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We aimed to identify leading dietary determinants for the change in CMR and create a healthy diet score (HDS) to predict CMR in children.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We included 5676 children aged 6\u201313\u2009years 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 \u2212\u20091), and triglycerides. Machine learning was used to identify leading dietary determinants for CMR and an HDS was then computed.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>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 \u22658 had a higher decrease in CMRS (\u03b2 (95% CI): \u2212\u20091.02 (\u2212\u20091.31, \u2212\u20090.73)), BMI (\u2212\u20090.08 (\u2212\u20090.16, \u2212\u20090.00)), SBP (\u2212\u20090.46 (\u2212\u20090.58, \u2212\u20090.34)), DBP (\u2212\u20090.46 (\u2212\u20090.58, \u2212\u20090.34)), mean arterial pressure (\u2212\u20090.50 (\u2212\u20090.62, \u2212\u20090.38)), fasting glucose (\u2212\u20090.22 (\u2212\u20090.32, \u2212\u20090.11)), insulin (\u2212\u20090.52 (\u2212\u20090.71, \u2212\u20090.32)), and HOMA-IR (\u2212\u20090.55 (\u2212\u20090.73, \u2212\u20090.36)) compared to those with HDS \u22663. 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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec>","DOI":"10.1186\/s12937-020-00611-2","type":"journal-article","created":{"date-parts":[[2020,9,19]],"date-time":"2020-09-19T16:02:28Z","timestamp":1600531348000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Leading dietary determinants identified using machine learning techniques and a healthy diet score for changes in cardiometabolic risk factors in children: a longitudinal analysis"],"prefix":"10.1186","volume":"19","author":[{"given":"Xianwen","family":"Shang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanping","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haiquan","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qian","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ailing","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Songming","family":"Du","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongwei","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8022-4597","authenticated-orcid":false,"given":"Guansheng","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,9,19]]},"reference":[{"issue":"1","key":"611_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1111\/obr.12229","volume":"16","author":"S O'Neill","year":"2015","unstructured":"O'Neill S, O'Driscoll L. 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