose, triglyceride, HDL-cholesterol, skinfolds, diastolic and systolic blood pressure). The standardized score used the subjects value minus sample mean, divided by standard deviation to produce a continuous overall MetS risk score. 17 The lower the standard score the more favorable the overall profile. However, this score has the problem because it lacks a cut-point above which to identify MetS. An identifying cut-point was found through another analysis where upper quartile in each risk factor was defined to be at risk, and the number of risk factors was then summed in each child. By using this approach the authors were able to calculate when risk factors were not independently distributed. An independent distribution of the risk factors would follow a binominal distribution, and the authors calculated for each number of risk factors if there were more children than expected from the binominal distribution. This approach selected between 10-15% of the children to have clustered risk, and the cut point in the continuous z-score could now be defined. 19 Since this approach was studyspecific comparisons with other studies could be difficult. However, data were available from three different countries, and it turned out that almost the same z-score defined clustered risk in the different populations, which may indicate that cut points may not be population ...

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“…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.…”

Section: Introductionmentioning

confidence: 97%

Positive Attributes Protect Adolescents From Risk for the Metabolic Syndrome

Midei¹,

Matthews²

2014

Journal of Adolescent Health

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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.

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Physical Activity, Stress, and Metabolic Risk Score in 8- to 18-Year-Old Boys

Cited by 28 publications

References 56 publications

Salivary Cortisol does not Correlate with Metabolic Syndrome Markers or Subjective Stress in Overweight Children

Salivary Cortisol does not Correlate with Metabolic Syndrome Markers or Subjective Stress in Overweight Children

The Influence of Exercise on Metabolic Syndrome in Youth: A Review

Positive Attributes Protect Adolescents From Risk for the Metabolic Syndrome

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