Predictive model for gestational diabetes based on anthropometric and metabolic factors

Authors

Keywords:

gestational diabetes; anthropometry; uric acid; predictive models; preventive medicine

Abstract

Introduction: Gestational diabetes mellitus represents a major public health problem due to its association with obstetric and neonatal complications. Early identification of women at risk using accessible tools is a relevant clinical challenge.
Objective: To develop and internally validate a predictive model for gestational diabetes mellitus based on anthropometric and biochemical parameters easily obtained in routine clinical practice.
Methods: An analytical observational study was conducted including 247 pregnant women between 24 and 28 weeks. Anthropometric measurements (neck circumference, wrist circumference, skinfold thickness) and serum uric acid levels were assessed. Independent predictors were identified using multivariate analysis, and a mathematical model was developed with its corresponding internal validation.
Results: Cervical circumference ≥35.1 centimeters (adjusted OR 3.72; 95% CI 2.01-6.89), uric acid ≥331 mg/dl (OR 2.85; 95% CI 1.52-5.33), and BMI ≥25 kg/m² (OR 2.40; 95% CI 1.30-4.42) emerged as significant predictors. The model showed an area under the ROC curve of 0.78 (95% CI 0.72-0.84), with adequate calibration (Hosmer-Lemeshow test p=0.32). Bootstrapping validation confirmed the stability of the estimators (bias <2.5%).
Conclusions: The proposed model, which integrates simple clinical parameters, demonstrated adequate discriminatory capacity to identify pregnant women at high risk of developing gestational diabetes mellitus.

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Author Biographies

Jose Alberto Castellano Peña, Provincial University Gynecological and Obstetric Hospital "Mariana Grajales"

Second-level specialist in Obstetrics and Gynecology. Assistant Professor

Juan Antonio Suárez Gonzalez, Provincial University Gynecological and Obstetric Hospital "Mariana Grajales"

Specialist in Gynecology and Obstetrics, first and second degrees. Assistant Professor at the Villa Clara University of Medical Sciences.

Daily Cruz García, Provincial University Gynecological and Obstetric Hospital "Mariana Grajales"

1st-degree specialist in Endocrinology.Assistant Professor

Elizabeth Machin Parapar, Provincial University Gynecological and Obstetric Hospital "Mariana Grajales"

Especialista primer grado Laboratorio Clínico. Profesora Asistente

Mylena Silverio Negrin, Provincial University Gynecological and Obstetric Hospital "Mariana Grajales"

Especialista de I Grado en Ginecología y Obstetricia. Profesora Instructora

References

1. Li D, Zhao Y, Zhang L, You Q, Jiang Q, Yin X, et al. Association between neck circumference and diabetes mellitus: a systematic review and meta-analysis. Diabetol Metab Syndr [Internet]. 2023 [citado 21/10/2024]; 15(1): [aprox. 2p.]. https://dmsjournal.biomedcentral.com/articles/10.1186/s13098-023-01111-z

https://doi.org/10.1186/s13098-023-01111-z

2. Pérez-López FR, Martínez-Domínguez SJ, Lajusticia H, Chedraui P. Effects of programmed exercise on depressive symptoms in midlife and older women: A meta-analysis of randomized controlled trials. Maturitas [Internet]. 2017 [citado 21/10/2024]; 106:[aprox. 2p.]. https://pubmed.ncbi.nlm.nih.gov/29150165/

https://doi.org/10.1016/j.maturitas.2017.09.001

3. García-Patterson A, Erdozain L, Ginovart G, Adelantado JM, Cubero JM, Gallo G, et al. In human gestational diabetes mellitus congenital malformations are related to pre-pregnancy body mass index and to severity of diabetes. Diabetologia [Internet]. 2004 [citado 21/10/2024]; 47(3): [aprox. 3p.]. https://pubmed.ncbi.nlm.nih.gov/14770278/

https://doi.org/10.1007/s00125-004-1337-3

4. Instituto Nacional de Endocrinología. Segundo Consenso Cubano de Diabetes y Embarazo. Rev Cubana Endocrinol [Internet]. 2018 [citado 08/05/2025]; 29(1): [aprox. 2p.]. Disponible en: https://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S1561-29532018000100001&lng=es.

5. Saeedi M, Cao Y, Fadl H, Gustafson H, Simmons D. Increasing prevalence of gestational diabetes mellitus when implementing the IADPSG criteria: A systematic review and meta-analysis. Diabetes Res Clin Pract [Internet]. 2021 [citado 08/05/2025]; 172: [aprox. 2p.]. Disponible en: https://pubmed.ncbi.nlm.nih.gov/33359574/

https://doi.org/10.1016/j.diabres.2020.108642

6. Gallardo-Rincón H, Cantoral A, Arrieta A, Espinal C, Magnus MH, Palacios C, et al. Review: Type 2 diabetes in Latin America and the Caribbean: Regional and country comparison on prevalence, trends, costs and expanded prevention. Prim Care Diabetes [Internet]. 2021 [citado 08/05/2025]; 15(2): [aprox. 2p.]. Disponible en: https://pubmed.ncbi.nlm.nih.gov/33077379/

https://doi.org/10.1016/j.pcd.2020.10.001

7. Xiong Q, Liu J, Xu Y. Effects of Uric Acid on Diabetes Mellitus and Its Chronic Complications. Int J Endocrinol [Internet]. 2019 [citado 08/05/2025]; 2019 [citado 08/05/2025]; 2019: [aprox.2p.] Disponible en: https://pmc.ncbi.nlm.nih.gov/articles/PMC6815590/

https://doi.org/10.1155/2019/9691345

8. Deng F, Wang Q, Wen X, Xu X, Jia L, He H, et al. Association between Body Mass Index and Serum Uric Acid: mediation analysis involving liver enzymes indicators. BMC Public Health [Internet]. 2024 [citado 08/05/2025]; 24(1): [aprox. 2p.]. Disponible en: https://pubmed.ncbi.nlm.nih.gov/39478457/

https://doi.org/10.1186/s12889-024-20457-1

9. Yang H, Liu H, Chen Y, Zhu C, Fang W, Mao W, et al. Long-term Efficacy of Neoadjuvant Chemoradiotherapy Plus Surgery for the Treatment of Locally Advanced Esophageal Squamous Cell Carcinoma: The NEOCRTEC5010 Randomized Clinical Trial. JAMA surg [Internet]. 2021 [citado 08/05/2025], 156(8):[aprox. 3p.]. Disponible en: https://pubmed.ncbi.nlm.nih.gov/34160577/

https://doi.org/10.1001/jamasurg.2021.2373

10. Minschart C, Beunen K, Benhalimai K. An Update on Screening Strategies for Gestational Diabetes Mellitus: A Narrative Review. Diabetes Metab Syndr Obes [Internet]. 2021 [citado 08/05/2025]; 14: [aprox. 2p.]. https://pubmed.ncbi.nlm.nih.gov/34262311/

https://doi.org/10.2147/DMSO.S287121

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Published

2025-09-01

How to Cite

1.
Castellano Peña JA, Suárez Gonzalez JA, Cruz García D, Machin Parapar E, Silverio Negrin M. Predictive model for gestational diabetes based on anthropometric and metabolic factors. Acta Méd Centro [Internet]. 2025 Sep. 1 [cited 2025 Sep. 8];19(1):e2260. Available from: https://revactamedicacentro.sld.cu/index.php/amc/article/view/2260

Issue

Vol. 19 (2025): PUBLICACIÓN CONTINUA

Section

Original Articles

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Copyright (c) 2025 Juan Antonio Suarez Gonzalez, Jose Alberto Castellano Peña, Daily Cruz Garcia, Eliza Machin Parapar, Mylena Silverio Negrin

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