Neonatal and perinatal mortality in the urban continuum: A geospatial analysis of the household survey, satellite imagery and travel time data in Tanzania

Abstract

Introduction 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/perinatal mortality in Tanzania. Methods 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/perinatal deaths. Results 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. Conclusion 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 diverse, and certain neighbourhoods or sub-groups may be disproportionately affected by poor birth outcomes. Research must sample within and across urban areas to differentiate, understand and minimize risks specific to urban settings.

Exploring the urban gradient in population health: insights from satellite-derived urbanicity classes across multiple countries and years in sub-Saharan Africa

“…Definitions that more accurately capture urban-rural continuum in the context of population health have never been more crucial. There is ongoing rapid urbanisation,1 reversal and shrinking of the urban advantage5 and increasing heterogeneity and inequalities within the urban areas 9. The dichotomous and crude classification of urban and rural areas lacks specificity in predicting health outcomes24 and is characterised by infrequent updates which all may lead to bias 20 25 37.…”

“…To reclassify the DHS urban-rural classes to an urban gradient, we followed the geospatial methodology illustrated in figure 1 from our previous work on mainland Tanzania 5. The GHS-Settlement Model layer (GHS-SMOD) data consist of two levels: level 1 with three classes and level 2 with seven classes.…”

“…Urban residence is associated with mortality rates for adults, children under 5 and newborns,4–7 all of which are used as proxy measures of population health. Additionally, urbanisation influences other health outcomes, such as disease burden, immunisation rates and the provision and use of reproductive and maternal healthcare, including childbirth care and associated quality 8–10.…”

“…Burdens are expected to be concentrated in a few hot spot areas; identification of these areas and directing suitable interventions ensures equitable resource allocation and understanding of why there is a reversal. Further, understanding the reversals or in fact determining to what extent these are artefacts of how urban areas are defined,5 and if true, to identify potential causal factors which can be effectively addressed by policies and interventions will require an objective defined urban gradient.…”