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Adiposity Criteria in Assessing Increased Cardiometabolic Risk in Prepubertal Children

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Date
2019
Author(s)
Tompuri, Tuomo Tapani
Jaaskelainen, Jarmo
Lindi, Virpi
Laaksonen, David Elliot
Eloranta, Aino-Maija
Viitasalo, Anna
Laitinen, Tomi
Lakka, Limo Antero
Unique identifier
10.3389/fendo.2019.00410
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Citation
Tompuri, Tuomo Tapani. Jaaskelainen, Jarmo. Lindi, Virpi. Laaksonen, David Elliot. Eloranta, Aino-Maija. Viitasalo, Anna. Laitinen, Tomi. Lakka, Limo Antero. (2019). Adiposity Criteria in Assessing Increased Cardiometabolic Risk in Prepubertal Children.  Frontiers in endocrinology, 10, 410. 10.3389/fendo.2019.00410.
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CC BY http://creativecommons.org/licenses/by/4.0/
Abstract

Objective: Adiposity induces the clustering of cardiometabolic risk factors, and pediatric adiposity is a better indicator for adulthood cardiometabolic diseases than pediatric metabolic syndrome. However, the observed prevalence of pediatric adiposity depends on the methods and cut-points used. Therefore, we aimed to define diagnostic criteria for adiposity which enable more valid identification of prepubertal children at increased cardiometabolic risk.

Methods: The participants were 470 prepubertal children (249 boys) aged 6–8 years. The measures of adiposity included body mass index—standard deviation score (BMI-SDS), waist-to-height ratio (WHtR) and body fat percentage (BF%) assessed by bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA). Criteria for adiposity were determined by increased cardiometabolic risk. Cardiometabolic risk factors which correlated with BF% assessed by DXA in the upper but not lower half of BF% (serum insulin and plasma high-density lipoprotein cholesterol, triglycerides, gamma-glutamyl transferase, high-sensitivity C-reactive protein and uric acid) were included in the cardiometabolic risk score (CMS). We computed receiver operating characteristics curves for the measures of adiposity using the ≥90th percentile of CMS as a measure of increased cardiometabolic risk, and local regression curves were graphed to demonstrate the associations of the measures of adiposity with CMS.

Results: In girls, WHtR of 0.445 (area under curve 0.778, its 95% confidence interval 0.65–0.91, sensitivity and specificity 0.73) and BF% of 19.5% assessed by BIA (0.801, 0.70–0.90, 0.73) were the best overall criteria for increased cardiometabolic risk. In boys, BMI-SDS of 0.48 (0.833, 0.75–0.92, 0.76) was the best overall criterion for increased cardiometabolic risk. While local regression curves in girls showed that WHtR of 0.445 corresponds well to a point where CMS began to increase, in boys local regression curves suggest that CMS began to increase even at a lower level of BMI-SDS than 0.48. Moreover, the diagnostic ability of the measures of adiposity to exclude increased cardiometabolic risk was poorer than the ability to detect it.

Conclusions: In general, the measures of adiposity have sufficient diagnostic accuracy to be utilized as the screening tool for increased cardiometabolic risk. The observed cut-points for adiposity were lower than the traditional cut-points for adiposity.

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https://erepo.uef.fi/handle/123456789/7989
Link to the original item
http://dx.doi.org/10.3389/fendo.2019.00410
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Frontiers Media SA
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  • Terveystieteiden tiedekunta [1324]
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