Literature DB >> 29173300

Persistent High Non-High-Density Lipoprotein Cholesterol in Early Childhood: A Latent Class Growth Model Analysis.

Jordan M Albaum1, Sarah Carsley2, Yang Chen3, David W H Dai3, Gerald Lebovic4, Brian W McCrindle5, Jonathon L Maguire6, Patricia C Parkin7, Catherine S Birken8.   

Abstract

OBJECTIVES: To examine patterns of non-high-density lipoprotein (HDL) cholesterol in early childhood and identify factors associated with persistent high non-HDL cholesterol in healthy urban children. STUDY
DESIGN: We identified all children enrolled in a primary care practice-based research network called TARGet Kids! (The Applied Research Group for Kids) with ≥3 laboratory measurements of non-HDL cholesterol. Latent class growth model analysis was performed to identify distinct trajectory groups for non-HDL cholesterol. Trajectory groups were then categorized into "normal" vs "persistent-high" non-HDL cholesterol based on guideline cut-off values and logistic regression was completed to examine the association between trajectory group and the presence of anthropometric and cardiometabolic risk factors.
RESULTS: A total of 608 children met inclusion criteria for the trajectory analysis (median age at enrolment = 18.3, IQR = 27.9 months). Four trajectory groups were identified with 2 groups (n = 451) categorized as normal non-HDL cholesterol and 2 groups (n = 157) as persistent high non-HDL cholesterol. Family history of high cholesterol (OR 2.04, 95% CI 1.27-3.28) was associated significantly with persistent high non-HDL cholesterol, whereas East/Southeast Asian vs European ethnicity (OR 0.33, 95% CI 0.14-0.78), longer breastfeeding duration (OR 0.96, 95% CI 0.93-1.00), and greater birth weight (OR 0.69, 95% CI 0.48-1.00) were associated with lower odds of persistent high non-HDL cholesterol.
CONCLUSIONS: Patterns of non-HDL cholesterol are identified during early childhood, and family history of high cholesterol was associated most strongly with persistent high non-HDL cholesterol. Future research should inform the development of a clinical prediction tool for lipids in early childhood to identify children who may benefit from interventions to promote cardiovascular health.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  cardiovascular; lipids; trajectory; trends

Mesh:

Substances:

Year:  2017        PMID: 29173300     DOI: 10.1016/j.jpeds.2017.08.079

Source DB:  PubMed          Journal:  J Pediatr        ISSN: 0022-3476            Impact factor:   4.406


  3 in total

1.  Trajectory assessment is useful when day-to-day esophageal acid exposure varies in prolonged wireless pH monitoring.

Authors:  R Yadlapati; J D Ciolino; J Craft; S Roman; J E Pandolfino
Journal:  Dis Esophagus       Date:  2019-03-01       Impact factor: 3.429

2.  Trajectories of Lymphocyte Counts in the Early Phase of Acute Pancreatitis Are Associated With Infected Pancreatic Necrosis.

Authors:  Jing Zhou; Wensong Chen; Yang Liu; Cheng Qu; Wendi Jiang; Jiangtao Yin; Jiajia Lin; Wenjian Mao; Bo Ye; Jing Zhou; Lu Ke; Zhihui Tong; Yuxiu Liu; Weiqin Li
Journal:  Clin Transl Gastroenterol       Date:  2021-09-22       Impact factor: 4.488

3.  Trajectories of physical activity, from young adulthood to older adulthood, and pancreatic cancer risk; a population-based case-control study in Ontario, Canada.

Authors:  Jaspreet Sandhu; Vanessa De Rubeis; Michelle Cotterchio; Brendan T Smith; Lauren E Griffith; Darren R Brenner; Ayelet Borgida; Steven Gallinger; Sean Cleary; Laura N Anderson
Journal:  BMC Cancer       Date:  2020-02-21       Impact factor: 4.430

  3 in total

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