ArticleNutrition journal2020
Leading dietary determinants identified using machine learning techniques and a healthy diet score for changes in cardiometabolic risk factors in children: a longitudinal analysis.
Article in Nutrition journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.
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Who cites it
7 citing papers in PubMed, 2 syntheses or guidelines pooled it, 18 citations in OpenAlex.
- The Relationship Between Children's Diet and Risk Factors for Cardiovascular Disease.Nutrients · 2026Pooled it
- Healthy and Sustainable Dietary Patterns in Children and Adolescents: A Systematic Review.Advances in nutrition (Bethesda, Md.) · 2022Pooled it
- Challenges for Predictive Modeling With Neural Network Techniques Using Error-Prone Dietary Intake Data.Statistics in medicine · 2025Article
- Advances in methods for characterizing dietary patterns: A scoping review.medRxiv : the preprint server for health sciences · 2024Article
- Classification and Prediction on Hypertension with Blood Pressure Determinants in a Deep Learning Algorithm.International journal of environmental research and public health · 2022Article
- Classification and Prediction on the Effects of Nutritional Intake on Overweight/Obesity, Dyslipidemia, Hypertension and Type 2 Diabetes Mellitus Using Deep Learning Model: 4-7th Korea National Health and Nutrition Examination Survey.International journal of environmental research and public health · 2021Article
- Moving Health Literacy Research and Practice towards a Vision of Equity, Precision and Transparency.International journal of environmental research and public health · 2020Article
Corrections and comments
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Authors and funding
8 authors at 7 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIdentifying leading dietary determinants for cardiometabolic risk (CMR) factors is urgent for prioritizing interventions in children. We aimed to identify leading dietary determinants for the change in CMR and create a healthy diet score (HDS) to predict CMR in children.
methodsWe included 5676 children aged 6-13 years in the final analysis with physical examinations, blood tests, and diets assessed at baseline and one year later. CMR score (CMRS) was computed by summing Z-scores of waist circumference, an average of systolic and diastolic blood pressure (SBP and DBP), fasting glucose, high-density lipoprotein cholesterol (HDL-C, multiplying by - 1), and triglycerides. Machine learning was used to identify leading dietary determinants for CMR and an HDS was then computed.
resultsThe nine leading predictors for CMRS were refined grains, seafood, fried foods, sugar-sweetened beverages, wheat, red meat other than pork, rice, fungi and algae, and roots and tubers with the contribution ranging from 3.9 to 19.6% of the total variance. Diets high in seafood, rice, and red meat other than pork but low in other six food groups were associated with a favorable change in CMRS. The HDS was computed based on these nine dietary factors. Children with HDS ≥8 had a higher decrease in CMRS (β (95% CI): - 1.02 (- 1.31, - 0.73)), BMI (- 0.08 (- 0.16, - 0.00)), SBP (- 0.46 (- 0.58, - 0.34)), DBP (- 0.46 (- 0.58, - 0.34)), mean arterial pressure (- 0.50 (- 0.62, - 0.38)), fasting glucose (- 0.22 (- 0.32, - 0.11)), insulin (- 0.52 (- 0.71, - 0.32)), and HOMA-IR (- 0.55 (- 0.73, - 0.36)) compared to those with HDS ≦3. Improved HDS during follow-up was associated with favorable changes in CMRS, BMI, percent body fat, SBP, DBP, mean arterial pressure, HDL-C, fasting glucose, insulin, and HOMA-IR.
conclusionDiets high in seafood, rice, and red meat other than pork and low in refined grains, fried foods, sugar-sweetened beverages, and wheat are leading healthy dietary factors for metabolic health in children. HDS is strongly predictive of CMR factors.
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