A residential habitat quality model for population health vulnerability assessment in Urban Nigeria

Authors

  • Yemi Adewoyin Department of Geography, University of Nigeria, Nsukka, Nigeria

DOI:

https://doi.org/10.18203/issn.2454-2156.IntJSciRep20180792

Keywords:

Residential habitat quality, Residential density, Neighborhoods, Malaria, Nigeria

Abstract

Background: The quality of the living environment affects the population’s exposure and susceptibility to diseases, yet most available indices for the measurement of residential environmental quality are based on the population’s perception of their environment rather than on objectively verifiable indicators. This paper develops an index based on the peculiarities of the urban environment in Africa.

Methods: In constructing the residential habitat quality (RHQ) model, 30 indicators measuring residential environmental quality and housing conditions were employed The indicators follow from an adaptation of the major risk factors of unhealthy living conditions of the WHO and from disease promoting habitat conditions highlighted in relevant theories. Primary data on household incidence of malaria was also collected from the study area.  

Results: The construct recorded a reliability coefficient of 0.979 while the factor-analytic procedure employed for validation identified three dimensions that accounted for 86.6% of the total variance in the construct. Its application in the analysis of the relationship between the quality of the living environment and the prevalence of malaria in urban Nigeria was further tested in the study. The result (r=-0.954, p<0.001) shows that there is a very strong and statistically significant negative correlation between the quality of the living environment and household incidence of malaria in the study area.

Conclusions: The RHQ model is sufficiently adequate to measure variations in residential environmental quality and becomes particularly useful in the identification of health risk habitats, and health planning for vulnerable population based on their places of residence.

 

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Published

2018-02-24

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Original Research Articles