Family History of Diabetes and Early-Life Exposures in Iraqi Children with Type 1 Diabetes: A Hospital-Based Case–Control Study
DOI:
https://doi.org/10.59675/M423Keywords:
Type 1 diabetes; Family history; Case selection; Control selection; Misclassification; Children; Iraq.Abstract
Background: There is clear evidence for familial aggregation of childhood Type 1 Diabetes Mellitus (T1DM), but evidence of pregnancy, perinatal and childhood exposures is less consistent. Case–control comparisons in hospital settings also rely on control selection and similar exposure measurement. Objective: We estimated the odds of T1DM in children based on parent-reported diabetes in first-degree relatives in Karbala, Iraq. We discussed limitations to interpret other exposure comparisons. Methods: This hospital-based case–control study included 258 children with established T1DM, and 383 non-diabetic hospital controls recruited from the Karbala Teaching Hospital of Paediatrics between September 2014 and March 2015. We did not verify exposure records. Because the questionnaire did not reliably predict diabetes Type I in relatives, we used any reported diabetes in a first-degree relative as the main exposure. We performed the main analysis in children aged ≥12 months (n=254; n=196 controls) using Firth-penalised logistic regression adjusted for sex and age, fitted with a restricted cubic spline. Sensitivity analyses tested age restriction, recall period length, and sibling exclusion and parent-only family history. All other exposures were exploration. Results: First-degree family history was reported for 57/254 cases (22.4%) and 16/196 controls (8.2%); adjusted OR 4.56 (95% CI 2.24–9.69). The sibling estimate was 15.39 (4.16–85.02), based on 35 exposed cases and two exposed controls; the parent estimate was 2.22 (0.98–5.11). We observed no association between any relative family history and case status (OR 1.03, 0.64–1.67), and second-degree family history was more common among controls. Type-labelled family-history estimates were conflicting but unconfirmed due to the lack of verification for type. An age trend for cases was seen with gestational diabetes. The differences in early-life exposure clustered on variables that may depend on health care contact or diagnosis. Conclusions: In this hospital sample, parent-reported diabetes in a first-degree relative was associated with T1DM case status with a more modest, though still fairly imprecise sibling-category estimate (based on two exposed controls). The results do not prove causation or a genetic cause. Comparability limitations include unverified and missing reporting versus negative coding, as well as the uncertain representativeness of hospital controls in terms of type and early life.
References
1. Karvonen M, Viik-Kajander M, Moltchanova E, Libman I, LaPorte R, Tuomilehto J. Incidence of childhood Type 1 diabetes worldwide. Diabetes Care. 2000;23(10):1516–1526. https://doi.org/10.2337/diacare.23.10.1516
2. Patterson CC, Dahlquist GG, Gyürüs E, Green A, Soltész G; EURODIAB Study Group. Incidence trends for childhood Type 1 diabetes in Europe during 1989–2003 and predicted new cases 2005–20: a multicentre prospective registration study. Lancet. 2009;373(9680):2027–2033. https://doi.org/10.1016/S0140-6736(09)60568-7
3. Soltész G, Patterson CC, Dahlquist G; EURODIAB Study Group. Worldwide childhood Type 1 diabetes incidence—what can we learn from epidemiology? Pediatr Diabetes. 2007;8(Suppl 6):6–14. https://doi.org/10.1111/j.1399-5448.2007.00280.x
4. Rewers M, Ludvigsson J. Environmental risk factors for Type 1 diabetes. Lancet. 2016;387(10035):2340–2348. https://doi.org/10.1016/S0140-6736(16)30507-4
5. Redondo MJ, Oram RA, Steck AK. Genetic risk scores for Type 1 diabetes prediction and diagnosis. Curr Diab Rep. 2017;17(12):129. https://doi.org/10.1007/s11892-017-0961-5
6. Pociot F, Lernmark Å. Genetic risk factors for Type 1 diabetes. Lancet. 2016;387(10035):2331–2339. https://doi.org/10.1016/S0140-6736(16)30582-7
7. Harjutsalo V, Podar T, Tuomilehto J. Cumulative incidence of Type 1 diabetes in 10,168 siblings of Finnish young-onset Type 1 diabetic patients. Diabetes. 2005;54(2):563–569. https://doi.org/10.2337/diabetes.54.2.563
8. Sipetić S, Vlajinac H, Kocev N, Marinković J, Radmanović S, Denić L. Family history and risk of Type 1 diabetes mellitus. Acta Diabetol. 2002;39(3):111–115. https://doi.org/10.1007/s005920200028
9. Wei Y, Liu S, Andersson T, Feychting M, Kuja-Halkola R, Carlsson S. Familial aggregation and heritability of childhood-onset and adult-onset Type 1 diabetes: a Swedish register-based cohort study. Lancet Diabetes Endocrinol. 2024;12(5):320–329.
10. Dahlquist GG, Blom LG, Persson LA, Sandström AI, Wall SG. Dietary factors and the risk of developing insulin-dependent diabetes in childhood. BMJ. 1990;300(6735):1302–1306. https://doi.org/10.1136/bmj.300.6735.1302
11. Sung CJ, Plowman OM, Maxwell AJ, Rawlinson WD, Craig ME, Kim KW. Respiratory infections in pregnancy and early life—association with the development of islet autoimmunity and Type 1 diabetes in children: systematic review and meta-analysis of observational studies. eClinicalMedicine. 2025;85:103324. https://doi.org/10.1016/j.eclinm.2025.103324
12. Zhai Y, Gou H, Sun X. The association between gestational age and Type 1 diabetes mellitus in children and adolescents: a systematic review and network meta-analysis. Paediatr Perinat Epidemiol. 2025;39(2):220–229. https://doi.org/10.1111/ppe.13170
13. Krischer JP, Liu X, Lernmark Å, Hagopian WA, Rewers MJ, She JX, et al.; TEDDY Study Group. Predictors of the initiation of islet autoimmunity and progression to multiple autoantibodies and clinical diabetes: the TEDDY Study. Diabetes Care. 2022;45(10):2271–2281. https://doi.org/10.2337/dc21-2612
14. Krischer JP, Lynch KF, Lernmark Å, Hagopian WA, Rewers MJ, She JX, et al.; TEDDY Study Group. Genetic and environmental interactions modify the risk of diabetes-related autoimmunity by 6 years of age: the TEDDY Study. Diabetes Care. 2017;40(9):1194–1202. https://doi.org/10.2337/dc17-0238
15. Isaacs SR, Roy A, Dance B, Ward EJ, Foskett DB, Maxwell AJ, et al. Enteroviruses and risk of islet autoimmunity or Type 1 diabetes: systematic review and meta-analysis of controlled observational studies detecting viral nucleic acids and proteins. Lancet Diabetes Endocrinol. 2023;11(8):578–592. https://doi.org/10.1016/S2213-8587(23)00122-5
16. Yang S, Zhao B, Zhang Z, Dai X, Zhang Y, Cui L. Association between enterovirus infection and clinical Type 1 diabetes mellitus: systematic review and meta-analysis of observational studies. Epidemiol Infect. 2021;150:e23. https://doi.org/10.1017/S0950268821002442
17. Lampousi AM, Carlsson S, Löfvenborg JE. Dietary factors and risk of islet autoimmunity and Type 1 diabetes: a systematic review and meta-analysis. EBioMedicine. 2021;72:103633. https://doi.org/10.1016/j.ebiom.2021.103633
18. Harder T, Roepke K, Diller N, Stechling Y, Dudenhausen JW, Plagemann A. Birth weight, early weight gain, and subsequent risk of Type 1 diabetes: systematic review and meta-analysis. Am J Epidemiol. 2009;169(12):1428–1436. https://doi.org/10.1093/aje/kwp065
19. Abdaljabbar HN, Al-Rubae AM, Faraj SA, Alsaffar H, Taher TMJ. Risk factors for Type 1 diabetes mellitus in children living in Karbala province, Iraq. Curr Pediatr Res. 2021;25(7):663–668.
20. Moussa MAA, Alsaeid M, Refai TMK, Abdella N, Al-Sheikh N, Gomez JE. Factors associated with Type 1 diabetes in Kuwaiti children. Acta Diabetol. 2005;42(3):129–137. https://doi.org/10.1007/s00592-005-0192-0
21. Altobelli E, Chiarelli F, Valenti M, Verrotti A, Blasetti A, Di Orio F. Family history and risk of insulin-dependent diabetes mellitus: a population-based case-control study. Acta Diabetol. 1998;35(1):57–60. https://doi.org/10.1007/s005920050102
22. Dahlquist GG, Patterson C, Soltész G; EURODIAB Substudy 2 Study Group. Perinatal risk factors for childhood Type 1 diabetes in Europe. Diabetes Care. 1999;22(10):1698–1702. https://doi.org/10.2337/diacare.22.10.1698
23. McKinney PA, Parslow R, Gurney KA, Law GR, Bodansky HJ, Williams R. Perinatal and neonatal determinants of childhood Type 1 diabetes: a case-control study in Yorkshire, UK. Diabetes Care. 1999;22(6):928–932. https://doi.org/10.2337/diacare.22.6.928
24. Stene LC, Magnus P, Lie RT, Søvik O, Joner G; Norwegian Childhood Diabetes Study Group. No association between preeclampsia or cesarean section and incidence of Type 1 diabetes among children: a large, population-based cohort study. Pediatr Res. 2003;54(4):487–490. https://doi.org/10.1203/01.PDR.0000081301.25600.5D
25. Algert CS, McElduff A, Morris JM, Roberts CL. Perinatal risk factors for early onset of Type 1 diabetes in a 2000–2005 birth cohort. Diabet Med. 2009;26(12):1193–1197. https://doi.org/10.1111/j.1464-5491.2009.02878.x
26. Cardwell CR, Stene LC, Joner G, Cinek O, Svensson J, Goldacre MJ, et al. Caesarean section is associated with an increased risk of childhood-onset Type 1 diabetes mellitus: a meta-analysis of observational studies. Diabetologia. 2008;51(5):726–735. https://doi.org/10.1007/s00125-008-0941-z
27. Visalli N, Sebastiani L, Adorisio E, Conte A, De Cicco AL, D'Elia R, et al.; IMDIAB Group. Environmental risk factors for Type 1 diabetes in Rome and province. Arch Dis Child. 2003;88(8):695–698. https://doi.org/10.1136/adc.88.8.695
28. Wacholder S, McLaughlin JK, Silverman DT, Mandel JS. Selection of controls in case-control studies. I. Principles. Am J Epidemiol. 1992;135(9):1019–1028. https://doi.org/10.1093/oxfordjournals.aje.a116396
29. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet. 2007;370(9596):1453–1457. https://doi.org/10.1016/S0140-6736(07)61602-X
30. Vandenbroucke JP, von Elm E, Altman DG, Gøtzsche PC, Mulrow CD, Pocock SJ, et al.; STROBE Initiative. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. PLoS Med. 2007;4(10):e297. https://doi.org/10.1371/journal.pmed.0040297
31. Firth D. Bias reduction of maximum likelihood estimates. Biometrika. 1993;80(1):27–38. https://doi.org/10.1093/biomet/80.1.27
32. Heinze G, Schemper M. A solution to the problem of separation in logistic regression. Stat Med. 2002;21(16):2409–2419. https://doi.org/10.1002/sim.1047
33. Harrell FE Jr, Lee KL, Pollock BG. Regression models in clinical studies: determining relationships between predictors and response. J Natl Cancer Inst. 1988;80(15):1198–1202. https://doi.org/10.1093/jnci/80.15.1198
34. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Series B Methodol. 1995;57(1):289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
35. Cardwell CR, Stene LC, Joner G, Davis EA, Cinek O, Rosenbauer J, et al. Birthweight and the risk of childhood-onset Type 1 diabetes: a meta-analysis of observational studies using individual patient data. Diabetologia. 2010;53(4):641–651. https://doi.org/10.1007/s00125-009-1648-5
36. Cardwell CR, Shields MD, Carson DJ, Patterson CC. A meta-analysis of the association between childhood Type 1 diabetes and atopic disease. Diabetes Care. 2003;26(9):2568–2574. https://doi.org/10.2337/diacare.26.9.2568
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Academic International Journal of Medical Sciences
This work is licensed under a Creative Commons Attribution 4.0 International License.
