AIMC Topic: Pediatric Obesity
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Predicting childhood obesity using electronic health records and publicly available data.
PloS one
Apr 22, 2019
BACKGROUND: Because of the strong link between childhood obesity and adulthood obesity comorbidities, and the difficulty in decreasing body mass index (BMI) later in life, effective strategies are needed to address this condition in early childhood. ...
Diagnostic performance of an artificial neural network to predict excess body fat in children.
Pediatric obesity
Dec 27, 2018
BACKGROUND: Waist circumference (WC) and z scores of body mass index (BMI) are commonly used to predict childhood obesity, although BMI and WC have a limited sensitivity.
Effect of a short-term physical activity intervention on liver fat content in obese children.
Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme
Dec 20, 2017
Nonalcoholic fatty liver disease is the most common chronic liver disease and can present with advanced fibrosis or nonalcoholic steatohepatitis. The purpose of this study was to investigate the effect of a 7-day intense physical activity interventio...
Recovery Responses to Maximal Exercise in Healthy-Weight Children and Children With Obesity.
Research quarterly for exercise and sport
Dec 20, 2017
PURPOSE: The purpose of this study was to examine differences in heart rate recovery (HRRec) and oxygen consumption recovery (VO recovery) between young healthy-weight children and children with obesity following a maximal volitional graded exercise ...
Genetic Variation in CD36 Is Associated with Decreased Fat and Sugar Intake in Obese Children and Adolescents.
Journal of nutrigenetics and nutrigenomics
Feb 25, 2017
BACKGROUND/AIMS: Taste is recognized as an important predictor of food choices. Thus, polymorphisms in genes encoding taste receptors may explain the variability in food preference and intake. Here, we aimed to determine whether genetic variation in ...
Genetic Association Studies
Pediatric Obesity
Eating
Food Preferences
Feeding Behavior
CD36 Antigens
Taste Perception
Dietary Fats
Dietary Sugars
Adolescent
Child
Genetic Predisposition to Disease
Risk Factors
Polymorphism, Single Nucleotide
Cross-Sectional Studies
Genotype
Humans
Male
Female
Brazil
Developing an Algorithm to Detect Early Childhood Obesity in Two Tertiary Pediatric Medical Centers.
Applied clinical informatics
Jul 20, 2016
OBJECTIVE: The objective of this study is to develop an algorithm to accurately identify children with severe early onset childhood obesity (ages 1-5.99 years) using structured and unstructured data from the electronic health record (EHR).
Low serum 25-hydroxyvitamin D concentrations are associated with total adiposity of children in the United States: National Health and Examination Survey 2005 to 2006.
Nutrition research (New York, N.Y.)
Nov 6, 2015
A negative association between serum 25-hydroxyvitamn D (25[OH]D) concentrations and adiposity has been found in adults. We hypothesized that serum 25(OH)D concentrations of children would correlate positively with vitamin D intake and correlate nega...
Adolescent Nutritional Physiological Phenomena
Humans
United States
Child Nutritional Physiological Phenomena
Pediatric Obesity
Diet
Overweight
Calcifediol
Prevalence
Body Mass Index
Vitamin D Deficiency
Biomarkers
Adiposity
Adolescent
Female
Nutritional Status
Child
Cross-Sectional Studies
Nutrition Surveys
Risk
Male
25-Hydroxyvitamin D 2
Interpretable Probabilistic Latent Variable Models for Automatic Annotation of Clinical Text.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Nov 5, 2015
We propose Latent Class Allocation (LCA) and Discriminative Labeled Latent Dirichlet Allocation (DL-LDA), two novel interpretable probabilistic latent variable models for automatic annotation of clinical text. Both models separate the terms that are ...
Exploring the forest instead of the trees: An innovative method for defining obesogenic and obesoprotective environments.
Health & place
Sep 19, 2015
Past research has assessed the association of single community characteristics with obesity, ignoring the spatial co-occurrence of multiple community-level risk factors. We used conditional random forests (CRF), a non-parametric machine learning appr...
Machine Learning Techniques for Prediction of Early Childhood Obesity.
Applied clinical informatics
Aug 12, 2015
OBJECTIVES: This paper aims to predict childhood obesity after age two, using only data collected prior to the second birthday by a clinical decision support system called CHICA.
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