Stratifying urban neighbourhoods by income: Comparison of a subjective participatory approach and an objective statistical analysis of deprivation indicators in Dar es Salaam,Tanzania

Abstract

Mapping out geographic heterogeneities across urban neighbourhoods can inform urban planning and intervention targeting. Despite their subjectivity, intuitive participatory stratification approaches (PSAs) are becoming increasingly popular because of their affordability and practicality. In contrast, more objective statistical approaches, like latent profile analysis (LPA), typically require rich survey data and advanced capacities that are often lacking in low- and middle-income countries. This study therefore assessed these two distinct approaches, to compare their effectiveness, applicability, and complementarity for identifying geoeconomic heterogeneities of urban neighbourhoods in a typical contemporary African city. This study assessed a PSA to stratify neighbourhoods across the Tanzania city of Dar es Salaam in terms of income, by comparing it with a complementary LPA of national census data to stratify them in terms of deprivation. A consultative community-based workshop was used for the PSA, while 15 selected deprivation indicators from the census data were used to profile them using LPA. While the PSA allocated neighbourhoods to five income strata, six clear deprivation strata could be distinguished by LPA. A strong positive correlation was observed between the stratum identified by the LPA and that obtained through the PSA (ρ = 0.739, p < .0001). Furthermore, paired comparison of the two sets of correlation coefficients between each deprivation indicator and the stratum assigned by each stratification approach revealed no difference (V = 33, p-value = .1354), confirming that the two approaches yielded very similar patterns of stratification. Also, the two approaches yielded broadly comparable cartographic pictures of the city, depicting similar spatial distribution of wealth and poverty. Overall, this evidence indicates that subjective community knowledge and lived experience may be invaluable for understanding built environment and for mapping out pockets of poverty and affluence at fine scales with minimum resources.