ArticlePublic health nutrition2015
Validation of a BMI cut-off point to predict an adverse cardiometabolic profile with adiposity measurements by dual-energy X-ray absorptiometry in Guatemalan children.
Article in Public health nutrition, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Relationship between Fat Mass Percentage and Glucose Metabolism in Children and Adolescents: A Systematic Review and Meta-Analysis.Nutrients · 2022Pooled it
- Waist circumference, waist-to-height ratio and conicity index to evaluate android fat excess in Brazilian children.Public health nutrition · 2019Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
objectiveTo identify a body fat percentage (%BF) threshold related to an adverse cardiometabolic profile and its surrogate BMI cut-off point.
designCross-sectional study.
settingTwo public schools in poor urban areas on the outskirts of Guatemala City. SUBJECTS: A convenience sample of ninety-three healthy, prepubertal, Ladino children (aged 7-12 years).
resultsSpearman correlations of cardiometabolic parameters were higher with %BF than with BMI-for-age Z-score. BMI-for-age Z-score and %BF were highly correlated (r=0·84). The %BF threshold that maximized sensitivity and specificity for predicting an adverse cardiometabolic profile (elevated homeostasis model assessment-insulin resistance index and/or total cholesterol:HDL-cholesterol ratio) according to receiver operating characteristic curve analysis was 36 %. The BMI-for-age Z-score cut-off point that maximized the prediction of BF ≥ 36 % by the same procedure was 1·5. The area under the curve (AUC) for %BF and for BMI data showed excellent accuracy to predict an adverse cardiometabolic profile (AUC 0·93 (sd 0·04)) and excess adiposity (AUC 0·95 (sd 0·02)).
conclusionsSince BMI standards have limitations in screening for adiposity, specific cut-off points based on ethnic-/sex- and age-specific %BF thresholds are needed to better predict an adverse cardiometabolic profile.
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Registered trials
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