Please use this identifier to cite or link to this item: http://www.repositorio.ufop.br/handle/123456789/10326
Title: Socioeconomic and demographic characterization of an endemic malaria region in Brazil by multiple correspondence analysis.
Authors: Lana, Raquel Martins
Riback, Thais Irene Souza
Lima, Tiago França Melo de
Nunes, Mônica da Silva
Cruz, Oswaldo Gonçalves
Oliveira, Francisco G. S.
Moresco, Gilberto Gilmar
Rocha, Nildimar Honorio
Codeço, Cláudia Torres
Keywords: Rurality
Urban malaria
Amazon
Micro-epidemiology
Issue Date: 2017
Citation: LANA, R. M. et al. Socioeconomic and demographic characterization of an endemic malaria region in Brazil by multiple correspondence analysis. Malaria Journal, v. 16, n. 397, p. 1-16, 2017. Disponível em: <https://malariajournal.biomedcentral.com/articles/10.1186/s12936-017-2045-z>. Acesso em: 03 mai. 2018.
Abstract: 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.
URI: http://www.repositorio.ufop.br/handle/123456789/10326
ISSN:  14752875
metadata.dc.rights.license: This 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. Fonte: o próprio artigo.
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