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ORIGINAL ARTICLE  EPIDEMIOLOGY AND CLINICAL MEDICINE 

The Journal of Sports Medicine and Physical Fitness 2021 July;61(7):997-1006

DOI: 10.23736/S0022-4707.20.11479-8

Copyright © 2020 EDIZIONI MINERVA MEDICA

lingua: Inglese

Tracking of cardiometabolic risk in a Brazilian schoolchildren cohort: a 3-year longitudinal study

João F. SILVEIRA 1, Cézane P. REUTER 1, 2 , Letícia WELSER 1, Karin A. PFEIFFER 3, Lars B. ANDERSEN 4, 5, Hildegard H. POHL 1, 2, Rodrigo A. LIMA 6, 7

1 University of Santa Cruz do Sul (UNISC), Santa Cruz do Sul, Brazil; 2 Department of Health Sciences, University of Santa Cruz do Sul (UNISC), Santa Cruz do Sul, Brazil; 3 Department of Kinesiology, Michigan State University (MSU), East Lansing, MI, USA; 4 Faculty of Education, Arts and Sport, Western Norway University of Applied Sciences, Songdal, Norway; 5 Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo, Norway; 6 Institute of Sport Science, University of Graz, Graz, Austria; 7 Research Group on Lifestyles and Health, University of Pernambuco, Recife, Brazil



BACKGROUND: Clustering of cardiometabolic risk factors is a sign of detrimental health. Tracking is a term used to describe a variable longitudinal stability across time. High tracking provides the chance to determine which cardiometabolic risk factors should be the target of early treatment and prevention efforts. The present study aims to analyze the tracking of cardiometabolic risk factors and clustered cardiometabolic risk score in children across a 3-year time span, and to verify the odds of staying at risk (measured by the clustered score) from baseline to follow-up.
METHODS: Longitudinal study that included 354 (155 boys) children, aged 7-12 years at baseline. A clustered score was calculated by summing the systolic blood pressure, waist circumference, triglycerides, glucose, and the TC/HDL-C ratio Z-scores divided by five. A second clustered score was calculated including cardiorespiratory fitness (CRF).
RESULTS: CRF and anthropometric parameters presented high tracking (r≥0.662), whereas the cardiometabolic parameters exhibited low-to-moderate tracking (0.100≤r≤0.571). The clustered scores’ tracking was moderate (r≥0.508; r≥0.588 [CRF]). Participants in the higher risk groups at baseline presented 3.81 (95% CI: 2.40; 6.05) and 4.64 (95% CI: 2.85; 7.56), including CRF, times higher chance of remaining at risk three years later. Moreover, participants in the worst profile regarding CRF or anthropometrics at baseline presented at least 4.00 times higher chance of being at risk three years later.
CONCLUSIONS: Participants with worst CRF and adiposity had an increased risk of presenting higher clustered risk after three years.


KEY WORDS: Cardiometabolic risk factors; Cardiovascular diseases; Metabolic syndrome; Child

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