Volume 34, Issue 2 (March & April 2026)                   J Adv Med Biomed Res 2026, 34(2): 175-183 | Back to browse issues page

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Namiranian N, Mirhosseini N, Foroozanfar Z, Khaki A, Mahmoudi Kohani H A, Injinari N. Risk Factors Associated with Early-Onset Type 1 Diabetes Mellitus in Children Under Five Years: A Cross-Sectional Study in Yazd, Iran. J Adv Med Biomed Res 2026; 34 (2) :175-183
URL: http://journal.zums.ac.ir/article-1-7868-en.html
1- Diabetes Research Center, Non-Communicable Diseases Research Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
2- Pediatric Endocrinology, Department of Pediatrics, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
3- Diabetes Research Center, Non-Communicable Diseases Research Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
4- Diabetes Research Center, Non-Communicable Diseases Research Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran & Department of Persian Medicine, School of Persian Medicine, Shahid Sadoughi University of Medical Sciences, Ardakan, Yazd, Iran , nastaraninjinari@gmail.com
Abstract:   (363 Views)
Background & Objective:  Type 1 diabetes mellitus (T1DM) is a common autoimmune disease in children. Recent trends show a decreasing age at onset, raising concerns about contributing factors. This study aimed to identify factors associated with early‑onset T1DM in children under five years of age in Yazd, Iran.
 Materials & Methods:  This cross-sectional study analyzed 108 newly diagnosed T1DM patients registered with the Iran Rare Diseases Foundation between March 2020 and March 2024. Participants were divided into two groups based on age at diagnosis:  ≤5 years and >5 years. Data on family history, pregnancy-related, neonatal, and early childhood factors were collected via standardized checklists and parental interviews. Statistical analyses, including logistic regression, were performed to evaluate factors associated with early-onset T1DM.
Results:  Of the participants, 22.2% were diagnosed at ≤5 years of age. Maternal infection during pregnancy was significantly more common among early-onset cases (20.8% vs. 4.8%, p=0.025), increasing the odds of early-onset T1DM by 5.26 times. Introduction of cow’s milk at or after one year of age showed a protective effect against early-onset T1DM (OR= 0.07, p=0.027). No other factors were significantly associated with early-onset T1DM.
Conclusion:  Maternal infections during pregnancy and early introduction of cow’s milk are important factors associated with early-onset T1DM in children under five years of age. These findings highlight the potential role of prenatal and nutritional factors in the development of early-onset T1DM and emphasize the need for targeted prevention strategies.
 
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Type of Study: Original Research Article | Subject: Clinical Medicine
Received: 2025/09/28 | Accepted: 2026/04/12 | Published: 2026/05/20

References
1. Mackay IM, Arden KE, Nitsche A. Real-time PCR in virology. Nucleic Acids Res. 2002 15;30(6):1292-305.
2. Navarro E, Serrano-Heras G, Castaño MJ, Solera JJ. Real-time PCR detection chemistry. Clinica Chimica Acta. 2015 15; 439:231-50. [DOI:10.1016/j.cca.2014.10.017] [PMID]
3. Frings A, Hold V, Steinwender G, El-Shabrawi Y, Ardjomand N. Use of true net power in intraocular lens power calculations in eyes with prior myopic laser refractive surgery. Int Ophthalmol. 2014; 34:1091-6. [DOI:10.1007/s10792-014-9916-x] [PMID]
4. Kim SW, Kim EK, Cho BJ,Sun W,Ki Y,Tae K.Use of the pentacam true net corneal power for intraocular lens calculation in eyes after refractive corneal surgery. J Refractive Surg. 2009 ;25(3):285-9. [DOI:10.3928/1081597X-20090301-08] [PMID]
5. Strain JF, Rahmani M, Donna D, Owen Ch, Jafri H,Vlassenko A,et al. Accuracy of TrUE-Net in comparison to established white matter hyperintensity segmentation methods: An independent validation study. NeuroImage. 285, 120494 (2024). [DOI:10.1016/j.neuroimage.2023.120494] [PMID] [PMCID]
6. Rajamani M, Maile A, Sugunan AP, Vijayachari P. TrueNat™-micro real-time-polymerase chain reaction for rapid diagnosis of leptospirosis at minimal resource settings. Indian J Med Res. 2021;154(1):115-20. [DOI:10.4103/ijmr.IJMR_2539_20] [PMID] [PMCID]
7. Inbaraj LR, Daniel J, Rajendran P, Bhaskar A, et al. TrueNat MTB assays for pulmonary tuberculosis and rifampicin resistance in adults. Coch Database System Rev. 2023;2023(1):CD015543.
8. Sowjanya DS, Behera G, Ramana Reddy VV, Praveen JV. CBNAAT: a novel diagnostic tool for rapid and specific detection of mycobacterium tuberculosis in pulmonary samples. Int J Health Res Modern Integr Med Sci. 2014:2394-8612.
9. Kandi S, Reddy V, Nagaraja SB. Diagnosis of pulmonary and extra pulmonary tuberculosis: How best is CBNAAT when compared to conventional methods of TB detection. Pulm Res Respir Med Open J. 2017;4(2):38-41 [DOI:10.17140/PRRMOJ-4-137]
10. Gupta S, Srivastava A, Kumar A, Mohan N. Relevance of CBNAAT in the early diagnosis of suspected tubercular swelling. MGM J Med Sci. 2023;10(3):500-4. [DOI:10.4103/mgmj.mgmj_87_23]
11. Fraga D, Meulia T, Fenster S. Real‐time PCR. Current protocols essential laboratory techniques. 2014;8(1):10-3 [DOI:10.1002/9780470089941.et1003s08]
12. Broeders S, Huber I, Grohmann L, Berben G, Taverniers I, Mazzara M,et al. Guidelines for validation of qualitative real-time PCR methods. Trend Food Sci Technol. 2014;37(2):115-26. [DOI:10.1016/j.tifs.2014.03.008]
13. Dewan R, Anuradha S, Khanna A, Garg S, Singla S, Ish P,et al. Role of cartridge-based nucleic acid amplification test (CBNAAT) for early diagnosis of pulmonary tuberculosis in HIV. J Indian Acad Clin Med. 2015;16(2):114-7.
14. Forootan A, Sjöback R, Björkman J, Sjögreen B, Linz L, Kubista M. Methods to determine limit of detection and limit of quantification in quantitative real-time PCR (qPCR). Biomolec Detect Quant. 2017;12:1-6. [DOI:10.1016/j.bdq.2017.04.001] [PMID] [PMCID]
15. Sharma M, Khan S, Chaurasia M, Bhatia S, Verma P. Comparative analysis of results of RT-PCR and TrueNat in diagnosis of covid 19. Indian J Med Microbiol. 2021;39:S57. [DOI:10.1016/j.ijmmb.2021.08.198] [PMCID]
16. Jaiswal A, Singh M, Chakraborty A. Comparative evaluation of TrueNat reverse transcription-polymerase chain reaction with commercially available reverse transcription-polymerase chain reaction kits for COVID-19 diagnosis. Adv Human Biol. 2022;12(1):34-7 [DOI:10.4103/aihb.aihb_120_21]
17. Ghoshal, U, Vasanth S. , Tejan N. A guide to laboratory diagnosis of corona virus disease-19 for the gastroenterologists. Indian J Gastroenterol. 2020; 39: 236-42. [DOI:10.1007/s12664-020-01082-3] [PMID] [PMCID]
18. Komanapalli SK, Prasad U, Atla B, Nammi V, Yendluri D. Role of CB-NAAT in diagnosing extra pulmonary tuberculosis in correlation with FNA in a tertiary care center. Int J Res Med Sci. 2018;6(12):4039-45. [DOI:10.18203/2320-6012.ijrms20184904]
19. Nishal N, Arjun P, Arjun R, Ameer KA, Nair S, Mohan A. Diagnostic yield of CBNAAT in the diagnosis of extrapulmonary tuberculosis: A prospective observational study. Lung India. 2022;39(5):443-8. [DOI:10.4103/lungindia.lungindia_165_22] [PMID] [PMCID]
20. Hindson CM, Chevillet JR, Briggs HA, Gallichotte EN, Ruf IK, Hindson BJ, et al. Absolute quantification by droplet digital PCR versus analog real-time PCR. Nature Method. 2013;10(10):1003-5. [DOI:10.1038/nmeth.2633] [PMID] [PMCID]
21. Singh C, Roy-Chowdhuri S. Quantitative real-time PCR: recent advances. Clin Applic PCR. 2016:161-76.
22. Ranjan P, Rukadikar AR, Hada V, Mohanty A, Singh P. Diagnostic evaluation of Tru-Nat MTB/Rif test in comparison with microscopy for diagnosis of pulmonary tuberculosis at tertiary care hospital of eastern Uttar Pradesh. Iran J Microbiol. 2024;16(4):470. [DOI:10.18502/ijm.v16i4.16305] [PMID] [PMCID]
23. Akhtar S, Kaur A, Kumar D, Sahni B, Chouhan R, Tabassum N,et al. Diagnostic accuracy between CBNAAT, TrueNat, and smear microscopy for diagnosis of pulmonary tuberculosis in Doda District of Jammu and Kashmir-A comparative study. J Clin Diag Res. 2022;16(11).
24. Nanda S, Bansal MK, Singh P, Shrivastav AK, Malav MK, Prakash C et al.Evaluation of the cerebrospinal fluid (CSF)-Truenat assay: A novel chip-based test in the diagnosis and management of tubercular meningitis at a tertiary care hospital. Cureus. 2024;16(11). [DOI:10.7759/cureus.74522]
25. Ryu W. (2016). Diagnosis and methods. In Elsevier eBooks (pp. 47-62). [DOI:10.1016/B978-0-12-800838-6.00004-7] [PMID] [PMCID]
26. Ram B, Raj S, Kumar R, Muni S, Kumar S, Kumari N. A comparative study between Cbnaat and Truenat on pattern of drug resistance in osteoarticular tuberculosis.J Res Med Sci. 2024; 18:296-9.
27. Ingole NA, Nataraj G. Comparison of CBNAAT and conventional real time RT PCR for HIV 1 viral load testing. Indian J Med Microbiol. 2021;39(4):504-8. [DOI:10.1016/j.ijmmb.2021.05.007] [PMID]
28. Ghoshal U, Garg A, Vasanth S, Arya AK, Pandey A, Tejan N,et al. Assessing a chip based rapid RTPCR test for SARS CoV-2 detection (TrueNat assay): A diagnostic accuracy study. PLoS One. 2021;16(10):e0257834. [DOI:10.1371/journal.pone.0257834] [PMID] [PMCID]
29. Riya Mishra, Rahul Pal, Raj Kumar Mandal. Emerging technologies in tuberculosis diagnosis: A comprehensive review. Int J Pharmaceut Res Develop. 2025;7(1):265-277. [DOI:10.33545/26646862.2025.v7.i1d.119]
30. Garg A, Agarwal L, Mathur R. Role of geneXpert or CBNAAT in diagnosing tuberculosis: Present scenario. Med J Dr. DY Patil Univ. 2022;15(1):14-9 [DOI:10.4103/mjdrdypu.mjdrdypu_182_20]
31. Birhman N, Payal N, Khandait M, Bhardwaj M. Comparative study on conventional diagnostic methods with GeneXpert and TrueNat Mycobacterium tuberculosis (MTB) assay of tuberculosis disease. MGM J Med Sci. 2024;11(3):508-13. [DOI:10.4103/mgmj.mgmj_229_24]
32. Angayarkanni B, Kumar S, Saadhali SA, Azger Dusthackeer VN. Advancement in the molecular diagnosis of Tuberculosis. InTranslational Research in Biomedical Sciences: Recent Progress and Future Prospects 2024 (pp. 191-205). Singapore: Springer Nature Singapore. [DOI:10.1007/978-981-97-1777-4_13]
33. Kralik P, Ricchi M. A basic guide to real time PCR in microbial diagnostics: definitions, parameters, and everything. Front Microbiol. 2017; 8:108. [DOI:10.3389/fmicb.2017.00108] [PMID] [PMCID]

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