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Subnational estimates of factors associated with under-five mortality in Kenya: A spatio-temporal analysis, 1993-2014

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Article numbere004544
<mark>Journal publication date</mark>15/04/2021
<mark>Journal</mark>BMJ Global Health
Issue number4
Number of pages17
Publication StatusPublished
<mark>Original language</mark>English


Background To improve child survival, it is necessary to describe and understand the spatial and temporal variation of factors associated with child survival beyond national aggregates, anchored at decentralised health planning units. Therefore, we aimed to provide subnational estimates of factors associated with child survival while elucidating areas of progress, stagnation and decline in Kenya. Methods Twenty household surveys and three population censuses conducted since 1989 were assembled and spatially aligned to 47 subnational Kenyan county boundaries. Bayesian spatio-temporal Gaussian process regression models accounting for inadequate sample size and spatio-temporal relatedness were fitted for 43 factors at county level between 1993 and 2014. Results Nationally, the coverage and prevalence were highly variable with 38 factors recording an improvement. The absolute percentage change (1993-2014) was heterogeneous ranging between 1% and 898%. At the county level, the estimates varied across space and over time with a majority showing improvements after 2008 which was preceded by a period of deterioration (late-1990 to early-2000). Counties in Northern Kenya were consistently observed to have lower coverage of interventions and remained disadvantaged in 2014 while areas around Central Kenya had and historically have had higher coverage across all intervention domains. Most factors in Western and South-East Kenya recorded moderate intervention coverage although having a high infection prevalence of both HIV and malaria. Conclusion The heterogeneous estimates necessitates prioritisation of the marginalised counties to achieve health equity and improve child survival uniformly across the country. Efforts are required to narrow the gap between counties across all the drivers of child survival. The generated estimates will facilitate improved benchmarking and establish a baseline for monitoring child development goals at subnational level.

Bibliographic note

Funding Information: Funding PMM is funded under the IDeAL’s Project, DELTAS Africa Initiative (DEL-15-003). The DELTAS Africa Initiative is an independent funding scheme of the African Academy of Sciences (AAS)’s Alliance for Accelerating Excellence in Science in Africa (AESA) and supported by the New Partnership for Africa’s Development Planning and Coordinating Agency (NEPAD Agency) with funding from the Wellcome Trust (number 107769/Z/10/Z) and the UK government. RWS is funded by Wellcome Trust Principal Fellowship (numbers 103602 and 212176) that also provided support for PMM. EO is supported as a Wellcome Trust Intermediate Fellow (number 201866) that provided support for NKJ; PMM, NKJ, RWS and EO acknowledge the support of the Wellcome Trust to the Kenya Major Overseas Programme (# 203077). The views expressed in this publication are those of the authors and not necessarily those of AAS, NEPAD Agency, Wellcome Trust or the UK government. disclaimer The funder of the study had no role in study design, data collection, data analysis, data interpretation or writing of the report. Publisher Copyright: © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.