Children's stress-related reports and stress biomarkers interact in their association with metabolic syndrome risk

Morning Serum Cortisol Is Uniquely Associated with Cardiometabolic Risk Independent of Body Composition in Latino Adolescents

Background: Alterations in morning serum cortisol (MSC) have been associated with higher cardiometabolic risk. This finding has been documented primarily in populations with overweight or obesity; however, it has not been clearly established if obesity plays a requisite role in this relationship. This study seeks to extend earlier findings by examining whether body composition measures alter the relationship between MSC with glucose and insulin markers, blood pressure, and lipid parameters in Latino youth in middle adolescence. Methods: This cross-sectional study included 196 healthy adolescents (130F/66M; mean age: 16.4 ± 0.6 years; 95% Latino; mean body mass index, BMI: 24.3 ± 5.7) from Los Angeles, California. Morning cortisol, glucose, insulin, glycated hemoglobin, and lipids (triglycerides and high-density lipoprotein cholesterol) were assessed from a fasting blood sample. Sitting systolic and diastolic blood pressure was averaged from duplicate measures. Body composition measures included BMI and waist circumference, which were used as proxies for total body and abdominal adiposity, respectively. Triplicate measurements of weight and height were averaged for calculation of BMI; age- and sex-specific BMI z-score was used to classify into normal BMI or overweight/obese BMI status. Waist circumference was measured in duplicate and the average was used to classify participants into two strata: normal/healthy waist circumference (<90th percentile for age, sex, and ethnicity) and high waist circumference (≥90th percentile). Results: The primary findings were that higher MSC was associated with higher fasting glucose and systolic blood pressure after adjusting for age, sex, and BMI z-score (and/or waist circumference). BMI status or waist circumference status did not alter these relationships. Main Conclusion: Our results suggest that the relationships between hypothalamic-pituitary-adrenal axis function and certain cardiometabolic risk factors may be independent of adiposity. Future research is warranted to discover the contributors and underlying mechanisms of these relationships in adolescent populations. ClinicalTrials.gov identifier: NCT02088294.

Association between Metabolic Syndrome Components and Cardiac Autonomic Modulation among Children and Adolescents: A Systematic Review and Meta-Analysis

Simple Summary

The clustering of metabolic syndrome (MetS) risk factors is becoming more prevalent in young people (up to the age of 19 years) leading to the development of type 2 diabetes (T2D) and cardiovascular diseases in early adulthood. The impact of MetS risk factors on cardiac autonomic modulation (CAM) or vice versa have been noted to track from childhood to pre-adolescence and adolescence. Understating associations in this age group may help improve the clinical outcomes of the MetS, even when MetS symptoms are not visible. Potential damage from each individual MetS component and the ability to predict early cardiac damage or upcoming cardiovascular events is very important. Therefore, the present systematic review and meta-analysis investigated the associations between CAM and MetS risk factors individually to verify which MetS risk components were significantly correlated with which heart rate variability (HRV) indices before or at the onset of the MetS among young people. The purpose of this review was to outline the importance of potentially screening HRV indices in young people even with only one MetS risk factor, as a pre-indicator for early cardiovascular risk stratification. Cross-sectional studies that examined the relationship of MetS risk factors with HRV indices were searched using four databases including PubMed, the Cochrane clinical trials library, Medline and the Web of Science. Correlation coefficients with 95% confidence intervals (95% CI), and random effects meta-analyses of the association between MetS risk factors with HRV indices were performed. Our results propose that lipid profiles including high density lipoprotein (HDL) and triglycerides (TGs), waist circumference (WC) and blood pressure (BP) are associated with CAM in young people up to the age of 19 years. The use of HRV indices to predict future MetS risk, and relationships with individual risk factors including HDL, BP, WC and TGs, were established. Furthermore, arterial pressure, respiration, stress and physical activity must be taken into consideration for future studies along with CAM related to young people (up to the age of 19 years), and it is recommended to explore further the associations reported here, as CAM is not the only determinant of neurovisceral regulation.

Abstract

Background: the clustering of metabolic syndrome (MetS) risk factors is becoming more prevalent in children, leading to the development of type 2 diabetes (T2D) and cardiovascular diseases in early adulthood. The impact of MetS risk factors on cardiac autonomic modulation (CAM) or vice versa has been noted to track from childhood to pre-adolescence and adolescence. Understating associations in this age group may help to improve the clinical outcomes of the MetS, even when MetS symptoms are not visible. Potential damage from each individual MetS component and the ability to predict early cardiac damage or upcoming cardiovascular events is very important. Therefore, the present systematic review and meta-analysis investigated the associations between CAM and MetS risk factors individually to verify which of the MetS risk components were significantly correlated with heart rate variability (HRV) indices before or at the onset of the MetS among young people. The purpose of this review was to outline the importance of potentially screening HRV indices in young people even with only one MetS risk factor, as a pre-indicator for early cardiovascular risk stratification. Methods: cross-sectional studies that examined the relationship of MetS risk factors with HRV indices were searched using four databases including PubMed, the Cochrane clinical trials library, Medline and the Web of Science. Correlation coefficients with 95% confidence intervals (95% CI), and random effects meta-analyses of the association between MetS risk factors with HRV indices were performed. Results: out of 14 cross-sectional studies and one case-control study, 8 studies (10 data sets) provided association data for the meta-analysis. Our results indicated significant positive correlations for systolic blood pressure (SBP) (correlation coefficient 0.13 (95%CI: 0.06; 0.19), I² = 47.26%) and diastolic blood pressure (DBP) (correlation coefficient 0.09 (95%CI: −0.01; 0.18), I² = 0%) with a Low Frequency/High Frequency ratio (LF/HF). Significant negative correlations for waist circumference (WC) (correlation coefficient −0.12 (95%CI: −0.19; −0.04), I² = 51.50%), Triglycerides (TGs) (correlation coefficient −0.09 (95%CI: −0.15; −0.02), I² = 0%) and ≥2 MetS risk factors (correlation coefficient −0.10 (95%CI: −0.16; −0.03), I² = 0%); with high frequency (HF) were revealed. Significant positive correlations for high density lipoprotein (HDL) (correlation coefficient 0.08 (95%CI: 0.05; 0.11), I² = 0%) and significant negative correlations of ≥2 MetS risk (correlation coefficient −0.04 (95%CI: −0.12; 0.03), I² = 0.0%) with low frequency (LF) were revealed. Significant negative correlations for TGs (correlation coefficient −0.09 (95%CI: −0.23; 0.05), I² = 2.01%) with a mean square root of the sum of differences between mean time between two successive intervals (rMSSD) and significant positive correlation of HDL (correlation coefficient 0.09 (95%CI: −0.01; 0.19), I² = 0.33%) with standard deviation of the time between two successive intervals (SDNN) were also revealed. An Egger’s test indicated that there was no obvious publication bias for any of the above relationships except for TGs and rMSSD. The significance level stipulated for the meta-analysis was p < 0.05. Conclusions: lipid profiles (HDL and TGs), WC and BP were associated with CAM in young people up to the age of 19 years. The use of HRV indices to predict future MetS risk, and relationships with individual risk factors including HDL, BP, WC and TGs, were established. Future studies related to young people (up to the age of 19 years) are recommended to explore the associations reported here further.

The role of lifestyle and non-modifiable risk factors in the development of metabolic disturbances from childhood to adolescence

Background

The study aimed to identify the effects of lifestyle, C-reactive protein (CRP) and non-modifiable risk factors on metabolic disturbances in the transition from childhood to adolescence.

Methods

In 3889 children of the IDEFICS/I.Family cohort, latent transition analysis was applied to estimate probabilities of metabolic disturbances based on waist circumference, blood pressure, blood glucose, and lipids assessed at baseline and at 2- and 6-year follow-ups. Multivariate mixed-effects models were used to assess the age-dependent associations of lifestyle, non-modifiable risk factors and CRP, with the transformed probabilities of showing abdominal obesity, hypertension, dyslipidemia, or several metabolic disturbances (reference: being metabolically healthy).

Results

Higher maternal body mass index, familial hypertension as well as higher CRP z-score increased the risk for all four metabolic outcomes while low/medium parental education increased the risk of abdominal obesity and of showing several metabolic disturbances. Out of the lifestyle factors, the number of media in the bedroom, membership in a sports club, and well-being were associated with some of the outcomes. For instance, having at least one media in the bedroom increased the risk for showing several metabolic disturbances where the odds ratio (OR) markedly increased with age (1.30 [95% confidence interval 1.18; 1.43] at age 8; 1.18 [1.14; 1.23] for interaction with age; i.e., resulting in an OR of 1.30 × 1.18 = 1.53 at age 9 and so forth). Further, entering puberty at an early age was strongly associated with the risk of abdominal obesity (2.43 [1.60; 3.69] at age 8; 0.75 [0.69; 0.81] for interaction with age) and the risk of showing several metabolic disturbances (2.46 [1.53; 3.96] at age 8; 0.71 [0.65; 0.77] for interaction with age).

Conclusions

Various factors influence the metabolic risk of children revealing the need for multifactorial interventions. Specifically, removing media from children’s bedroom as well as membership in a sports club seem to be promising targets for prevention.