Clustering of HIV Patients in Ethiopia.

Ethiopian Demographic Health Survey; EDHS HIV patients cluster analysis principal component analysis

Journal

HIV/AIDS (Auckland, N.Z.)
ISSN: 1179-1373
Titre abrégé: HIV AIDS (Auckl)
Pays: New Zealand
ID NLM: 101515943

Informations de publication

Date de publication:
2021
Historique:
received: 04 02 2021
accepted: 28 04 2021
entrez: 3 6 2021
pubmed: 4 6 2021
medline: 4 6 2021
Statut: epublish

Résumé

Among the many worldwide health problems, HIV/AIDS has caused severe health problems in several countries. The problem is also widely seen in Ethiopia. The general objective of the study is to cluster HIV patients and to find out the factors that mostly affect the prevalence of HIV within a group (cluster) and between groups (clusters) of HIV patients. The study is made based on the 2016 Ethiopian Demographic Health Survey (EDHS) which was collected by the Central Statistical Agency (CSA) of Ethiopia, and the survey collected a total of 26,753 samples, of which 14,785 were women and 11,968 were men and the age group was between 15 and 49 years for both. Binary logistic regression, principal component analysis, cluster analysis, and ANOVA were applied to analyze the data. The result from binary logistic regression reveals that 15 factors such as ever heard of AIDS, region, water not available for at least a day in the last 2 weeks, has a radio, family members wash their hands, location of the source of water, everything completed to water to make it harmless to drink, food cooked in the house/separate house/outside, has a mobile telephone, has a table, type of place of residence, highest education level attained, current marital status, sex of household members, and age of household members are all significant factors that affect HIV status. Using these significant variables, 12 principal components are identified which describe 78% of the variation in the data. The result of HIV patients are clustered into 3 clusters and determine the status of HIV levels. Mainly, cluster 2 accounts for 50% of HIV patients whereas cluster 3 and 1 accounts for 40% and 10%, respectively.

Sections du résumé

BACKGROUND BACKGROUND
Among the many worldwide health problems, HIV/AIDS has caused severe health problems in several countries. The problem is also widely seen in Ethiopia. The general objective of the study is to cluster HIV patients and to find out the factors that mostly affect the prevalence of HIV within a group (cluster) and between groups (clusters) of HIV patients.
METHODS METHODS
The study is made based on the 2016 Ethiopian Demographic Health Survey (EDHS) which was collected by the Central Statistical Agency (CSA) of Ethiopia, and the survey collected a total of 26,753 samples, of which 14,785 were women and 11,968 were men and the age group was between 15 and 49 years for both. Binary logistic regression, principal component analysis, cluster analysis, and ANOVA were applied to analyze the data.
RESULTS RESULTS
The result from binary logistic regression reveals that 15 factors such as ever heard of AIDS, region, water not available for at least a day in the last 2 weeks, has a radio, family members wash their hands, location of the source of water, everything completed to water to make it harmless to drink, food cooked in the house/separate house/outside, has a mobile telephone, has a table, type of place of residence, highest education level attained, current marital status, sex of household members, and age of household members are all significant factors that affect HIV status.
CONCLUSION CONCLUSIONS
Using these significant variables, 12 principal components are identified which describe 78% of the variation in the data. The result of HIV patients are clustered into 3 clusters and determine the status of HIV levels. Mainly, cluster 2 accounts for 50% of HIV patients whereas cluster 3 and 1 accounts for 40% and 10%, respectively.

Identifiants

pubmed: 34079385
doi: 10.2147/HIV.S301510
pii: 301510
pmc: PMC8164663
doi:

Types de publication

Journal Article

Langues

eng

Pagination

581-592

Informations de copyright

© 2021 Biressaw et al.

Déclaration de conflit d'intérêts

The authors report no conflicts of interests in this research article.

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Auteurs

Wondimu Biressaw (W)

Benishangul-Gumuz, Wombera Sineor Secondary and Preparatory School, Benishangul, Ethiopia.

Habtamu Tilaye (H)

University of Gondar, College of Natural and Computational Science, Departmentof Statistics, Gondar, Ethiopia.

Dessie Melese (D)

University of Gondar, College of Natural and Computational Science, Departmentof Statistics, Gondar, Ethiopia.

Classifications MeSH