Overview of migration, poverty and health dynamics in Nairobi City's slum settlements

Abstract

The Urbanization, Poverty, and Health Dynamics research program was designed to generate and provide the evidence base that would help governments, development partners, and other stakeholders understand how the urban slum context affects health outcomes in order to stimulate policy and action for uplifting the wellbeing of slum residents. The program was nested into the Nairobi Urban Health and Demographic Surveillance System, a uniquely rich longitudinal research platform, set up in Korogocho and Viwandani slum settlements in Nairobi city, Kenya. Findings provide rich insights on the context in which slum dwellers live and how poverty and migration status interacts with health issues over the life course. Contrary to popular opinions and beliefs that see slums as homogenous residential entities, the findings paint a picture of a highly dynamic and heterogeneous setting. While slum populations are highly mobile, about half of the population comprises relatively well doing long-term dwellers who have lived in slum settlements for over 10 years. The poor health outcomes that slum residents exhibit at all stages of the life course are rooted in three key characteristics of slum settlements: poor environmental conditions and infrastructure; limited access to services due to lack of income to pay for treatment and preventive services; and reliance on poor quality and mostly informal and unregulated health services that are not well suited to meeting the unique realities and health needs of slum dwellers. Consequently, policies and programs aimed at improving the wellbeing of slum dwellers should address comprehensively the underlying structural, economic, behavioral, and service-oriented barriers to good health and productive lives among slum residents.

African urbanization trends and prospects

“…The third policy implication is that of reducing these inequalities. The 'urban penalty' (the excess mortality in poor urban areas) that was thought to belong to the European 19 th century (Gould, 1998), is now revived in African cities slums (Zulu et al, 2011). Population and health policies directed at the poorest and often very mobile urban slum population need to be designed.…”

Determining Factors for Slum Growth with Predictive Data Mining Methods

“…As mentioned above, we cannot make any statements about causal relations, but only hypotheses about them. The high "Fertility rate" could be a consequence of poorer sexual education [14] as well as a cause for the strong growth of slums. Both are probably correct at the same time.…”

“…Although there are no data on the ratio of economic performance in the cities compared to the whole country, we found individual indicators-mainly from agriculture or economy-having a high correlation with slum development. These includex "Cereal Yield" (rank 19, 13, 9), "Agriculture, value added" (rank 18, 38, 50), "Imports of goods and services" (rank 20,15,32), and "Merchandise imports" (rank 15,12,14). The here-specified information can be seen in the information gain ratio lists presented in Table 4 for the specified rank for the timesteps 5, 10, and 20 years.…”

First Steps in Initiating an Effective Maternal, Neonatal, and Child Health Program in Urban Slums: the BRAC Manoshi Project’s Experience with Community Engagement, Social Mapping, and Census Taking in Bangladesh

“…[11][12][13][14] Even governments that prioritize serving the poor often have difficulty creating programs that can effectively reach this highly mobile, dense, socio-culturally heterogeneous population. [15][16][17] Furthermore, the authority of urban municipalities often overlaps with that of national ministries of health, leading to weak governmental health infrastructure and patient reliance on an uncoordinated, poorly regulated Bmish-mash^of private and non-governmental organization (NGO) providers.…”