Contrasting BMI and Height z-Score Trajectories in Children With New-Onset T1DM: A Case-Control Study Across Latin American Centers

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Witte, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9054431/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background: Children with type 1 diabetes (T1DM) may experience some growth delay. Objective: To compare growth trajectories assessed by z-height and z-BMI over a three-year follow-up period between children with new-onset T1DM and a control group without T1DM across multiple Latin American centers. Methods: A retrospective analysis of medical records was conducted over three years (2021-2024) in children with T1DM onset and their controls from ten Latin American centers, collecting data on age, sex, and anthropometric measures. A mixed-effects model was used to analyze z-height and z-BMI over three years. Results: A total of 534 participants were included, comprising 245 children with T1DM (51.4% female; mean age, 8.8 years) and 289 controls (45.7% female; mean age, 8.1 years). The mean z-BMI in children with T1DM compared to controls was at years 0 (−0.12 vs. 0.54), 1 (0.36 vs. 0.63), 2 (0.32 vs. 0.55), and 3 (0.34 vs. 0.47). Children with T1DM had a significantly lower z-BMI than controls, with mean differences of -0.71, -0.33, and -0.28 in years 0, 1, and 2, respectively. However, by year 3, the mean difference (-0.18) was no longer significant. Z-Height in children with T1DM vs. controls was at years 1 (−0.08 vs. −0.09), 2 (−0.24 vs. −0.12), and 3 (−0.35 vs. −0.12). Z-Height remained stable in controls but declined in the T1DM group, reaching a mean difference of −0.25 (p<0.01) by year 3. These findings highlight the need to improve early diagnosis and access to diabetes technologies in Latin America. Conclusions: This study suggested that despite treatment and equalization of z-BMI, children with T1DM in Latin America experience some growth delay. Z-Height T1DM Onset and Latin American Children Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Growth during childhood can be impaired in children with type 1 diabetes (T1DM) [ 1 ]. Studies have demonstrated that children with T1DM experience decreased z-height and growth velocity following the onset of the disease [ 2 – 5 ]. A reduction in growth rate has been observed in children with T1DM due to multiple factors, with poor metabolic control being the primary contributor [ 6 , 7 ]. Nowadays, growth outcomes have improved thanks to modern insulin treatment regimens and consistent patient glycemic control [ 1 ]. At T1DM onset, children frequently show a reduced BMI due to delayed diagnosis and initiation of treatment, highlighting the essential need for early and accurate diagnosis [ 8 ]. Consistently, a previous study conducted by our group across multiple centers in Latin America found a high prevalence of diabetic ketoacidosis at disease onset, likely linked to delayed diagnosis and associated with a low BMI at the time of diagnosis [ 9 ]. Promoting normal growth and development in children with T1DM is a primary goal of T1DM treatment. To our knowledge, no multicenter study from Latin America has compared longitudinal trajectories of z-BMI and z-height in children with new-onset type 1 diabetes and healthy controls. Therefore, the objective of the present study was to compare growth trajectories assessed by z-height and z-BMI over a three-year follow-up period between children with new-onset T1DM and a control group without T1DM across multiple Latin American centers. Material and Methods We retrospectively defined a case-control study based on an analysis of medical records across 10 centers in three Latin American countries (Argentina, Peru, and Uruguay), and collected data covering the three years following the case and control definition (baseline), from 2021 to 2024. Potential cases were identified from all consecutive new-onset cases of T1DM attending the 10 centers between September 2021and February 2022. Controls were identified in equivalent numbers from the same centers, using records of children without T1DM or other known chronic conditions who routinely attended health check-ups. In the Latin American hospitals included, there are designated pediatric outpatient services for children without underlying medical conditions who present for routine assessments such as growth monitoring and immunizations. We selected the controls from these hospital-based services for healthy children. As such, these children are considered representative of the general pediatric population without chronic illness, despite being recruited within hospital settings. Beyond case-control status, the inclusion criteria were age 2 to 16, sex information, and anthropometric measures obtained at least 2 times during the follow-up window. Exclusion criteria were relocation during follow-up, psychiatric disorders, current corticosteroid therapy, the presence of genetic syndromes (e.g., Prader-Willi syndrome, Down syndrome), and pregnancy. Additionally, children with biologically implausible height values at the time of diagnosis (height z-score: 4), as defined by the Centers for Disease Control and Prevention (CDC) growth charts, were excluded [ 10 ]. Ten health centers were grouped into six categories based on common features, including geographic location and level of urbanization. The categories and their proportions were as follows: Riverside provinces (n = 80, 15%; includes Corrientes and Misiones [Argentina]), Mountain provinces (n = 108, 20.2%; Ushuaia, Río Grande, and Mendoza [Argentina]), Rural provinces (n = 51, 9.6%; Misiones [Argentina]), Urban 1 (n = 162, 30.3%; Buenos Aires, Argentina), Urban 2 (n = 47, 8.8%; Montevideo, Uruguay), and Urban 3 (n = 86, 16.1%; Lima, Peru). This grouping aimed to address potential differences in outcomes across centers or regions. Key factors considered included proximity to urban hubs, the number of healthcare staff, challenges in accessing services, rural versus urban classification, center complexity, availability of medical equipment, patient understanding and adherence to treatments, and the presence of a multidisciplinary care team, among others. For instance, the distinction between urban center 1 (Buenos Aires) and urban center 2 (Montevideo) reflects differences in population density. Buenos Aires and its surrounding suburbs, with a population of approximately 15.6 million, make up Argentina's largest metropolitan area. In contrast, Montevideo, home to approximately 1.3 million residents, is Uruguay's largest city. These population disparities reflect significant differences in urbanization and infrastructure, influencing factors such as access to healthcare, transportation networks, and population density. All participating centers serve as the main tertiary pediatric diabetes care facility in their region, meaning that nearly all presumed new-onset T1DM cases in these areas are referred there. Each center included in the study selected one physician to submit the information to prevent duplication. Each submission was reviewed for transcription errors and missing data. The protocol was submitted to the Ethics Review Board of each center, and all obtained approval with a waiver of consent. The study was approved by the institutional review board (IRB) numbers: 8828-2023508; PRISABA BA 10224; 1476/2024; 08/24; 024/24; 07 − 04; 2024-696-GDEBA-SSGIEPYFMSALGP. All collected data was pseudonymized, and only unidentified data was sent to the coordinating center. Upon consideration of follow-up data, fewer than 5% of the initially included cases were lost, primarily due to relocation or the absence of at least two data points. The following information was gathered: sex, date of birth, age at diabetes onset, and anthropometric measurements in the T1DM and control groups. In the T1DM group, initial height and weight measurements were taken 2 months post-diagnosis, as children often experience weight loss due to dehydration and insulin deficiency at the onset of T1DM. Height and weight were measured with participants dressed in lightweight clothing and barefoot, with height recorded to the nearest 0.1 cm using a wall-mounted stadiometer and weight to the nearest 0.1 kg on a medical scale. A medical doctor recorded these anthropometric measurements annually at subsequent clinic visits. In addition, information on hemoglobin A1c (HbA1c) (%) was collected yearly in the T1DM group during the follow-up. Therefore, follow-up measurements were scheduled as closely as possible to the initial measurement date (year 0), at intervals of + 1 year, + 2 years, and + 3 years. Children were categorized according to CDC guidelines as underweight (< 5th percentile), normal weight (5th to < 85th percentile), overweight (85th to < 95th percentile), or obese (≥ 95th percentile) [ 11 ]. Additionally, BMI and height were converted to z-scores (based on CDC standards) for analysis as continuous variables, allowing comparison with a broad base of existing literature [ 11 ]. Short stature was defined as z-Height < − 2. Although CDC growth references may not perfectly reflect Latin American populations, they were used in this study due to the absence of region-specific reference standards and to facilitate comparison with the existing international literature. The diagnosis of T1DM was based on the criteria established by the American Diabetes Association (ADA) [ 12 ]. HbA1c levels were measured as a percentage using the National Glycohemoglobin Standardization Program standards and assessed with the Bio-Rad D-10™ Dual Program, which uses ion-exchange high-performance liquid chromatography. HbA1c values were mathematically standardized to a reference range of 4.05%–6.05% according to the Diabetes Control and Complications Trial using the multiple-of-the-mean method. Data analysis: The primary objective was to compare z-height and z-BMI trends over a three-year follow-up between children with new-onset T1DM and a control group without T1DM across multiple Latin American centers. Descriptive statistics for the variables were reported as mean ± SD. Chi-square tests were used to compare proportions, with Fisher’s exact test applied when > 20% of cells had expected frequencies < 5. The Shapiro-Wilks test was used to check for the normality of continuous variables. For comparisons between two groups with normally distributed data, a Student’s t-test was conducted. The progression of height and BMI in children was evaluated using age- and sex-adjusted z-scores. A mixed-effect model was used to analyze z-height and z-BMI over a three-year period. Since each individual was measured at only one center, the individual factor was considered nested within the center. The center factor was included in the model primarily because it was part of the sample design. The center was treated as a random factor rather than a fixed one because, by design, the centers represent a sample of the population of centers. Profile plots depicting the changes over time for z-height and z-BMI curves were generated using the two-way ANOVA method with repeated measures. A Bonferroni adjustment was applied to account for multiple comparisons. As HbA1c was measured solely in the T1DM group, the following section of our analysis will focus exclusively on this group. A univariate correlation analysis was conducted to assess the association between relative changes in HbA1c and relative changes in z-BMI and z-height. Additionally, a multiple linear regression analysis was performed to evaluate whether relative changes in BMI were influenced by relative changes in HbA1c, adjusted for confounding variables. Statistical significance was inferred at p < 0.05. All analyses were performed using SPSS version 22.0® (Chicago, IL). Results A total of 534 children (48.3% female), comprising 245 children with newly diagnosed T1DM (51.4% female; mean age, 8.8 years) and 289 controls (45.7% female; mean age, 8.1 years) were included in the study. Initially, 257 children with T1DM were enrolled; however, 12 were later excluded — 2 due to insufficient data points and 10 due to relocation, resulting in a final sample of 245 children with T1DM. Table 1 shows the baseline clinical characteristics. At baseline, there were no significant differences in age or sex between the two groups. However, children with T1DM had a significantly lower BMI and were taller than the controls. Table 1 Clinical characteristics at baseline Age Controls ( n = 289) T1DM ( n = 245) Total (n = 534) 8.10 3.33 8.84 3.47 8.44 3.41 Sex (F) 132 45.7% 126 51.4% 258 48.3% Weight (kg) 31.08 14.45 32.23 13.81 31.56 14.18 Height (m)* 126.60 20.36 132.90 21.03 129.23 20.85 BMI* 18.33 3.65 17.34 3.30 17.92 3.54 Z-BMI* 0.54 1.14 -0.10 1.42 0.27 1.30 BMI Percentile* 63.91 29.84 50.49 33.56 58.31 32.10 Z-height* -0.11 1.07 0.21 1.12 0.02 1,10 Data are presented as mean ± SD. Abbreviations; SD standard deviation; BMI body mass index; z-BMI and z-height (z-scores). Z-score is a quantitative measure of the deviation of a specific variable taken from the mean of that population. CDC z-BMI takes into account age and sex. Significance*p < 0.01. Changes of Underweight and Obesity Over the Follow-Up Period At baseline, the prevalence of underweight was significantly higher in children with T1DM compared to the control group (14% vs. 4%, p < 0.001). Starting in the first year of treatment, the prevalence of underweight in the T1DM group significantly declined, aligning with that observed in the control group (Fig. 1 ), likely due to improved HbA1c (from 9.9% at onset to 8.7% at year 3). Conversely, the prevalence of obesity was significantly lower in the T1DM group than in the controls at year 0 (9% vs. 18%), year 1 (10% vs. 21%), year 2 (9% vs. 18%), and year 3 (7% vs. 19%). Changes of Short Stature Over the Follow-Up Period At baseline and year 1, the prevalence of short stature was similar in both groups. However, by year 2, the prevalence of short stature had increased significantly in the T1DM group compared to controls (6% vs. 1%), and this trend continued into year 3 (9% vs. 2%). Consequently, the prevalence of short stature in children with T1DM rose significantly from the second year of treatment onward (Fig. 2 ). Mixed Model–Adjusted Means of z-BMI and z-Height Over Three Years of Follow-Up in T1DM and Control Groups The adjusted model illustrates the magnitude of differences in means between the control and T1DM groups, as well as their evolution over the follow-up period. The Center factor was incorporated into the model as part of the sample design; moreover, the descriptive analysis indicates that variations in trends across centers further support its inclusion. Changes in z-BMI Over the Follow-Up Period Figure 3 displays the mean values for both groups over the follow-up period in the adjusted model. Children with T1DM had a significantly lower z-BMI compared to controls at year 0 (-0.12 vs. 0.54; p<0.01), year 1 (0.36 vs. 0.63; p<0.01), and year 2 (0.32 vs. 0.55; p<0.01). However, by year 3 (0.34 vs. 0.47, p=0.08), the difference in z-BMI between the two groups was no longer significant. Therefore, the comparison of effect levels indicates a significant difference between the control and T1DM groups at baseline, which persists for up to two years (Table 2 & Figure 3). Table 2: Difference in z-BMI means between T1DM children and controls with corresponding confidence intervals Difference in means Confidence Interval Year 0 0.71 (0.51; 0.90)* Year 1 0.33 (0.13; 0.52)* Year 2 0.28 (0.09; 0.48)* Year 3 0.18 (-0.02; 0.37) *P<0.01 Changes in z-Height Over the Follow-Up Period Figure 4 displays the mean z-height values over the follow-up period for both groups in the adjusted model. At baseline, children with T1DM had a significantly higher z-score for height than controls (0.17 vs. -0.12; p<0.01). However, no significant differences in z-height were observed between the T1DM group and controls at years 1 and 2 (-0.08 vs. -0.09 and -0.24 vs. -0.12, respectively). By year 3, children with T1DM had lower z-height than controls (-0.35 for the T1DM group and -0.12 for controls, p=0.02). It is important to highlight the trend lines in the z-height evolution chart. The trajectories of z-height demonstrate significant differences between the control and T1DM groups at both baseline and the end of the follow-up, but in opposite directions (Table 3 & Figure 4). While the z-height trend in the control group remained stable over time, the T1DM group exhibited a sharp decline, reflecting a markedly different trajectory compared to the controls. Table 3 : Difference in z-Height means between T1DM Children and Controls with Corresponding Confidence Intervals, by Year. Control vs. T1DM Difference in means Confidence interval Year 0* -0.29 -0.47 -0.11 Year 1 0.02 -0.16 0.20 Year 2 0.13 -0.05 0.31 Year 3* 0.25 0.07 0.43 *P<0.01 T1DM group Since HbA1c was measured exclusively in the T1DM group, we will focus this part of the analysis solely on this group. The mean HbA1c was 9.9% at diagnosis, 8.4% at year 1, 8.7% at year 2, and 8.7% at year 3 in the T1DM group. As observed, HbA1c levels significantly decreased after diagnosis, reaching their lowest point in the first year and then increasing in years 2 and 3, although remaining significantly lower than at diagnosis. However, only 12.4% of the children achieved the cutoff value of HbA1c <7% by the third year. The mean insulin dose increased throughout the follow-up period, from 0.54 IU/kg at diagnosis to 0.58 IU/kg at year 1, 0.66 IU/kg at year 2, and 0.73 IU/kg at year 3. Only 8.4% (n=45) of the children used CGM, and 1.5% (n=8) were on continuous subcutaneous insulin infusion. No significant differences in z-BMI or z-height were observed during follow-up between users and non-users of CGM or continuous subcutaneous insulin infusion. In addition, celiac disease and thyroid disorders were observed only in the T1DM group, with a prevalence of 1.7% (n=9) and 4.1% (n=22), respectively. There were no significant differences in z-BMI or z-height between those with and without these conditions. Univariate and multivariate correlations: There was a significant univariate inverse correlation between the relative changes in HbA1c and z-BMI (r=-0.19, p <0.05) and z-height (r=-0.28, p <0.01). The multiple linear regression analysis showed that the relative change in BMI is inversely and significantly associated with the relative change in HbA1c (β = 0.11), after adjustment for confounding variables. Discussion This multicenter study across Latin American pediatric diabetes centers shows that although BMI normalizes after treatment initiation, children with T1DM exhibit a progressive decline in z- height compared with healthy controls over the first three years after diagnosis. It is important to note that there is limited research on the trajectories of BMI and height in Latin American children with T1DM compared with those in a control group. The group with T1DM had significantly lower z-BMI levels at the onset than their controls. In addition, insulin treatment for the T1DM group results in a BMI catch-up, leading to a similar distribution between the T1DM and control groups by year 3. In contrast, while the z-height trend remained stable in the control group, the T1DM group experienced a sharp decline, indicating a notably different growth trajectory. Additionally, we showed a significant inverse association between the relative change in HbA1c over the three years following onset and the shift in growth in the T1DM group, suggesting that improved metabolic control was linked to better anthropometric outcomes. Children with T1DM onset often are exposed to a delayed diagnosis and treatment that can lead to a significant BMI decrease at presentation, emphasizing the importance of accurate and timely diagnosis [ 8 ]. Consistently, the present study found that the prevalence of underweight was significantly higher in children with T1DM onset compared to the control group. This could be due to a delay in the initial diagnosis of diabetes. A study conducted by our group in several centers across Latin America observed a high prevalence of diabetic ketoacidosis, especially at disease onset [ 9 ]. The high prevalence of diabetic ketoacidosis at diagnosis may be due to delayed recognition by healthcare providers and late consultation by families, potentially resulting in a significant reduction in BMI due to the negative energy balance caused by untreated T1DM. T1DM treatment led to BMI catch-up, resulting in a similar distribution in year 3. Newfield et al. examined changes in BMI during the first 7 months after T1DM diagnosis across different age groups [ 8 ]. They observed that BMI was initially lower than expected at diagnosis, followed by rapid, substantial increases within 7 months of starting insulin therapy [ 8 ]. Similarly, Frohlich-Reiterer et al. investigated factors predicting an increase in BMI over a 4– to 5-year period in children and adolescents with T1DM [ 13 ]. They found that several factors were significantly associated with weight gain, including female sex, age at diagnosis, intensive insulin therapy, higher insulin doses, and a lower z-BMI at the onset of T1DM [ 13 ]. Consistently, we found that from the first year of treatment onward, the prevalence of underweight in the T1DM group decreased significantly, reaching levels comparable to those of the control group. The present study also found a significant association between the relative change in HbA1c and BMI, adjusted for confounding variables. This indicates that the change in BMI depends inversely and significantly on the relative change in HbA1c, suggesting that better metabolic control is key to improving BMI. Growth impairment in T1DM is a complex, multifactorial issue influenced by the age at diagnosis, metabolic control, and the effectiveness of therapy [ 14 ]. Evaluating these factors and implementing appropriate management strategies is essential to support normal growth and development in children with T1DM [ 14 ]. Bonfig et al. showed that children with T1DM were taller at diagnosis than control children, particularly those diagnosed at a young age [ 15 ]. Several studies have shown that children are taller at diagnosis, between the ages of five and ten, but later experience a loss in relative height for their age that offsets the earlier height gain [ 16 , 17 ]. It has been suggested that excessive weight and puberty may accelerate height growth in children and contribute to increased insulin resistance. The baseline z-height was 0.21 (positive), despite the mean BMI z-score being only − 0.10 following T1DM diagnosis. Although the BMI of the T1DM group was significantly lower than that of the control group, likely due to weight loss associated with untreated T1DM, their height at T1DM onset (0.21) was significantly higher than that of controls (–0.11). Therefore, the relatively higher stature in the T1DM group does not fully explain their lower BMI. Mechanisms that may have contributed to the observed higher stature at T1DM onset include hormonal deficits associated with prolonged low circulating insulin levels. Insulin reaches the liver through the portal vein. In patients with poorly controlled diabetes, there may be reduced levels of intraportal insulin [ 18 , 19 ]. In addition, insulin regulates the GH/IGF-1 growth axis by stimulating the expression of the growth hormone receptor in the liver, thereby regulating the synthesis of IGF-1 and its binding proteins (IGFBPs) [ 14 ]. Insufficient portal vein insulin results in low concentrations of IGF-1 and IGFBP-3, which, in turn, slow growth [ 18 , 19 ]. A possible reason for the increased height observed at T1DM onset is enhanced IGFBP-3 proteolysis during the prediabetic period, leading to increased IGF-1 availability. Due to reduced insulin secretion during the prediabetic phase, IGF-1 becomes more available [ 20 ]. However, the initial height gain is often followed by a decline in growth velocity after diagnosis [ 14 ]. Consistently, a study of 206 adolescents with T1DM showed significant pubertal growth impairment, with a reduction in z-height from 0.145 to − 0.003 SDS [ 21 ]. Accordingly, this study showed that z-height declined sharply each year after the onset in children with T1DM, whereas it remained stable in the control group. A study in diabetic adults categorized adult height according to glycemic control [ 15 ]. The group with HbA1c levels below 7.0% had a final adult z-height of + 0.03 SDS, whereas the groups with HbA1c levels between 7.0% and 8.0%, and those with HbA1c levels above 8.0%, had final adult z-height values of − 0.12 SDS and − 0.308 SDS, respectively [ 15 ]. Consistently, a previous report from our group, involving a different set of 433 children with newly diagnosed T1DM, examined the associations among CGM use, hemoglobin A1c levels, and linear growth over 3 years [ 22 ]. The findings revealed that children using CGM had lower mean HbA1c levels. Although z-height declined over time in all children, the decrease was less pronounced in children using CGM than in those not using it [ 22 ]. The present study revealed poor metabolic control in the T1DM group, with only 12% of the children achieving an HbA1c below 7% by the third year of follow-up. This may be associated with the sharply decreased z-height compared to controls. Long-term future studies in Latin America are necessary to determine whether these children will reach a height comparable to that of the controls. Structural barriers to diabetes care, including limited access to CGM and delayed diagnosis, likely contribute to suboptimal metabolic control and may partly explain the observed growth patterns in this cohort. Strengths and Limitations The major strengths of this study lie in its thoroughness, drawing on data from T1DM referral centers across underrepresented regions of Latin American countries over three years. Additionally, controls from the same center were sought, which resulted in a similar population between the children with diabetes and the controls. Anthropometric data were robust, as children had height and weight measurements taken at each healthcare encounter, which improved the accuracy of height and BMI z-score calculations. However, there were inherent limitations, including the retrospective nature of data collection and varying post-onset visit intervals across subjects. Due to the observational design of this study, associations should be interpreted cautiously. We used the CDC standards for calculating z-scores. This may not be entirely appropriate for Latin American populations. However, in the absence of suitable national standardization tables and wishing to apply the same standard to children from all three participating countries, the CDC standards were deemed the most appropriate solution. Interpreting z-height was also challenging without information on mid-parental heights or genetic growth potential. Additionally, the records lacked information on pubertal development, despite its importance as a determinant of changes in growth patterns. In addition, there was insufficient information on lifestyle behaviors (dietary and physical activity) that could influence growth. Conclusions This study found that Latin American children with T1DM had significantly lower z-BMI at disease onset than their controls. However, treatment for T1DM prompted a BMI catch-up, leading to a similar distribution between the two groups by year 3. In contrast, while the z-height trend remained stable in the control group, the T1DM group exhibited a marked decline, reflecting a distinct growth trajectory. Our z-height findings suggest that, even with treatment and z-BMI equalization, children with T1DM in Latin America experience some growth delay compared with the control group. These findings highlight the importance of monitoring growth as an endocrine outcome in children with T1DM, particularly in settings where delayed diagnosis and limited access to diabetes technologies remain common. Future directions: Improving access to diabetes care and technologies in Latin American low- and middle-income settings may help mitigate growth disparities. Abbreviations T1DM, type 1 diabetes; HbA1C, glycated hemoglobin Declarations Conflict of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest Funding: This research received no grant from any funding agency in the public, commercial, or not-for-profit sectors. Author Contributions: V.H. conceived and designed the study. V.H., C.M., and C.G. collected and verified the data. C.M. performed the statistical analyses. V.H. drafted the manuscript. D.R.W. contributed to interpretation of the data and critically revised the manuscript. All authors reviewed and approved the final version of the manuscript. Compliance with Ethical Standards Conflict of Interest: The authors declare that they have no conflict of interest. Ethical Approval: The study protocol was approved by the institutional review boards of all participating centers (IRB numbers: 8828-2023508; PRISABA BA 10224; 1476/2024; 08/24; 024/24; 07-04; 2024-696-GDEBA-SSGIEPYFMSALGP) and was conducted in accordance with the Declaration of Helsinki. Informed Consent: Due to the retrospective nature of the study and the use of anonymized data, informed consent was waived by the ethics committees of the participating institutions. References Santi E, Tascini G, Toni G, Berioli MG, Esposito S (2019) Linear growth in children and adolescents with type 1 diabetes mellitus. Int J Environ Res Public Health 16:3677. https://doi.org/10.3390/ijerph16193677 Jivani SK, Rayner PH (1973) Does control influence the growth of diabetic children? Arch Dis Child 48:109–115. Elamin A, Hussein O, Tuvemo T (2006) Growth, puberty, and final height in children with type 1 diabetes. J Diabetes Complications 20:252–256. https://doi.org/10.1016/j.jdiacomp.2005.07.001 Bizzarri C, Timpanaro TA, Matteoli MC, Patera IP, Cappa M, Cianfarani S (2018) Growth trajectory in children with type 1 diabetes mellitus: the impact of insulin treatment and metabolic control. Horm Res Paediatr 89:172–177. https://doi.org/10.1159/000486698 Ahmed ML, Connors MH, Drayer NM, Jones JS, Dunger DB (1998) Pubertal growth in IDDM is determined by HbA1c levels, sex, and bone age. Diabetes Care 21:1382. Blasetti A, Castorani V, Polidori N, Mascioli I, Chiarelli F, Giannini C (2023) Role of glucose variability on linear growth in children with type 1 diabetes. Endocr Connect 12:e220370. https://doi.org/10.1530/EC-22-0370 Bizzarri C, Benevento D, Patera IP, Bongiovanni M, Boiani A, Fusco C, Cianfarani S, Cappa M (2013) Residual β-cell mass influences growth of prepubertal children with type 1 diabetes. Horm Res Paediatr 80:287–292. Newfield RS, Cohen D, Capparelli EV, Shragg P (2009) Rapid weight gain in children soon after diagnosis of type 1 diabetes: is there room for concern? Pediatr Diabetes 10:310–315. Hirschler V, Gonzalez CD, Krochik G et al (2024) Diabetic ketoacidosis in type 1 diabetes onset in Latin American children. J Pediatr Health Care 38:544–551. https://doi.org/10.1016/j.pedhc.2024.01.006 Kuczmarski RJ, Ogden CL, Grummer-Strawn LM et al (2000) CDC growth charts: United States. Adv Data (8):1–27. National Center for Health Statistics (2000) Cut-off to define outliers in 2000 CDC growth charts: United States. http://www.cdc.gov/growthcharts/ American Diabetes Association (2021) Classification and diagnosis of diabetes: standards of medical care in diabetes. Diabetes Care 44(Suppl 1):S15–S33. https://doi.org/10.2337/dc21-S002 Frohlich-Reiterer EE, Rosenbauer J, Bechtold-Dalla Pozza S, Hofer SE, Schober E, Holl RW (2014) Predictors of increasing BMI during the course of diabetes in children and adolescents with type 1 diabetes. Arch Dis Child 99:738–743. Jadhav I, Chakole S (2023) Effects of type 1 diabetes mellitus on linear growth: a comprehensive review. Cureus 15:e45428. https://doi.org/10.7759/cureus.45428 Bonfig W, Kapellen T, Dost A, Fritsch M, Rohrer T, Wolf J, Holl RW (2012) Growth in children and adolescents with type 1 diabetes. J Pediatr 160:900–903.e2. https://doi.org/10.1016/j.jpeds.2011.12.007 Dunger D, Ahmed L, Ong K (2002) Growth and body composition in type 1 diabetes mellitus. Horm Res 58(Suppl 1):66–71. Brown M, Ahmed ML, Clayton KL, Dunger DB (1994) Growth during childhood and final height in type 1 diabetes. Diabet Med 11:182–187. https://doi.org/10.1111/j.1464-5491.1994.tb02017.x Dunger DB, Cheetham TD (1996) Growth hormone insulin-like growth factor I axis in insulin-dependent diabetes mellitus. Horm Res 46:2–6. https://doi.org/10.1159/000184969 Zachrisson I, Brismar K, Hall K, Wallensteen M, Dahlqvist G (1997) Determinants of growth in diabetic pubertal subjects. Diabetes Care 20:1261–1265. https://doi.org/10.2337/diacare.20.8.1261 Bizzarri C, Benevento D, Patera IP et al (2013) Residual β-cell mass influences growth of prepubertal children with type 1 diabetes. Horm Res Paediatr 80:287–292. https://doi.org/10.1159/000355116 Marcovecchio ML, Heywood JJ, Dalton RN, Dunger DB (2014) The contribution of glycemic control to impaired growth during puberty in young people with type 1 diabetes. Pediatr Diabetes 15:303–308. Hirschler V, Molinari C, Gonzalez CD, CODIAPED Study Group (2024) Impact of continuous glucose monitoring on hemoglobin A1c and height trends in Latin American children with type 1 diabetes onset over 3 years: a multicenter study. J Pediatr Clin Pract 14:200130. https://doi.org/10.1016/j.jpedcp.2024.200130 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 03 Apr, 2026 Reviews received at journal 03 Apr, 2026 Reviews received at journal 27 Mar, 2026 Reviewers agreed at journal 19 Mar, 2026 Reviewers agreed at journal 19 Mar, 2026 Reviewers invited by journal 19 Mar, 2026 Editor assigned by journal 17 Mar, 2026 Submission checks completed at journal 17 Mar, 2026 First submitted to journal 06 Mar, 2026 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. 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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-9054431","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":609150887,"identity":"8893bc74-e66d-48b1-a386-f78985f4828a","order_by":0,"name":"Valeria Hirschler","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYDACCcYGIHlAhoGB+QCIK0O0Fh4GBrYEEJeHCC1gEqSFxwDEIqzF4HZz28cfNXd4+KXPfH51o8aCh4H98NENeLXcOdg8m+fYMx7Jvtxt1jnHgA7jSUu7gU+L5IzEZmbGhsM8Bmd4txnnsAG1SPCYEdTC+BOoxf4MzzPjnH9EaOGXSGxm4AXZwsPD/Di3jUgtzDzHDvNInGEzY87tk+BhI+QXNon0x4w/ag7L8fcwP/6c861Ojp/98DG8WlC1g0lilYMA8wdSVI+CUTAKRsHIAQB/akMA6o04/QAAAABJRU5ErkJggg==","orcid":"","institution":"Argentine Diabetes Society (SAD)","correspondingAuthor":true,"prefix":"","firstName":"Valeria","middleName":"","lastName":"Hirschler","suffix":""},{"id":609150892,"identity":"b25310f7-40c7-4e0f-8be2-19b505ff766d","order_by":1,"name":"Claudia Molinari","email":"","orcid":"","institution":"UBA School of Pharmacy and Biochemistry, Mathematics","correspondingAuthor":false,"prefix":"","firstName":"Claudia","middleName":"","lastName":"Molinari","suffix":""},{"id":609150893,"identity":"f45b1697-ac2c-49b7-a6e0-b2c5d5de60c6","order_by":2,"name":"Claudio Gonzalez","email":"","orcid":"","institution":"Argentine Diabetes Society (SAD)","correspondingAuthor":false,"prefix":"","firstName":"Claudio","middleName":"","lastName":"Gonzalez","suffix":""},{"id":609150895,"identity":"3a3b37de-2abe-4bc6-a8ef-e67921b00a9c","order_by":3,"name":"Daniel R. 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Elizalde","correspondingAuthor":false,"prefix":"","firstName":"Arzamendia","middleName":"Maria","lastName":"Laura","suffix":""}],"badges":[],"createdAt":"2026-03-07 00:08:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9054431/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9054431/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105297067,"identity":"5f26752b-8f5b-4980-9519-24cd2a9ea880","added_by":"auto","created_at":"2026-03-24 13:16:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":61766,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of Underweight Over the Follow-Up Period.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9054431/v1/f02c4caf263613305155a47c.png"},{"id":105297069,"identity":"e379aca5-71b5-46f8-b047-0342863d4cc9","added_by":"auto","created_at":"2026-03-24 13:16:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":70712,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of Short Stature Over the Follow-Up Period.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9054431/v1/5f6ab0537b05f4e3aca0a321.png"},{"id":105297071,"identity":"738da28e-e109-4d78-98ee-35549e38c2e7","added_by":"auto","created_at":"2026-03-24 13:16:19","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":57647,"visible":true,"origin":"","legend":"\u003cp\u003eMixed Model–Adjusted Mean z-BMI Over Three Years of Follow-Up in Children with T1DM and Controls.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9054431/v1/3bd9ac09d52a7c3dd94862d5.png"},{"id":105297070,"identity":"6549d23e-b313-4b33-a878-8e088ccf3d42","added_by":"auto","created_at":"2026-03-24 13:16:19","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":53876,"visible":true,"origin":"","legend":"\u003cp\u003eMixed Model–Adjusted Mean z-Height Over Three Years of Follow-Up in Children with T1DM and Controls.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9054431/v1/5fb3d2f0fb87037813fc9141.png"},{"id":105565142,"identity":"8b27b9ba-a47a-4da6-a581-0469e6c9f7b0","added_by":"auto","created_at":"2026-03-27 12:52:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":962501,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9054431/v1/b6bd3d12-0b33-4c13-85cb-2a9c97747a2b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Contrasting BMI and Height z-Score Trajectories in Children With New-Onset T1DM: A Case-Control Study Across Latin American Centers","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGrowth during childhood can be impaired in children with type 1 diabetes (T1DM) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Studies have demonstrated that children with T1DM experience decreased z-height and growth velocity following the onset of the disease [\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. A reduction in growth rate has been observed in children with T1DM due to multiple factors, with poor metabolic control being the primary contributor [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Nowadays, growth outcomes have improved thanks to modern insulin treatment regimens and consistent patient glycemic control [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. At T1DM onset, children frequently show a reduced BMI due to delayed diagnosis and initiation of treatment, highlighting the essential need for early and accurate diagnosis [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Consistently, a previous study conducted by our group across multiple centers in Latin America found a high prevalence of diabetic ketoacidosis at disease onset, likely linked to delayed diagnosis and associated with a low BMI at the time of diagnosis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePromoting normal growth and development in children with T1DM is a primary goal of T1DM treatment. To our knowledge, no multicenter study from Latin America has compared longitudinal trajectories of z-BMI and z-height in children with new-onset type 1 diabetes and healthy controls. Therefore, the objective of the present study was to compare growth trajectories assessed by z-height and z-BMI over a three-year follow-up period between children with new-onset T1DM and a control group without T1DM across multiple Latin American centers.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003eWe retrospectively defined a case-control study based on an analysis of medical records across 10 centers in three Latin American countries (Argentina, Peru, and Uruguay), and collected data covering the three years following the case and control definition (baseline), from 2021 to 2024. Potential cases were identified from all consecutive new-onset cases of T1DM attending the 10 centers between September 2021and February 2022. Controls were identified in equivalent numbers from the same centers, using records of children without T1DM or other known chronic conditions who routinely attended health check-ups. In the Latin American hospitals included, there are designated pediatric outpatient services for children without underlying medical conditions who present for routine assessments such as growth monitoring and immunizations. We selected the controls from these hospital-based services for healthy children. As such, these children are considered representative of the general pediatric population without chronic illness, despite being recruited within hospital settings.\u003c/p\u003e \u003cp\u003eBeyond case-control status, the inclusion criteria were age 2 to 16, sex information, and anthropometric measures obtained at least 2 times during the follow-up window. Exclusion criteria were relocation during follow-up, psychiatric disorders, current corticosteroid therapy, the presence of genetic syndromes (e.g., Prader-Willi syndrome, Down syndrome), and pregnancy. Additionally, children with biologically implausible height values at the time of diagnosis (height z-score: \u0026lt;\u0026minus;4 or \u0026gt;\u0026thinsp;4), as defined by the Centers for Disease Control and Prevention (CDC) growth charts, were excluded [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTen health centers were grouped into six categories based on common features, including geographic location and level of urbanization. The categories and their proportions were as follows: Riverside provinces (n\u0026thinsp;=\u0026thinsp;80, 15%; includes Corrientes and Misiones [Argentina]), Mountain provinces (n\u0026thinsp;=\u0026thinsp;108, 20.2%; Ushuaia, R\u0026iacute;o Grande, and Mendoza [Argentina]), Rural provinces (n\u0026thinsp;=\u0026thinsp;51, 9.6%; Misiones [Argentina]), Urban 1 (n\u0026thinsp;=\u0026thinsp;162, 30.3%; Buenos Aires, Argentina), Urban 2 (n\u0026thinsp;=\u0026thinsp;47, 8.8%; Montevideo, Uruguay), and Urban 3 (n\u0026thinsp;=\u0026thinsp;86, 16.1%; Lima, Peru). This grouping aimed to address potential differences in outcomes across centers or regions. Key factors considered included proximity to urban hubs, the number of healthcare staff, challenges in accessing services, rural versus urban classification, center complexity, availability of medical equipment, patient understanding and adherence to treatments, and the presence of a multidisciplinary care team, among others. For instance, the distinction between urban center 1 (Buenos Aires) and urban center 2 (Montevideo) reflects differences in population density. Buenos Aires and its surrounding suburbs, with a population of approximately 15.6\u0026nbsp;million, make up Argentina's largest metropolitan area. In contrast, Montevideo, home to approximately 1.3\u0026nbsp;million residents, is Uruguay's largest city. These population disparities reflect significant differences in urbanization and infrastructure, influencing factors such as access to healthcare, transportation networks, and population density.\u003c/p\u003e \u003cp\u003eAll participating centers serve as the main tertiary pediatric diabetes care facility in their region, meaning that nearly all presumed new-onset T1DM cases in these areas are referred there. Each center included in the study selected one physician to submit the information to prevent duplication. Each submission was reviewed for transcription errors and missing data. The protocol was submitted to the Ethics Review Board of each center, and all obtained approval with a waiver of consent. The study was approved by the institutional review board (IRB) numbers: 8828-2023508; PRISABA BA 10224; 1476/2024; 08/24; 024/24; 07\u0026thinsp;\u0026minus;\u0026thinsp;04; 2024-696-GDEBA-SSGIEPYFMSALGP. All collected data was pseudonymized, and only unidentified data was sent to the coordinating center.\u003c/p\u003e \u003cp\u003eUpon consideration of follow-up data, fewer than 5% of the initially included cases were lost, primarily due to relocation or the absence of at least two data points. The following information was gathered: sex, date of birth, age at diabetes onset, and anthropometric measurements in the T1DM and control groups. In the T1DM group, initial height and weight measurements were taken 2 months post-diagnosis, as children often experience weight loss due to dehydration and insulin deficiency at the onset of T1DM. Height and weight were measured with participants dressed in lightweight clothing and barefoot, with height recorded to the nearest 0.1 cm using a wall-mounted stadiometer and weight to the nearest 0.1 kg on a medical scale. A medical doctor recorded these anthropometric measurements annually at subsequent clinic visits. In addition, information on hemoglobin A1c (HbA1c) (%) was collected yearly in the T1DM group during the follow-up. Therefore, follow-up measurements were scheduled as closely as possible to the initial measurement date (year 0), at intervals of +\u0026thinsp;1 year, +\u0026thinsp;2 years, and +\u0026thinsp;3 years.\u003c/p\u003e \u003cp\u003eChildren were categorized according to CDC guidelines as underweight (\u0026lt;\u0026thinsp;5th percentile), normal weight (5th to \u0026lt;\u0026thinsp;85th percentile), overweight (85th to \u0026lt;\u0026thinsp;95th percentile), or obese (\u0026ge;\u0026thinsp;95th percentile) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Additionally, BMI and height were converted to z-scores (based on CDC standards) for analysis as continuous variables, allowing comparison with a broad base of existing literature [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Short stature was defined as z-Height\u0026thinsp;\u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;2. Although CDC growth references may not perfectly reflect Latin American populations, they were used in this study due to the absence of region-specific reference standards and to facilitate comparison with the existing international literature.\u003c/p\u003e \u003cp\u003eThe diagnosis of T1DM was based on the criteria established by the American Diabetes Association (ADA) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. HbA1c levels were measured as a percentage using the National Glycohemoglobin Standardization Program standards and assessed with the Bio-Rad D-10\u0026trade; Dual Program, which uses ion-exchange high-performance liquid chromatography. HbA1c values were mathematically standardized to a reference range of 4.05%\u0026ndash;6.05% according to the Diabetes Control and Complications Trial using the multiple-of-the-mean method.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData analysis:\u003c/h2\u003e \u003cp\u003eThe primary objective was to compare z-height and z-BMI trends over a three-year follow-up between children with new-onset T1DM and a control group without T1DM across multiple Latin American centers. Descriptive statistics for the variables were reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Chi-square tests were used to compare proportions, with Fisher\u0026rsquo;s exact test applied when \u0026gt;\u0026thinsp;20% of cells had expected frequencies\u0026thinsp;\u0026lt;\u0026thinsp;5. The Shapiro-Wilks test was used to check for the normality of continuous variables. For comparisons between two groups with normally distributed data, a Student\u0026rsquo;s t-test was conducted. The progression of height and BMI in children was evaluated using age- and sex-adjusted z-scores. A mixed-effect model was used to analyze z-height and z-BMI over a three-year period. Since each individual was measured at only one center, the individual factor was considered nested within the center. The center factor was included in the model primarily because it was part of the sample design. The center was treated as a random factor rather than a fixed one because, by design, the centers represent a sample of the population of centers.\u003c/p\u003e \u003cp\u003eProfile plots depicting the changes over time for z-height and z-BMI curves were generated using the two-way ANOVA method with repeated measures. A Bonferroni adjustment was applied to account for multiple comparisons. As HbA1c was measured solely in the T1DM group, the following section of our analysis will focus exclusively on this group. A univariate correlation analysis was conducted to assess the association between relative changes in HbA1c and relative changes in z-BMI and z-height. Additionally, a multiple linear regression analysis was performed to evaluate whether relative changes in BMI were influenced by relative changes in HbA1c, adjusted for confounding variables. Statistical significance was inferred at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. All analyses were performed using SPSS version 22.0\u0026reg; (Chicago, IL).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 534 children (48.3% female), comprising 245 children with newly diagnosed T1DM (51.4% female; mean age, 8.8 years) and 289 controls (45.7% female; mean age, 8.1 years) were included in the study. Initially, 257 children with T1DM were enrolled; however, 12 were later excluded \u0026mdash; 2 due to insufficient data points and 10 due to relocation, resulting in a final sample of 245 children with T1DM.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the baseline clinical characteristics. At baseline, there were no significant differences in age or sex between the two groups. However, children with T1DM had a significantly lower BMI and were taller than the controls.\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\u003eClinical characteristics at baseline\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eControls ( n\u0026thinsp;=\u0026thinsp;289)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eT1DM ( n\u0026thinsp;=\u0026thinsp;245)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;534)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.10\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.33\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.84\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.47\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.44\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.41\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e51.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e48.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (m)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e126.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e132.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e129.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZ-BMI*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI Percentile*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e32.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZ-height*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eData are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. Abbreviations; SD standard deviation; BMI body mass index; z-BMI and z-height (z-scores). Z-score is a quantitative measure of the deviation of a specific variable taken from the mean of that population. CDC z-BMI takes into account age and sex. Significance*p\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e\n\u003ch3\u003eChanges of Underweight and Obesity Over the Follow-Up Period\u003c/h3\u003e\n\u003cp\u003eAt baseline, the prevalence of underweight was significantly higher in children with T1DM compared to the control group (14% vs. 4%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Starting in the first year of treatment, the prevalence of underweight in the T1DM group significantly declined, aligning with that observed in the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), likely due to improved HbA1c (from 9.9% at onset to 8.7% at year 3). Conversely, the prevalence of obesity was significantly lower in the T1DM group than in the controls at year 0 (9% vs. 18%), year 1 (10% vs. 21%), year 2 (9% vs. 18%), and year 3 (7% vs. 19%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eChanges of Short Stature Over the Follow-Up Period\u003c/h3\u003e\n\u003cp\u003eAt baseline and year 1, the prevalence of short stature was similar in both groups. However, by year 2, the prevalence of short stature had increased significantly in the T1DM group compared to controls (6% vs. 1%), and this trend continued into year 3 (9% vs. 2%). Consequently, the prevalence of short stature in children with T1DM rose significantly from the second year of treatment onward (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e\u003cstrong\u003eMixed Model\u0026ndash;Adjusted Means of z-BMI and z-Height Over Three Years of Follow-Up in T1DM and Control Groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe adjusted model illustrates the magnitude of differences in means between the control and T1DM groups, as well as their evolution over the follow-up period. The Center factor was incorporated into the model as part of the sample design; moreover, the descriptive analysis indicates that variations in trends across centers further support its inclusion.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChanges in z-BMI Over the Follow-Up Period\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 3 displays the mean values for both groups over the follow-up period in the adjusted model. \u0026nbsp;Children with T1DM had a significantly lower z-BMI compared to controls at year 0 (-0.12 vs. 0.54; p\u0026lt;0.01), year 1 (0.36 vs. 0.63; p\u0026lt;0.01), and year 2 (0.32 vs. 0.55; p\u0026lt;0.01). However, by year 3 (0.34 vs. 0.47, p=0.08), the difference in z-BMI between the two groups was no longer significant. Therefore, the comparison of effect levels indicates a significant difference between the control and T1DM groups at baseline, which persists for up to two years (Table 2 \u0026amp; Figure 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u003c/strong\u003e Difference in z-BMI means between T1DM children and controls with corresponding confidence intervals\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 26.5306%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 32.6531%;\"\u003e\n \u003cp\u003eDifference in means\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 40.8163%;\"\u003e\n \u003cp\u003eConfidence Interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 26.5306%;\"\u003e\n \u003cp\u003eYear 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 32.6531%;\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 40.8163%;\"\u003e\n \u003cp\u003e(0.51; 0.90)*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 26.5306%;\"\u003e\n \u003cp\u003eYear 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 32.6531%;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 40.8163%;\"\u003e\n \u003cp\u003e(0.13; 0.52)*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 26.5306%;\"\u003e\n \u003cp\u003eYear 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 32.6531%;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 40.8163%;\"\u003e\n \u003cp\u003e(0.09; 0.48)*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 26.5306%;\"\u003e\n \u003cp\u003eYear 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 32.6531%;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 40.8163%;\"\u003e\n \u003cp\u003e(-0.02; 0.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*P\u0026lt;0.01\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChanges in z-Height Over the Follow-Up Period\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 4 displays the mean z-height values over the follow-up period for both groups in the adjusted model. At baseline, children with T1DM had a significantly higher z-score for height than controls (0.17 vs. -0.12; p\u0026lt;0.01). However, no significant differences in z-height were observed between the T1DM group and controls at years 1 and 2 (-0.08 vs. -0.09 and -0.24 vs. -0.12, respectively). By year 3, children with T1DM had lower z-height than controls (-0.35 for the T1DM group and -0.12 for controls, p=0.02).\u003c/p\u003e\n\u003cp\u003eIt is important to highlight the trend lines in the z-height evolution chart. The trajectories of z-height demonstrate significant differences between the control and T1DM groups at both baseline and the end of the follow-up, but in opposite directions (Table 3 \u0026amp; Figure 4). While the z-height trend in the control group remained stable over time, the T1DM group exhibited a sharp decline, reflecting a markedly different trajectory compared to the controls.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e: Difference in z-Height means between T1DM Children and Controls with Corresponding Confidence Intervals, by Year.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 32px;\"\u003e\n \u003cp\u003eControl vs. T1DM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 29px;\"\u003e\n \u003cp\u003eDifference in means\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"2\" valign=\"bottom\" style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Confidence interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 32px;\"\u003e\n \u003cp\u003eYear 0*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 29px;\"\u003e\n \u003cp\u003e-0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 19px;\"\u003e\n \u003cp\u003e-0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003e-0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 32px;\"\u003e\n \u003cp\u003eYear 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 19px;\"\u003e\n \u003cp\u003e-0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 32px;\"\u003e\n \u003cp\u003eYear 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 19px;\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 32px;\"\u003e\n \u003cp\u003eYear 3*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 29px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 19px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 18px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*P\u0026lt;0.01\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eT1DM group\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSince HbA1c was measured exclusively in the T1DM group, we will focus this part of the analysis solely on this group. The mean HbA1c was 9.9% at diagnosis, 8.4% at year 1, 8.7% at year 2, and 8.7% at year 3 in the T1DM group. As observed, HbA1c levels significantly decreased after diagnosis, reaching their lowest point in the first year and then increasing in years 2 and 3, although remaining significantly lower than at diagnosis. However, only 12.4% of the children achieved the cutoff value of HbA1c \u0026lt;7% by the third year. The mean insulin dose increased throughout the follow-up period, from 0.54 IU/kg at diagnosis to 0.58 IU/kg at year 1, 0.66 IU/kg at year 2, and 0.73 IU/kg at year 3. Only 8.4% (n=45) of the children used CGM, and 1.5% (n=8) were on continuous subcutaneous insulin infusion. No significant differences in z-BMI or z-height were observed during follow-up between users and non-users of CGM or continuous subcutaneous insulin infusion. In addition, celiac disease and thyroid disorders were observed only in the T1DM group, with a prevalence of 1.7% (n=9) and 4.1% (n=22), respectively. There were no significant differences in z-BMI or z-height between those with and without these conditions.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eUnivariate and multivariate correlations:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThere was a significant univariate inverse correlation between the relative changes in HbA1c and z-BMI (r=-0.19, p \u0026lt;0.05) and z-height (r=-0.28, p \u0026lt;0.01). The multiple linear regression analysis showed that the relative change in BMI is inversely and significantly associated with the relative change in HbA1c (\u0026beta; = 0.11), after adjustment for confounding variables.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis multicenter study across Latin American pediatric diabetes centers shows that although BMI normalizes after treatment initiation, children with T1DM exhibit a progressive decline in z- height compared with healthy controls over the first three years after diagnosis. It is important to note that there is limited research on the trajectories of BMI and height in Latin American children with T1DM compared with those in a control group. The group with T1DM had significantly lower z-BMI levels at the onset than their controls. In addition, insulin treatment for the T1DM group results in a BMI catch-up, leading to a similar distribution between the T1DM and control groups by year 3. In contrast, while the z-height trend remained stable in the control group, the T1DM group experienced a sharp decline, indicating a notably different growth trajectory. Additionally, we showed a significant inverse association between the relative change in HbA1c over the three years following onset and the shift in growth in the T1DM group, suggesting that improved metabolic control was linked to better anthropometric outcomes.\u003c/p\u003e \u003cp\u003eChildren with T1DM onset often are exposed to a delayed diagnosis and treatment that can lead to a significant BMI decrease at presentation, emphasizing the importance of accurate and timely diagnosis [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Consistently, the present study found that the prevalence of underweight was significantly higher in children with T1DM onset compared to the control group. This could be due to a delay in the initial diagnosis of diabetes. A study conducted by our group in several centers across Latin America observed a high prevalence of diabetic ketoacidosis, especially at disease onset [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The high prevalence of diabetic ketoacidosis at diagnosis may be due to delayed recognition by healthcare providers and late consultation by families, potentially resulting in a significant reduction in BMI due to the negative energy balance caused by untreated T1DM.\u003c/p\u003e \u003cp\u003eT1DM treatment led to BMI catch-up, resulting in a similar distribution in year 3. Newfield et al. examined changes in BMI during the first 7 months after T1DM diagnosis across different age groups [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. They observed that BMI was initially lower than expected at diagnosis, followed by rapid, substantial increases within 7 months of starting insulin therapy [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Similarly, Frohlich-Reiterer et al. investigated factors predicting an increase in BMI over a 4\u0026ndash; to 5-year period in children and adolescents with T1DM [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. They found that several factors were significantly associated with weight gain, including female sex, age at diagnosis, intensive insulin therapy, higher insulin doses, and a lower z-BMI at the onset of T1DM [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Consistently, we found that from the first year of treatment onward, the prevalence of underweight in the T1DM group decreased significantly, reaching levels comparable to those of the control group. The present study also found a significant association between the relative change in HbA1c and BMI, adjusted for confounding variables. This indicates that the change in BMI depends inversely and significantly on the relative change in HbA1c, suggesting that better metabolic control is key to improving BMI.\u003c/p\u003e \u003cp\u003eGrowth impairment in T1DM is a complex, multifactorial issue influenced by the age at diagnosis, metabolic control, and the effectiveness of therapy [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Evaluating these factors and implementing appropriate management strategies is essential to support normal growth and development in children with T1DM [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Bonfig et al. showed that children with T1DM were taller at diagnosis than control children, particularly those diagnosed at a young age [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Several studies have shown that children are taller at diagnosis, between the ages of five and ten, but later experience a loss in relative height for their age that offsets the earlier height gain [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. It has been suggested that excessive weight and puberty may accelerate height growth in children and contribute to increased insulin resistance. The baseline z-height was 0.21 (positive), despite the mean BMI z-score being only \u0026minus;\u0026thinsp;0.10 following T1DM diagnosis. Although the BMI of the T1DM group was significantly lower than that of the control group, likely due to weight loss associated with untreated T1DM, their height at T1DM onset (0.21) was significantly higher than that of controls (\u0026ndash;0.11). Therefore, the relatively higher stature in the T1DM group does not fully explain their lower BMI.\u003c/p\u003e \u003cp\u003eMechanisms that may have contributed to the observed higher stature at T1DM onset include hormonal deficits associated with prolonged low circulating insulin levels. Insulin reaches the liver through the portal vein. In patients with poorly controlled diabetes, there may be reduced levels of intraportal insulin [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In addition, insulin regulates the GH/IGF-1 growth axis by stimulating the expression of the growth hormone receptor in the liver, thereby regulating the synthesis of IGF-1 and its binding proteins (IGFBPs) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Insufficient portal vein insulin results in low concentrations of IGF-1 and IGFBP-3, which, in turn, slow growth [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. A possible reason for the increased height observed at T1DM onset is enhanced IGFBP-3 proteolysis during the prediabetic period, leading to increased IGF-1 availability. Due to reduced insulin secretion during the prediabetic phase, IGF-1 becomes more available [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, the initial height gain is often followed by a decline in growth velocity after diagnosis [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Consistently, a study of 206 adolescents with T1DM showed significant pubertal growth impairment, with a reduction in z-height from 0.145 to \u0026minus;\u0026thinsp;0.003 SDS [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Accordingly, this study showed that z-height declined sharply each year after the onset in children with T1DM, whereas it remained stable in the control group.\u003c/p\u003e \u003cp\u003eA study in diabetic adults categorized adult height according to glycemic control [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The group with HbA1c levels below 7.0% had a final adult z-height of +\u0026thinsp;0.03 SDS, whereas the groups with HbA1c levels between 7.0% and 8.0%, and those with HbA1c levels above 8.0%, had final adult z-height values of \u0026minus;\u0026thinsp;0.12 SDS and \u0026minus;\u0026thinsp;0.308 SDS, respectively [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Consistently, a previous report from our group, involving a different set of 433 children with newly diagnosed T1DM, examined the associations among CGM use, hemoglobin A1c levels, and linear growth over 3 years [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The findings revealed that children using CGM had lower mean HbA1c levels. Although z-height declined over time in all children, the decrease was less pronounced in children using CGM than in those not using it [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The present study revealed poor metabolic control in the T1DM group, with only 12% of the children achieving an HbA1c below 7% by the third year of follow-up. This may be associated with the sharply decreased z-height compared to controls. Long-term future studies in Latin America are necessary to determine whether these children will reach a height comparable to that of the controls. Structural barriers to diabetes care, including limited access to CGM and delayed diagnosis, likely contribute to suboptimal metabolic control and may partly explain the observed growth patterns in this cohort.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eStrengths and Limitations\u003c/strong\u003e \u003cp\u003eThe major strengths of this study lie in its thoroughness, drawing on data from T1DM referral centers across underrepresented regions of Latin American countries over three years. Additionally, controls from the same center were sought, which resulted in a similar population between the children with diabetes and the controls. Anthropometric data were robust, as children had height and weight measurements taken at each healthcare encounter, which improved the accuracy of height and BMI z-score calculations. However, there were inherent limitations, including the retrospective nature of data collection and varying post-onset visit intervals across subjects. Due to the observational design of this study, associations should be interpreted cautiously. We used the CDC standards for calculating z-scores. This may not be entirely appropriate for Latin American populations. However, in the absence of suitable national standardization tables and wishing to apply the same standard to children from all three participating countries, the CDC standards were deemed the most appropriate solution. Interpreting z-height was also challenging without information on mid-parental heights or genetic growth potential. Additionally, the records lacked information on pubertal development, despite its importance as a determinant of changes in growth patterns. In addition, there was insufficient information on lifestyle behaviors (dietary and physical activity) that could influence growth.\u003c/p\u003e \u003c/p\u003e "},{"header":"Conclusions","content":"\u003cp\u003eThis study found that Latin American children with T1DM had significantly lower z-BMI at disease onset than their controls. However, treatment for T1DM prompted a BMI catch-up, leading to a similar distribution between the two groups by year 3. In contrast, while the z-height trend remained stable in the control group, the T1DM group exhibited a marked decline, reflecting a distinct growth trajectory. Our z-height findings suggest that, even with treatment and z-BMI equalization, children with T1DM in Latin America experience some growth delay compared with the control group. These findings highlight the importance of monitoring growth as an endocrine outcome in children with T1DM, particularly in settings where delayed diagnosis and limited access to diabetes technologies remain common. Future directions: Improving access to diabetes care and technologies in Latin American low- and middle-income settings may help mitigate growth disparities.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eT1DM, type 1 diabetes; HbA1C, glycated hemoglobin\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research received no grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e V.H. conceived and designed the study. V.H., C.M., and C.G. collected and verified the data. C.M. performed the statistical analyses. V.H. drafted the manuscript. D.R.W. contributed to interpretation of the data and critically revised the manuscript. All authors reviewed and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompliance with Ethical Standards\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest:\u003c/strong\u003e The authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval:\u003c/strong\u003e The study protocol was approved by the institutional review boards of all participating centers (IRB numbers: 8828-2023508; PRISABA BA 10224; 1476/2024; 08/24; 024/24; 07-04; 2024-696-GDEBA-SSGIEPYFMSALGP) and was conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent:\u003c/strong\u003e Due to the retrospective nature of the study and the use of anonymized data, informed consent was waived by the ethics committees of the participating institutions.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSanti E, Tascini G, Toni G, Berioli MG, Esposito S (2019) Linear growth in children and adolescents with type 1 diabetes mellitus. Int J Environ Res Public Health 16:3677. https://doi.org/10.3390/ijerph16193677\u003c/li\u003e\n\u003cli\u003eJivani SK, Rayner PH (1973) Does control influence the growth of diabetic children? Arch Dis Child 48:109\u0026ndash;115.\u003c/li\u003e\n\u003cli\u003eElamin A, Hussein O, Tuvemo T (2006) Growth, puberty, and final height in children with type 1 diabetes. J Diabetes Complications 20:252\u0026ndash;256. https://doi.org/10.1016/j.jdiacomp.2005.07.001\u003c/li\u003e\n\u003cli\u003eBizzarri C, Timpanaro TA, Matteoli MC, Patera IP, Cappa M, Cianfarani S (2018) Growth trajectory in children with type 1 diabetes mellitus: the impact of insulin treatment and metabolic control. Horm Res Paediatr 89:172\u0026ndash;177. https://doi.org/10.1159/000486698\u003c/li\u003e\n\u003cli\u003eAhmed ML, Connors MH, Drayer NM, Jones JS, Dunger DB (1998) Pubertal growth in IDDM is determined by HbA1c levels, sex, and bone age. Diabetes Care 21:1382.\u003c/li\u003e\n\u003cli\u003eBlasetti A, Castorani V, Polidori N, Mascioli I, Chiarelli F, Giannini C (2023) Role of glucose variability on linear growth in children with type 1 diabetes. Endocr Connect 12:e220370. https://doi.org/10.1530/EC-22-0370\u003c/li\u003e\n\u003cli\u003eBizzarri C, Benevento D, Patera IP, Bongiovanni M, Boiani A, Fusco C, Cianfarani S, Cappa M (2013) Residual \u0026beta;-cell mass influences growth of prepubertal children with type 1 diabetes. Horm Res Paediatr 80:287\u0026ndash;292.\u003c/li\u003e\n\u003cli\u003eNewfield RS, Cohen D, Capparelli EV, Shragg P (2009) Rapid weight gain in children soon after diagnosis of type 1 diabetes: is there room for concern? Pediatr Diabetes 10:310\u0026ndash;315.\u003c/li\u003e\n\u003cli\u003eHirschler V, Gonzalez CD, Krochik G et al (2024) Diabetic ketoacidosis in type 1 diabetes onset in Latin American children. J Pediatr Health Care 38:544\u0026ndash;551. https://doi.org/10.1016/j.pedhc.2024.01.006\u003c/li\u003e\n\u003cli\u003eKuczmarski RJ, Ogden CL, Grummer-Strawn LM et al (2000) CDC growth charts: United States. Adv Data (8):1\u0026ndash;27.\u003c/li\u003e\n\u003cli\u003eNational Center for Health Statistics (2000) Cut-off to define outliers in 2000 CDC growth charts: United States. http://www.cdc.gov/growthcharts/\u003c/li\u003e\n\u003cli\u003eAmerican Diabetes Association (2021) Classification and diagnosis of diabetes: standards of medical care in diabetes. Diabetes Care 44(Suppl 1):S15\u0026ndash;S33. https://doi.org/10.2337/dc21-S002\u003c/li\u003e\n\u003cli\u003eFrohlich-Reiterer EE, Rosenbauer J, Bechtold-Dalla Pozza S, Hofer SE, Schober E, Holl RW (2014) Predictors of increasing BMI during the course of diabetes in children and adolescents with type 1 diabetes. Arch Dis Child 99:738\u0026ndash;743.\u003c/li\u003e\n\u003cli\u003eJadhav I, Chakole S (2023) Effects of type 1 diabetes mellitus on linear growth: a comprehensive review. Cureus 15:e45428. https://doi.org/10.7759/cureus.45428\u003c/li\u003e\n\u003cli\u003eBonfig W, Kapellen T, Dost A, Fritsch M, Rohrer T, Wolf J, Holl RW (2012) Growth in children and adolescents with type 1 diabetes. J Pediatr 160:900\u0026ndash;903.e2. https://doi.org/10.1016/j.jpeds.2011.12.007\u003c/li\u003e\n\u003cli\u003eDunger D, Ahmed L, Ong K (2002) Growth and body composition in type 1 diabetes mellitus. Horm Res 58(Suppl 1):66\u0026ndash;71.\u003c/li\u003e\n\u003cli\u003eBrown M, Ahmed ML, Clayton KL, Dunger DB (1994) Growth during childhood and final height in type 1 diabetes. Diabet Med 11:182\u0026ndash;187. https://doi.org/10.1111/j.1464-5491.1994.tb02017.x\u003c/li\u003e\n\u003cli\u003eDunger DB, Cheetham TD (1996) Growth hormone insulin-like growth factor I axis in insulin-dependent diabetes mellitus. Horm Res 46:2\u0026ndash;6. https://doi.org/10.1159/000184969\u003c/li\u003e\n\u003cli\u003eZachrisson I, Brismar K, Hall K, Wallensteen M, Dahlqvist G (1997) Determinants of growth in diabetic pubertal subjects. Diabetes Care 20:1261\u0026ndash;1265. https://doi.org/10.2337/diacare.20.8.1261\u003c/li\u003e\n\u003cli\u003eBizzarri C, Benevento D, Patera IP et al (2013) Residual \u0026beta;-cell mass influences growth of prepubertal children with type 1 diabetes. Horm Res Paediatr 80:287\u0026ndash;292. https://doi.org/10.1159/000355116\u003c/li\u003e\n\u003cli\u003eMarcovecchio ML, Heywood JJ, Dalton RN, Dunger DB (2014) The contribution of glycemic control to impaired growth during puberty in young people with type 1 diabetes. Pediatr Diabetes 15:303\u0026ndash;308.\u003c/li\u003e\n\u003cli\u003eHirschler V, Molinari C, Gonzalez CD, CODIAPED Study Group (2024) Impact of continuous glucose monitoring on hemoglobin A1c and height trends in Latin American children with type 1 diabetes onset over 3 years: a multicenter study. J Pediatr Clin Pract 14:200130. https://doi.org/10.1016/j.jpedcp.2024.200130\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejpe","sideBox":"Learn more about [European Journal of Pediatrics](https://www.springer.com/journal/431)","snPcode":"431","submissionUrl":"https://submission.nature.com/new-submission/431/3","title":"European Journal of Pediatrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Z-Height, T1DM Onset, and Latin American Children","lastPublishedDoi":"10.21203/rs.3.rs-9054431/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9054431/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Children with type 1 diabetes (T1DM) may experience some growth delay.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e To compare growth trajectories assessed by z-height and z-BMI over a three-year follow-up period between children with new-onset T1DM and a control group without T1DM across multiple Latin American centers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A retrospective analysis of medical records was conducted over three years (2021-2024) in children with T1DM onset and their controls from ten Latin American centers, collecting data on age, sex, and anthropometric measures. A mixed-effects model was used to analyze z-height and z-BMI over three years.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e A total of 534 participants were included, comprising 245 children with T1DM (51.4% female; mean age, 8.8 years) and 289 controls (45.7% female; mean age, 8.1 years). The mean z-BMI in children with T1DM compared to controls was at years 0 (−0.12 vs. 0.54), 1 (0.36 vs. 0.63), 2 (0.32 vs. 0.55), and 3 (0.34 vs. 0.47). Children with T1DM had a significantly lower z-BMI than controls, with mean differences of -0.71, -0.33, and -0.28 in years 0, 1, and 2, respectively. However, by year 3, the mean difference (-0.18) was no longer significant. Z-Height in children with T1DM vs. controls was at years 1 (−0.08 vs. −0.09), 2 (−0.24 vs. −0.12), and 3 (−0.35 vs. −0.12). Z-Height remained stable in controls but declined in the T1DM group, reaching a mean difference of −0.25 (p\u0026lt;0.01) by year 3.\u003c/p\u003e\n\u003cp\u003eThese findings highlight the need to improve early diagnosis and access to diabetes technologies in Latin America.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e This study suggested that despite treatment and equalization of z-BMI, children with T1DM in Latin America experience some growth delay.\u003c/p\u003e","manuscriptTitle":"Contrasting BMI and Height z-Score Trajectories in Children With New-Onset T1DM: A Case-Control Study Across Latin American Centers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-24 13:16:14","doi":"10.21203/rs.3.rs-9054431/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-03T17:09:51+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-03T07:02:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-27T13:15:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"120689041118643450109498952129799168872","date":"2026-03-20T00:03:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"90282012674563883921910603768549764176","date":"2026-03-19T11:41:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-19T06:53:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-18T00:02:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-17T22:48:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Pediatrics","date":"2026-03-06T23:59:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejpe","sideBox":"Learn more about [European Journal of Pediatrics](https://www.springer.com/journal/431)","snPcode":"431","submissionUrl":"https://submission.nature.com/new-submission/431/3","title":"European Journal of Pediatrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6853ca7f-599f-43cb-8fc5-d7d8e00f61c9","owner":[],"postedDate":"March 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-11T06:12:17+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-24 13:16:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9054431","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9054431","identity":"rs-9054431","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}