Assessment of Indicators of Urban Housing Quality in Owerri Municipal, Nigeria: A Factor Analysis Approach

• Published in: Promoting Statistical Practice and Collaboration in Developing Countries pp. 387 - 405
• Main Author: Uzoma, Ifeoma Evan
• Format: Book Chapter
• Language: English
• Published: CRC Press 2022
• Edition: 1
• Subjects: Residential Housing Units; Housing Quality Indicators; SCS; Undergraduate Statistics Programs; Exponential Ratio Type Estimator; Vice Versa; HPD Interval; Urban Housing; Quality; Data Science Practice; Nigeria Introduction; Indicators; Housing Quality; Pennsylvania State University; Factor Analysis; Kaiser Normalization Rotation; Stratified Sampling Technique; Statistical Consulting Centers; Imo State; LISA; Data Science Skills; Ventilation Factor; Undergraduate Statistics Students; Crowding Factor; Outdoor Characteristics; Factor Analysis Method; Tertiary Education; Autoregressive Distributed Lag Model; Underlying Factor Structure; HPD
• ISBN: 103219555X; 9781032195551; 1032198508; 9781032198507
• DOI: 10.1201/9781003261148-34

Nigeria, with a growing urban population, is faced with urban housing provision challenges. It is on this premise that this study assessed the indicators of urban housing quality in Owerri Municipal, Imo State, Nigeria. The objective of this study was to investigate the underlying factor structure of housing quality in the study area. A survey design was adopted and structured questionnaires were designed and administered to household heads to elicit information on demography and housing. A total of 390 household heads were randomly sampled using a stratified sampling technique, including 13 respondents from each of the 30 sectors. To select samples in each sector, a detailed map of Owerri Municipal was divided into grid cells (quadrates) and a point random approach was applied to sample 13 residential houses from each sector. Factor analysis was used to reduce the 30 housing indicators on which data were collected into eight factors that were further subjected to cluster analysis, yielding three housing quality regions. The results indicate that the factors most strongly associated with housing quality in the area were accessibility, water supply, ventilation, hygiene, sanitation, neighborhood, crowding, and outdoor characteristics. It was concluded that considerable disparities exist in the levels of urban housing quality indicators among the housing sectors in Owerri. It is recommended that housing quality indicators be improved by channeling resources to appropriate targets, particularly in the lagging factors. The objective of this chapter was to investigate the underlying factor structure of housing quality in the study area. Urban housing is a contentious issue in most developing countries. In addition, the application of statistics and statistical techniques to urban housing quality issues is also important as, according to Udofia, there is a need to see patterns, dimensions, and classifications with statistical techniques as a guide. Studies abound of housing quality around the world, but are more prevalent in the developing nations of the world, as housing is a major problem in developing countries. Primary data were obtained through direct observation and questionnaire administration, as well as a building demographic and facility survey. One of the methods used for the data analysis was factor analysis method, which was used to collapse the sets of variables into fewer factors, thereby identifying groups of interrelated variables for housing quality in the study area.