{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T14:18:33Z","timestamp":1783433913823,"version":"3.54.6"},"reference-count":26,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T00:00:00Z","timestamp":1763942400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"\u015etefan cel Mare University of Suceava, Romania","award":["CNFIS-FDI-2025-F-0603"],"award-info":[{"award-number":["CNFIS-FDI-2025-F-0603"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Life"],"abstract":"<jats:p>Type 1 Diabetes Mellitus (T1D) can be related to various factors, including neonatal and perinatal conditions. This study investigated the impact of neonatal and perinatal factors\u2014Apgar score, birth weight, feeding type, sex, and delivery type\u2014on the risk of Type 1 Diabetes Mellitus and evaluated predictive models. A cohort of 327 patients was analyzed using correlations, General Linear Model, and artificial neural network. T1D patients showed higher birth weight, lower Apgar score, a predominance of formula feeding, and more cesarean deliveries. Diabetes risk showed a moderate positive correlation with birth weight class and nutrition type (p &lt; 0.05) and a weak negative correlation with Apgar score (p &lt; 0.05), while birth weight, birth weight class, and nutrition type were all weakly positively correlated with each other and with delivery type (p &lt; 0.05). General linear model identified nutrition type, birth weight, and Apgar score as key predictors, with significant interactions among them (R2 = 0.88). Artificial neural network achieved high accuracy (84.2%), AUC (0.95), sensitivity (89.1%), and specificity (76.7%). ANN successfully modeled the complex non-linear interactions among early-life factors, allowing it to discriminate between high-risk and low-risk cases, as evidenced by the low prediction errors (RMSE 0.31 and MAE 0.09) and strong agreement (Kappa 0.81). The models\u2019 strong internal predictive performance points to potential applications in early T1D diagnosis and personalized management, although confirmation in larger and independent datasets is needed.<\/jats:p>","DOI":"10.3390\/life15121800","type":"journal-article","created":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T13:09:25Z","timestamp":1763989765000},"page":"1800","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Neonatal and Birth Risk Factors for Type 1 Diabetes Mellitus: Prediction Using an Artificial Neural Network"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-2795-8491","authenticated-orcid":false,"given":"Claudiu","family":"Cobuz","sequence":"first","affiliation":[{"name":"Faculty of Medicine and Biological Sciences, \u015etefan cel Mare University of Suceava, 13th Universit\u0103\u0163ii Street, 720229 Suceava, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1314-5957","authenticated-orcid":false,"given":"M\u0103d\u0103lina","family":"Ungureanu-Iuga","sequence":"additional","affiliation":[{"name":"Integrated Center for Research, Development and Innovation in Advanced Materials, Nanotechnologies, and Distributed Systems for Fabrication and Control (MANSiD), \u015etefan cel Mare University of Suceava, 13th Universit\u0103\u0163ii Street, 720229 Suceava, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-8343-5025","authenticated-orcid":false,"given":"Maricela","family":"Cobuz","sequence":"additional","affiliation":[{"name":"Faculty of Medicine and Biological Sciences, \u015etefan cel Mare University of Suceava, 13th Universit\u0103\u0163ii Street, 720229 Suceava, Romania"},{"name":"\u201dSf\u00e2ntul Ioan cel Nou\u201d Emergency Clinical Hospital, 720224 Suceava, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,11,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1093\/ije\/dys209","article-title":"The society for social medicine John Pemberton Lecture 2011. Developmental overnutrition-an old hypothesis with new importance","volume":"42","author":"Lawlor","year":"2013","journal-title":"Int. J. Epidemiol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"586","DOI":"10.1111\/pedi.12994","article-title":"Perinatal factors and the risk of Type 1 Diabetes Mellitus in childhood and adolescence\u2014A register-based case-cohort study in Finland, years 1987 to 2009","volume":"21","author":"Hakola","year":"2020","journal-title":"Pediatr. Diabetes"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Censin, J.C., Nowak, C., Cooper, N., Bergsten, P., Todd, J.A., and Fall, T. (2017). Childhood adiposity and risk of Type 1 Diabetes Mellitus: A Mendelian randomization study. PLoS Med., 14.","DOI":"10.1371\/journal.pmed.1002362"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Anghel, L., Cobuz, C., Benchea, L.C., Maciuc, V., Cobuz, M., Sasc\u0103u, R.A., and St\u0103tescu, C. (2025). Sudomotor Dysfunction as an Early Marker of Autonomic and Cardiovascular Risk in Diabetes: Insights from a Cross-Sectional Study Using SUDOSCAN. Biosensors, 15.","DOI":"10.3390\/bios15060372"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"143","DOI":"10.6065\/apem.2019.24.3.143","article-title":"Genetic aspects of Type 1 Diabetes Mellitus","volume":"24","author":"Lee","year":"2019","journal-title":"Ann. Pediatr. Endocrinol. Metab."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Robertson, L., and Harrild, K. (2010). Maternal and neonatal risk factors for childhood Type 1 Diabetes Mellitus: A matched case-control study. BMC Public Health, 10.","DOI":"10.1186\/1471-2458-10-281"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Ornoy, A., Becker, M., Weinstein-fudim, L., and Ergaz, Z. (2021). Diabetes during Pregnancy: A Maternal Disease Complicating the Course of Pregnancy with Long-Term Deleterious Effects on the Offspring. A Clinical Review. Int. J. Mol. Sci., 22.","DOI":"10.3390\/ijms22062965"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1023","DOI":"10.2337\/diab.29.12.1023","article-title":"Banting Lecture 1980 Of Pregnancy and Progeny","volume":"29","author":"Freinkel","year":"1980","journal-title":"Diabetes"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1113","DOI":"10.1007\/s00125-021-05381-y","article-title":"Size for gestational age affects the risk for Type 1 Diabetes Mellitus in children and adolescents: A Swedish national case\u2013control study","volume":"64","author":"Lindell","year":"2021","journal-title":"Diabetologia"},{"key":"ref_10","first-page":"e944513","article-title":"Predicting Neonatal Hypoglycemia Using AI Neural Networks in Infants from Mothers with Gestational Diabetes Mellitus","volume":"30","author":"Zhang","year":"2024","journal-title":"Med. Sci. Monit."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"564","DOI":"10.1111\/j.1464-5491.2007.02149.x","article-title":"Perinatal risk factors for childhood Type 1 Diabetes Mellitus in Western Australia\u2014A population-based study (1980\u20132002)","volume":"24","author":"Haynes","year":"2007","journal-title":"Diabet. Med."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1007\/s00125-009-1648-5","article-title":"Birthweight and the risk of childhood-onset Type 1 Diabetes Mellitus: A meta-analysis of observational studies using individual patient data","volume":"53","author":"Cardwell","year":"2010","journal-title":"Diabetologia"},{"key":"ref_13","first-page":"817S","article-title":"Pr\u00e1cticas de alimentaci\u00f3n con leche infantil y resultados de la diabetes en la descendencia: Una revisi\u00f3n sistem\u00e1tica","volume":"109","author":"Nadaud","year":"2019","journal-title":"Am. J. Clin. Nutr."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"920","DOI":"10.2337\/dc17-0016","article-title":"Infant feeding and risk of Type 1 Diabetes Mellitus in two large scandinavian birth cohorts","volume":"40","author":"Sander","year":"2017","journal-title":"Diabetes Care"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"726","DOI":"10.1007\/s00125-008-0941-z","article-title":"Caesarean section is associated with an increased risk of childhood-onset Type 1 Diabetes Mellitus mellitus: A meta-analysis of observational studies","volume":"51","author":"Cardwell","year":"2008","journal-title":"Diabetologia"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Yasmin, F., Tun, H.M., Konya, T.B., Guttman, D.S., Chari, R.S., Field, C.J., Becker, A.B., Mandhane, P.J., Turvey, S.E., and Subbarao, P. (2017). Cesarean section, formula feeding, and infant antibiotic exposure: Separate and combined impacts on gut microbial changes in later infancy. Front. Pediatr., 5.","DOI":"10.3389\/fped.2017.00200"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Cobuz, C., Ungureanu-Iuga, M., Anton-Paduraru, D.-T., and Cobuz, M. (2025). Possible Use of the SUDOSCAN Nephropathy Risk Score in Chronic Kidney Disease Diagnosis: Application in Patients with Type 2 Diabetes. Biosensors, 15.","DOI":"10.3390\/bios15090620"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1203\/PDR.0b013e31815ed662","article-title":"Neonatal formula feeding leads to immunological alterations in an animal model of Type 1 Diabetes Mellitus","volume":"63","author":"Caicedo","year":"2008","journal-title":"Pediatr. Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1114","DOI":"10.1007\/s00125-005-1759-6","article-title":"Birthweight and risk of Type 1 Diabetes Mellitus in children and young adults: A population-based register study","volume":"48","author":"Dahlquist","year":"2005","journal-title":"Diabetologia"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1428","DOI":"10.1093\/aje\/kwp065","article-title":"Birth weight, early weight gain, and subsequent risk of Type 1 Diabetes Mellitus: Systematic review and meta-analysis","volume":"169","author":"Harder","year":"2009","journal-title":"Am. J. Epidemiol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1186","DOI":"10.1007\/s00125-016-3924-5","article-title":"The relationship between BMI and insulin resistance and progression from single to multiple autoantibody positivity and Type 1 Diabetes Mellitus among TrialNet Pathway to Prevention participants","volume":"59","author":"Meah","year":"2016","journal-title":"Diabetologia"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1111\/j.1467-789X.2011.00867.x","article-title":"Birth weight and subsequent risk of obesity: A systematic review and meta-analysis","volume":"12","author":"Yu","year":"2011","journal-title":"Obes. Rev."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1849","DOI":"10.2337\/db11-0400","article-title":"Maternal environment and the transgenerational cycle of obesity and diabetes","volume":"60","author":"Dabelea","year":"2011","journal-title":"Diabetes"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1186\/s13006-021-00399-9","article-title":"Impact of cesarean section on timely initiation of breastfeeding in Ethiopia: A systematic review and meta-analysis","volume":"16","author":"Getaneh","year":"2021","journal-title":"Int. Breastfeed. J."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Liu, X., Zhang, J., Liu, Y., Li, Y., and Li, Z. (2012). The association between cesarean delivery on maternal request and method of newborn feeding in china. PLoS ONE, 7.","DOI":"10.1371\/journal.pone.0037336"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Anton-Paduraru, D., Mindru, D.E., Stefania, R., Trofin, F., Cobuz, C., Cobuz, M., Sur, L.M., Petroaie, A., Maria, A., and Manole, M. (2025). Unraveling Metabolic Syndrome in Youth: The Obesity Epidemic\u2019 s Hidden Complication. Children, 12.","DOI":"10.3390\/children12040482"}],"container-title":["Life"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-1729\/15\/12\/1800\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T13:29:25Z","timestamp":1763990965000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-1729\/15\/12\/1800"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,24]]},"references-count":26,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["life15121800"],"URL":"https:\/\/doi.org\/10.3390\/life15121800","relation":{},"ISSN":["2075-1729"],"issn-type":[{"value":"2075-1729","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,24]]}}}