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Examining the determinants of mosquito-avoidance practices in two Kenyan cities

BACKGROUND: This study assesses the behavioural and socio-economic factors associated with avoiding mosquitoes and preventing malaria in urban environments in Kenya. METHODS: Data from two cities in Kenya were gathered using a household survey and a two-stage cluster sample design. The cities were s...

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Autores principales: Macintyre, Kate, Keating, Joseph, Sosler, Stephen, Kibe, Lydiah, Mbogo, Charles M, Githeko, Andrew K, Beier, John C
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2002
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC149385/
https://www.ncbi.nlm.nih.gov/pubmed/12495438
http://dx.doi.org/10.1186/1475-2875-1-14
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author Macintyre, Kate
Keating, Joseph
Sosler, Stephen
Kibe, Lydiah
Mbogo, Charles M
Githeko, Andrew K
Beier, John C
author_facet Macintyre, Kate
Keating, Joseph
Sosler, Stephen
Kibe, Lydiah
Mbogo, Charles M
Githeko, Andrew K
Beier, John C
author_sort Macintyre, Kate
collection PubMed
description BACKGROUND: This study assesses the behavioural and socio-economic factors associated with avoiding mosquitoes and preventing malaria in urban environments in Kenya. METHODS: Data from two cities in Kenya were gathered using a household survey and a two-stage cluster sample design. The cities were stratified based on planning and drainage observed across the urban areas. This helped control for the strong environmental and topographical variation that we assumed influences mosquito ecology. Individual interviews given to each household included questions on socio-economic status, education, housing type, water source, rubbish disposal, mosquito-prevention practices and knowledge of mosquitoes. In multivariate regression, factors measuring wealth, education level, and the communities' level of planning and drainage were used to estimate the probability that a household engages in multiple mosquito-avoidance activities, or has all members sleeping under a bed net. RESULTS: Our analysis shows that people from wealthier, more educated households were more likely to sleep under a net, in Kisumu (OR = 6.88; 95% CI = 2.56,18.49) and Malindi (OR = 3.80; 95% CI = 1.91,7.55). Similarly, the probability that households use several mosquito-prevention activities was highest among the wealthiest, best-educated households in Kisumu (OR = 5.15; 95% CI = 2.04,12.98), while in Malindi household wealth alone is the major determinant. CONCLUSION: We demonstrate the importance of examining human-mosquito interaction in terms of how access to resources may enhance human activities. The findings illustrate that the poorest segments of society are already doing many things to protect themselves from being bitten, but they are doing less than their richer neighbours.
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spelling pubmed-1493852003-02-25 Examining the determinants of mosquito-avoidance practices in two Kenyan cities Macintyre, Kate Keating, Joseph Sosler, Stephen Kibe, Lydiah Mbogo, Charles M Githeko, Andrew K Beier, John C Malar J Research BACKGROUND: This study assesses the behavioural and socio-economic factors associated with avoiding mosquitoes and preventing malaria in urban environments in Kenya. METHODS: Data from two cities in Kenya were gathered using a household survey and a two-stage cluster sample design. The cities were stratified based on planning and drainage observed across the urban areas. This helped control for the strong environmental and topographical variation that we assumed influences mosquito ecology. Individual interviews given to each household included questions on socio-economic status, education, housing type, water source, rubbish disposal, mosquito-prevention practices and knowledge of mosquitoes. In multivariate regression, factors measuring wealth, education level, and the communities' level of planning and drainage were used to estimate the probability that a household engages in multiple mosquito-avoidance activities, or has all members sleeping under a bed net. RESULTS: Our analysis shows that people from wealthier, more educated households were more likely to sleep under a net, in Kisumu (OR = 6.88; 95% CI = 2.56,18.49) and Malindi (OR = 3.80; 95% CI = 1.91,7.55). Similarly, the probability that households use several mosquito-prevention activities was highest among the wealthiest, best-educated households in Kisumu (OR = 5.15; 95% CI = 2.04,12.98), while in Malindi household wealth alone is the major determinant. CONCLUSION: We demonstrate the importance of examining human-mosquito interaction in terms of how access to resources may enhance human activities. The findings illustrate that the poorest segments of society are already doing many things to protect themselves from being bitten, but they are doing less than their richer neighbours. BioMed Central 2002-11-15 /pmc/articles/PMC149385/ /pubmed/12495438 http://dx.doi.org/10.1186/1475-2875-1-14 Text en Copyright © 2002 Macintyre et al; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.
spellingShingle Research
Macintyre, Kate
Keating, Joseph
Sosler, Stephen
Kibe, Lydiah
Mbogo, Charles M
Githeko, Andrew K
Beier, John C
Examining the determinants of mosquito-avoidance practices in two Kenyan cities
title Examining the determinants of mosquito-avoidance practices in two Kenyan cities
title_full Examining the determinants of mosquito-avoidance practices in two Kenyan cities
title_fullStr Examining the determinants of mosquito-avoidance practices in two Kenyan cities
title_full_unstemmed Examining the determinants of mosquito-avoidance practices in two Kenyan cities
title_short Examining the determinants of mosquito-avoidance practices in two Kenyan cities
title_sort examining the determinants of mosquito-avoidance practices in two kenyan cities
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC149385/
https://www.ncbi.nlm.nih.gov/pubmed/12495438
http://dx.doi.org/10.1186/1475-2875-1-14
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