Stress, Inflammation and Metabolic Biomarkers Are Associated with Body Composition Measures in Lean, Overweight, and Obese Children and Adolescents

Abstract

The aim of this study was to examine the associations between multiple indices of stress, inflammation and metabolism vs. body composition parameters in 121 (43 boys, 78 girls) children and adolescents, aged 5–15 y. Subjects were divided into two groups: normal weight (N) (N = 40, BMI z-score = −0.1923 ± 0.6), and overweight/obese (OB) (N = 81, BMI z-score = 2.1947 ± 1.4). All subjects completed the State-Trait Anxiety Inventory for Children (STAIC) and Children’s Depression Inventory, and underwent cortisol measurements in hair, diurnal series of saliva, and morning serum. Circulating concentrations of high sensitivity C-reactive protein (hsCRP) and other inflammation biomarkers were also obtained. Body composition analysis was performed with a clinically validated, advanced bioimpedance apparatus (BIA), while heart rate variability (HRV) was measured as a stress biomarker by photoplethysmography (PPG). The OB group had a higher STAIC-state score, waist-to-hip ratio, skeletal muscle mass, and total and abdominal fat mass, and a lower percent fat-free mass (FFM) and bone density than the N group. HRV did not differ between the groups. In the entire population, percent fat mass correlated strongly with circulating hsCRP (r = 0.397, p = 0.001), ferritin, and other inflammatory biomarkers, as well as with indices of insulin resistance. A strong correlation between serum hsCRP and hair cortisol was also observed (r = 0.777, p < 0.001), suggesting interrelation of chronic stress and inflammation. Thus, body fat accumulation in children and adolescents was associated with an elevation in clinical and laboratory biomarkers of stress, inflammation, and insulin resistance. BIA-ACC and PPG can be utilized as a direct screening tool for assessing overweight- and obesity -related health risks in children and adolescents.

The Association Between METS-IR and Serum Ferritin Level in United States Female: A Cross-Sectional Study Based on NHANES

“…In summary, on the basis of the same METS-IR, dyslipidemia may be a potential mechanism for lower BMI individuals to have higher levels of serum ferritin. In addition, previous studies have shown a significant positive association between fat percentage and serum ferritin levels ( 26 ), and the strength of the evidence for assessing fat percentage using BMI alone may remain limited, particularly as individuals with a higher proportion of visceral fat are more likely to develop insulin resistance, and the use of BMI in this assessment is even more limited ( 27 ). In conclusion, non-obese female participants should also be assessed regularly for changes in METS-IR, particularly if METS-IR exceeds 35.84, with caution.…”

Circulating FGF21 vs. Stress Markers in Girls during Childhood and Adolescence, and in Their Caregivers: Intriguing Inter-Relations between Overweight/Obesity, Emotions, Behavior, and the Cared-Caregiver Relationship

“…This correlation was not detected in the OB group, where hair and total diurnal salivary cortisol are normally elevated, implicating different factors in the activation of the HPA axis that has been observed in childhood and adolescent obesity [ 30 ]. Excessive body weight in children was associated with elevated hair and salivary cortisol in previous studies [ 31 ]. This association may be interfering with a possible association of FGF21 with cortisol.…”

The relationship between worker-occupation fit and cortisol concentration of hair and plasma among medical workers

“…The specimen was shaken for 2 minutes to ensure proper mixing of the extract. Once the extraction process was completed, the determination of BCC (blood cortisol concentration) and HCC (hair cortisol concentration) was carried out using an automated Electrochemiluminescence immunoassay (ECLIA) method [43].…”

“…The mean level of worker-occupation t (WOF, CF, NSF and DAF) of the 156 participants was 44. 43 45, 91.19] respectively. By comparing the levels of hair and plasma cortisol concentration in different demography and occupational characteristics, it was found that there were statistical differences in plasma cortisol concentrations between different sex (p < 0.05), while there were no statistical differences in hair and plasma cortisol levels between different ages, working years, education, events, occupational categories, job title, night shift, working years, working hours per week and monthly income (p > 0.05).…”