Rural-Urban Differences in Trends in the Wealth Index in Kenya: 1993-2009

• Main Authors: Leonard E. Egede (Author), Delia Voronca (Author), Rebekah J. Walker (Author), Craig Thomas (Author)
• Format: Book
• Published: Ubiquity Press, 2017-05-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2214-9996; 10.1016/j.aogh.2017.04.001
• Keywords: wealth; rural; urban; Demographic and Health Survey; Kenya; Infectious and parasitic diseases; RC109-216; Public aspects of medicine; RA1-1270
• Source: Annals of Global Health, Vol 83, Iss 2, Pp 248-258 (2017)

Background: The aim of this study was to construct a wealth index that could be compared over time in order to understand the trends in wealth in Kenya and determine predictors of change in wealth index. Methods: Data were from the Demographic and Health Survey program collected in Kenya between 1993 and 2009. Variable categories were collapsed to match and factor analysis was performed on the 4-year pooled data to generate a harmonized wealth index. Possible predictors of wealth were selected from household variables available for all 4 years. Household sampling weights and stratification by rural/urban was used. Results: Overall, wealth increased in Kenya between 1993 and 2008; however, when stratified, no significant increase existed in urban areas and a significant increase was identified in rural areas specifically between 2003 and 2008. The strongest predictor was education, with more than a standard deviation difference for secondary or higher levels of education over those with no education. The association of gender of the head of household and whether the head of household had a partner differed between rural and urban areas, with household heads who were women and those who had a partner having more wealth in urban areas but less wealth in rural areas. Conclusion: Wealth in Kenya increased over time, specifically in rural regions. Differences were identified in predictors of wealth by urban/rural residence, educational level, and gender of the head of household and should be taken into account when planning interventions to target those in disproportionately low wealth brackets.