Fractures in children and adolescents with diabetes mellitus during 2001-2020

Fractures in children and adolescents with diabetes mellitus during 2001-2020 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Fractures in children and adolescents with diabetes mellitus during 2001-2020 Galia Zacay, Hagit Gabay, Liana Tripto-Shkolnik, Noah Gruber, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4949270/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose: To compare fracture risk among paediatric patients, between those with diabetes mellitus (DM) and a matched comparison group. Methods: In this registry-based cohort study, individuals who were diagnosed with DM during 2001-2020, at age 1-17 years, were matched in a 1:5 ratio to a comparison group. Clinical, laboratory and demographic data were obtained from the electronic database of Meuhedet Health Services. Results: The DM and comparison groups included 1049 and 5245 individuals, respectively. The median age at DM diagnosis was 10.9 years. The median follow-up period of both groups was 5.5 years (IQR 3.6-8.2). We did not find a statistically significant risk for fractures among children with DM (adjusted hazard ratio (HR) 1.10, 95% confidence interval (CI) 0.93-1.31, p=0.25). In a subgroup analysis of boys aged >11 years at DM diagnosis, the adjusted HR for fractures was 1.47 (95%CI 1.06-2.04, p=0.02) relative to the comparison group. In a multivariate analysis, male gender (adjusted HR 1.99, 95%CI 1.46-2.73, p<0.001) and recurrent hospitalizations (adjusted HR 1.53 95%CI 1.02-2.30, p=0.04) were associated with increased risks for fractures among children with DM. Conclusions : We found increased fracture risk among boys aged >11 years at diagnosis of DM compared to a matched comparison group. diabetes fractures children adolescents Figures Figure 1 Figure 2 What is known While several studies showed impaired bone health and increased fracture risk among adults with diabetes mellitus (DM), data regarding children is still sparse. What is new: We found that among boys aged >11 years at DM diagnosis, the adjusted HR for fractures was 1.47 relative to the comparison group. Male gender and recurrent hospitalization were associated with increased risks for fractures among the DM group. Recognition of the risk factors of fractures in this population may promote developing guidance for prevention and treatment. Introduction Several studies have shown reduced bone mineral content and reduced bone mineral density (BMD), both in children and adults with type 1 diabetes (T1D) [ 1 , 2 ]. Deficits in BMD are defined as mild to moderate [ 3 ]. Other contributors to bone fragility in T1D are impaired bone microarchitecture, geometry and strength [ 4 ]. In T1D, accumulation of excessive advanced glycation end products in the bone leads to the formation of abnormal cross-links between type 1 collagen fibers, resulting in reduced bone strength [ 5 ]. Moreover, several studies have shown low concentrations of both bone formation and bone resorption markers in individuals with T1D, suggesting a state of low bone turnover [ 6 ]. Indeed, this emerging complication was the focus of the 2022 clinical practice consensus guidelines of the International Society for Pediatric and Adolescent Diabetes (ISPAD) [ 7 ]. Impaired bone quality and quantity may translate to a higher fracture risk across the life span [ 8 , 9 ]. A meta-analysis of six studies, including 39,925 adults with T1D aged 18–50 years old, verified increased fracture risk in young and middle-aged adults.[ 10 ] A 1.9-fold increased risk of any fracture and a 4.4-fold increased risk of hip fracture were reported among individuals with T1D compared to individuals without. In other studies among adult populations, reported risks of hip fracture were 3–12 fold increased in individuals with T1D [ 3 ]. Only a few studies have explored risks of fractures among children and adolescents with TID. A large population-based cohort study used data from The Health Improvement Network (THIN) in the U.K., in which 30,394 individuals aged 0–89 years with T1D were compared with 303,872 age-, sex-, and practice-matched individuals without T1D [ 8 ]. Among those with T1D, aged 0–19 years, the adjusted hazard ratios (HRs) for any fracture were 1.14 in males and 1.35 in females. Two other studies that explored the impact of glycemic control on fracture risk among the paediatric population with T1D did not include healthy comparison groups [ 11 , 12 ]. Bone fragility has been identified as a complication also of type 2 diabetes (T2D) [ 13 ]. T2D face has been reported to pose an increased risk of fracture, albeit less than that of T1D [ 14 ]. A meta-analysis of 21 studies revealed a relative risk for hip fracture of 5.67 in T1D (95% CI 3.66–9.07) and 1.34 in T2D (95% CI 1.19–1.51) [ 15 ]. Contrasting with T1D, individuals with T2D show preserved or even increased BMD compared to healthy controls [ 13 ]. Mechanisms underlying bone fragility in T2D include impaired bone quality, decreased bone turnover and reduced bone strength. In recent years, the prevalence of T2D in adolescents has rapidly increased [ 16 , 17 ]. Young-onset T2D may have a more severe phenotype than T2D occurring at an older age [ 14 ]. The aim of our study was to compare the fracture risk during childhood and adolescence, between individuals with DM and a large matched population without DM, and to identify factors that contribute to the risk. Methods Study design and data source For the purpose of this historical cohort study, we extracted information from the electronic database of Meuhedet, a health maintenance organization that provides complete healthcare services to 1.3 million people of all ages and ethnicities in Israel, across all regions of the country. A comprehensive data warehouse maintains patient information, including demographic data, laboratory tests, referrals to outpatient clinics, and diagnoses given at ambulatory medical encounters and hospital discharge letters. Study population and diagnosis of DM The study inclusion criteria were the diagnosis of DM during 2001–2020, at the age of 1–17 years, and insurance with Meuhedet at least two years before the diagnosis. The end of the follow-up period was defined as the earliest of the following three dates: age 18 years, the study census date (August 31, 2023), or the end of insurance by Meuhedet Health Services. DM was identified according to the International Classification of Diseases, Ninth Revision (ICD-9) code 250, and included both T1D and T2D. The incidence rate of T1D in Israel in 2015 was 13.8/100,000 [ 17 ]. The incidence of youth-onset T2D in Israel was 0.6/100,000 in 2008 and 3.4/100,000 in 2019 [ 17 ]. Among children and adolescents with diabetes in Israel in 2015, 92.5% had TID, 5.1% T2D and 2.4% another DM type [ 18 ]. Accordingly, we assume that during the study period (2001–2020), about 95% of our patients with DM had T1D. The DM group was matched in a 1:5 ratio to individuals from the general population who were insured by Meuhedet Health Services and not diagnosed with DM. As various factors have been reported to affect the incidence of fractures [ 19 ], we matched the comparison group by age (year and month of birth), sex, resident socioeconomic status (SES) and population sector, as detailed below. We marked the date of DM diagnosis as the index date for both groups. The exclusion criteria of both groups were any chronic disease that may affect bone health according to the (ICD)-9 codes: malignant neoplasm (ICD9 codes 140–208), parathyroid disorder (ICD9 252, 275), disorders of the pituitary gland (ICD9 253), adrenal disease (ICD9 255), ovarian and testicular hypofunction (ICD9 256–258), neuromuscular disorders (ICD9 330, 342, 343, 344, 348.1), inflammatory bowel disease (ICD9 555, 556), chronic kidney disease (ICD9 582, 585, 586), rheumatic diseases (ICD9 710, 714, 715, 720), eating disorders (ICD9 307.1, 307.5, 783) and primary bone disease (ICD9 733.0, 733.2, 733.3, 733.9, 733.92). Celiac disease (ICD9 579.3) and thyroid disorder (ICD9 240, 242–245) were not excluded, since they are common among individuals with TID, and we aimed to explore associations of these comorbidities on fracture risk. Clinical and demographic data For each child, we obtained age, sex, population sector, SES, anthropometric measurements, laboratory test results, fractures and hospitalizations. We defined recurrent hospitalization as two or more hospitalizations since DM diagnosis. The three main population sectors recorded in the Meuhedet Health Service’s database are the general Jewish population (41%), ultra-orthodox Jews (43%) and Arabs (16%). These sectors differ in paediatric fracture incidence [ 19 ]. The SES index (Points Location Intelligence, Israel), an integral part of the electronic database of Meuhedet Health Service, is based on residency address, according to classification by the Israel Central Bureau of Statistics. The index is rated on a scale of 1–10, with 1 as the lowest. For this study, we classified three levels: low (1–3), medium (4–6) and high (7–10). Laboratory results Data of HbA1C and 25-hydroxy vitamin D (25-OH-vitD) were extracted at DM diagnosis (± 90 days, the nearest to the index date); and during the entire follow-up period. Data of 25-OH-vitD test results were available from 2015. Diagnosis of fracture All the fracture events that occurred between the index date and the end of the study period were included in the analysis. The fractures were identified by coded diagnoses from an ambulatory clinic or a hospital emergency room. Fracture type was classified according to ICD-9 codes 800–829. To differentiate between a single fracture event that was recorded at repetitive visits, and two distinct fracture events, we defined a period within all the fracture diagnoses that were related to the same fracture. Accordingly, we extracted all the fracture diagnoses of the first 200 children who experienced a fracture during 2019, as we previously described [ 19 ]. We then manually reviewed the patients’ electronic medical records, and used the results as a guideline. An interval of 90 days from the previous fracture diagnosis was considered the cut-off for defining a new fracture. The sensitivities and specificities to identify two distinct fracture events were 88%, and 95%, respectively. When the same fracture event was reported more than once using different ICD-9 codes, the more specific code was used. Statistical analysis We described categorical variables as numbers and percentages, and the χ2 test to compare between proportions. Continuous variables were evaluated for normal distributions using histograms, and reported as means and standard deviations, or as medians and interquartile ranges (IQRs), as appropriate. We used the T-test to compare normally distributed variables and the Mann–Whitney test for non-normally distributed variables. We calculated incidence rate ratios using negative binomial regression models. We compared the risk for fractures between the two groups and within the DM group using Cox proportional hazard regression analyses for crude and adjusted hazard (HRs). We used Kaplan–Meier curves to illustrate the first fracture event for each child since the index date. In subgroup analyses according to sex and age at DM diagnosis, we used the typical age of entering puberty as the cut-off point. Accordingly, the boys were divided into two subgroups, ≤ 11 or > 11 years; and the girls, ≤ 10 years or > 10 years. All the statistical tests were two-sided, and p < 0.05 was considered statistically significant. Statistical analysis was performed with R version 4.3.0 (R Foundation for Statistical Computing). Ethical Considerations The Institutional Review Board of Meuhedet Health Services (number 01-10.06.20) approved the study protocol. Informed consent was waived due to de-identification of the data. Results Study population A total of 1049 children diagnosed with DM met the study criteria. The comparison group included 5245 matched children who were not diagnosed with DM before or during the follow-up period. Sociodemographic characteristics and clinical data of the two groups are presented in Table 1 . The median age at DM diagnosis was 11.4 years (IQR 7.8–13.8) in males and 10.3 years (IQR 7.4–13.0) in females. The median follow-up period was 5.48 years (IQR 3.55–8.17). The mean 25-OH-vitD values were 18.5 ± 7.2 ng/ml (n = 565) and 18.3 ± 8.0 ng/ml (n = 1,408), for the DM and comparison groups, respectively (p = 0.7). Table 1 Characteristics of children with diabetes mellitus and a matched comparison group Diabetes group (n = 1,049) Comparison group (n = 5,245) p-value Sex 1 Female 500 (47.7%) 2500 (47.7%) Male 549 (52.3%) 2745 (52.3%) Socioeconomic status 1 Low 222 (22.7%) 1110 (22.7%) Medium 523 (53.5%) 2615 (53.5%) High 232 (23.7%) 1160 (23.7%) Sector 1 Jewish general population 589 (56.1%) 2945 (56.1%) Ultra-orthodox Jews 277 (26.4%) 1385 (26.4%) Arabs 183 (17.4%) 915 (17.4%) Age at diabetes diagnosis, y 10.9 (7.5–13.4) HbA1c at diagnosis, mg% 9.7 (8.1–11.7) HbA1c during the follow up, mg% 8.3 ± 1.6 Celiac disease 126 (12.0%) 112 (2.1%) < 0.001 Thyroid disorder 108 (10.3%) 144 (2.7%) < 0.001 Median length of follow-up, years 5.48 (3.5–8.2) 5.48 (3.5–8.2) 1 Total follow up, patient-years 6,342 31,710 Continuous data are presented as medians (interquartile ranges) or means ± standard deviations. Categorical data are presented as numbers and percentages of the groups. Fracture incidence rates In the DM group, 178 (17%) had at least one fracture, as did 792 (15%) in the comparison group (p = 0.14). In the respective groups, 249 and 1019 fractures occurred. The respective overall fracture incidence rates were 393 and 321 per 10,000 patient-years (PY). This difference was not statistically significant (incidence rate ratio 1.09 95%CI = 0.94–1.25, p = 0.24). In a Cox regression analysis that controlled for patient sex, population sector, age at the index date, and a comorbidity with celiac or thyroid disease, the adjusted HR for fractures among children with DM compared to those without DM was 1.1 (95%CI 0.93–1.31, p = 0.25). Figure 1 presents in both groups, the cumulative incidence curves of the incidence of fractures from the index date. Fracture risk according to sex and age at diagnosis Figure 2 presents the results of subgroup analyses for boys according to age at diagnosis of DM. Compared to their matched counterparts, boys diagnosed at age ≤ 11 years had the same risk of fracture (adjusted HR = 1.03, 95%CI 0.79–1.34, p = 0.84); while boys diagnosed at > 11 years had a higher risk (adjusted HR = 1.48, 95%CI 1.09–2.02, p = 0.01). Among the girls, we did not find a significantly increased fracture risk for either age group examined (≤ 10 and > 10 years). the adjusted HRs were 1.32, 95%CI 0.96–1.82 (p = 0.09) among those aged ≤ 10 years at diagnosis and 0.59, 95%CI 0.32–1.07 (p = 0.08) among those aged > 10 years. Comorbidity with celiac disease A total of 126 (12%) children were diagnosed with both DM and celiac disease. We did not find an increased fracture risk among these children compared to children without either of these diseases (HR-1.37, 95%CI 0.95–1.99, p = 0.10). Fracture site Table 2 presents the sites of first fractures for children with DM and the comparison group. The most common site was the upper limb in both groups (66.3% and 67.9% of the fractures, respectively). We did not find significant differences between the groups regarding fracture sites. Table 2 First facture sites of children with diabetes mellitus and a matched comparison group Diabetes group (n = 178) Comparison group (n = 792) Upper limb carpal 9 (5.1) 31 (3.9) metacarpal 11 (6.2) 28 (3.5) phalanges 37 (20.8) 163 (20.6) radius/ulna 52 (29.2) 256 (32.3) humerus 6 (3.4) 42 (5.3) upper limb NOS 3 (1.7) 19 (2.4) Lower limb tarsal/metatarsal 20 (11.2) 48 (6.1) phalanges 8 (4.5) 34 (4.3) tibia/fibula 14 (7.9) 69 (8.7) femur 1 (0.6) 5 (0.6) patella 1 (0.6) 2 (0.2) lower limb NOS 0 (0.0) 1 (0.1) Face and skull face bone 2 (1.1) 31 (3.9) skull 0 (0.0) 0 (0.0) Trunk clavicle 1 (0.6) 14 (1.8) pelvis 0 (0.0) 1 (0.1) rib 0 (0.0) 1 (0.1) scapula 1 (0.6) 1 (0.1) vertebra 0 (0.0) 3 (0.4) Other NOS 12 (6.7) 43 (5.4) The data are presented as numbers (percentages of the total group). n, number of first fractures; NOS, not otherwise specified Variables associated with fractures in the DM group In the multivariable analysis of the DM group (Table 3 ), we adjusted for the following variables: patient sex, population sector, age at the index date, recurrent hospitalization and comorbidity with celiac or thyroid disease. Male gender (adjusted HR = 1.99, 95% CI 1.46–2.73, p < 0.001) and recurrent hospitalizations (adjusted HR = 1.53, 95% CI 1.02–2.30, p = 0.04) were associated with increased risks for fractures. We did not find an association of HbA1C levels or of 25OH-vitD with fractures; however, data regarding these parameters were incomplete. Table 3 Crude and adjusted hazard ratios, obtained from univariate and multivariable analyses, respectively, of parameters associated with fractures in children diagnosed with diabetes mellitus Crude HR (95%CI) p Adjusted HR (95%CI) p Age at diagnosis (for each additional year) 0.99 (0.95–1.04) 0.74 1.00 (0.96–1.05) 0.97 Sex : Female Ref Ref Male 2.06 (1.51–2.81) < 0.001 1.99 (1.46–2.73) < 0.001 Sector : General Jewish Ref Ref Ultra-orthodox Jews 1.01 (0.71–1.43) 0.96 0.96 (0.68–1.37) 0.83 Arabs 1.04 (0.69–1.57) 0.86 1.01 (0.66–1.53) 0.98 Celiac disease 1.23 (0.82–1.83) 0.32 1.20 (0.80–1.80) 0.38 Thyroid disease 0.52 (0.28–0.96) 0.04 0.63 (0.34–1.17) 0.14 Recurrent hospitalizations 1.54 (1.03–2.29) 0.03 1.53 (1.02–2.30) 0.04 All the variables were included in the multivariable analysis. HR-hazard ratio, CI-confidence interval Discussion Among paediatric patients with DM followed for 5.5 years after the diagnosis of DM, we did not find a statistically significant risk of fractures compared to a large comparison group. However, among the boys diagnosed with DM during pubertal years, the risk was 1.5-fold greater than that of a matched group. We report an adjusted HR for fractures among children with DM of 1.1 (95% CI 0.93–1.31). Though this result was not statistically significant, the trend was similar to the finding of the THIN study, which included 5,195 patients with T1D aged 0–19 years, and a comparison group in a ratio of 1:10. The adjusted HR for any fracture during childhood was 1.14 in males with T1D compared to the matched group, and 1.35 in females [ 8 ]. This finding and the finding of our study differ considerably from reports of a 2-6-fold increased fracture risk in adults with T1D [ 3 , 10 ]. One line of explanation may be that most fractures during childhood occur during physical activity, especially in high-risk sports like snowboarding or soccer [ 20 , 21 ]. Notably, children with T1D were reported to perform less vigorous physical activity that increases the risk of trauma and fractures than their healthy peers [ 22 ]. Moreover, in adults, fracture risk reflects a combination of increased bone fragility and increased risk of falls. The latter may be related to microvascular complications: peripheral and autonomous neuropathy, retinopathy and orthostatic hypotension [ 12 ]. Obviously, significant microvascular complications that may affect the risk of falls are less common during childhood. Interestingly, we found a 1.5-fold increased fracture risk among boys who were diagnosed with DM during pubertal years compared to the matched group. This novel finding may reflect an effect of diagnosing DM during adolescence, which is a vulnerable period for fractures, especially in boys [ 23 , 24 ]. The unique characteristics of the rapid growth of the long bones in adolescents pose a risk for fractures, as demonstrated in our previous study [ 19 ]. In individuals with T1D, deficits in BMD may develop early in the disease course [ 25 ]. In a prospective study, Weber et al. described deficits in BMD at the time of T1D diagnosis, suggestive that the negative effect on bone health begins in the pre-diabetes stage of the disease [ 25 ]. The authors also reported low bone accrual during the first year following diagnosis among those with poor glycemic control [ 25 ]. The combination of bone fragility during the pubertal spurt and the findings of the study by Weber et al. may explain our finding of increased fracture risk among boys diagnosed with DM during puberty. Among girls with DM, we did not find an increased fracture risk for either age group examined (≤ 10 and > 10 years). We report similar fracture sites in the DM and the comparison groups; the most common site was the upper limb (about two thirds of the fractures). This corroborates another study that evaluated bone fractures in children [ 11 ]. For the DM group of our cohort, we found that male gender and recurrent hospitalizations were associated with increased risks of fractures. Several studies tried to identify risk factors for fractures among individuals with TID, with inconsistent results. Poor glycemic control [ 8 , 12 , 26 , 27 ], the presence of diabetes-related complications [ 8 ] and hypoglycemia [ 28 ] were identified in some, but not all, studies as contributing to fracture risk. In the THIN study [ 8 ], each 1% increase in the average HbA1c level was associated with a 5% greater risk of fracture in males and an 11% greater risk in females. Diabetic neuropathy was a significant risk factor in males (HR 1.33, 95% CI 1.03–1.72) and females (HR 1.52, 95% CI 1.19–1.92). Diabetic retinopathy was significant only in males (HR 1.13, 95% CI 1.01–1.28) [ 8 ]. We found a trend of increased fracture risk among children with comorbidity of both DM and celiac disease. Celiac disease is known to increase bone fragility [ 29 ]; however, the risk of the comorbidity of T1D and celiac is still controversial. In a population-based study that included 4598 individuals with T1D and 958 with T1D and celiac disease, having celiac disease did not affect the fracture risk [ 30 ]. By contrast, Eckert et al showed an increased fracture risk among children and young adults with T1D and celiac disease, especially among prepubertal children. In the THIN study, the comorbidity of celiac disease was a significant risk factor in females (HR 1.80, 95% CI 1.18–2.76), but not in males [ 8 ]. Strengths and limitations The main strengths of this study were the sole focus on the age group of the paediatric population and the inclusion of a matched comparison group without diabetes. The DM and the comparison groups were matched by several factors that may affect the incidence of fractures. To the best of our knowledge, a similar study design was not previously reported. Last, the database afforded including the majority of fractures, as its comprehensive medical data comprise primary care visits, community-based emergency services and hospitalizations. The limitations of the study include the mixed population of various types of diabetes. However, as detailed above, about 95% of the cohort likely had T1D [ 17 , 18 ]. As a smaller risk of fractures has been reported for T2D than T1D, the inclusion of only patients with T1D would probably strengthen the results. Another limitation is the relatively small cohort, which limited the power of this study. Lastly, our database did not include complete laboratory results and data regarding medications provided along the entire 20 years of the study period. In conclusion, our study showed an increased fracture risk among boys who were diagnosed with diabetes during their pubertal years. Further research is needed to support our results, calculate the risk in larger cohorts, elucidate the mechanism of bone fragility and identify risk factors for fractures in the paediatric DM population. This may promote developing guidance for prevention and treatment of fragility fractures in this population. Abbreviations BMD-bone mineral density, CI-confidence interval, DM-diabetes mellitus, HR-hazard ratio, ICD-9-International Classification of Diseases, Ninth Revision, IQR-interquartile range, PY-patient-year, SES-socioeconomic status, T1D-type 1 diabetes, T2D-type 2 diabetes. Declarations Author Contributions: GZ, HG and YLS: conception and design of the study, acquisition of data. GZ and YLS: analysis and interpretation of data and drafting the initial manuscript and editing it. All the authors reviewed the manuscript, revised it and approved the final manuscript as submitted. Funding: No specific fund supports the current study. Competing Interests: The authors have no competing interests to disclose. Data Availability Statement: The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Ethics approval : This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Institutional Review Board of Meuhedet Health Services (number 01-10.06.20 ). Because there was no identification of subjects for whom data were retrieved, informed consent was waived. References Zheng Y, Rostami Haji Abadi M, Ghafouri Z, Meira Goes S, Johnston JJD, Nour M, et al (2022). 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Thayakaran R, Perrins M, Gokhale KM, Kumaran S, Narendran P, Price MJ, et al (2019). Impact of glycaemic control on fracture risk in 5368 people with newly diagnosed Type 1 diabetes: a time-dependent analysis. Diabet Med 36(8):1013-9. Epub 2019/03/09. doi: 10.1111/dme.13945. Faienza MF, Pontrelli P, Brunetti G (2022). Type 2 diabetes and bone fragility in children and adults. World J Diabetes;13(11):900-11 Epub 2022/11/29. doi: 10.4239/wjd.v13.i11.900. Shah VN (2021). Editorial: Bone health in type 1 and type 2 diabetes: current knowledge and future direction. Curr Opin Endocrinol Diabetes Obes 28(4):337-9. Epub 2021/05/15. doi: 10.1097/MED.0000000000000643. Fan Y, Wei F, Lang Y, Liu Y (2016). Diabetes mellitus and risk of hip fractures: a meta-analysis. Osteoporos Int;27(1):219-28 Epub 2015/08/13. doi: 10.1007/s00198-015-3279-7. Mayer-Davis EJ, Lawrence JM, Dabelea D, Divers J, Isom S, Dolan L, et al (2017). Incidence Trends of Type 1 and Type 2 Diabetes among Youths, 2002-2012. N Engl J Med ;376(15):1419-29Epub 2017/04/14. doi: 10.1056/NEJMoa1610187. Zuckerman Levin N, Cohen M, Phillip M, Tenenbaum A, Koren I, Tenenbaum-Rakover Y, et al (2022). Youth-onset type 2 diabetes in Israel: A national cohort. Pediatr Diabetes 23(6):649-59. Epub 2022/05/07. doi: 10.1111/pedi.13351. Israel center for diabetes registry. https://www.health.gov.il/publicationsfiles/diabetes_0-17_2015.pdf.pdf. 2015. Zacay G, Dubnov-Raz G, Modan-Moses D, Tripto-Shkolnik L, Levy-Shraga Y (2022). Epidemiology of childhood fractures in Israel during 2000-2019. Bone 154:116174. Epub 2021/09/12. doi: 10.1016/j.bone.2021.116174. Goulding A (2007). Risk factors for fractures in normally active children and adolescents. Med Sport Sci51:102-20. Epub 2007/05/17. doi: 10.1159/000103007. Randsborg PH, Gulbrandsen P, Saltyte Benth J, Sivertsen EA, Hammer OL, Fuglesang HF, et al (2013). Fractures in children: epidemiology and activity-specific fracture rates. J Bone Joint Surg Am95(7):e42. Epub 2013/04/05. doi: 10.2106/JBJS.L.00369. Valerio G, Spagnuolo MI, Lombardi F, Spadaro R, Siano M, Franzese A (2007). Physical activity and sports participation in children and adolescents with type 1 diabetes mellitus. Nutr Metab Cardiovasc Dis17(5):376-82. Epub 2007/06/15. doi: 10.1016/j.numecd.2005.10.012. Farr JN, Khosla S (2015). Skeletal changes through the lifespan--from growth to senescence. Nat Rev Endocrinol 11(9):513-21. Epub 2015/06/03. doi: 10.1038/nrendo.2015.89. Rizzoli R, Bonjour JP, Ferrari SL (2001). Osteoporosis, genetics and hormones. J Mol Endocrinol. 2001;26(2):79-94. Epub 2001/03/10. doi: 10.1677/jme.0.0260079. Weber DR, Gordon RJ, Kelley JC, Leonard MB, Willi SM, Hatch-Stein J, et al (2019). Poor Glycemic Control Is Associated With Impaired Bone Accrual in the Year Following a Diagnosis of Type 1 Diabetes. J Clin Endocrinol Metab 104(10):4511-20. Epub 2019/04/30. doi: 10.1210/jc.2019-00035. Stumpf U, Hadji P, van den Boom L, Bocker W, Kostev K (2020). Incidence of fractures in patients with type 1 diabetes mellitus-a retrospective study with 4420 patients. Osteoporos Int. 31(7):1315-22. Epub 2020/02/25. doi: 10.1007/s00198-020-05344-w. Neumann T, Samann A, Lodes S, Kastner B, Franke S, Kiehntopf M, et al (2011). Glycaemic control is positively associated with prevalent fractures but not with bone mineral density in patients with Type 1 diabetes. Diabet Med 28(7):872-5. Epub 2011/03/15. doi: 10.1111/j.1464-5491.2011.03286.x. Jensen MH, Vestergaard P (2019). Hypoglycaemia and type 1 diabetes are associated with an increased risk of fractures. Osteoporos Int. 2019;30(8):1663-70. Epub 2019/05/28. doi: 10.1007/s00198-019-05014-6. Zacay G, Weintraub I, Regev R, Modan-Moses D, Levy-Shraga Y (2024). Fracture risk among children and adolescents with celiac disease: a nationwide cohort study. Pediatr Res 95(1):386-92. Epub 2023/09/26. doi: 10.1038/s41390-023-02826-5. Reilly NR, Lebwohl B, Mollazadegan K, Michaelsson K, Green PH, Ludvigsson JF (2016). Celiac Disease Does Not Influence Fracture Risk in Young Patients with Type 1 Diabetes. J Pediatr 169:49-54. Epub 2015/11/22. doi: 10.1016/j.jpeds.2015.10.032. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4949270","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":356024053,"identity":"eb92a998-32c4-4fc2-9bb7-f48f1bb83a03","order_by":0,"name":"Galia Zacay","email":"","orcid":"","institution":"Tel Aviv University","correspondingAuthor":false,"prefix":"","firstName":"Galia","middleName":"","lastName":"Zacay","suffix":""},{"id":356024055,"identity":"5cfb0ada-7f1a-480c-ad25-9930b0e170b9","order_by":1,"name":"Hagit Gabay","email":"","orcid":"","institution":"Meuhedet Health Services","correspondingAuthor":false,"prefix":"","firstName":"Hagit","middleName":"","lastName":"Gabay","suffix":""},{"id":356024056,"identity":"6574e789-d9a9-48c0-afaa-c30b70f00834","order_by":2,"name":"Liana Tripto-Shkolnik","email":"","orcid":"","institution":"Tel Aviv University","correspondingAuthor":false,"prefix":"","firstName":"Liana","middleName":"","lastName":"Tripto-Shkolnik","suffix":""},{"id":356024057,"identity":"e8e7d6de-dd9a-44fe-93b3-158b56625716","order_by":3,"name":"Noah Gruber","email":"","orcid":"","institution":"Tel Aviv University","correspondingAuthor":false,"prefix":"","firstName":"Noah","middleName":"","lastName":"Gruber","suffix":""},{"id":356024058,"identity":"32dcd265-c17a-423a-a116-99be6fab6110","order_by":4,"name":"Dalit Modan-Moses","email":"","orcid":"","institution":"Tel Aviv University","correspondingAuthor":false,"prefix":"","firstName":"Dalit","middleName":"","lastName":"Modan-Moses","suffix":""},{"id":356024059,"identity":"c36c135e-b0f4-4ba5-a7a9-6e9821a4ddec","order_by":5,"name":"Yael Levy-Shraga","email":"data:image/png;base64,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","orcid":"","institution":"Tel Aviv University","correspondingAuthor":true,"prefix":"","firstName":"Yael","middleName":"","lastName":"Levy-Shraga","suffix":""}],"badges":[],"createdAt":"2024-08-21 06:50:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4949270/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4949270/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66674068,"identity":"61bc4f9c-c15b-4dd8-8e5d-f3c35088fa47","added_by":"auto","created_at":"2024-10-15 10:56:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":620629,"visible":true,"origin":"","legend":"\u003cp\u003eCumulative incidence curves demonstrating the incidence of fractures from the index date in children diagnosed with DM (n=1,049) and in the comparison group (n=5,245).\u003c/p\u003e","description":"","filename":"Figures121.8.24.png","url":"https://assets-eu.researchsquare.com/files/rs-4949270/v1/30f71724f320ebba2cb1a8b2.png"},{"id":66674067,"identity":"eaec052c-746d-4da3-800a-14f1cdcf0fb6","added_by":"auto","created_at":"2024-10-15 10:56:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":793377,"visible":true,"origin":"","legend":"\u003cp\u003eCumulative incidence curves demonstrating the incidence of fractures from the index date among boys according to age (years) at the index date: (A) boys aged ≤11, and (b) boys aged \u0026gt;11.\u003c/p\u003e\n\u003cp\u003eDM, diabetes mellitus\u003c/p\u003e","description":"","filename":"Figure221.8.24.png","url":"https://assets-eu.researchsquare.com/files/rs-4949270/v1/d6df8547936f412cbafe0ba7.png"},{"id":66676059,"identity":"eabd53d8-c9a2-416c-bda6-40bccce4d314","added_by":"auto","created_at":"2024-10-15 11:12:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2481720,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4949270/v1/8aad866f-db10-4088-a2fd-d612970e2524.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Fractures in children and adolescents with diabetes mellitus during 2001-2020","fulltext":[{"header":"What is known","content":"\u003cul\u003e\n \u003cli\u003eWhile several studies showed impaired bone health and increased fracture risk\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eamong adults with diabetes mellitus (DM), data regarding children is still sparse.\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eWhat is new:\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eWe found that among\u0026nbsp;boys aged \u0026gt;11 years at DM diagnosis, the adjusted HR for fractures was 1.47 relative to the comparison group.\u003c/li\u003e\n \u003cli\u003eMale gender and recurrent hospitalization were associated with increased risks for fractures among the DM group.\u003c/li\u003e\n \u003cli\u003eRecognition of the risk factors of fractures in this population may promote developing guidance for prevention and treatment.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Introduction","content":"\u003cp\u003eSeveral studies have shown reduced bone mineral content and reduced bone mineral density (BMD), both in children and adults with type 1 diabetes (T1D) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Deficits in BMD are defined as mild to moderate [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Other contributors to bone fragility in T1D are impaired bone microarchitecture, geometry and strength [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In T1D, accumulation of excessive advanced glycation end products in the bone leads to the formation of abnormal cross-links between type 1 collagen fibers, resulting in reduced bone strength [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Moreover, several studies have shown low concentrations of both bone formation and bone resorption markers in individuals with T1D, suggesting a state of low bone turnover [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Indeed, this emerging complication was the focus of the 2022 clinical practice consensus guidelines of the International Society for Pediatric and Adolescent Diabetes (ISPAD) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eImpaired bone quality and quantity may translate to a higher fracture risk across the life span [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. A meta-analysis of six studies, including 39,925 adults with T1D aged 18\u0026ndash;50 years old, verified increased fracture risk in young and middle-aged adults.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] A 1.9-fold increased risk of any fracture and a 4.4-fold increased risk of hip fracture were reported among individuals with T1D compared to individuals without. In other studies among adult populations, reported risks of hip fracture were 3\u0026ndash;12 fold increased in individuals with T1D [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOnly a few studies have explored risks of fractures among children and adolescents with TID. A large population-based cohort study used data from The Health Improvement Network (THIN) in the U.K., in which 30,394 individuals aged 0\u0026ndash;89 years with T1D were compared with 303,872 age-, sex-, and practice-matched individuals without T1D [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Among those with T1D, aged 0\u0026ndash;19 years, the adjusted hazard ratios (HRs) for any fracture were 1.14 in males and 1.35 in females. Two other studies that explored the impact of glycemic control on fracture risk among the paediatric population with T1D did not include healthy comparison groups [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBone fragility has been identified as a complication also of type 2 diabetes (T2D) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. T2D face has been reported to pose an increased risk of fracture, albeit less than that of T1D [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. A meta-analysis of 21 studies revealed a relative risk for hip fracture of 5.67 in T1D (95% CI 3.66\u0026ndash;9.07) and 1.34 in T2D (95% CI 1.19\u0026ndash;1.51) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Contrasting with T1D, individuals with T2D show preserved or even increased BMD compared to healthy controls [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Mechanisms underlying bone fragility in T2D include impaired bone quality, decreased bone turnover and reduced bone strength. In recent years, the prevalence of T2D in adolescents has rapidly increased [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Young-onset T2D may have a more severe phenotype than T2D occurring at an older age [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe aim of our study was to compare the fracture risk during childhood and adolescence, between individuals with DM and a large matched population without DM, and to identify factors that contribute to the risk.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and data source\u003c/h2\u003e \u003cp\u003eFor the purpose of this historical cohort study, we extracted information from the electronic database of Meuhedet, a health maintenance organization that provides complete healthcare services to 1.3\u0026nbsp;million people of all ages and ethnicities in Israel, across all regions of the country. A comprehensive data warehouse maintains patient information, including demographic data, laboratory tests, referrals to outpatient clinics, and diagnoses given at ambulatory medical encounters and hospital discharge letters.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy population and diagnosis of DM\u003c/h2\u003e \u003cp\u003eThe study inclusion criteria were the diagnosis of DM during 2001\u0026ndash;2020, at the age of 1\u0026ndash;17 years, and insurance with Meuhedet at least two years before the diagnosis. The end of the follow-up period was defined as the earliest of the following three dates: age 18 years, the study census date (August 31, 2023), or the end of insurance by Meuhedet Health Services. DM was identified according to the International Classification of Diseases, Ninth Revision (ICD-9) code 250, and included both T1D and T2D. The incidence rate of T1D in Israel in 2015 was 13.8/100,000 [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The incidence of youth-onset T2D in Israel was 0.6/100,000 in 2008 and 3.4/100,000 in 2019 [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Among children and adolescents with diabetes in Israel in 2015, 92.5% had TID, 5.1% T2D and 2.4% another DM type [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Accordingly, we assume that during the study period (2001\u0026ndash;2020), about 95% of our patients with DM had T1D.\u003c/p\u003e \u003cp\u003eThe DM group was matched in a 1:5 ratio to individuals from the general population who were insured by Meuhedet Health Services and not diagnosed with DM. As various factors have been reported to affect the incidence of fractures [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], we matched the comparison group by age (year and month of birth), sex, resident socioeconomic status (SES) and population sector, as detailed below. We marked the date of DM diagnosis as the index date for both groups.\u003c/p\u003e \u003cp\u003eThe exclusion criteria of both groups were any chronic disease that may affect bone health according to the (ICD)-9 codes: malignant neoplasm (ICD9 codes 140\u0026ndash;208), parathyroid disorder (ICD9 252, 275), disorders of the pituitary gland (ICD9 253), adrenal disease (ICD9 255), ovarian and testicular hypofunction (ICD9 256\u0026ndash;258), neuromuscular disorders (ICD9 330, 342, 343, 344, 348.1), inflammatory bowel disease (ICD9 555, 556), chronic kidney disease (ICD9 582, 585, 586), rheumatic diseases (ICD9 710, 714, 715, 720), eating disorders (ICD9 307.1, 307.5, 783) and primary bone disease (ICD9 733.0, 733.2, 733.3, 733.9, 733.92). Celiac disease (ICD9 579.3) and thyroid disorder (ICD9 240, 242\u0026ndash;245) were not excluded, since they are common among individuals with TID, and we aimed to explore associations of these comorbidities on fracture risk.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eClinical and demographic data\u003c/h2\u003e \u003cp\u003e For each child, we obtained age, sex, population sector, SES, anthropometric measurements, laboratory test results, fractures and hospitalizations. We defined recurrent hospitalization as two or more hospitalizations since DM diagnosis.\u003c/p\u003e \u003cp\u003eThe three main population sectors recorded in the Meuhedet Health Service\u0026rsquo;s database are the general Jewish population (41%), ultra-orthodox Jews (43%) and Arabs (16%). These sectors differ in paediatric fracture incidence [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e The SES index (Points Location Intelligence, Israel), an integral part of the electronic database of Meuhedet Health Service, is based on residency address, according to classification by the Israel Central Bureau of Statistics. The index is rated on a scale of 1\u0026ndash;10, with 1 as the lowest. For this study, we classified three levels: low (1\u0026ndash;3), medium (4\u0026ndash;6) and high (7\u0026ndash;10).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eLaboratory results\u003c/h2\u003e \u003cp\u003eData of HbA1C and 25-hydroxy vitamin D (25-OH-vitD) were extracted at DM diagnosis (\u0026plusmn;\u0026thinsp;90 days, the nearest to the index date); and during the entire follow-up period. Data of 25-OH-vitD test results were available from 2015.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eDiagnosis of fracture\u003c/h2\u003e \u003cp\u003eAll the fracture events that occurred between the index date and the end of the study period were included in the analysis. The fractures were identified by coded diagnoses from an ambulatory clinic or a hospital emergency room. Fracture type was classified according to ICD-9 codes 800\u0026ndash;829.\u003c/p\u003e \u003cp\u003eTo differentiate between a single fracture event that was recorded at repetitive visits, and two distinct fracture events, we defined a period within all the fracture diagnoses that were related to the same fracture. Accordingly, we extracted all the fracture diagnoses of the first 200 children who experienced a fracture during 2019, as we previously described [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. We then manually reviewed the patients\u0026rsquo; electronic medical records, and used the results as a guideline. An interval of 90 days from the previous fracture diagnosis was considered the cut-off for defining a new fracture. The sensitivities and specificities to identify two distinct fracture events were 88%, and 95%, respectively. When the same fracture event was reported more than once using different ICD-9 codes, the more specific code was used.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eWe described categorical variables as numbers and percentages, and the χ2 test to compare between proportions. Continuous variables were evaluated for normal distributions using histograms, and reported as means and standard deviations, or as medians and interquartile ranges (IQRs), as appropriate. We used the T-test to compare normally distributed variables and the Mann\u0026ndash;Whitney test for non-normally distributed variables.\u003c/p\u003e \u003cp\u003eWe calculated incidence rate ratios using negative binomial regression models. We compared the risk for fractures between the two groups and within the DM group using Cox proportional hazard regression analyses for crude and adjusted hazard (HRs). We used Kaplan\u0026ndash;Meier curves to illustrate the first fracture event for each child since the index date. In subgroup analyses according to sex and age at DM diagnosis, we used the typical age of entering puberty as the cut-off point. Accordingly, the boys were divided into two subgroups, \u0026le;\u0026thinsp;11 or \u0026gt;\u0026thinsp;11 years; and the girls, \u0026le;\u0026thinsp;10 years or \u0026gt;\u0026thinsp;10 years.\u003c/p\u003e \u003cp\u003eAll the statistical tests were two-sided, and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Statistical analysis was performed with R version 4.3.0 (R Foundation for Statistical Computing).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eEthical Considerations\u003c/h2\u003e \u003cp\u003e The Institutional Review Board of Meuhedet Health Services (number 01-10.06.20) approved the study protocol. Informed consent was waived due to de-identification of the data.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eA total of 1049 children diagnosed with DM met the study criteria. The comparison group included 5245 matched children who were not diagnosed with DM before or during the follow-up period. Sociodemographic characteristics and clinical data of the two groups are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The median age at DM diagnosis was 11.4 years (IQR 7.8\u0026ndash;13.8) in males and 10.3 years (IQR 7.4\u0026ndash;13.0) in females. The median follow-up period was 5.48 years (IQR 3.55\u0026ndash;8.17). The mean 25-OH-vitD values were 18.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2 ng/ml (n\u0026thinsp;=\u0026thinsp;565) and 18.3\u0026thinsp;\u0026plusmn;\u0026thinsp;8.0 ng/ml (n\u0026thinsp;=\u0026thinsp;1,408), for the DM and comparison groups, respectively (p\u0026thinsp;=\u0026thinsp;0.7).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of children with diabetes mellitus and a matched comparison group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003cp\u003egroup\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1,049)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eComparison group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;5,245)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e500 (47.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2500 (47.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e549 (52.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2745 (52.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocioeconomic status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e222 (22.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1110 (22.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e523 (53.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2615 (53.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e232 (23.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1160 (23.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSector\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJewish general population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e589 (56.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2945 (56.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUltra-orthodox Jews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e277 (26.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1385 (26.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArabs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e183 (17.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e915 (17.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at diabetes diagnosis, y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.9 (7.5\u0026ndash;13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1c at diagnosis, mg%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.7 (8.1\u0026ndash;11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1c during the follow up, mg%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCeliac disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e126 (12.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThyroid disorder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108 (10.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144 (2.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian length of follow-up, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.48 (3.5\u0026ndash;8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.48 (3.5\u0026ndash;8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal follow up, patient-years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31,710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eContinuous data are presented as medians (interquartile ranges) or means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviations. Categorical data are presented as numbers and percentages of the groups.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eFracture incidence rates\u003c/h2\u003e \u003cp\u003eIn the DM group, 178 (17%) had at least one fracture, as did 792 (15%) in the comparison group (p\u0026thinsp;=\u0026thinsp;0.14). In the respective groups, 249 and 1019 fractures occurred. The respective overall fracture incidence rates were 393 and 321 per 10,000 patient-years (PY). This difference was not statistically significant (incidence rate ratio 1.09 95%CI\u0026thinsp;=\u0026thinsp;0.94\u0026ndash;1.25, p\u0026thinsp;=\u0026thinsp;0.24).\u003c/p\u003e \u003cp\u003eIn a Cox regression analysis that controlled for patient sex, population sector, age at the index date, and a comorbidity with celiac or thyroid disease, the adjusted HR for fractures among children with DM compared to those without DM was 1.1 (95%CI 0.93\u0026ndash;1.31, p\u0026thinsp;=\u0026thinsp;0.25). Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents in both groups, the cumulative incidence curves of the incidence of fractures from the index date.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eFracture risk according to sex and age at diagnosis\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the results of subgroup analyses for boys according to age at diagnosis of DM. Compared to their matched counterparts, boys diagnosed at age\u0026thinsp;\u0026le;\u0026thinsp;11 years had the same risk of fracture (adjusted HR\u0026thinsp;=\u0026thinsp;1.03, 95%CI 0.79\u0026ndash;1.34, p\u0026thinsp;=\u0026thinsp;0.84); while boys diagnosed at \u0026gt;\u0026thinsp;11 years had a higher risk (adjusted HR\u0026thinsp;=\u0026thinsp;1.48, 95%CI 1.09\u0026ndash;2.02, p\u0026thinsp;=\u0026thinsp;0.01). Among the girls, we did not find a significantly increased fracture risk for either age group examined (\u0026le;\u0026thinsp;10 and \u0026gt;\u0026thinsp;10 years). the adjusted HRs were 1.32, 95%CI 0.96\u0026ndash;1.82 (p\u0026thinsp;=\u0026thinsp;0.09) among those aged\u0026thinsp;\u0026le;\u0026thinsp;10 years at diagnosis and 0.59, 95%CI 0.32\u0026ndash;1.07 (p\u0026thinsp;=\u0026thinsp;0.08) among those aged\u0026thinsp;\u0026gt;\u0026thinsp;10 years.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eComorbidity with celiac disease\u003c/h2\u003e \u003cp\u003eA total of 126 (12%) children were diagnosed with both DM and celiac disease. We did not find an increased fracture risk among these children compared to children without either of these diseases (HR-1.37, 95%CI 0.95\u0026ndash;1.99, p\u0026thinsp;=\u0026thinsp;0.10).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eFracture site\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the sites of first fractures for children with DM and the comparison group. The most common site was the upper limb in both groups (66.3% and 67.9% of the fractures, respectively). We did not find significant differences between the groups regarding fracture sites.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFirst facture sites of children with diabetes mellitus and a matched comparison group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiabetes group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;178)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eComparison group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;792)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpper limb\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecarpal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31 (3.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emetacarpal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28 (3.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ephalanges\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37 (20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e163 (20.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eradius/ulna\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52 (29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e256 (32.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehumerus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42 (5.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eupper limb NOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19 (2.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLower limb\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etarsal/metatarsal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20 (11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48 (6.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ephalanges\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34 (4.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etibia/fibula\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69 (8.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efemur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (0.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epatella\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (0.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003elower limb NOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (0.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFace and skull\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eface bone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31 (3.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eskull\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTrunk\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eclavicle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14 (1.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epelvis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (0.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003erib\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (0.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003escapula\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (0.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003evertebra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (0.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOther NOS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43 (5.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eThe data are presented as numbers (percentages of the total group).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003en, number of first fractures; NOS, not otherwise specified\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eVariables associated with fractures in the DM group\u003c/h2\u003e \u003cp\u003eIn the multivariable analysis of the DM group (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), we adjusted for the following variables: patient sex, population sector, age at the index date, recurrent hospitalization and comorbidity with celiac or thyroid disease. Male gender (adjusted HR\u0026thinsp;=\u0026thinsp;1.99, 95% CI 1.46\u0026ndash;2.73, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and recurrent hospitalizations (adjusted HR\u0026thinsp;=\u0026thinsp;1.53, 95% CI 1.02\u0026ndash;2.30, p\u0026thinsp;=\u0026thinsp;0.04) were associated with increased risks for fractures. We did not find an association of HbA1C levels or of 25OH-vitD with fractures; however, data regarding these parameters were incomplete.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCrude and adjusted hazard ratios, obtained from univariate and multivariable analyses, respectively, of parameters associated with fractures in children diagnosed with diabetes mellitus\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCrude HR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted HR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at diagnosis\u003c/b\u003e (for each additional year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.99 (0.95\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.00 (0.96\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e: Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.06 (1.51\u0026ndash;2.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.99 (1.46\u0026ndash;2.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSector\u003c/b\u003e: General Jewish\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUltra-orthodox Jews\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01 (0.71\u0026ndash;1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.96 (0.68\u0026ndash;1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArabs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.04 (0.69\u0026ndash;1.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01 (0.66\u0026ndash;1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCeliac disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.23 (0.82\u0026ndash;1.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.20 (0.80\u0026ndash;1.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eThyroid disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.52 (0.28\u0026ndash;0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.63 (0.34\u0026ndash;1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRecurrent hospitalizations\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.54 (1.03\u0026ndash;2.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.53 (1.02\u0026ndash;2.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAll the variables were included in the multivariable analysis. HR-hazard ratio, CI-confidence interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eAmong paediatric patients with DM followed for 5.5 years after the diagnosis of DM, we did not find a statistically significant risk of fractures compared to a large comparison group. However, among the boys diagnosed with DM during pubertal years, the risk was 1.5-fold greater than that of a matched group.\u003c/p\u003e \u003cp\u003eWe report an adjusted HR for fractures among children with DM of 1.1 (95% CI 0.93\u0026ndash;1.31). Though this result was not statistically significant, the trend was similar to the finding of the THIN study, which included 5,195 patients with T1D aged 0\u0026ndash;19 years, and a comparison group in a ratio of 1:10. The adjusted HR for any fracture during childhood was 1.14 in males with T1D compared to the matched group, and 1.35 in females [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This finding and the finding of our study differ considerably from reports of a 2-6-fold increased fracture risk in adults with T1D [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. One line of explanation may be that most fractures during childhood occur during physical activity, especially in high-risk sports like snowboarding or soccer [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Notably, children with T1D were reported to perform less vigorous physical activity that increases the risk of trauma and fractures than their healthy peers [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Moreover, in adults, fracture risk reflects a combination of increased bone fragility and increased risk of falls. The latter may be related to microvascular complications: peripheral and autonomous neuropathy, retinopathy and orthostatic hypotension [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Obviously, significant microvascular complications that may affect the risk of falls are less common during childhood.\u003c/p\u003e \u003cp\u003eInterestingly, we found a 1.5-fold increased fracture risk among boys who were diagnosed with DM during pubertal years compared to the matched group. This novel finding may reflect an effect of diagnosing DM during adolescence, which is a vulnerable period for fractures, especially in boys [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The unique characteristics of the rapid growth of the long bones in adolescents pose a risk for fractures, as demonstrated in our previous study [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In individuals with T1D, deficits in BMD may develop early in the disease course [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In a prospective study, Weber et al. described deficits in BMD at the time of T1D diagnosis, suggestive that the negative effect on bone health begins in the pre-diabetes stage of the disease [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The authors also reported low bone accrual during the first year following diagnosis among those with poor glycemic control [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The combination of bone fragility during the pubertal spurt and the findings of the study by Weber et al. may explain our finding of increased fracture risk among boys diagnosed with DM during puberty. Among girls with DM, we did not find an increased fracture risk for either age group examined (\u0026le;\u0026thinsp;10 and \u0026gt;\u0026thinsp;10 years).\u003c/p\u003e \u003cp\u003eWe report similar fracture sites in the DM and the comparison groups; the most common site was the upper limb (about two thirds of the fractures). This corroborates another study that evaluated bone fractures in children [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor the DM group of our cohort, we found that male gender and recurrent hospitalizations were associated with increased risks of fractures. Several studies tried to identify risk factors for fractures among individuals with TID, with inconsistent results. Poor glycemic control [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], the presence of diabetes-related complications [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and hypoglycemia [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] were identified in some, but not all, studies as contributing to fracture risk. In the THIN study [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], each 1% increase in the average HbA1c level was associated with a 5% greater risk of fracture in males and an 11% greater risk in females. Diabetic neuropathy was a significant risk factor in males (HR 1.33, 95% CI 1.03\u0026ndash;1.72) and females (HR 1.52, 95% CI 1.19\u0026ndash;1.92). Diabetic retinopathy was significant only in males (HR 1.13, 95% CI 1.01\u0026ndash;1.28) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe found a trend of increased fracture risk among children with comorbidity of both DM and celiac disease. Celiac disease is known to increase bone fragility [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]; however, the risk of the comorbidity of T1D and celiac is still controversial. In a population-based study that included 4598 individuals with T1D and 958 with T1D and celiac disease, having celiac disease did not affect the fracture risk [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. By contrast, Eckert et al showed an increased fracture risk among children and young adults with T1D and celiac disease, especially among prepubertal children. In the THIN study, the comorbidity of celiac disease was a significant risk factor in females (HR 1.80, 95% CI 1.18\u0026ndash;2.76), but not in males [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eThe main strengths of this study were the sole focus on the age group of the paediatric population and the inclusion of a matched comparison group without diabetes. The DM and the comparison groups were matched by several factors that may affect the incidence of fractures. To the best of our knowledge, a similar study design was not previously reported. Last, the database afforded including the majority of fractures, as its comprehensive medical data comprise primary care visits, community-based emergency services and hospitalizations.\u003c/p\u003e \u003cp\u003eThe limitations of the study include the mixed population of various types of diabetes. However, as detailed above, about 95% of the cohort likely had T1D [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. As a smaller risk of fractures has been reported for T2D than T1D, the inclusion of only patients with T1D would probably strengthen the results. Another limitation is the relatively small cohort, which limited the power of this study. Lastly, our database did not include complete laboratory results and data regarding medications provided along the entire 20 years of the study period.\u003c/p\u003e \u003cp\u003eIn conclusion, our study showed an increased fracture risk among boys who were diagnosed with diabetes during their pubertal years. Further research is needed to support our results, calculate the risk in larger cohorts, elucidate the mechanism of bone fragility and identify risk factors for fractures in the paediatric DM population. This may promote developing guidance for prevention and treatment of fragility fractures in this population.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBMD-bone mineral density, CI-confidence interval, DM-diabetes mellitus, HR-hazard ratio, ICD-9-International Classification of Diseases, Ninth Revision, IQR-interquartile range, PY-patient-year, SES-socioeconomic status, T1D-type 1 diabetes, T2D-type 2 diabetes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eGZ, HG and YLS: conception and design of the study, acquisition of data. GZ and YLS: analysis and interpretation of data and drafting the initial manuscript and editing it. All the authors reviewed the manuscript, revised it and approved\u003csup\u003e\u0026nbsp;\u003c/sup\u003ethe final manuscript as submitted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e No specific fund supports the current study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u003c/strong\u003e The authors have no competing interests to disclose.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u0026nbsp;\u003c/strong\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Approval was granted\u0026nbsp;by the Institutional Review Board of Meuhedet Health Services (number\u0026nbsp;\u003cspan dir=\"RTL\"\u003e01-10.06.20\u003c/span\u003e). \u0026nbsp;Because there was no identification of subjects for whom data were retrieved, informed consent was waived.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eZheng Y, Rostami Haji Abadi M, Ghafouri Z, Meira Goes S, Johnston JJD, Nour M, et al (2022). Bone deficits in children and youth with type 1 diabetes: A systematic review and meta-analysis. Bone 163:116509. Epub 2022/08/02. doi: 10.1016/j.bone.2022.116509. \u003c/li\u003e\n\u003cli\u003eShah VN, Harrall KK, Shah CS, Gallo TL, Joshee P, Snell-Bergeon JK, et al. Bone mineral density at femoral neck and lumbar spine in adults with type 1 diabetes: a meta-analysis and review of the literature. Osteoporos Int. 2017;28(9):2601-10. Epub 2017/06/06. doi: 10.1007/s00198-017-4097-x. \u003c/li\u003e\n\u003cli\u003eWeber DR, Schwartz G (2016). Epidemiology of Skeletal Health in Type 1 Diabetes. Curr Osteoporos Rep 14(6):327-36. Epub 2016/10/17. doi: 10.1007/s11914-016-0333-0. \u003c/li\u003e\n\u003cli\u003eShanbhogue VV, Hansen S, Frost M, Jorgensen NR, Hermann AP, Henriksen JE, et al (2015). Bone Geometry, Volumetric Density, Microarchitecture, and Estimated Bone Strength Assessed by HR-pQCT in Adult Patients With Type 1 Diabetes Mellitus. J Bone Miner Res 30(12):2188-99. Epub 2015/06/23. doi: 10.1002/jbmr.2573. \u003c/li\u003e\n\u003cli\u003eFarlay D, Armas LA, Gineyts E, Akhter MP, Recker RR, Boivin G (2016). Nonenzymatic Glycation and Degree of Mineralization Are Higher in Bone From Fractured Patients With Type 1 Diabetes Mellitus. J Bone Miner Res 31(1):190-5. Epub 2015/08/04. doi: 10.1002/jbmr.2607. \u003c/li\u003e\n\u003cli\u003eHygum K, Starup-Linde J, Harslof T, Vestergaard P, Langdahl BL (2017). MECHANISMS IN ENDOCRINOLOGY: Diabetes mellitus, a state of low bone turnover - a systematic review and meta-analysis. Eur J Endocrinol 176(3):R137-R57. Epub 2017/01/05. doi: 10.1530/EJE-16-0652. \u003c/li\u003e\n\u003cli\u003eFrohlich-Reiterer E, Elbarbary NS, Simmons K, Buckingham B, Humayun KN, Johannsen J, et al (2022). ISPAD Clinical Practice Consensus Guidelines 2022: Other complications and associated conditions in children and adolescents with type 1 diabetes. Pediatr Diabetes 23(8):1451-67. Epub 2022/12/21. doi: 10.1111/pedi.13445. \u003c/li\u003e\n\u003cli\u003eWeber DR, Haynes K, Leonard MB, Willi SM, Denburg MR (2015). Type 1 diabetes is associated with an increased risk of fracture across the life span: a population-based cohort study using The Health Improvement Network (THIN). Diabetes Care 38(10):1913-20. Epub 2015/07/29. doi: 10.2337/dc15-0783. \u003c/li\u003e\n\u003cli\u003eStarup-Linde J, Hygum K, Harslof T, Langdahl B (2019). Type 1 Diabetes and Bone Fragility: Links and Risks. Diabetes Metab Syndr Obes 12:2539-47. Epub 2019/12/11. doi: 10.2147/DMSO.S191091.\u003c/li\u003e\n\u003cli\u003eThong EP, Herath M, Weber DR, Ranasinha S, Ebeling PR, Milat F, et al (2018). Fracture risk in young and middle-aged adults with type 1 diabetes mellitus: A systematic review and meta-analysis. Clin Endocrinol (Oxf) 89(3):314-23. Epub 2018/06/08. doi: 10.1111/cen.13761. \u003c/li\u003e\n\u003cli\u003eEckert AJ, Semler O, Schnabel D, Kostner K, Wurm D, Bechtold-Dalla Pozza S, et al (2021). Bone Fractures in Children and Young Adults With Type 1 Diabetes: Age Distribution, Fracture Location, and the Role of Glycemic Control. J Bone Miner Res. 36(12):2371-80. Epub 2021/09/28. doi: 10.1002/jbmr.4451. \u003c/li\u003e\n\u003cli\u003eThayakaran R, Perrins M, Gokhale KM, Kumaran S, Narendran P, Price MJ, et al (2019). Impact of glycaemic control on fracture risk in 5368 people with newly diagnosed Type 1 diabetes: a time-dependent analysis. Diabet Med 36(8):1013-9. Epub 2019/03/09. doi: 10.1111/dme.13945. \u003c/li\u003e\n\u003cli\u003eFaienza MF, Pontrelli P, Brunetti G (2022). Type 2 diabetes and bone fragility in children and adults. World J Diabetes;13(11):900-11 Epub 2022/11/29. doi: 10.4239/wjd.v13.i11.900. \u003c/li\u003e\n\u003cli\u003eShah VN (2021). Editorial: Bone health in type 1 and type 2 diabetes: current knowledge and future direction. Curr Opin Endocrinol Diabetes Obes 28(4):337-9. Epub 2021/05/15. doi: 10.1097/MED.0000000000000643. \u003c/li\u003e\n\u003cli\u003eFan Y, Wei F, Lang Y, Liu Y (2016). Diabetes mellitus and risk of hip fractures: a meta-analysis. Osteoporos Int;27(1):219-28 Epub 2015/08/13. doi: 10.1007/s00198-015-3279-7. \u003c/li\u003e\n\u003cli\u003eMayer-Davis EJ, Lawrence JM, Dabelea D, Divers J, Isom S, Dolan L, et al (2017). Incidence Trends of Type 1 and Type 2 Diabetes among Youths, 2002-2012. N Engl J Med ;376(15):1419-29Epub 2017/04/14. doi: 10.1056/NEJMoa1610187. \u003c/li\u003e\n\u003cli\u003eZuckerman Levin N, Cohen M, Phillip M, Tenenbaum A, Koren I, Tenenbaum-Rakover Y, et al (2022). Youth-onset type 2 diabetes in Israel: A national cohort. Pediatr Diabetes 23(6):649-59. Epub 2022/05/07. doi: 10.1111/pedi.13351. \u003c/li\u003e\n\u003cli\u003eIsrael center for diabetes registry. https://www.health.gov.il/publicationsfiles/diabetes_0-17_2015.pdf.pdf. 2015.\u003c/li\u003e\n\u003cli\u003eZacay G, Dubnov-Raz G, Modan-Moses D, Tripto-Shkolnik L, Levy-Shraga Y (2022). Epidemiology of childhood fractures in Israel during 2000-2019. Bone 154:116174. Epub 2021/09/12. doi: 10.1016/j.bone.2021.116174.\u003c/li\u003e\n\u003cli\u003eGoulding A (2007). Risk factors for fractures in normally active children and adolescents. Med Sport Sci51:102-20. Epub 2007/05/17. doi: 10.1159/000103007. \u003c/li\u003e\n\u003cli\u003eRandsborg PH, Gulbrandsen P, Saltyte Benth J, Sivertsen EA, Hammer OL, Fuglesang HF, et al (2013). Fractures in children: epidemiology and activity-specific fracture rates. J Bone Joint Surg Am95(7):e42. Epub 2013/04/05. doi: 10.2106/JBJS.L.00369. \u003c/li\u003e\n\u003cli\u003eValerio G, Spagnuolo MI, Lombardi F, Spadaro R, Siano M, Franzese A (2007). Physical activity and sports participation in children and adolescents with type 1 diabetes mellitus. Nutr Metab Cardiovasc Dis17(5):376-82. Epub 2007/06/15. doi: 10.1016/j.numecd.2005.10.012. \u003c/li\u003e\n\u003cli\u003eFarr JN, Khosla S (2015). Skeletal changes through the lifespan--from growth to senescence. Nat Rev Endocrinol 11(9):513-21. Epub 2015/06/03. doi: 10.1038/nrendo.2015.89. \u003c/li\u003e\n\u003cli\u003eRizzoli R, Bonjour JP, Ferrari SL (2001). Osteoporosis, genetics and hormones. J Mol Endocrinol. 2001;26(2):79-94. Epub 2001/03/10. doi: 10.1677/jme.0.0260079. \u003c/li\u003e\n\u003cli\u003eWeber DR, Gordon RJ, Kelley JC, Leonard MB, Willi SM, Hatch-Stein J, et al (2019). Poor Glycemic Control Is Associated With Impaired Bone Accrual in the Year Following a Diagnosis of Type 1 Diabetes. J Clin Endocrinol Metab 104(10):4511-20. Epub 2019/04/30. doi: 10.1210/jc.2019-00035. \u003c/li\u003e\n\u003cli\u003eStumpf U, Hadji P, van den Boom L, Bocker W, Kostev K (2020). Incidence of fractures in patients with type 1 diabetes mellitus-a retrospective study with 4420 patients. Osteoporos Int. 31(7):1315-22. Epub 2020/02/25. doi: 10.1007/s00198-020-05344-w. \u003c/li\u003e\n\u003cli\u003eNeumann T, Samann A, Lodes S, Kastner B, Franke S, Kiehntopf M, et al (2011). Glycaemic control is positively associated with prevalent fractures but not with bone mineral density in patients with Type 1 diabetes. Diabet Med 28(7):872-5. Epub 2011/03/15. doi: 10.1111/j.1464-5491.2011.03286.x. \u003c/li\u003e\n\u003cli\u003eJensen MH, Vestergaard P (2019). Hypoglycaemia and type 1 diabetes are associated with an increased risk of fractures. Osteoporos Int. 2019;30(8):1663-70. Epub 2019/05/28. doi: 10.1007/s00198-019-05014-6. \u003c/li\u003e\n\u003cli\u003eZacay G, Weintraub I, Regev R, Modan-Moses D, Levy-Shraga Y (2024). Fracture risk among children and adolescents with celiac disease: a nationwide cohort study. Pediatr Res 95(1):386-92. Epub 2023/09/26. doi: 10.1038/s41390-023-02826-5. \u003c/li\u003e\n\u003cli\u003eReilly NR, Lebwohl B, Mollazadegan K, Michaelsson K, Green PH, Ludvigsson JF (2016). Celiac Disease Does Not Influence Fracture Risk in Young Patients with Type 1 Diabetes. J Pediatr 169:49-54. Epub 2015/11/22. doi: 10.1016/j.jpeds.2015.10.032. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"diabetes, fractures, children, adolescents","lastPublishedDoi":"10.21203/rs.3.rs-4949270/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4949270/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose: \u003c/strong\u003eTo compare fracture risk among paediatric patients, between those with diabetes mellitus (DM) and a matched comparison group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eIn this registry-based cohort study, individuals who were diagnosed with DM during 2001-2020, at age 1-17 years, were matched in a 1:5 ratio to a comparison group. Clinical, laboratory and demographic data were obtained from the electronic database of Meuhedet Health Services.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe DM and comparison groups included 1049 and 5245 individuals, respectively. The median age at DM diagnosis was 10.9 years. The median follow-up period of both groups was 5.5 years (IQR 3.6-8.2). We did not find a statistically significant risk for fractures among children with DM (adjusted hazard ratio (HR) 1.10, 95% confidence interval (CI) 0.93-1.31, p=0.25). In a subgroup analysis of boys aged \u0026gt;11 years at DM diagnosis, the adjusted HR for fractures was 1.47 (95%CI 1.06-2.04, p=0.02) relative to the comparison group. In a multivariate analysis, male gender (adjusted HR 1.99, 95%CI 1.46-2.73, p\u0026lt;0.001) and recurrent hospitalizations (adjusted HR 1.53 95%CI 1.02-2.30, p=0.04) were associated with increased risks for fractures among children with DM.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: We found increased fracture risk among boys aged \u0026gt;11 years at diagnosis of DM compared to a matched comparison group.\u003c/p\u003e","manuscriptTitle":"Fractures in children and adolescents with diabetes mellitus during 2001-2020","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-15 10:56:00","doi":"10.21203/rs.3.rs-4949270/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f1317f8b-4755-4d08-a6ef-a5faf169f639","owner":[],"postedDate":"October 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-15T10:56:03+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-15 10:56:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4949270","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4949270","identity":"rs-4949270","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}