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Socioeconomic and demographic characterization of an endemic malaria region in Brazil by multiple correspondence analysis

BACKGROUND: In the process of geographical retraction of malaria, some important endemicity pockets remain. Here, we report results from a study developed to obtain detailed community data from an important malaria hotspot in Latin America (Alto Juruá, Acre, Brazil), to investigate the association o...

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Autores principales: Lana, Raquel M., Riback, Thais I. S., Lima, Tiago F. M., da Silva-Nunes, Mônica, Cruz, Oswaldo G., Oliveira, Francisco G. S., Moresco, Gilberto G., Honório, Nildimar A., Codeço, Cláudia T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5625626/
https://www.ncbi.nlm.nih.gov/pubmed/28969634
http://dx.doi.org/10.1186/s12936-017-2045-z
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author Lana, Raquel M.
Riback, Thais I. S.
Lima, Tiago F. M.
da Silva-Nunes, Mônica
Cruz, Oswaldo G.
Oliveira, Francisco G. S.
Moresco, Gilberto G.
Honório, Nildimar A.
Codeço, Cláudia T.
author_facet Lana, Raquel M.
Riback, Thais I. S.
Lima, Tiago F. M.
da Silva-Nunes, Mônica
Cruz, Oswaldo G.
Oliveira, Francisco G. S.
Moresco, Gilberto G.
Honório, Nildimar A.
Codeço, Cláudia T.
author_sort Lana, Raquel M.
collection PubMed
description BACKGROUND: In the process of geographical retraction of malaria, some important endemicity pockets remain. Here, we report results from a study developed to obtain detailed community data from an important malaria hotspot in Latin America (Alto Juruá, Acre, Brazil), to investigate the association of malaria with socioeconomic, demographic and living conditions. METHODS: A household survey was conducted in 40 localities (n = 520) of Mâncio Lima and Rodrigues Alves municipalities, Acre state. Information on previous malaria, schooling, age, gender, income, occupation, household structure, habits and behaviors related to malaria exposure was collected. Multiple correspondence analysis (MCA) was applied to characterize similarities between households and identify gradients. The association of these gradients with malaria was assessed using regression. RESULTS: The first three dimensions of MCA accounted for almost 50% of the variability between households. The first dimension defined an urban/rurality gradient, where urbanization was associated with the presence of roads, basic services as garbage collection, water treatment, power grid energy, and less contact with the forest. There is a significant association between this axis and the probability of malaria at the household level, OR = 1.92 (1.23–3.02). The second dimension described a gradient from rural settlements in agricultural areas to those in forested areas. Access via dirt road or river, access to electricity power-grid services and aquaculture were important variables. Malaria was at lower risk at the forested area, OR = 0.55 (1.23–1.12). The third axis detected intraurban differences and did not correlate with malaria. CONCLUSIONS: Living conditions in the study area are strongly geographically structured. Although malaria is found throughout all the landscapes, household traits can explain part of the variation found in the odds of having malaria. It is expected these results stimulate further discussions on modelling approaches targeting a more systemic and multi-level view of malaria dynamics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12936-017-2045-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-56256262017-10-12 Socioeconomic and demographic characterization of an endemic malaria region in Brazil by multiple correspondence analysis Lana, Raquel M. Riback, Thais I. S. Lima, Tiago F. M. da Silva-Nunes, Mônica Cruz, Oswaldo G. Oliveira, Francisco G. S. Moresco, Gilberto G. Honório, Nildimar A. Codeço, Cláudia T. Malar J Research BACKGROUND: In the process of geographical retraction of malaria, some important endemicity pockets remain. Here, we report results from a study developed to obtain detailed community data from an important malaria hotspot in Latin America (Alto Juruá, Acre, Brazil), to investigate the association of malaria with socioeconomic, demographic and living conditions. METHODS: A household survey was conducted in 40 localities (n = 520) of Mâncio Lima and Rodrigues Alves municipalities, Acre state. Information on previous malaria, schooling, age, gender, income, occupation, household structure, habits and behaviors related to malaria exposure was collected. Multiple correspondence analysis (MCA) was applied to characterize similarities between households and identify gradients. The association of these gradients with malaria was assessed using regression. RESULTS: The first three dimensions of MCA accounted for almost 50% of the variability between households. The first dimension defined an urban/rurality gradient, where urbanization was associated with the presence of roads, basic services as garbage collection, water treatment, power grid energy, and less contact with the forest. There is a significant association between this axis and the probability of malaria at the household level, OR = 1.92 (1.23–3.02). The second dimension described a gradient from rural settlements in agricultural areas to those in forested areas. Access via dirt road or river, access to electricity power-grid services and aquaculture were important variables. Malaria was at lower risk at the forested area, OR = 0.55 (1.23–1.12). The third axis detected intraurban differences and did not correlate with malaria. CONCLUSIONS: Living conditions in the study area are strongly geographically structured. Although malaria is found throughout all the landscapes, household traits can explain part of the variation found in the odds of having malaria. It is expected these results stimulate further discussions on modelling approaches targeting a more systemic and multi-level view of malaria dynamics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12936-017-2045-z) contains supplementary material, which is available to authorized users. BioMed Central 2017-10-02 /pmc/articles/PMC5625626/ /pubmed/28969634 http://dx.doi.org/10.1186/s12936-017-2045-z Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Lana, Raquel M.
Riback, Thais I. S.
Lima, Tiago F. M.
da Silva-Nunes, Mônica
Cruz, Oswaldo G.
Oliveira, Francisco G. S.
Moresco, Gilberto G.
Honório, Nildimar A.
Codeço, Cláudia T.
Socioeconomic and demographic characterization of an endemic malaria region in Brazil by multiple correspondence analysis
title Socioeconomic and demographic characterization of an endemic malaria region in Brazil by multiple correspondence analysis
title_full Socioeconomic and demographic characterization of an endemic malaria region in Brazil by multiple correspondence analysis
title_fullStr Socioeconomic and demographic characterization of an endemic malaria region in Brazil by multiple correspondence analysis
title_full_unstemmed Socioeconomic and demographic characterization of an endemic malaria region in Brazil by multiple correspondence analysis
title_short Socioeconomic and demographic characterization of an endemic malaria region in Brazil by multiple correspondence analysis
title_sort socioeconomic and demographic characterization of an endemic malaria region in brazil by multiple correspondence analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5625626/
https://www.ncbi.nlm.nih.gov/pubmed/28969634
http://dx.doi.org/10.1186/s12936-017-2045-z
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