Leading dietary determinants identified using machine learning techniques and a healthy diet score for changes in cardiometabolic risk factors in children: a longitudinal analysis.
Background: Identifying 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.Methods: We inclu...
| Publicado en: | Nutrition Journal Vol. 19; no. 1 |
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| Autores principales: | , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
BioMed Central
9/19/2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=145975607&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 145975607 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14752891 1CYY jtl: Nutrition Journal issn: 14752891 maglogo: N pubinfo: dt: 9/19/2020 vid: 19 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 145975607 145975607 NLM32950062 145975607 10.1186/s12937-020-00611-2 NLM32950062 145975607 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Leading dietary determinants identified using machine learning techniques and a healthy diet score for changes in cardiometabolic risk factors in children: a longitudinal analysis. aug: au: Shang, Xianwen Li, Yanping Xu, Haiquan Zhang, Qian Liu, Ailing Du, Songming Guo, Hongwei Ma, Guansheng affil: National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China sug: ab: Background: Identifying 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.Methods: We 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.Results: The 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.Conclusion: Diets 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. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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