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Updated: Nov 21, 2025
Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Alternative pediatric metabolic syndrome definitions impact prevalence estimates and socioeconomic gradients
Alexander Lepe1, Marlou L A de Kroon2, Andrea F de Winter2
1Department of Health Sciences, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. a.lepe@umcg.nl.
Insights
Different definitions of pediatric metabolic syndrome (MetS) yield varying prevalence rates but consistently identify low socioeconomic status (SES) as a risk factor. This impacts comparisons of prevalence studies but not SES association studies.
Area of Science:
- Pediatrics
- Metabolic Health
- Public Health
Background:
- Lack of a standardized definition for pediatric metabolic syndrome (MetS) complicates research.
- Existing definitions yield diverse prevalence estimates and identify different children at risk.
Purpose of the Study:
- To assess the impact of alternative MetS definitions on prevalence and identification of affected children.
- To evaluate how different MetS definitions influence the association with socioeconomic status (SES).
Main Methods:
- Utilized data from the prospective, multigenerational Dutch Lifelines Cohort Study.
- Calculated MetS prevalence using five distinct published definitions.
- Employed logistic regression to analyze the association between MetS and SES, adjusting for covariates.
Main Results:
- MetS prevalence varied significantly across definitions, ranging from 0.7% to 3.0% at baseline.
- A consistent socioeconomic gradient was observed, with lower SES linked to higher MetS risk.
- Each additional year of parental education reduced MetS odds by 8% to 19% in longitudinal analyses.
Conclusions:
- The choice of MetS definition significantly impacts prevalence estimates and the identification of affected children.
- Despite definition variability, low SES remains a consistent risk factor for pediatric MetS.
- Comparisons of MetS prevalence across studies are limited by definitional differences, while SES associations are more robust.
Background:
There is no consensus regarding the definition of pediatric metabolic syndrome (MetS). This study assessed the impact of alternative definitions on the prevalence, children identified, and association with socioeconomic status (SES).
Methods:
Data were from the prospective multigenerational Dutch Lifelines Cohort Study. At baseline, 9754 children participated, and 5085 (52.1%) with average follow-up of 3.0 (SD = 0.75) years were included in the longitudinal analyses; median ages were 12 (IQR = 10-14) and 14 years (IQR = 12-15), respectively. We computed MetS prevalence according to five published definitions and measured the observed proportion of positive agreement. We used logistic regression to assess the SES-MetS association, adjusted for age and sex. Longitudinal models were also adjusted for baseline MetS.
Results:
MetS prevalence and positive agreement varied between definitions, from 0.7 to 3.0% and from 0.34 (95% CI: 0.28; 0.41) to 0.66 (95% CI: 0.58; 0.75) at baseline, respectively. We consistently found a socioeconomic gradient; in the longitudinal analyses, each additional year of parental education reduced the odds of having MetS by 8% (95% CI: 1%; 14%) to 19% (95% CI: 7%; 30%).
Conclusions:
Alternative MetS definitions had differing prevalence estimates and agreed on 50% of the average number of cases. Additionally, regardless of the definition, low SES was a risk factor for MetS.
Impact:
Little is known about the impact of using different definitions of pediatric metabolic syndrome on study results. Our study showed that the choice of pediatric metabolic syndrome definition produces very different prevalence estimates. We also showed that the choice of definition influences the socioeconomic gradient. However, low socioeconomic status was consistently a risk factor for having pediatric metabolic syndrome. In conclusion, studies using different definitions of metabolic syndrome could be reasonably compared when investigating the association with socioeconomic status but not always validly when comparing prevalence studies.
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