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Antropometría como predictor de diabetes gestacional: Estudio de cohorte

    1. [1] Universidad Católica del Maule

      Universidad Católica del Maule

      Provincia de Talca, Chile

    2. [2] Pontificia Universidad Católica de Chile

      Pontificia Universidad Católica de Chile

      Santiago, Chile

    3. [3] London school of Hygiene and tropical Medicine Public Health and Nutrition Department
  • Localización: Revista Médica de Chile, ISSN-e 0034-9887, Vol. 138, Nº. 11, 2010, págs. 1373-1377
  • Idioma: español
  • Títulos paralelos:
    • Anthropometry as predictor of gestational diabetes mellitus
  • Enlaces
  • Resumen
    • Background: Gestational diabetes mellitus (GDM) is a high incidence disease. Easily measured predictor factors could help to implement preventive policies and early detection tests. Aim: To measure recognizable risk factors for GDM such as skinfolds and analyze the association between these factors and the development of GDM in a cohort of pregnant women. Material and Methods: Evaluation of 76 mothers that developed gestational diabetes, aged 32.2 ± 0.6 years and 324 control mothers that did not develop the disease, aged 30.1 ± 0.3 years. Weight, height, arm circumference, tricipital, bicipital, subscapular, suprailiac, knee, costal and mid-thigh skinfolds were measured in the pre-diseased stage. History of diabetes, fasting glucose and insulin levels were also evaluated. Results: Age, body mass index (BMI), fasting blood glucose, the homeostasis model assessment of insulin resistance (HOMA), bi-cipital, tricipital, costal, subscapular, suprailiac, and knee skinfolds were associated with GDM development. Age, fasting blood glucose and subscapular skinfolds were independent predictors in the logistic regression model. The odds ratio for a subs-capular skinfold over percentile 90 was 1.7 (95% confdence intervals: 1.07-3.04). Conclusions: Age and fasting blood glucose are independent risk factors for GDM. Subscapular skinfold is also an independent risk factor and could be used to detect high risk pregnant women and implement preventive policies.

Los metadatos del artículo han sido obtenidos de SciELO Chile

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