Abstract
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
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Little is known about the impact of using different definitions of pediatric metabolic syndrome on study results.
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Our study showed that the choice of pediatric metabolic syndrome definition produces very different prevalence estimates.
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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.
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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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Acknowledgements
The authors are grateful to Josué Almansa, PhD (Department of Health Sciences, University Medical Center Groningen, University of Groningen) who provided valuable methodological guidance when discussing how to impute data and measure agreement. This study is part of the TRANSSES project which is funded by ZonMw (Grant 531003011).
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A.L. conceptualized and designed this study, carried out the analyses, drafted the initial manuscript, and reviewed and revised the manuscript. M.L.A.d.K. and S.A.R. conceptualized, designed, and supervised this study; reviewed and revised the manuscript; conceived the project; and obtained the grant for the project TRANSSES. A.F.d.W. conceptualized, designed, and supervised this study and reviewed and revised the manuscript. All authors read and approved the final manuscript as submitted and agree to be accountable for all aspects of the work.
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The authors declare no competing interests.
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This study uses data from the Lifelines Cohort study, which obtained written informed consent for each participant prior to participating in the cohort.
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Lepe, A., de Kroon, M.L.A., de Winter, A.F. et al. Alternative pediatric metabolic syndrome definitions impact prevalence estimates and socioeconomic gradients. Pediatr Res 90, 694–700 (2021). https://doi.org/10.1038/s41390-020-01331-3
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DOI: https://doi.org/10.1038/s41390-020-01331-3
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