ORCID Profile
0000-0003-3410-1881
Current Organisation
Institute of Tropical Medicine Antwerp
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Publisher: Cold Spring Harbor Laboratory
Date: 14-11-2022
DOI: 10.1101/2022.11.14.22282287
Abstract: Neonatal mortality might be higher in urban areas. This paper aims to minimize challenges related to misclassification of neonatal deaths and stillbirths, and oversimplification of the variation in urban environments to accurately estimate the direction and strength of the association between urban residence and neonatal erinatal mortality in Tanzania. The Tanzania Demographic and Health Survey (DHS) 2015-16 was used to assess birth outcomes for 8,915 pregnancies among 6,156 women of reproductive age, by urban or rural categorization in the DHS and based on satellite imagery. The coordinates of 527 DHS clusters were spatially overlaid with the 2015 Global Human Settlement Layer, showing the degree of urbanisation based on built environment and population density. A three-category urbanicity measure (core urban, semi-urban, and rural) was defined and compared to the binary DHS measure. Travel time to the nearest hospital was modelled using least-cost path algorithm for each cluster. Bivariate and multi-level multivariable logistic regression models were constructed to explore associations between urbanicity and neonatal erinatal deaths. Both perinatal and neonatal mortality rates were highest in core urban and lowest in rural clusters. Bivariate models showed higher odds of neonatal death (OR=1.85 95% CI: 1.12, 3.08) and perinatal death (OR=1.60 95% CI 1.12, 2.30) in core urban compared to rural clusters. In multivariable models, these associations had the same direction and size, but were no longer statistically significant. Travel time to nearest hospital was not associated with neonatal or perinatal mortality. Addressing the higher rates of neonatal and perinatal mortality in densely populated urban areas is critical for Tanzania to meet national and global reduction targets. Urban populations are erse, and certain neighbourhoods or sub-groups may be disproportionately affected by poor birth outcomes. Research must s le within and across urban areas to differentiate, understand and minimize risks specific to urban settings. - Urban advantage in health outcomes has been questioned, both for adult and child mortality - An analysis of neonatal mortality using Demographic and Health Survey data in Tanzania in 2015-16 showed double risk in urban compared to rural areas - This phenomenon might be occurring in other sub-Saharan African countries - Categorisation of locations as urban or rural on the 2015-16 Demographic and Health Survey in Tanzania is both simplistic and inaccurate - Risks of neonatal and perinatal mortality are highest in core, densely populated urban areas in mainland Tanzania, and lowest in rural areas - Travel time to nearest public hospital was not associated with neonatal or perinatal mortality in mainland Tanzania - Extent of urbanicity as an exposure follows a spectrum and needs to be measured and understood as such - Explanatory models specific to neonatal and perinatal mortality in core urban areas are urgently needed to guide actions toward reducing existing high rate - Known risk factors such as anaemia and young maternal age continue to play a role in neonatal and perinatal mortality and must be urgently addressed.
Publisher: BMJ
Date: 04-2023
DOI: 10.1136/BMJGH-2022-011253
Abstract: Recent studies suggest that the urban advantage of lower neonatal mortality in urban compared with rural areas may be reversing, but methodological challenges include misclassification of neonatal deaths and stillbirths, and oversimplification of the variation in urban environments. We address these challenges and assess the association between urban residence and neonatal erinatal mortality in Tanzania. The Tanzania Demographic and Health Survey (DHS) 2015–2016 was used to assess birth outcomes for 8915 pregnancies among 6156 women of reproductive age, by urban or rural categorisation in the DHS and based on satellite imagery. The coordinates of 527 DHS clusters were spatially overlaid with the 2015 Global Human Settlement Layer, showing the degree of urbanisation based on built environment and population density. A three-category urbanicity measure (core urban, semi-urban and rural) was defined and compared with the binary DHS measure. Travel time to the nearest hospital was modelled using least-cost path algorithm for each cluster. Bivariate and multilevel multivariable logistic regression models were constructed to explore associations between urbanicity and neonatal erinatal deaths. Both neonatal and perinatal mortality rates were highest in core urban and lowest in rural clusters. Bivariate models showed higher odds of neonatal death (OR=1.85 95% CI 1.12 to 3.08) and perinatal death (OR=1.60 95% CI 1.12 to 2.30) in core urban compared with rural clusters. In multivariable models, these associations had the same direction and size, but were no longer statistically significant. Travel time to the nearest hospital was not associated with neonatal or perinatal mortality. Addressing high rates of neonatal and perinatal mortality in densely populated urban areas is critical for Tanzania to meet national and global reduction targets. Urban populations are erse, and certain neighbourhoods or subgroups may be disproportionately affected by poor birth outcomes. Research must capture, understand and minimise risks specific to urban settings.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: Kenya
No related grants have been discovered for Peter M Macharia.