Diabetes Epidemiology and Management (Oct 2024)

Anthropometric measures of obesity as risk indicators for prediabetes. A systematic review and meta-analysis

  • Víctor Juan Vera-Ponce,
  • Fiorella E. Zuzunaga-Montoya,
  • Luisa Erika Milagros Vásquez-Romero,
  • Joan A. Loayza-Castro,
  • Cori Raquel Iturregui Paucar,
  • Carmen Inés Gutiérrez De Carrillo,
  • Mario J. Valladares-Garrido,
  • Maritza Placencia Medina

Journal volume & issue
Vol. 16
p. 100230

Abstract

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Introduction: Several previous studies have provided evidence that obesity is a significant risk factor for the increase in prediabetes, but there are discrepancies regarding whether all the classic ways of measuring obesity, the body mass index (BMI), the waist circumference (WC) or the Waist to height ratio (WHtR) present the same level of risk. Objective: to carry out a systematic review (SR) with meta-analysis to determine the association between indicators of obesity and prediabetes. Methods: A systematic review (SR) with a meta-analysis of observational studies was performed. The search was conducted in four databases: Pubmed/Medline, SCOPUS, Web of Science, and EMBASE. Association measures were presented as odds ratios (OR), relative risk (RR), or hazard ratio (HR), together with their 95% confidence intervals (95% CI). Results: Of the total number of manuscripts chosen, 12 had an analytical cross-sectional design, and 4 were cohort studies. For the cross-sectional studies, together they presented a statistically significant association for BMI (OR: 1.99; 95% CI 1.65 – 1.34), WC (OR: 1.41; 95% CI 1.30 – 1.54), and WHtR (OR: 2.47 IC 95 % 1.50 – 4.06). In the meta-analysis of the cohort studies, an association was found with WC (RR: 4.95; 95% CI 3.42 – 7.17) but not with BMI (HR: 1.22; 95% CI 0.81 – 1.85). There were no studies with WHtR. Conclusions: According to the results, considering cohort studies, WC could be the best risk indicator for prediabetes. There is a high degree of heterogeneity between the studies about the way obesity is measured, including the cut-off points used, so further longitudinal studies are needed to evaluate the association and confirm the results found.

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