Keyword search (4,164 papers available)

"Paradis G" Authored Publications:

Title Authors PubMed ID
1 The longitudinal effects of maternal parenting practices on children's body mass index z-scores are lagged and differential Kakinami L; Danieles PK; Hosseininasabnajar F; Barnett TA; Henderson M; Van Hulst A; Serbin LA; Stack DM; Paradis G; 37248489
PERFORM
2 Social support and C-reactive protein in a Québec population cohort of children and adolescents Fairbank EJ; McGrath JJ; Henderson M; O' Loughlin J; Paradis G; 35731783
PSYCHOLOGY
3 Comparison of different severe obesity definitions in predicting future cardiometabolic risk in a longitudinal cohort of children Kakinami L; Smyrnova A; Paradis G; Tremblay A; Henderson M; 35705336
PERFORM
4 Body Mass Index Z Score vs Weight-for-Length Z Score in Infancy and Cardiometabolic Outcomes at Age 8-10 Years Roberge JB; Harnois-Leblanc S; McNealis V; van Hulst A; Barnett TA; Kakinami L; Paradis G; Henderson M; 34302856
PERFORM
5 Parenting style and obesity risk in children. Kakinami L, Barnett TA, Séguin L, Paradis G 25797329
PERFORM
6 The association between income and leisure-time physical activity is moderated by utilitarian lifestyles: A nationally representative US population (NHANES 1999-2014) Kakinami L; Wissa R; Khan R; Paradis G; Barnett TA; Gauvin L; 29753806
PERFORM

 

Title:Comparison of different severe obesity definitions in predicting future cardiometabolic risk in a longitudinal cohort of children
Authors:Kakinami LSmyrnova AParadis GTremblay AHenderson M
Link:pubmed.ncbi.nlm.nih.gov/35705336/
DOI:10.1136/bmjopen-2021-058857
Publication:BMJ open
Keywords:community child healthepidemiologypaediatricspublic healthstatistics and research methods
PMID:35705336 Category: Date Added:2022-06-16
Dept Affiliation: PERFORM
1 PERFORM Centre, Concordia University, Montreal, Québec, Canada lisa.kakinami@concordia.ca.
2 Department of Mathematics and Statistics, Concordia University, Montreal, Québec, Canada.
3 Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, Canada.
4 Département de kinésiologie, Université Laval, Quebec City, Quebec, Canada.
5 Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada.
6 Research Center of CHU Sainte Justine, Université de Montréal, Montreal, Quebec, Canada.

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<sub>age</sub>=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<sub>age</sub>=11.6 years) and second follow-up (2015-2017, M<sub>age</sub>=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 <underline>></underline>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<sup>2</sup> 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.




BookR developed by Sriram Narayanan
for the Concordia University School of Health
Copyright © 2011-2026
Cookie settings
Concordia University