{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T17:11:59Z","timestamp":1786554719095,"version":"build-2736575974"},"reference-count":43,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,26]],"date-time":"2022-12-26T00:00:00Z","timestamp":1672012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Israel Defense Forces (IDF) Medical Corps"},{"name":"Directorate of Defense Research &amp; Development, Israeli Ministry of Defense"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Metabolites"],"abstract":"<jats:p>The objectives of the research were to analyze the association between Body Mass Index (BMI) and dental caries using novel approaches of both statistical and machine learning (ML) models while adjusting for cardiovascular risk factors and metabolic syndrome (MetS) components, consequences, and related conditions. This research is a data-driven analysis of the Dental, Oral, Medical Epidemiological (DOME) big data repository, that integrates comprehensive socio-demographic, medical, and dental databases of a nationwide sample of dental attendees to military dental clinics for 1 year aged 18\u201350 years. Obesity categories were defined according to the World Health Organization (WHO): under-weight: BMI &lt; 18.5 kg\/m2, normal weight: BMI 18.5 to 24.9 kg\/m2, overweight: BMI 25 to 29.9 kg\/m2, and obesity: BMI \u2265 30 kg\/m2. General linear models were used with the mean number of decayed teeth as the dependent variable across BMI categories, adjusted for (1) socio-demographics, (2) health-related habits, and (3) each of the diseases comprising the MetS definition MetS and long-term sequelae as well as associated illnesses, such as hypertension, diabetes, hyperlipidemia, cardiovascular disease, obstructive sleep apnea (OSA) and non-alcoholic fatty liver disease (NAFLD). After the statistical analysis, we run the XGBoost machine learning algorithm on the same set of clinical features to explore the features\u2019 importance according to the dichotomous target variable of decayed teeth as well as the obesity category. The study included 66,790 subjects with a mean age of 22.8 \u00b1 7.1. The mean BMI score was 24.2 \u00b1 4.3 kg\/m2. The distribution of BMI categories: underweight (3113 subjects, 4.7%), normal weight (38,924 subjects, 59.2%), overweight (16,966, 25.8%), and obesity (6736, 10.2%). Compared to normal weight (2.02 \u00b1 2.79), the number of decayed teeth was statistically significantly higher in subjects with obesity [2.40 \u00b1 3.00; OR = 1.46 (1.35\u20131.57)], underweight [2.36 \u00b1 3.04; OR = 1.40 (1.26\u20131.56)] and overweight [2.08 \u00b1 2.76, OR = 1.05 (1.01\u20131.11)]. Following adjustment, the associations persisted for obesity [OR = 1.56 (1.39\u20131.76)] and underweight [OR = 1.29 (1.16\u20131.45)], but not for overweight [OR = 1.11 (1.05\u20131.17)]. Features important according to the XGBoost model were socioeconomic status, teeth brushing, birth country, and sweetened beverage consumption, which are well-known risk factors of caries. Among those variables was also our main theory independent variable: BMI categories. We also performed clinical features importance based on XGBoost with obesity set as the target variable and received an AUC of 0.702, and accuracy of 0.896, which are considered excellent discrimination, and the major features that are increasing the risk of obesity there were: hypertension, NAFLD, SES, smoking, teeth brushing, age as well as our main theory dependent variable: caries as a dichotomized variable (Yes\/no). The study demonstrates a positive association between underweight and obesity BMI categories and caries, independent of the socio-demographic, health-related practices, and other systemic conditions related to MetS that were studied. Better allocation of resources is recommended, focusing on populations underweight and obese in need of dental care.<\/jats:p>","DOI":"10.3390\/metabo13010037","type":"journal-article","created":{"date-parts":[[2022,12,27]],"date-time":"2022-12-27T04:42:47Z","timestamp":1672116167000},"page":"37","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Body Mass Index and Caries: Machine Learning and Statistical Analytics of the Dental, Oral, Medical Epidemiological (DOME) Nationwide Big Data Study"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1975-6647","authenticated-orcid":false,"given":"Ofir","family":"Ben-Assuli","sequence":"first","affiliation":[{"name":"Faculty of Business Administration, Ono Academic College, Kiryat Ono 55000, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ori","family":"Bar","sequence":"additional","affiliation":[{"name":"Faculty of Dental Medicine, Hebrew University of Jerusalem, Jerusalem 91120, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gaya","family":"Geva","sequence":"additional","affiliation":[{"name":"Faculty of Business Administration, Ono Academic College, Kiryat Ono 55000, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shlomit","family":"Siri","sequence":"additional","affiliation":[{"name":"Faculty of Business Administration, Ono Academic College, Kiryat Ono 55000, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dorit","family":"Tzur","sequence":"additional","affiliation":[{"name":"Medical Information Department, General Surgeon Headquarter, Medical Corps, Israel Defense Forces, Tel-Hashomer, Ramat Gan 02149, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9671-0047","authenticated-orcid":false,"given":"Galit","family":"Almoznino","sequence":"additional","affiliation":[{"name":"Faculty of Dental Medicine, Hebrew University of Jerusalem, Big Biomedical Data Research Laboratory, Dean\u2019s Office, Hadassah Medical Center, Jerusalem, 91120, Israel"},{"name":"Faculty of Dental Medicine, Hebrew University of Jerusalem, Department of Endodontics, Hadassah Medical Center, Jerusalem, 91120, Israel"},{"name":"Faculty of Dental Medicine, Hebrew University of Jerusalem, Department of Oral Medicine, Sedation & Maxillofacial Imaging, Hadassah Medical Center, Jerusalem, 91120, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1093\/oxfordjournals.aje.a008733","article-title":"How useful is body mass index for comparison of body fatness across age, sex, and ethnic groups?","volume":"143","author":"Gallagher","year":"1996","journal-title":"Am. J. Epidemiol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"978","DOI":"10.1093\/ajcn\/75.6.978","article-title":"Validity of body mass index compared with other body-composition screening indexes for the assessment of body fatness in children and adolescents","volume":"75","author":"Mei","year":"2002","journal-title":"Am. J. Clin. Nutr."},{"key":"ref_3","unstructured":"Khanna, D., and Rehman, A. (2022). Pathophysiology of Obesity. StatPearls, StatPearls Publishing."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"776","DOI":"10.1016\/S0140-6736(16)30175-1","article-title":"Body-mass index and all-cause mortality: Individual-participant-data meta-analysis of 239 prospective studies in four continents","volume":"388","author":"Global","year":"2016","journal-title":"Lancet"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"650","DOI":"10.1177\/0022034515573272","article-title":"Global burden of untreated caries: A systematic review and metaregression","volume":"94","author":"Kassebaum","year":"2015","journal-title":"J. Dent. Res."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"e10714","DOI":"10.1016\/j.heliyon.2022.e10714","article-title":"Changes in the global burden of untreated dental caries from 1990 to 2019: A systematic analysis for the Global Burden of Disease study","volume":"8","author":"Qin","year":"2022","journal-title":"Heliyon"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Paisi, M., Kay, E., Bennett, C., Kaimi, I., Witton, R., Nelder, R., and Lapthorne, D. (2019). Body mass index and dental caries in young people: A systematic review. BMC Pediatr, 19.","DOI":"10.1186\/s12887-019-1511-x"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"522","DOI":"10.1016\/j.identj.2021.01.009","article-title":"Association of Body Mass Index and Waist Circumference With Dental Caries and Consequences of Untreated Dental Caries Among 12- to 14-Year-old Boys: A Cross-Sectional Study","volume":"71","author":"Gudipaneni","year":"2021","journal-title":"Int. Dent. J."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"S176","DOI":"10.4103\/jpbs.JPBS_53_20","article-title":"Dental Caries and Its Association with Body Mass Index among School Children of Riyadh, Saudi Arabia","volume":"12","author":"Abdellatif","year":"2020","journal-title":"J. Pharm. Bioallied Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.sdentj.2019.11.002","article-title":"Association between body mass index and dental caries in the Kingdom of Saudi Arabia: Systematic review","volume":"32","author":"Alshehri","year":"2020","journal-title":"Saudi Dent. J."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"147","DOI":"10.14740\/jocmr2433w","article-title":"The Association Between Body Mass Index and Dental Caries: Cross-Sectional Study","volume":"8","author":"Alswat","year":"2016","journal-title":"J. Clin. Med. Res."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Kim, K., Han, K., and Yang, S. (2020). Association between overweight, obesity and incidence of advanced dental caries in South Korean adults: A 10-year nationwide population-based observational study. PLoS One, 15.","DOI":"10.1371\/journal.pone.0229572"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"e616","DOI":"10.1542\/peds.2013-0846","article-title":"Dental caries and growth in school-age children","volume":"133","author":"Alkarimi","year":"2014","journal-title":"Pediatrics"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"52","DOI":"10.4103\/2231-0762.151978","article-title":"Caries experience and its association with weight status among 8-year-old children in Qingdao, China","volume":"5","author":"Yang","year":"2015","journal-title":"J. Int. Soc. Prev. Community Dent."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1111\/ipd.12039","article-title":"Is dental caries experience associated with adiposity status in preschool children?","volume":"24","author":"Peng","year":"2014","journal-title":"Int. J. Paediatr. Dent."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1034\/j.1600-0528.2000.028006399.x","article-title":"The common risk factor approach: A rational basis for promoting oral health","volume":"28","author":"Sheiham","year":"2000","journal-title":"Community Dent. Oral Epidemiol"},{"key":"ref_17","first-page":"63","article-title":"Eslam M Shehata Nagwa A Sabri, impact of Applied Protective Measures of COVID-19 on Public Health","volume":"5","author":"Sara","year":"2021","journal-title":"Acta Sci. Pharm. Sci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.neuro.2018.07.006","article-title":"Molecular mechanisms of neuroprotective effect of adjuvant therapy with phenytoin in pentylenetetrazole-induced seizures: Impact on Sirt1\/NRF2 signaling pathways","volume":"68","author":"Nagib","year":"2018","journal-title":"Neurotoxicology"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1007\/s00210-017-1435-7","article-title":"Effects of genistein on pentylenetetrazole-induced behavioral and neurochemical deficits in ovariectomized rats","volume":"391","author":"Elsayed","year":"2018","journal-title":"Naunyn Schmiedebergs Arch. Pharm."},{"key":"ref_20","first-page":"812","article-title":"Nagwa Ali Sabri, Effect of Silymarin Supplementation on Glycemic Control, Lipid Profile and Insulin Resistance in Patients with Type 2 Diabetes Mellitus","volume":"3","year":"2015","journal-title":"Int. J. Adv. Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.jsps.2009.08.008","article-title":"Evaluation of clinical activity and safety of Daflon 500 mg in type 2 diabetic female patients","volume":"17","author":"Rizk","year":"2009","journal-title":"Saudi Pharm. J."},{"key":"ref_22","first-page":"4198","article-title":"A Clinical Study on The Impact of Different Treatment Modalities on Improving The Clinical Outcomes in Chronic Periodontitis Patients","volume":"6","author":"Sabri","year":"2015","journal-title":"IJPSR"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.metabol.2015.10.019","article-title":"Metabolic health and weight: Understanding metabolically unhealthy normal weight or metabolically healthy obese patients","volume":"65","author":"Mathew","year":"2016","journal-title":"Metabolism"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"758","DOI":"10.7326\/0003-4819-159-11-201312030-00008","article-title":"Are metabolically healthy overweight and obesity benign conditions? A systematic review and meta-analysis","volume":"159","author":"Kramer","year":"2013","journal-title":"Ann. Intern. Med."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1111\/ger.12432","article-title":"Application of machine learning for diagnostic prediction of root caries","volume":"36","author":"Hung","year":"2019","journal-title":"Gerodontology"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Park, Y.H., Kim, S.H., and Choi, Y.Y. (2021). Prediction Models of Early Childhood Caries Based on Machine Learning Algorithms. Int. J. Environ. Res. Public Health, 18.","DOI":"10.3390\/ijerph18168613"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1055\/s-0040-1718582","article-title":"The Dental, Oral, Medical Epidemiological (DOME) Study: Protocol and Study Methods","volume":"59","author":"Almoznino","year":"2020","journal-title":"Methods Inf. Med."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Almoznino, G., Zini, A., Kedem, R., Protter, N.E., Zur, D., and Abramovitz, I. (2021). Hypertension and Its Associations with Dental Status: Data from the Dental, Oral, Medical Epidemiological (DOME) Nationwide Records-Based Study. J. Clin. Med., 10.","DOI":"10.3390\/jcm10020176"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Abramovitz, I., Zini, A., Atzmoni, M., Kedem, R., Zur, D., Protter, N.E., and Almoznino, G. (2021). Cognitive Performance and Its Associations with Dental Caries: Results from the Dental, Oral, Medical Epidemiological (DOME) Records-Based Nationwide Study. Biology, 10.","DOI":"10.3390\/biology10030178"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Abramovitz, I., Zini, A., Kessler Baruch, O., Kedem, R., Protter, N.E., Shay, B., Yavnai, N., Zur, D., Mijiritsky, E., and Almoznino, G. (2021). SOS teeth with advanced caries and sociodemographic indicators, health-related habits and dental attendance patterns: Data from the Dental, Oral, Medical Epidemiological (DOME) nationwide records-based study. BMC Oral Health, 21.","DOI":"10.1186\/s12903-021-01751-5"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Abramovitz, I., Zini, A., Pribluda, P., Kedem, R., Zur, D., Protter, N.E., and Almoznino, G. (2021). \u201cDental Cluster\u201d Versus \u201cMetabolic Cluster\u201d: Analyzing the Associations of Planned and Delivered Dental Procedures with Metabolic Syndrome, Utilizing Data from the Dental, Oral, Medical Epidemiological (DOME) Cross-Sectional Record-Based Nationwide Study. Biology, 10.","DOI":"10.3390\/biology10070608"},{"key":"ref_32","unstructured":"Israel Defence Forces (IDF) (2022, November 30). The Stges of Volunteering in the IDF. Available online: https:\/\/www.mitgaisim.idf.il\/%D7%9B%D7%AA%D7%91%D7%95%D7%AA\/english\/exclusive-service\/the-stages-of-volunteering-in-the-idf\/#\/."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1186\/s12933-020-01143-z","article-title":"Adolescent BMI and early-onset type 2 diabetes among Ethiopian immigrants and their descendants: A nationwide study","volume":"19","author":"Simchoni","year":"2020","journal-title":"Cardiovasc. Diabetol"},{"key":"ref_34","unstructured":"Weir, C.B., and Jan, A. (2022). BMI Classification Percentile And Cut Off Points. StatPearls, StatPearls Publishing."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1214\/aos\/1013203450","article-title":"Greedy function approximation: A gradient boosting machine","volume":"29","author":"Jh","year":"2001","journal-title":"Ann. Statist."},{"key":"ref_36","first-page":"2825","article-title":"Scikit-Learn: Machine Learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Liu, H., Zhou, M., Lu, X.S., and Yao, C. (2018, January 27\u201329). Weighted Gini index feature selection method for imbalanced data. Proceedings of the ICNSC 2018\u201415th IEEE International Conference on Networking, Sensing and Control, Zhuhai, China.","DOI":"10.1109\/ICNSC.2018.8361371"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Huang, N., Lu, G., Cai, G., Xu, D., Xu, J., Li, F., and Zhang, L. (2016). Feature selection of power quality disturbance signals with an entropy-importance-based random forest. Entropy, 18.","DOI":"10.3390\/e18020044"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Newton, S., Braithwaite, D., and Akinyemiju, T.F. (2017). Socio-economic status over the life course and obesity: Systematic review and meta-analysis. PLoS One, 12.","DOI":"10.1371\/journal.pone.0177151"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"e016557","DOI":"10.1136\/bmjopen-2017-016557","article-title":"Association between socio-economic status and dental caries in elderly people in Sichuan Province, China: A cross-sectional study","volume":"7","author":"Wang","year":"2017","journal-title":"BMJ Open"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1093\/epirev\/mxm001","article-title":"Socioeconomic status and obesity","volume":"29","author":"McLaren","year":"2007","journal-title":"Epidemiol Rev."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1177\/0022034513508954","article-title":"Effect on caries of restricting sugars intake: Systematic review to inform WHO guidelines","volume":"93","author":"Moynihan","year":"2014","journal-title":"J. Dent. Res."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1016\/j.ypmed.2006.01.011","article-title":"Clustering of risk behaviors with cigarette consumption: A population-based survey","volume":"42","author":"Chiolero","year":"2006","journal-title":"Prev. Med."}],"container-title":["Metabolites"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2218-1989\/13\/1\/37\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:51:25Z","timestamp":1760147485000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2218-1989\/13\/1\/37"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,26]]},"references-count":43,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,1]]}},"alternative-id":["metabo13010037"],"URL":"https:\/\/doi.org\/10.3390\/metabo13010037","relation":{},"ISSN":["2218-1989"],"issn-type":[{"value":"2218-1989","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,26]]}}}