Urban–rural disparities in adult mortality in sub-Saharan Africa

High Child Mortality and Interventions Coverage in the City of Dar es Salaam, Tanzania: Are the Poorest Paying an Urban Penalty?

The 'urban penalty' in health refers to the loss of a presumed survival advantage due to adverse consequences of urban life. This study investigated the levels and trends in neonatal, post-neonatal and under-5 mortality rate and key determinants of child survival using data from Tanzania Demographic and Health Surveys (TDHS) (2004/05, 2010 and 2015/16), AIDS Indicator Survey (AIS), Malaria Indicator survey (MIS) and health facility data in Tanzania mainland. We compared Dar es Salaam results with other urban and rural areas in Tanzania mainland, and between the poorest and richest wealth tertiles within Dar es Salaam. Under-5 mortality declined by 41% between TDHS 2004/05 and 2015/2016 from 132 to 78 deaths per 1000 live births, with a greater decline in rural areas compared to Dar es Salaam and other urban areas. Neonatal mortality rate was consistently higher in Dar es Salaam during the same period, with the widest gap (> 50%) between Dar es Salaam and rural areas in TDHS 2015/2016. Coverage of maternal, new-born and child health interventions as well as living conditions were generally better in Dar es Salaam than elsewhere. Within the city, neonatal mortality was 63 and 44 per 1000 live births in the poorest 33% and richest 33%, respectively. The poorest had higher rates of stunting, more overcrowding, inadequate sanitation and lower coverage of institutional deliveries and C-section rate, compared to richest tertile. Children in Dar es Salaam do not have improved survival chances compared to rural children, despite better living conditions and higher coverage of essential health interventions. This urban penalty is higher among children of the poorest households which could only partly be explained by the available indicators of coverage of services and living conditions. Further research is urgently needed to understand the reasons for the urban penalty, including quality of care, health behaviours and environmental conditions.

Estimating geographic access to healthcare facilities in Sub-Saharan Africa by Degree of Urbanisation

Measuring rates of coverage and spatial access to healthcare services is essential to inform policies for development. These rates tend to reflect the urban-rural divide, typically with urban areas experiencing higher accessibility than rural ones. Especially in Sub-Saharan Africa (SSA), a region experiencing high disease burden amid fast urbanisation and population growth. However, such assessment has been hindered by a lack of updated and comparable geospatial data on urbanisation and health facilities. In this study, we apply the UN-endorsed Degree of Urbanisation (DoU or DEGURBA) method to investigate how geographic access to healthcare facilities varies across the urban-rural continuum in SSA as a whole and in each country, for circa 2020. Results show that geographic access is overall highest in cities and peri-urban areas, where more than 95% of inhabitants live within 30 min from the nearest HCF, with this share decreasing to 80-90% in towns. This share is lowest in villages and dispersed rural areas (65%), with about 10-15% of population more than 3 h away from any health post. Challenges in geographic access seem mostly determined by high travel impedance, since overall spatial densities of HCF are comparable to European levels.

Spatial analysis of cardiovascular mortality and associated factors around the world

BACKGROUND

Cardiovascular disease (CVD) is one of the most serious health issues and the leading cause of death worldwide in both developed and developing countries. The risk factors for CVD include demographic, socioeconomic, behavioral, environmental, and physiological factors. However, the spatial distribution of these risk factors, as well as CVD mortality, are not uniformly distributed across countries. Therefore, the goal of this study is to compare and evaluate some models commonly used in mortality and health studies to investigate whether the CVD mortality rates in the adult population (over 30 years of age) of a country are associated with the characteristics of surrounding countries from 2013 to 2017.

METHODS

We present the spatial distribution of the age-standardized crude mortality rate from cardiovascular disease, as well as conduct an exploratory data analysis (EDA) to obtain a basic understanding of the behavior of the variables of interest. Then, we apply the ordinary least squares (OLS) to the country level dataset. As OLS does not take into account the spatial dependence of the data, we apply two spatial modelling techniques, that is, spatial lag and spatial error models.

RESULTS

Our empirical findings show that the relationship between CVD and income, as well as other socioeconomic variables, are important. In addition, we highlight the importance of understanding how changes in individual behavior across different countries might affect future trends in CVD mortality, especially related to smoking and dietary behaviors.

CONCLUSIONS

We argue that this study provides useful clues for policymakers establishing effective public health planning and measures for the prevention of deaths from cardiovascular disease. The reduction of CVD mortality can positively impact GDP growth because increasing life expectancy enables people to contribute to the economy of the country and its regions for longer.

The shifting rural-urban gap in mortality over the life course in low- and middle-income countries

Studies have shown that children in rural areas face excess risks of dying, but the little research on spatial inequalities in adult mortality has reached mixed conclusions. We examine rural-urban differences in mortality in 53 low- and middle-income countries. We consider how the rural-urban mortality gap evolves from birth to age 60 by estimating mortality based on birth and sibling histories from 138 Demographic and Health Surveys run between 1992 and 2018. We observe excess rural mortality until age 15, finding the largest differences between urban and rural sectors among 1-59-month-olds. While we cannot claim higher mortality among urban adults than those in rural areas, we find a reduced gap between the sectors over the life course and a diminishing urban advantage in adult mortality with age. This shift over the life course reflects a divergence in the epidemiologic transition between the rural and urban sectors.

Rural-Urban Differences: Using Finer Geographic Classifications to Reevaluate Distance and Choice of Health Services in Malawi

There is no universal understanding of what defines urban or rural areas nor criteria for differentiating within these. When assessing access to health services, traditional urban-rural dichotomies may mask substantial variation. We use geospatial methods to link household data from the 2015-2016 Malawi Demographic Health Survey to health facility data from the Malawi Service Provision Assessment and apply a new proposed four-category classification of geographic area (urban major metropolitan area, urban township, rural, and remote) to evaluate households' distance to, and choice of, primary, secondary, and tertiary health care in Malawi. Applying this new four-category definition, approximately 3.8 million rural- and urban-defined individuals would be reclassified into new groups, nearly a quarter of Malawi's 2015 population. There were substantial differences in distance to the nearest facility using this new categorization: remote households are (on average) an additional 5 km away from secondary and tertiary care services versus rural households. Health service choice differs also, particularly in urban areas, a distinction that is lost when using a simple binary classification: those living in major metropolitan households have a choice of five facilities offering comprehensive primary care services within a 10-km zone, whereas urban township households have no choice, with only one such facility within 10 km. Future research should explore how such expanded classifications can be standardized and used to strengthen public health and demographic research.

An urban-to-rural continuum of malaria risk: new analytic approaches characterize patterns in Malawi

BACKGROUND

The urban-rural designation has been an important risk factor in infectious disease epidemiology. Many studies rely on a politically determined dichotomization of rural versus urban spaces, which fails to capture the complex mosaic of infrastructural, social and environmental factors driving risk. Such evaluation is especially important for Plasmodium transmission and malaria disease. To improve targeting of anti-malarial interventions, a continuous composite measure of urbanicity using spatially-referenced data was developed to evaluate household-level malaria risk from a house-to-house survey of children in Malawi.

METHODS

Children from 7564 households from eight districts throughout Malawi were tested for presence of Plasmodium parasites through finger-prick blood sampling and slide microscopy. A survey questionnaire was administered and latitude and longitude coordinates were recorded for each household. Distances from households to features associated with high and low levels of development (health facilities, roads, rivers, lakes) and population density were used to produce a principal component analysis (PCA)-based composite measure for all centroid locations of a fine geo-spatial grid covering Malawi. Regression methods were used to test associations of the urbanicity measure against Plasmodium infection status and to predict parasitaemia risk for all locations in Malawi.

RESULTS

Infection probability declined with increasing urbanicity. The new urbanicity metric was more predictive than either a governmentally defined rural/urban dichotomous variable or a population density variable. One reason for this was that 23% of cells within politically defined rural areas exhibited lower risk, more like those normally associated with "urban" locations.

CONCLUSIONS

In addition to increasing predictive power, the new continuous urbanicity metric provided a clearer mechanistic understanding than the dichotomous urban/rural designations. Such designations often ignore urban-like, low-risk pockets within traditionally rural areas, as were found in Malawi, along with rural-like, potentially high-risk environments within urban areas. This method of characterizing urbanicity can be applied to other infectious disease processes in rapidly urbanizing contexts.

Chronic respiratory disease mortality and its associated factors in selected Asian countries: evidence from panel error correction model

Background

Chronic Respiratory Diseases (CRDs) in Asian countries are a growing concern in terms of morbidity and mortality. However, a systematic understanding of the increasing age-adjusted mortality rate of chronic respiratory disease (CRD) and its associated factors is not readily available for many Asian countries. We aimed to determine country-level factors affecting CRD mortality using a panel error correction model.

Methods

Based on data from the Global Burden of Disease Study 2017, we estimated the trends and distribution of CRD mortality for selected Asian countries from 2010 to 2017. Furthermore, we evaluated the relationship between CRD mortality and Gross Domestic Product (GDP) per capita, average years of schooling, urbanization, and pollutant emission (PM2.5 concentration) using a fixed-effect model. We corrected the estimates for heteroscedasticity and autocorrelation through Prais-Winsten adjustment along with robust standard error.

Results

Between 2010 and 2017, approximately 21.4 million people died from chronic respiratory diseases in the countries studied. Age-standardized crude mortality rate from CRDs in the period had minimum and maximum values of 8.19 (Singapore in 2016) and 155.42 (North Korea in 2010) per 100,000 population, respectively. The coefficients corrected for autocorrelation and heteroskedasticity based on the final model of our study (Prais-Winsten), showed that all explanatory variables were statistically significant (p < 0.001). The model shows that the 1% increase in GDP per capita results in a 20% increase (0.203) in the CRD mortality rate and that a higher concentration of air pollution is also positively associated with the CRD deaths (0.00869). However, an extra year of schooling reduces the mortality rate by 4.79% (− 0.0479). Further, rate of urbanization is negatively associated with the CRD death rate (− 0.0252).

Conclusions

Our results indicate that both socioeconomic and environmental factors impact CRD mortality rates. Mortality due to CRD increases with rising GDP per capita and decreases with the percentage of the total population residing in urban areas. Further, mortality increases with greater exposure to PM2.5. Also, higher years of schooling mitigate rising CRD mortality rates, showing that education can act as a safety net against CRD mortality. These results are an outcome of sequential adjustments in the final model specification to correct for heteroscedasticity and autocorrelation.

Prevalence and determinants of the place of delivery among reproductive age women in sub-Saharan Africa

Introduction

Maternal mortality is an issue of global public health concern with over 300,000 women dying globally each year. In sub-Saharan Africa (SSA), these deaths mainly occur around childbirth and the first 24hours after delivery. The place of delivery is, therefore, important in reducing maternal deaths and accelerating progress towards attaining the 2030 sustainable development goals (SDGs) related to maternal health. In this study, we examined the prevalence and determinants of the place of delivery among reproductive age women in SSA.

Materials and methods

This was a cross-sectional study among women in their reproductive age using data from the most recent demographic and health surveys of 28 SSA countries. Frequency, percentage, chi-square, and logistic regression were used in analysing the data. All analyses were done using STATA.

Results

The overall prevalence of health facility delivery was 66%. This ranged from 23% in Chad to 94% in Gabon. More than half of the countries recorded a less than 70% prevalence of health facility delivery. The adjusted odds of health facility delivery were lowest in Chad. The probability of giving birth at a health facility also declined with increasing age but increased with the level of education and wealth status. Women from rural areas had a lower likelihood (AOR = 0.59, 95%CI = 0.57–0.61) of delivering at a health facility compared with urban women.

Conclusions

Our findings point to the inability of many SSA countries to meet the SDG targets concerning reductions in maternal mortality and improving the health of reproductive age women. The findings thus justify the need for peer learning among SSA countries for the adaption and integration into local contexts, of interventions that have proven to be successful in improving health facility delivery among reproductive age women.