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Author Spotlight: Assessing the Cardiovascular Profile of Patients with Metabolic Syndrome
Published on: September 27, 2024
Cardiovascular risk biomarkers and metabolically unhealthy status in prepubertal children: Comparison of definitions
A I Rupérez1, J Olza2, M Gil-Campos3
1Growth, Exercise, NUtrition and Development (GENUD) Research Group, University of Zaragoza, Food and Agriculture Institute of Aragón (IA2), Health Research Institute of Aragón (ISS Aragón), Zaragoza, Spain.
Insights
Metabolically unhealthy status in children is linked to obesity and cardiovascular disease risks. Definitions using age, sex, and insulin resistance criteria best identify these risks in prepubertal children.
Area of Science:
- Pediatric Endocrinology
- Cardiovascular Disease Research
- Metabolic Health
Background:
- Metabolically unhealthy (MU) status in early life is associated with obesity, cardiovascular disease (CVD), and long-term morbidity/mortality.
- A lack of consensus exists for classifying MU status in prepubertal children, necessitating comparative analysis of existing definitions.
Purpose of the Study:
- To compare the effectiveness of various MU definitions in identifying CVD risk biomarkers in prepubertal children.
- To determine which MU classification criteria are most strongly associated with established CVD risk factors.
Main Methods:
- Recruited 930 prepubertal children (ages 5-10.9 years), including 622 with overweight/obesity.
- Classified children using eight MU definitions based on blood pressure, lipids, glucose, and HOMA-IR.
- Analyzed plasma biomarkers including resistin, leptin, myeloperoxidase (MPO), adiponectin, and total plasminogen activator inhibitor 1 (tPAI-1).
Main Results:
- MU prevalence varied from 30% to 60% among overweight/obese children across different definitions.
- MU children exhibited higher MPO and tPAI-1 levels and lower adiponectin levels compared to metabolically healthy (MH) children.
- Linear regression identified MPO and tPAI-1 as significant contributors to MU status, particularly with age/sex-specific criteria and HOMA-IR inclusion.
Conclusions:
- Plasma MPO and tPAI-1 concentrations are elevated in prepubertal MU children, regardless of weight status.
- Incorporating age/sex-specific criteria and insulin resistance (HOMA-IR) enhances MU definition quality by strengthening associations with CVD biomarkers.
Background And Aims:
The early onset of cardio-metabolic abnormalities, known as metabolically unhealthy (MU) status, is highly associated with obesity and cardiovascular disease (CVD), as well as with increased morbidity and mortality later in life. Given the lack of a consensus MU classification for prepubertal children, we aimed to compare available MU definitions in terms of their association with CVD risk biomarkers.
Methods And Results:
A total of 930 prepubertal children (622 with overweight/obesity, 462 males) aged 5-10.9 years were recruited, anthropometric measures were taken and biomarkers were analyzed. Children were classified using eight MU definitions based on different cut-offs for blood pressure, triacylglycerides, high-density lipoprotein cholesterol, glucose and homeostasis model assessment for insulin resistance (HOMA-IR). MU prevalence in children with overweight/obesity ranged between 30% and 60% across definitions. Plasma concentrations of resistin, leptin, myeloperoxidase (MPO) and total plasminogen activator inhibitor 1 (tPAI-1) were higher, and those of adiponectin were lower, in MU compared to MH children with overweight/obesity. Linear regression analyses confirmed the contribution of MPO and tPAI-1 concentrations to MU status, with most significant results derived from definitions that use age and sex-specific criteria and that account for HOMA-IR.
Conclusion:
Plasma concentrations of MPO and tPAI-1 are increased in prepubertal MU children irrespective of having normal-weight or overweight/obesity. Inclusion of age and sex-specific cut-offs for cardio-metabolic components as well as insulin resistance criteria increases the quality of MU definitions as seen by their stronger association with CVD biomarkers concentrations.
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