Evidence map›Paper›PMID 39819197›Full record

ArticleGlobal health action2024

Cluster analysis of social determinants of health and HIV/AIDS knowledge among Peruvian youths using Kohonen's self-organized maps: a data-exploration study based on a Demographic and health survey.

Alejandro Aybar-Flores, Alvaro Talavera, Elizabeth Espinoza-Portilla

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Article in Global health action, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

3 authors.

Alejandro Aybar-FloresDepartment of Engineering, Universidad del Pacifico, Lima, Peru.ORCID 0000-0001-7080-3325
Alvaro TalaveraDepartment of Engineering, Universidad del Pacifico, Lima, Peru.ORCID 0000-0002-2193-4270
Elizabeth Espinoza-PortillaFaculty of Health Sciences, School of Medicine, Universidad Continental, Lima, Peru.ORCID 0000-0002-5068-5357

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHuman immunodeficiency virus (HIV) and acquired immunodeficiency syndrome (AIDS) have evolved into a global development burden, with nearly 40 million infections and 25 million deaths. Compared to other age groups, youth have increased risks of contracting the disease due to social and health structural factors; thus, additional efforts are needed to effectively tackle the challenges associated with this age group. Epidemiological studies employing unsupervised learning techniques are essential for shaping public health policies.

objectiveThis study aimed to describe the Peruvian youth population based on their sociodemographic, health, and economic characteristics using an unsupervised learning approach through the development of a neural network model based on Kohonen's self-organizing maps (SOMs), allowing the identification of social profiles in the study population.

methodsThis quantitative study used data from the 2019 Peruvian Demographic and Family Health Survey. An SOM network model for clustering individuals with similar attributes and clustering prototype vectors based on the agglomerative hierarchical clustering (AHC) method and their visualization on an SOM was applied to the study sample.

resultsClustering of prototype vectors yielded four clusters, each of which represented a profile of Peruvian youths based on their knowledge of HIV/AIDS and structural health determinants.

conclusionsKohonen's neural networks allowed the identification of patterns and behaviors among youths in Peru, quantifying and characterizing the four social clusters regarding HIV/AIDS and their social determinants. Kohonen's maps may benefit healthcare professionals and policymakers by offering a useful method for tailoring interventions and policies based on the detected profiles, thereby enhancing the visibility of these focal points at the national level.

Indexed as

Health Knowledge, Attitudes, PracticeHIV InfectionsSocial Determinants of HealthAcquired Immunodeficiency SyndromeAdolescentCluster AnalysisFemaleHealth SurveysHumansMaleNeural Networks, ComputerPeruSocioeconomic FactorsYoung Adultagglomerative hierarchical clusteringHIV/AIDSKohonenPeruself-organizing mapssocial determinants of healthunsupervised learningyouth

Identifiers

PMID39819197
PMCPMC11748869

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