A growing disadvantage of being born in an urban area? Analysing urban–rural disparities in neonatal mortality in 21 African countries with a focus on Tanzania

Introduction

Sub-Saharan Africa (SSA) has one of the highest levels of neonatal mortality in the world.1 Neonatal mortality is the number of deaths during the first month of life per 1000 live births, and can be further divided into early neonatal mortality (death within the first 7 days) and late neonatal mortality (death between day 8 and day 28).2 3 Globally, as mortality rates of children have declined more rapidly than those of neonates, the contribution of deaths during the neonatal period to the under-5 mortality rate has increased from 40% to 47% between 1990 and 2018.1 4 5 The causes of early neonatal mortality and late neonatal mortality differ.4 Most important causes of early neonatal deaths are prematurity, low birth weight and birth asphyxia, which is related to quality of intrapartum care, such as the facility and presence of a skilled birth attendant (SBA).6–8 On the other hand, deaths in the late neonatal period are more likely to be caused by infectious diseases.4 9 Such infections, whether nosocomial or community-acquired, are often preventable and treatable, but are intertwined with underlying vulnerabilities such as prematurity and factors related to poor maternal education, poverty, and access to water and sanitation facilities.10–12

Neonatal mortality rates (NMRs) vary between countries, but also within countries.8 13–19 Historically, NMRs have been higher in rural areas when compared with urban areas in SSA, most likely due to lower healthcare provision and utilisation,2 20 lower education and poorer housing conditions, and other issues such as poorer community-level infrastructure of water and electricity supply.21 Recently, researchers have started questioning the so-called ‘urban advantage’ as evidence emerged on NMR declining more rapidly in rural settings thus narrowing the urban–rural differences.22 23 Urban population growth in low resource countries is predominantly poverty-driven, with a large proportion of the urban population residing in slums.24 25 Low levels of education among women, limited access to clean water, sanitation, good quality antenatal and intrapartum care, and poor air quality, all highly prevalent in urban settings and slums, link to poorer neonatal health outcomes.10 26–30

This study has two objectives: (1) to understand the trends over time in urban–rural differentials in NMR in SSA and (2) to identify the country with the most pronounced urban–rural differential in NMR, disadvantaging urban areas, and to examine whether this difference can be accounted for by known obstetric and socio-economic risk factors.

Methods

Results

NMRs in SSA countries

For the analysis of time trends in urban–rural differences in NMR in sub-Saharan African (SSA) countries, 21 countries met the inclusion criteria of DHS data availability. Graphs showing each country’s time trends in urban and rural NMR are in online supplemental appendix S1. Within these 21 countries, we identified six broad categories of countries (table 1). Regardless of time trends, the most common category of countries in regard to urban–rural differences was one where the rural NMR estimate was higher than urban, but the 95% CIs overlapped. Only in two countries was rural NMR significantly higher than in urban areas (Guinea and Niger). On the other hand, the most recent DHS estimates of NMR in seven countries showed that the NMR in urban areas was higher compared with rural; but only in Tanzania did the CIs not overlap, indicating that urban NMR was significantly higher than rural NMR (figure 1).

Table 1

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Categorisation of included countries based on NMR time trends and recent NMR

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Figure 1

Time trends in neonatal mortality rate (per 1000 live births) from the Tanzania Demographic and Health Survey (DHS), by year of DHS.

Discussion

We assessed time trends of neonatal mortality in 21 SSA countries by urban and rural areas between 1990 and 2019. The analysis revealed that urban–rural disparities in NMR differ across countries, with most countries showing a narrowing of the urban–rural gap. Whereas in two countries, Guinea and Niger, rural NMR was still significantly higher than urban NMR, Tanzania is the one country that has a reverse pattern. While the NMR point estimate in urban areas had been higher than rural since 1999, it was significantly higher for the first time in the most recent DHS collected in 2015–2016. It is a result of continued decline in rural NMR over time, which was not matched by equal speed of decline in urban areas; a pattern seen in other SSA countries examined. We assessed potential explanatory factors of this twofold higher urban–rural difference in NMR in Tanzania, but found that even after inclusion of other risk factors, the odds of neonatal death remained 1.9–2.1 times higher in urban compared with rural areas. There could be three broad explanations for this finding: (1) it is a result of confounding (ie, important explanatory factors/confounders are not included, or insufficiently included, in the multivariable model); (2) the result is due to biased reporting of neonatal deaths (ie, that neonatal deaths are over-reported in urban areas and/or under-reported in rural areas) or some level of misclassification of the exposure to urban/rural environments and (3) that the NMR is truly higher in urban compared with rural areas. It is possible that several of these explanations are involved. The overarching question we raise in this paper is, if such difference truly exists in Tanzania, whether such pattern of higher NMR in urban areas is an indication of a phenomenon occurring also in other SSA countries. We focus on three potential explanations for the high estimated NMR in urban areas in Tanzania, with a view of understanding the drivers that could potentially contribute to such findings, and implications for further research and policy-making.

First, the urban–rural difference in NMR in Tanzania could not be explained by the available socioeconomic, pregnancy-related and sanitation measures, although some of these factors were independently associated with NMR (multiplicity of pregnancy, birth order and birth interval, older maternal age and male sex). The higher NMR in urban areas was largely driven by higher mortality rate of newborns between 1 and 7 days following birth. The most likely causes of death in this time period relate to the quality of intrapartum care. If our finding is true, the most likely contributing factors are quality of maternal and newborn care during the intrapartum period, followed by delays in care-seeking for babies with complications (whether born at home or those who developed symptoms after discharge from facility where they were born), and quality of care provided to sick newborns. The chance of being born in a hospital is three times as high for babies from urban compared with rural areas (62% vs 21%). Given the pressure exerted by population increase in urban areas on existing resources, particularly public health facilities providing care to the poor, it is possible that crowding, staff shortages, and lack of routine provision of essential care elements converge in such urban health facilities and contribute to increased risk of neonatal mortality.37–39 Additionally, the risk of acquiring nosocomial infections within health facilities is particularly relevant to premature and low-birth newborns who are highly vulnerable to acquiring and dying from such infections.

As for the analyses in the subsample of babies weighed at birth, we report some nuances. If the babies were being weighed that means an SBA was probably present. However, the presence of an SBA did not necessarily decrease the risk of NMR. No distinction was made between SBA cadres, and the overall category SBA consists of varying levels of skilled health personnel including doctors, nurses, midwives and combinations of these providers within professional teams. Women tend to seek help at a healthcare facility more often when complications occur, which might explain our finding of nearly double risk of NMR associated with caesarean sections. In future studies, the reasons for women delivering in a healthcare facility or at home, incorporating the diversity of people involved/services provided by the different SBAs, needs to be disentangled.

Second, beyond individual health-seeking behaviour, obstetric risk factors, and quality of care, broader issues related to socioeconomic determinants, urban living conditions and urbanisation processes might also play a role in an increased risk of neonatal mortality in urban settings. Today, Tanzania is undergoing rapid urbanisation and Dar es Salaam is predicted to have over 10 million inhabitants by 2030, increasing from 2.3 million in 2000.40 This growth is largely fuelled by rural–urban migration resulting in the lateral expansion of informal settlements and rapid expansion of rural trading centres amalgamating with other rural towns and nearby cities within Tanzania.25 Where historically the urban population was better educated and had higher incomes compared with the rural population,2 3 rapid urbanisation, including in peripheral towns, has led to haphazard informal settlements evident today, increasing the heterogeneity of the urban population25 and exacerbating vulnerability through a complex interplay between urban conditions, health service provision, and suboptimal quality of care. For example, air pollution is worse in urban areas and is a risk factor for prematurity, which in turn is a risk factor for neonatal mortality in the absence of accessible, affordable high-quality care for sick/small newborns. Mapping urbanisation processes, and the consequences for sociodemographics and quality of care affecting population health need to be further examined in future research.10 11 41 This can be done, for example, by examining whether a dose–response relationship exists between the extent of urbanisation and NMR in Tanzania and other countries at risk of reversing the urban advantage in neonatal survival, including Ghana, Ethiopia, Malawi, Uganda, Zambia and Kenya.

Third, the potential presence of bias needs to be considered. The characterisation of clusters as urban or rural on the DHS sampling strategy might not accurately capture the lived reality, especially if it based on historical census tract designations rather than on urbanicity at the time of survey. It is also possible that the higher NMR in urban areas in Tanzania can be partly explained by the under-reporting of neonatal death in rural areas; these deaths might have been misclassified as stillbirths or not reported at all.42 However, the Tanzania DHS 2015–2016 results showed that also the perinatal mortality rate (stillbirths and early neonatal deaths per 1000 pregnancies of seven or more months’ duration) was higher in urban (47) compared to rural areas (37). If this bias plays a role in the findings in our paper, it is therefore more likely to operate through under-reporting of perinatal deaths in rural areas rather than through differential misclassification of neonatal deaths as stillbirths. Lower levels of maternal education were more common in rural areas, and may contribute to underreporting neonatal deaths. This resonates with our finding that women with some education reported higher NMR than women without education. Furthermore, reporting of neonatal deaths in urban areas may be higher as more births take place with the presence of an SBA.43 There is potential that recall bias is present and future studies should focus on the urban–rural differences in the combined phenomenon of perinatal mortality as both are critically linked to quality of intrapartum care. However, it seems implausible that bias would account for the entirety of the urban–rural difference in NMR in Tanzania, as this pattern, has been evident in the DHS data since 1999 and not just persisted but widened over time, while many of the socioeconomic characteristics giving rise to under-reporting and misclassifications have changed dramatically over the past 20 years.

Conclusion

The time series analysis of 21 SSA countries indicates that Tanzania is the first country in SSA to show a reversed pattern in the urban–rural difference in neonatal mortality, with levels of NMR in urban areas double those in rural. While we acknowledge the need for additional research to elucidate the causal pathways underlying this association, we also call for urgent action to address important gaps in access to high-quality childbirth and postnatal care in urban settings in Tanzania and SSA. The high NMR rate in Tanzania (25 per 1000 live births) means that substantial changes are needed to achieve the SDG of 16 deaths per 1000 by 2030. However, the specific strategy to achieve this should consider separate approaches in urban vs rural areas. Further research should delve into the reporting of stillbirths, as underreporting and misclassification of perinatal deaths appears to be more prominent in rural areas. Accurate documentation of pregnancies and pregnancy outcomes could address differential self-reporting of stillbirths between the areas. Finally, this study highlights the shifting burden in neonatal mortality, from rural to urban areas. If this pattern is true and causal, we would expect that other SSA countries such as Ghana, Ethiopia, Malawi, Uganda, Zambia and Kenya are at risk of this phenomenon.