Startseite Relationships among biological sex, body composition, and bone mineral density in young persons with and without diabetes
Artikel
Lizenziert
Nicht lizenziert Erfordert eine Authentifizierung

Relationships among biological sex, body composition, and bone mineral density in young persons with and without diabetes

  • Carson Platnick EMAIL logo , Ye Ji Choi , Phoom Narongkiatikhun , Nathan Bekelman , Callie Rountree-Jablin , Carissa Birznieks , Emily Sell , Kalie L. Tommerdahl , Ian de Boer , Viral N. Shah , Kristen J. Nadeau , Alexandra Sawyer , Laura Pyle und Petter Bjornstad
Veröffentlicht/Copyright: 10. April 2025
Journal of Pediatric Endocrinology and Metabolism
Aus der Zeitschrift Journal of Pediatric Endocrinology and Metabolism Band 38 Heft 5

Abstract

Objectives

Bone mineral density (BMD) is influenced by factors including age, sex, body composition, and diabetes. However, data regarding these relationships in young individuals is limited. The objective of this study was to address this gap in the literature. 

Methods

We conducted a post-hoc analysis of participants from six cross-sectional cohort studies, encompassing individuals with type 1 diabetes (T1D) and type 2 diabetes (T2D), as well as controls of healthy weight (HWC) and with obesity (OC). Whole-body dual-energy X-ray absorptiometry (DXA) was employed to measure BMD and body composition. Multiple linear regression models assessed sexual dimorphism in BMD, adjusting for age and exploring effect modification by group and sex.

Results

A total of 325 participants were included (T1D [n=123, mean age 22.4 years, 50 % male], T2D [n=72, mean age 16.2 years, 33 % male], HWC [n=79, mean age 16.6 years, 41 % male], and OC [n=51, mean age 13.8 years, 53 % male]). Sexual dimorphism in BMD was evident only in T1D and HWC, with males having higher BMD than females (p=0.021; p<0.001, respectively). BMI was positively correlated with BMD in all groups (p<0.001 for HWC; p=0.001 for OC; p<0.001 for T1D; p=0.008 for T2D). Body fat percentage was inversely correlated with BMD in HWC and T1D (p<0.001; p=0.011, respectively), but not in OC or T2D. Additionally, lean mass percentage was significantly associated with higher BMD in HWC and OC (p<0.001; p=0.023, respectively), but not in groups with diabetes.

Conclusions

Our study documents sexual dimorphism in BMD in youth, with varied associations between body composition metrics and BMD across groups with diabetes and in controls without diabetes, underscoring the importance of understanding these relationships for optimizing bone health during adolescence.

Keywords: bone mineral density; body composition; obesity; diabetes; body fat percentage; lean mass percentage
Corresponding author: Carson Platnick, MD, Section of Endocrinology, Department of Pediatrics, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA, E-mail:

Funding source: Juvenile Diabetes Research Foundation International

Award Identifier / Grant number: 2-SRA-2018-627-M-B

Award Identifier / Grant number: 2-SRA-2019-845-S-B

Funding source: American Heart Association

Award Identifier / Grant number: 20IPA35260142

Funding source: Colorado Clinical and Translational Sciences Institute

Funding source: Boettcher Foundation

Funding source: Division of Diabetes, Endocrinology, and Metabolic Diseases

Award Identifier / Grant number: DK-076169

Award Identifier / Grant number: DK-115255

Award Identifier / Grant number: K23-DK-116720

Award Identifier / Grant number: P30-DK-116073

Award Identifier / Grant number: R01-DK-129211-01

Award Identifier / Grant number: R01-DK-132399

Funding source: Division of Intramural Research

Award Identifier / Grant number: K24-HL145076

Award Identifier / Grant number: UL1-RR025780

Funding source: Center for Women’s Health Research at University of Colorado, the Department of Pediatrics, Section of Endocrinology and Barbara Davis Center for Diabetes at University of Colorado School of Medicine, and by the Intramural Research Program of the NIDDK

Funding source: Boettcher Foundation and in part by the Intramural Research Program at NIDDK and the Centers for Disease Control and Prevention (CKD Initiative) under inter-Agency Agreement #21FED2100157DPG

Funding source: NIH/NIDDK, American Heart Association, Children’s Hospital Colorado Research Institute, Colorado Clinical and Translational Sciences Institute (CCTSI)

Funding source: NIH/NIDDK K23 DK116720, as well as Boettcher Foundation

Funding source: NHLBI (HL165433)

Funding source: JDRF

Award Identifier / Grant number: 3-SRA-2022-1097-M-B, 3-SRA-2022-1230-M-B, 3-SRA-2022-1243-M-B, 3-SRA-2023-1373-M-B

Funding source: American Heart Association

Award Identifier / Grant number: 20IPA35260142

Funding source: American Diabetes Association

Award Identifier / Grant number: 7-23-ICTST2DY-08

Award Identifier / Grant number: 7-23-ICTST2DY-01

Funding source: Boettcher Foundation, Ludeman Family Center for Women’s Health Research at the University of Colorado, the Department of Pediatrics, Section of Endocrinology and Barbara Davis Center for Diabetes at University of Colorado School of Medicine

Funding source: NHLBI

Award Identifier / Grant number: HL159292

Funding source: American Diabetes Association

Award Identifier / Grant number: 11-23-ICTST2DY

Funding source: the Ludeman Family Center for Women’s Health Research at the University of Colorado, and the Department of Pediatrics, Section of Endocrinology

  1. Research ethics: Study protocols were reviewed and approved by the Colorado Multiple Institutional Review Board (COMIRB), approval numbers 17–0820 (CASPER), 19–1,282 (CROCODILE), 16–1752 (RENAL-HEIR), 18–0704 (IMPROVE-T2D), 22–0250, and 21–3,019 (PANTHER).

  2. Informed consent: All participants underwent assent plus written parental consent if age <18 years, or written participant consent if age ≥ 18 years.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission. CP: literature search, study design, data interpretation, writing. YC: study design, data analysis, data interpretation, writing. PN: critical revision. NB: critical revision. CR: critical revision. CB: critical revision. ES: critical revision. KLT: critical revision. ID: critical revision. VS: critical revision. KJN: critical revision. AS: critical revision. LP: critical revision. PB: study design, data interpretation, writing.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interests: Authors state no conflict of interest.

  6. Research funding: CASPER: Financial support for this work was provided by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Diabetic Complications Consortium (RRID:SCR_001415, www.diacomp.org), grants DK-076169 and DK115255 (18AU3871 [P.B.]), JDRF International grant 2-SRA-2018-627-M-B (P.B.), and National Institutes of Health (NIH) NIDDK grant K23-DK-116720 (P.B.), National Heart, Lung, and Blood Institute grant K24-HL145076 (K.J.N.), and UL1-RR025780 (University of Colorado Denver), support from the Center for Women’s Health Research at University of Colorado, the Department of Pediatrics, Section of Endocrinology and Barbara Davis Center for Diabetes at University of Colorado School of Medicine, and by the Intramural Research Program of the NIDDK. CROCODILE: This study was supported by NIDDK (P30 DK116073), JDRF (2-SRA-2019-845-S-B), Boettcher Foundation and in part by the Intramural Research Program at NIDDK and the Centers for Disease Control and Prevention (CKD Initiative) under inter-Agency Agreement #21FED2100157DPG. RENAL-HEIR: This work was supported by the NIH/NIDDK K23 DK116720, as well as Boettcher Foundation. IMPROVE-T2D: This was supported by NIH/NIDDK, American Heart Association, Children’s Hospital Colorado Research Institute, Colorado Clinical and Translational Sciences Institute (CCTSI). PANDA: This work was supported by the NIH/NIDDK R01 DK132399. PANTHER: This study receives support from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) (R01 DK129211-01). P.B. receives salary and research support from NIDDK (DK132399, DK129211, DK129720, DK116720), NHLBI (HL165433), JDRF (3-SRA-2022-1097-M-B, 3-SRA-2022-1230-M-B, 3-SRA-2022-1243-M-B, 3-SRA-2023-1373-M-B), American Heart Association (20IPA35260142), and American Diabetes Association (7-23-ICTST2DY-08, 7-23-ICTST2DY-01), Boettcher Foundation, Ludeman Family Center for Women’s Health Research at the University of Colorado, the Department of Pediatrics, Section of Endocrinology and Barbara Davis Center for Diabetes at University of Colorado School of Medicine. K.L.T. receives salary and research support from NHLBI (HL159292), the American Diabetes Association (11-23-ICTST2DY), the Ludeman Family Center for Women’s Health Research at the University of Colorado, and the Department of Pediatrics, Section of Endocrinology.

  7. Data availability: Not applicable.

References

1. Rasmussen, NH, Dal, J, Kvist, AV, van den Bergh, JP, Jensen, MH, Vestergaard, P. Bone parameters in T1D and T2D assessed by DXA and HR-pQCT - a cross-sectional study: the DIAFALL study. Bone 2023;172:116753. https://doi.org/10.1016/j.bone.2023.116753.Suche in Google Scholar PubMed

2. Weber, DR, Haynes, K, Leonard, MB, Willi, SM, Denburg, MR. Type 1 diabetes is associated with an increased risk of fracture across the life span: a population-based cohort study using the Health Improvement Network (THIN). Diabetes Care 2015;38:1913–20. https://doi.org/10.2337/dc15-0783.Suche in Google Scholar PubMed PubMed Central

3. Friedrich, N, Thuesen, B, Jørgensen, T, Juul, A, Spielhagen, C, Wallaschofksi, H, et al.. The association between IGF-I and insulin resistance: a general population study in Danish adults. Diabetes Care 2012;35:768–73. https://doi.org/10.2337/dc11-1833.Suche in Google Scholar PubMed PubMed Central

4. Gutefeldt, K, Hedman, CA, Thyberg, ISM, Bachrach-Lindström, M, Spångeus, A, Arnqvist, HJ. Dysregulated growth hormone-insulin-like growth factor-1 axis in adult type 1 diabetes with long duration. Clin Endocrinol (Oxf) 2018;89:424–30. https://doi.org/10.1111/cen.13810.Suche in Google Scholar PubMed

5. Yuan, S, Wan, ZH, Cheng, SL, Michaëlsson, K, Larsson, SC. Insulin-like growth factor-1, bone mineral density, and fracture: a Mendelian randomization study. J Clin Endocrinol Metab 2021;106:e1552–8. https://doi.org/10.1210/clinem/dgaa963.Suche in Google Scholar PubMed PubMed Central

6. Schwartz, AV, Backlund, JC, de Boer, IH, Rubin, MR, Barnie, A, Farrell, K, et al.. Risk factors for lower bone mineral density in older adults with type 1 diabetes: a cross-sectional study. Lancet Diabetes Endocrinol 2022;10:509–18. https://doi.org/10.1016/s2213-8587(22)00103-6.Suche in Google Scholar PubMed

7. Heilman, K, Zilmer, M, Zilmer, K, Tillmann, V. Lower bone mineral density in children with type 1 diabetes is associated with poor glycemic control and higher serum ICAM-1 and urinary isoprostane levels. J Bone Miner Metab 2009;27:598–604. https://doi.org/10.1007/s00774-009-0076-4.Suche in Google Scholar PubMed

8. Loxton, P, Narayan, K, Munns, CF, Craig, ME. Bone mineral density and type 1 diabetes in children and adolescents: a meta-analysis. Diabetes Care 2021;44:1898–905. https://doi.org/10.2337/dc20-3128.Suche in Google Scholar PubMed PubMed Central

9. Perng, W, Conway, R, Mayer-Davis, E, Dabelea, D. Youth-onset type 2 diabetes: the epidemiology of an awakening epidemic. Diabetes Care 2023;46:490–9. https://doi.org/10.2337/dci22-0046.Suche in Google Scholar PubMed PubMed Central

10. Vestergaard, P. Discrepancies in bone mineral density and fracture risk in patients with type 1 and type 2 diabetes-a meta-analysis. Osteoporos Int 2007;18:427–44. https://doi.org/10.1007/s00198-006-0253-4.Suche in Google Scholar PubMed

11. Melton3rdLJ, Riggs, BL, Leibson, CL, Achenbach, SJ, Camp, JJ, Bouxsein, ML, et al.. A bone structural basis for fracture risk in diabetes. J Clin Endocrinol Metab 2008;93:4804–9. https://doi.org/10.1210/jc.2008-0639.Suche in Google Scholar PubMed PubMed Central

12. van Daele, PL, Stolk, RP, Burger, H, Algra, D, Grobbee, DE, Hofman, A, et al.. Bone density in non-insulin-dependent diabetes mellitus. The Rotterdam study. Ann Intern Med 1995;122:409–14. https://doi.org/10.7326/0003-4819-122-6-199503150-00002.Suche in Google Scholar PubMed

13. Weinstock, RS, Goland, RS, Shane, E, Clemens, TL, Lindsay, R, Bilezikian, JP. Bone mineral density in women with type II diabetes mellitus. J Bone Min Res 1989;4:97–101. https://doi.org/10.1002/jbmr.5650040114.Suche in Google Scholar PubMed

14. Plymate, SR, Matej, LA, Jones, RE, Friedl, KE. Inhibition of sex hormone-binding globulin production in the human hepatoma (Hep G2) cell line by insulin and prolactin. J Clin Endocrinol Metab 1988;67:460–4. https://doi.org/10.1210/jcem-67-3-460.Suche in Google Scholar PubMed

15. Birkeland, KI, Hanssen, KF, Torjesen, PA, Vaaler, S. Level of sex hormone-binding globulin is positively correlated with insulin sensitivity in men with type 2 diabetes. J Clin Endocrinol Metab 1993;76:275–8. https://doi.org/10.1210/jcem.76.2.8432768.Suche in Google Scholar PubMed

16. van Hemert, AM, Birkenhäger, JC, De Jong, FH, Vandenbroucke, JP, Valkenburg, HA. Sex hormone binding globulin in postmenopausal women: a predictor of osteoporosis superior to endogenous oestrogens. Clin Endocrinol (Oxf) 1989;31:499–509. https://doi.org/10.1111/j.1365-2265.1989.tb01274.x.Suche in Google Scholar PubMed

17. Hein, G, Weiss, C, Lehmann, G, Niwa, T, Stein, G, Franke, S. Advanced glycation end product modification of bone proteins and bone remodelling: hypothesis and preliminary immunohistochemical findings. Ann Rheum Dis 2006;65:101–4. https://doi.org/10.1136/ard.2004.034348.Suche in Google Scholar PubMed PubMed Central

18. Odetti, P, Rossi, S, Monacelli, F, Poggi, A, Cirnigliaro, M, Federici, M, et al.. Advanced glycation end products and bone loss during aging. Ann N Y Acad Sci 2005;1043:710–7. https://doi.org/10.1196/annals.1333.082.Suche in Google Scholar PubMed

19. Saito, M, Fujii, K, Soshi, S, Tanaka, T. Reductions in degree of mineralization and enzymatic collagen cross-links and increases in glycation-induced pentosidine in the femoral neck cortex in cases of femoral neck fracture. Osteoporos Int 2006;17:986–95. https://doi.org/10.1007/s00198-006-0087-0.Suche in Google Scholar PubMed

20. Yamagishi, S, Nakamura, K, Inoue, H. Possible participation of advanced glycation end products in the pathogenesis of osteoporosis in diabetic patients. Med Hypotheses 2005;65:1013–5. https://doi.org/10.1016/j.mehy.2005.07.017.Suche in Google Scholar PubMed

21. Picke, AK, Campbell, G, Napoli, N, Hofbauer, LC, Rauner, M. Update on the impact of type 2 diabetes mellitus on bone metabolism and material properties. Endocr Connect 2019;8:R55–r70. https://doi.org/10.1530/ec-18-0456.Suche in Google Scholar

22. Bouillon, R. Diabetic bone disease. Calcif Tissue Int 1991;49:155–60. https://doi.org/10.1007/bf02556109.Suche in Google Scholar PubMed

23. Pollock, NK. Childhood obesity, bone development, and cardiometabolic risk factors. Mol Cell Endocrinol 2015;410:52–63. https://doi.org/10.1016/j.mce.2015.03.016.Suche in Google Scholar PubMed PubMed Central

24. Streeter, AJ, Hosking, J, Metcalf, BS, Jeffery, AN, Voss, LD, Wilkin, TJ. Body fat in children does not adversely influence bone development: a 7-year longitudinal study (EarlyBird 18). Pediatr Obes 2013;8:418–27. https://doi.org/10.1111/j.2047-6310.2012.00126.x.Suche in Google Scholar

25. Deng, KL, Yang, WY, Hou, JL, Li, H, Feng, H, Xiao, SM. Association between body composition and bone mineral density in children and adolescents: a systematic review and meta-analysis. Int J Environ Res Public Health 2021;18. https://doi.org/10.3390/ijerph182212126.Suche in Google Scholar PubMed PubMed Central

26. Nordström, P, Nordström, G, Thorsen, K, Lorentzon, R. Local bone mineral density, muscle strength, and exercise in adolescent boys: a comparative study of two groups with different muscle strength and exercise levels. Calcif Tissue Int 1996;58:402–8. https://doi.org/10.1007/bf02509438.Suche in Google Scholar

27. Torres-Costoso, A, López-Muñoz, P, Martínez-Vizcaíno, V, Álvarez-Bueno, C, Cavero-Redondo, I. Association between muscular strength and bone health from children to young adults: a systematic review and meta-analysis. Sports Med 2020;50:1163–90. https://doi.org/10.1007/s40279-020-01267-y.Suche in Google Scholar PubMed

28. Callaway, DA, Jiang, JX. Reactive oxygen species and oxidative stress in osteoclastogenesis, skeletal aging and bone diseases. J Bone Miner Metab 2015;33:359–70. https://doi.org/10.1007/s00774-015-0656-4.Suche in Google Scholar PubMed

29. Shapses, SA, Pop, LC, Wang, Y. Obesity is a concern for bone health with aging. Nutr Res 2017;39:1–13. https://doi.org/10.1016/j.nutres.2016.12.010.Suche in Google Scholar PubMed PubMed Central

30. Fintini, D, Brufani, C, Grossi, A, Ubertini, G, Fiori, R, Pecorelli, L, et al.. Gender differences in bone mineral density in obese children during pubertal development. J Endocrinol Invest 2011;34:e86–91. https://doi.org/10.1007/bf03347097.Suche in Google Scholar

31. Dolan, E, Swinton, PA, Sale, C, Healy, A, O’Reilly, J. Influence of adipose tissue mass on bone mass in an overweight or obese population: systematic review and meta-analysis. Nutr Rev 2017;75:858–70. https://doi.org/10.1093/nutrit/nux046.Suche in Google Scholar PubMed

32. Khalid, AB, Krum, SA. Estrogen receptors alpha and beta in bone. Bone 2016;87:130–5. https://doi.org/10.1016/j.bone.2016.03.016.Suche in Google Scholar PubMed PubMed Central

33. Wawrzkiewicz-Jałowiecka, A, Lalik, A, Soveral, G. Recent update on the molecular mechanisms of gonadal steroids action in adipose tissue. Int J Mol Sci 2021;22. https://doi.org/10.3390/ijms22105226.Suche in Google Scholar PubMed PubMed Central

34. Weaver, CM, Gordon, CM, Janz, KF, Kalkwarf, HJ, Lappe, JM, Lewis, R, et al.. The National Osteoporosis Foundation’s position statement on peak bone mass development and lifestyle factors: a systematic review and implementation recommendations. Osteoporos Int 2016;27:1281–386. https://doi.org/10.1007/s00198-015-3440-3.Suche in Google Scholar PubMed PubMed Central

35. Baxter-Jones, AD, Mirwald, RL, McKay, HA, Bailey, DA. A longitudinal analysis of sex differences in bone mineral accrual in healthy 8-19-year-old boys and girls. Ann Hum Biol 2003;30:160–75. https://doi.org/10.1080/0301446021000034642.Suche in Google Scholar PubMed

36. Bonjour, JP, Chevalley, T. Pubertal timing, bone acquisition, and risk of fracture throughout life. Endocr Rev 2014;35:820–47. https://doi.org/10.1210/er.2014-1007.Suche in Google Scholar PubMed

37. Centers for Disease Control and Prevention NCfHS. Growth charts - percentile data files with LMS values [Website]; 2000. Available from: https://www.cdc.gov/growthcharts/percentile_data_files.htm.Suche in Google Scholar

38. Notelovitz, M. Androgen effects on bone and muscle. Fertil Steril 2002;77:S34–41. https://doi.org/10.1016/s0015-0282(02)02968-0.Suche in Google Scholar PubMed

39. De Oliveira, DH, Fighera, TM, Bianchet, LC, Kulak, CA, Kulak, J. Androgens and bone. Minerva Endocrinol 2012;37:305–14.Suche in Google Scholar

40. Li, Y. Association between obesity and bone mineral density in middle-aged adults. J Orthop Surg Res 2022;17:268. https://doi.org/10.1186/s13018-022-03161-x.Suche in Google Scholar PubMed PubMed Central

41. Seo, YG, Kim, Y, Lim, H, Kang, MJ, Park, KH. Relationship between bone mineral density and body composition according to obesity status in children. Endocr Pract 2021;27:983–91. https://doi.org/10.1016/j.eprac.2021.06.006.Suche in Google Scholar PubMed

42. Arisaka, O, Hoshi, M, Kanazawa, S, Numata, M, Nakajima, D, Kanno, S, et al.. Preliminary report: effect of adrenal androgen and estrogen on bone maturation and bone mineral density. Metabolism 2001;50:377–9. https://doi.org/10.1053/meta.2001.21678.Suche in Google Scholar PubMed

43. Kuryłowicz, A. Estrogens in adipose tissue physiology and obesity-related dysfunction. Biomedicines 2023;11. https://doi.org/10.3390/biomedicines11030690.Suche in Google Scholar PubMed PubMed Central

44. Navarro, G, Allard, C, Xu, W, Mauvais-Jarvis, F. The role of androgens in metabolism, obesity, and diabetes in males and females. Obesity (Silver Spring) 2015;23:713–9. https://doi.org/10.1002/oby.21033.Suche in Google Scholar PubMed PubMed Central

45. Van Hulten, V, Sarodnik, C, Driessen, JHM, Viggers, R, Rasmussen, NH, Geusens, P, et al.. Bone microarchitecture and strength assessed by HRpQCT in individuals with type 2 diabetes and prediabetes: the Maastricht study. JBMR Plus 2024;8:ziae086. https://doi.org/10.1093/jbmrpl/ziae086.Suche in Google Scholar PubMed PubMed Central

46. Thong, EP, Herath, M, Weber, DR, Ranasinha, S, Ebeling, PR, Milat, F, et al.. Fracture risk in young and middle-aged adults with type 1 diabetes mellitus: a systematic review and meta-analysis. Clin Endocrinol (Oxf) 2018;89:314–23. https://doi.org/10.1111/cen.13761.Suche in Google Scholar PubMed PubMed Central

47. Rasmussen, NH, Driessen, JHM, Kvist, AV, Souverein, PC, van den Bergh, JP, Vestergaard, P. Fracture patterns and associated risk factors in pediatric and early adulthood type 1 diabetes: findings from a nationwide retrospective cohort study. Bone 2024;180:116997. https://doi.org/10.1016/j.bone.2023.116997.Suche in Google Scholar PubMed

48. Cichosz, SL, Rasmussen, NH, Vestergaard, P, Hejlesen, O. Precise prediction of total body lean and fat mass from anthropometric and demographic data: development and validation of neural network models. J Diabetes Sci Technol 2021;15:1337–43. https://doi.org/10.1177/1932296820971348.Suche in Google Scholar PubMed PubMed Central

Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/jpem-2024-0254).

Received: 2024-05-26
Accepted: 2025-03-02
Published Online: 2025-04-10
Published in Print: 2025-05-26

© 2025 Walter de Gruyter GmbH, Berlin/Boston

Artikel in diesem Heft

  1. Frontmatter
  2. Review
  3. A recent update on childhood obesity: aetiology, treatment and complications
  4. Original Articles
  5. Chronotype, sleep, and glycemic control in children and adolescents with type 1 diabetes: a case-control study
  6. Determinants of childhood and adolescent obesity and it’s effect on metabolism in South Indian population
  7. Evaluation of continuous glucose monitoring and nutritional status in glycogen storage diseases
  8. Retrospective assessment of hepatic involvement in patients with inherited metabolic disorders: nine-year single-center experience
  9. Relationships among biological sex, body composition, and bone mineral density in young persons with and without diabetes
  10. The clinical characteristics of 10 cases and adult height of six cases of rare familial male-limited precocious puberty
  11. Optimal timing of repeat thyroid fine-needle aspiration biopsy
  12. Medium-chain acyl-CoA dehydrogenase deficiency in North Macedonia – ten years experience
  13. The effect of antenatal steroids on metabolic bone disease of prematurity
  14. Prader-Willi syndrome gene expression profiling of obese and non-obese patients reveals transcriptional changes in CLEC4D and ANXA3
  15. Early-onset growth hormone treatment in Prader–Willi syndrome attenuates transition to severe obesity
  16. Case Reports
  17. Neonatal severe hyperparathyroidism with inactivating calcium sensing receptor (CaSR) mutation (p.I81K)
  18. Clinical manifestations and molecular genetics of seven patients with Niemann–Pick type-C: a case series with a novel variant
  19. Expanding the genotypic spectrum of 3β-hydroxy-δ5-C27-steroid dehydrogenase (HSD3B7) deficiency: novel mutations and clinical outcomes
https://doi.org/10.1515/jpem-2024-0254
Schlagwörter für diesen Artikel
bone mineral density; body composition; obesity; diabetes; body fat percentage; lean mass percentage

Artikel in diesem Heft

  1. Frontmatter
  2. Review
  3. A recent update on childhood obesity: aetiology, treatment and complications
  4. Original Articles
  5. Chronotype, sleep, and glycemic control in children and adolescents with type 1 diabetes: a case-control study
  6. Determinants of childhood and adolescent obesity and it’s effect on metabolism in South Indian population
  7. Evaluation of continuous glucose monitoring and nutritional status in glycogen storage diseases
  8. Retrospective assessment of hepatic involvement in patients with inherited metabolic disorders: nine-year single-center experience
  9. Relationships among biological sex, body composition, and bone mineral density in young persons with and without diabetes
  10. The clinical characteristics of 10 cases and adult height of six cases of rare familial male-limited precocious puberty
  11. Optimal timing of repeat thyroid fine-needle aspiration biopsy
  12. Medium-chain acyl-CoA dehydrogenase deficiency in North Macedonia – ten years experience
  13. The effect of antenatal steroids on metabolic bone disease of prematurity
  14. Prader-Willi syndrome gene expression profiling of obese and non-obese patients reveals transcriptional changes in CLEC4D and ANXA3
  15. Early-onset growth hormone treatment in Prader–Willi syndrome attenuates transition to severe obesity
  16. Case Reports
  17. Neonatal severe hyperparathyroidism with inactivating calcium sensing receptor (CaSR) mutation (p.I81K)
  18. Clinical manifestations and molecular genetics of seven patients with Niemann–Pick type-C: a case series with a novel variant
  19. Expanding the genotypic spectrum of 3β-hydroxy-δ5-C27-steroid dehydrogenase (HSD3B7) deficiency: novel mutations and clinical outcomes
Jetzt anmelden und 20% sparen
Institutioneller Zugang
Wie funktioniert Authentifizierung?
Haben Sie eine Idee, wie wir unsere Website verbessern können?
Bitte schreiben Sie uns.
© 2025 De Gruyter Brill
Heruntergeladen am 15.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/jpem-2024-0254/html
Button zum nach oben scrollen