International Journal of Scientific Reports | March 2018 | Vol 4 | Issue 3 Page 59 International Journal of Scientific Reports Adewoyin Y. Int J Sci Rep. 2018 Mar;4(3):59-67 http://www.sci-rep.com pISSN 2454-2156 | eISSN 2454-2164 Original Research Article A residential habitat quality model for population health vulnerability assessment in Urban Nigeria Yemi Adewoyin* INTRODUCTION The role of the environment, both biotic and abiotic, in shaping population health outcomes has been widely acknowledged in the literature over the years. 1-5 This follows from the understanding that most disease conditions are caused, influenced - directly or indirectly, or attenuated by conditions in the environment. Such environmental conditions include weather and climate, air and water quality, as well as population agglomeration and its impact on traffic, pollution, noise, accessibility, sanitation, waste management, and living conditions among others. While the population may be unable to prevent or control the impacts of the abiotic elements of the environment on their health totally, the residential environment, on the other hand presents opportunities for the control of exposure to disease vectors and pathogens, and susceptibility to diseases. The residential environment, otherwise referred to as residential habitat, is defined as the housing units, the surroundings, the neighborhoods, and the communities in which they are located. 6 The quality of the residential environment 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. Keywords: Residential habitat quality, Residential density, Neighborhoods, Malaria, Nigeria Department of Geography, University of Nigeria, Nsukka, Nigeria Received: 19 December 2017 Revised: 17 January 2018 Accepted: 18 January 2018 *Correspondence: Dr. Yemi Adewoyin, E-mail: yemiadewoyin@yahoo.com Copyright: © the author(s), publisher and licensee Medip Academy. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. DOI: http://dx.doi.org/10.18203/issn.2454-2156.IntJSciRep20180792