Determinants of household vulnerability to poverty in urban informal settlements
Description
This dataset contains primary data collected for a quantitative study investigating the determinants of vulnerability to poverty in informal settlements within the City of Tshwane Metropolitan Municipality, specifically in Atteridgeville, Nellmapius, and Olievenhoutbosch. The study aimed to analyze how factors such as employment status, education level, access to basic services, food insecurity, breadwinner status, marital status, and social channels influence households' vulnerability to poverty. The data was collected through structured household surveys conducted with 366 households, selected using a stratified sampling technique. The survey questionnaire captured demographic information, socioeconomic characteristics, and access to services, with a focus on indicators related to poverty and vulnerability. The dataset supports stepwise binary logistic regression analysis and is intended to inform policy recommendations for poverty reduction and improved service delivery in urban informal settlements. All data have been anonymized to protect participant privacy.
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Steps to reproduce
The study was conducted in three informal settlements in the City of Tshwane and was selected due to their high prevalence of poverty and socio economic vulnerability. The study employed a cross-sectional study design to capture data at a single point in time. Stratified sampling was used to ensure representation from different socio-economic strata within the settlements. A total of 366 households were selected for the study, based on statistical power calculations to achieve generalizable results. A structured questionnaire was developed to collect data on demographics, socioeconomic characteristics, income levels, and education, access to services, food security and social channels. Data were collected through face-to-face interviews conducted by trained enumerators. Enumerators received training to minimize errors, and surveys were checked daily for completeness and accuracy. Responses were digitized and anonymized during the entry process to ensure confidentiality and the raw data was entered into an Excel spreadsheet. Next, the data was thoroughly cleaned and coded. Once this was complete, the prepared data was transferred to IBM's Statistical Package for Social Sciences (SPSS) software for detailed analysis. Within SPSS, descriptive statistics were computed, and a stepwise binary probit model analysis was conducted to identify the key determinants of vulnerability in the selected informal settlements. The dataset was stored securely, with restricted access to protect sensitive information. The study received ethics approval from the University of Pretoria, and informed consent was obtained from all participants. The dataset was collected to identify the key determinants of vulnerability to poverty and inform targeted policy interventions to address socio-economic challenges in informal settlements.