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Comparison of different severe obesity definitions in predicting future cardiometabolic risk in a longitudinal cohort of children

OBJECTIVES: Severe obesity (SO) prevalence varies between reference curve-based definitions (WHO: ≥99th percentile, Centers for Disease Control and Prevention (CDC): >1.2×95th percentile). Whether SO definitions differentially predict cardiometabolic disease risk is critical for proper clinical c...

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Autores principales: Kakinami, Lisa, Smyrnova, Anna, Paradis, Gilles, Tremblay, Angelo, Henderson, Melanie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9204411/
https://www.ncbi.nlm.nih.gov/pubmed/35705336
http://dx.doi.org/10.1136/bmjopen-2021-058857
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author Kakinami, Lisa
Smyrnova, Anna
Paradis, Gilles
Tremblay, Angelo
Henderson, Melanie
author_facet Kakinami, Lisa
Smyrnova, Anna
Paradis, Gilles
Tremblay, Angelo
Henderson, Melanie
author_sort Kakinami, Lisa
collection PubMed
description OBJECTIVES: Severe obesity (SO) prevalence varies between reference curve-based definitions (WHO: ≥99th percentile, Centers for Disease Control and Prevention (CDC): >1.2×95th percentile). Whether SO definitions differentially predict cardiometabolic disease risk is critical for proper clinical care and management but is unknown. DESIGN: Prospective cohort study SETTING: SO definitions were applied at baseline (2005–2008, M(age)=9.6 years, n=548), and outcomes (fasting lipids, glucose, homoeostatic model assessment (HOMA-IR) and blood pressure) were assessed at first follow-up (F1: 2008–2011, M(age)=11.6 years) and second follow-up (2015–2017, M(age)=16.8 years) of the Quebec Adipose and Lifestyle Investigation in Youth cohort in Montreal, Quebec. PARTICIPANTS: Respondents were youth who had at least one biological parent with obesity. PRIMARY OUTCOME MEASURES: Unfavourable cardiometabolic levels of fasting blood glucose (≥6.1 mmol/L), insulin resistance (HOMA-IR index ≥2.0), high-density lipoprotein <1.03 mmol/L, low-density lipoprotein ≥2.6 mmol/L and triglycerides >1.24 mmol/L. Unfavourable blood pressure was defined as ≥90th percentile for age-adjusted, sex-adjusted and height-adjusted systolic or diastolic blood pressure. ANALYSIS: Area under the receiver operating characteristic curve (AUC) and McFadden psuedo R(2) for predicting F1 or F2 unfavourable cardiometabolic levels from baseline SO definitions were calculated. Agreement was assessed with kappas. RESULTS: Baseline SO prevalence differed (WHO: 18%, CDC: 6.7%). AUCs ranged from 0.52 to 0.77, with fair agreement (kappa=37%–55%). WHO-SO AUCs for detecting unfavourable HOMA-IR (AUC>0.67) and high-density lipoprotein (AUC>0.59) at F1 were statistically superior than CDC-SO (AUC>0.59 and 0.53, respectively; p<0.05). Only HOMA-IR and the presence of more than three risk factors had acceptable model fit. WHO-SO was not more predictive than WHO-obesity, but CDC-SO was statistically inferior to CDC-obesity. CONCLUSION: WHO-SO is statistically superior at predicting cardiometabolic risk than CDC-SO. However, as most AUCs were generally uninformative, and obesity definitions were the same if not better than SO, the improvement may not be clinically meaningful.
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spelling pubmed-92044112022-06-29 Comparison of different severe obesity definitions in predicting future cardiometabolic risk in a longitudinal cohort of children Kakinami, Lisa Smyrnova, Anna Paradis, Gilles Tremblay, Angelo Henderson, Melanie BMJ Open Epidemiology OBJECTIVES: Severe obesity (SO) prevalence varies between reference curve-based definitions (WHO: ≥99th percentile, Centers for Disease Control and Prevention (CDC): >1.2×95th percentile). Whether SO definitions differentially predict cardiometabolic disease risk is critical for proper clinical care and management but is unknown. DESIGN: Prospective cohort study SETTING: SO definitions were applied at baseline (2005–2008, M(age)=9.6 years, n=548), and outcomes (fasting lipids, glucose, homoeostatic model assessment (HOMA-IR) and blood pressure) were assessed at first follow-up (F1: 2008–2011, M(age)=11.6 years) and second follow-up (2015–2017, M(age)=16.8 years) of the Quebec Adipose and Lifestyle Investigation in Youth cohort in Montreal, Quebec. PARTICIPANTS: Respondents were youth who had at least one biological parent with obesity. PRIMARY OUTCOME MEASURES: Unfavourable cardiometabolic levels of fasting blood glucose (≥6.1 mmol/L), insulin resistance (HOMA-IR index ≥2.0), high-density lipoprotein <1.03 mmol/L, low-density lipoprotein ≥2.6 mmol/L and triglycerides >1.24 mmol/L. Unfavourable blood pressure was defined as ≥90th percentile for age-adjusted, sex-adjusted and height-adjusted systolic or diastolic blood pressure. ANALYSIS: Area under the receiver operating characteristic curve (AUC) and McFadden psuedo R(2) for predicting F1 or F2 unfavourable cardiometabolic levels from baseline SO definitions were calculated. Agreement was assessed with kappas. RESULTS: Baseline SO prevalence differed (WHO: 18%, CDC: 6.7%). AUCs ranged from 0.52 to 0.77, with fair agreement (kappa=37%–55%). WHO-SO AUCs for detecting unfavourable HOMA-IR (AUC>0.67) and high-density lipoprotein (AUC>0.59) at F1 were statistically superior than CDC-SO (AUC>0.59 and 0.53, respectively; p<0.05). Only HOMA-IR and the presence of more than three risk factors had acceptable model fit. WHO-SO was not more predictive than WHO-obesity, but CDC-SO was statistically inferior to CDC-obesity. CONCLUSION: WHO-SO is statistically superior at predicting cardiometabolic risk than CDC-SO. However, as most AUCs were generally uninformative, and obesity definitions were the same if not better than SO, the improvement may not be clinically meaningful. BMJ Publishing Group 2022-06-15 /pmc/articles/PMC9204411/ /pubmed/35705336 http://dx.doi.org/10.1136/bmjopen-2021-058857 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Epidemiology
Kakinami, Lisa
Smyrnova, Anna
Paradis, Gilles
Tremblay, Angelo
Henderson, Melanie
Comparison of different severe obesity definitions in predicting future cardiometabolic risk in a longitudinal cohort of children
title Comparison of different severe obesity definitions in predicting future cardiometabolic risk in a longitudinal cohort of children
title_full Comparison of different severe obesity definitions in predicting future cardiometabolic risk in a longitudinal cohort of children
title_fullStr Comparison of different severe obesity definitions in predicting future cardiometabolic risk in a longitudinal cohort of children
title_full_unstemmed Comparison of different severe obesity definitions in predicting future cardiometabolic risk in a longitudinal cohort of children
title_short Comparison of different severe obesity definitions in predicting future cardiometabolic risk in a longitudinal cohort of children
title_sort comparison of different severe obesity definitions in predicting future cardiometabolic risk in a longitudinal cohort of children
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9204411/
https://www.ncbi.nlm.nih.gov/pubmed/35705336
http://dx.doi.org/10.1136/bmjopen-2021-058857
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