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Prevalence of diabetes and prediabetes in Peru: a systematic review and meta-analysis
Víctor Juan Vera-Ponce1,2, Fiorella E Zuzunaga-Montoya3,4, Luisa Erika Milagros Vásquez-Romero3,4
1Instituto de Investigación de Enfermedades Tropicales, Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas (UNTRM), Amazonas, Perú. vicvepo@gmail.com.
Introduction:
Diabetes mellitus (DM) and prediabetes represent significant public health challenges in Peru, with prevalence rates showing considerable variation across recent epidemiological studies.
Objective:
To conduct a systematic review and meta-analysis to determine the pooled prevalence of diabetes and prediabetes in Peru and identify temporal trends and sources of heterogeneity.
Methodology:
A comprehensive search was conducted in PubMed, Web of Science, SCOPUS, EMBASE and LILACS databases for studies reporting DM and prediabetes prevalence in Peru. Both national and subnational studies using standardized diagnostic criteria and representative sampling were included. Random-effects meta-analysis was performed, with subgroup analyses by sex, age and geographic scope. Meta-regression was conducted to explore temporal trends and sources of heterogeneity.
Results:
Eight independent studies comprising 18,502 participants provided diabetes data, while five studies with 11,056 participants reported prediabetes data, spanning 2005-2018. The pooled DM prevalence was 7.47% (95% CI: 5.02-10.35%) and prediabetes prevalence was 10.66% (95% CI: 4.29-19.42%). Meta-regression revealed a significant increasing temporal trend for DM (p < 0.0001), with prevalence rising from 2.99% in 2005 to 16.97% in 2018. Substantial heterogeneity was observed for both conditions (I² = 98-99%).
Conclusions:
Diabetes and prediabetes prevalence in Peru have increased significantly over the past decade, reaching concerning levels that require urgent public health attention. The substantial heterogeneity observed emphasizes the need for standardized diagnostic protocols and more comprehensive national surveillance systems to accurately monitor these conditions and guide evidence-based prevention strategies.
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