Spatial variations and determinants of infant and under-five mortality in Bangladesh

Spatial spillover impact of determinants on child mortality in Pakistan: evidence from Spatial Durbin Model

BACKGROUND

Child mortality is a major challenge to public health in Pakistan and other developing countries. Reduction of the child mortality rate would improve public health and enhance human well-being and prosperity. This study recognizes the spatial clusters of child mortality across districts of Pakistan and identifies the direct and spatial spillover effects of determinants on the Child Mortality Rate (CMR).

METHOD

Data of the multiple indicators cluster survey (MICS) conducted by the United Nations International Children's Emergency Fund (UNICEF) was used to study the CMR. We used spatial univariate autocorrelation to test the spatial dependence between contiguous districts concerning CMR. We also applied the Spatial Durbin Model (SDM) to measure the spatial spillover effects of factors on CMR.

RESULTS

The study results showed 31% significant spatial association across the districts and identified a cluster of hot spots characterized by the high-high CMR in the districts of Punjab province. The empirical analysis of the SDM confirmed that the direct and spatial spillover effect of the poorest wealth quintile and MPI vulnerability on CMR is positive whereas access to postnatal care to the newly born child and improved drinking water has negatively (directly and indirectly) determined the CMR in Pakistan.

CONCLUSION

The instant results concluded that spatial dependence and significant spatial spillover effects concerning CMR exist across districts. Prioritization of the hot spot districts characterized by higher CMR can significantly reduce the CMR with improvement in financial statuses of households from the poorest quintile and MPI vulnerability as well as improvement in accessibility to postnatal care services and safe drinking water.

Spatiotemporal trends in neonatal, infant, and child mortality (1990-2019) based on Bayesian spatiotemporal modeling

Background

Neonatal mortality rate (NMR), infant mortality rate (IMR), and child mortality rate (CMR) show a huge difference across countries, which has been posing challenges for public health policies and medical resource allocation.

Methods

Bayesian spatiotemporal model is applied to assess the detailed spatiotemporal evolution of NMR, IMR, and CMR from a global perspective. Panel data from 185 countries from 1990 to 2019 are collected.

Results

The continuously decreasing trend of NMR, IMR, and CMR indicated a great improvement in neonatal, infant, and child mortality worldwide. Further, huge differences in the NMR, IMR, and CMR still exist across countries. In addition, the gap of NMR, IMR, and CMR across the countries presented a widening trend from the perspective of dispersion degree and kernel densities. The spatiotemporal heterogeneities demonstrated that the decline degree among these three indicators could be observed as CMR > IMR > NMR. Countries such as Brazil, Sweden, Libya, Myanmar, Thailand, Uzbekistan, Greece, and Zimbabwe showed the highest values of b_1i , indicating a weaker downward trend compared to the overall downward trend in the world.

Conclusions

This study revealed the spatiotemporal patterns and trends in the levels and improvement of NMR, IMR, and CMR across countries. Further, NMR, IMR, and CMR show a continuously decreasing trend, but the differences in improvement degree present a widening trend across countries. This study provides further implications for policy in newborns, infants, and children's health to reduce health inequality worldwide.

Spatiotemporal distributions of under-five mortality in Ethiopia between 2000 and 2019

Under-five mortality declined in the last two decades in Ethiopia, but sub-national and local progress remains unclear. This study aimed to investigate the spatiotemporal distributions and ecological level factors of under-five mortality in Ethiopia. Data on under-five mortality were obtained from five different Ethiopian Demographic and Health Surveys (EDHS), conducted in 2000, 2005, 2011, 2016, and 2019. Environmental and healthcare access data were obtained from different publicly available sources. Bayesian geostatistical models were used to predict and visualize spatial risks for under-five mortality. The national under-five mortality rate in Ethiopia declined from 121 per 1000 live births in 2000 to 59 per 1000 live births in 2019. Spatial variation in under-five mortality was observed at regional and local levels with the highest rates reported in the Western, Eastern, and Central parts of Ethiopia. Spatial clustering of under-five mortality was significantly associated with population density, access to a water body, and climatic factors such as temperature. Under-five mortality rate declined over the past two decades and varied substantially at sub-national and local levels in Ethiopia. Increasing access to water and health care may help to reduce under-five mortality in high-risk areas. Therefore, interventions targeted to reduce under-five mortality should be strengthened in the areas that had a clustering of under-five mortality in Ethiopia by increasing access to quality health care access.

Patterns of child mortality in rural area of Burkina Faso: evidence from the Nanoro health and demographic surveillance system (HDSS)

Background

Half of global child deaths occur in sub-Saharan Africa. Understanding child mortality patterns and risk factors will help inform interventions to reduce this heavy toll. The Nanoro Health and Demographic Surveillance System (HDSS), Burkina Faso was described previously, but patterns and potential drivers of heterogeneity in child mortality in the district had not been studied. Similar studies in other districts indicated proximity to health facilities as a risk factor, usually without distinction between facility types.

Methods

Using Nanoro HDSS data from 2009 to 2013, we estimated the association between under-5 mortality and proximity to inpatient and outpatient health facilities, seasonality of death, age group, and standard demographic risk factors.

Results

Living in homes 40–60 min and > 60 min travel time from an inpatient facility was associated with 1.52 (95% CI: 1.13–2.06) and 1.74 (95% CI: 1.27–2.40) greater hazard of under-5 mortality, respectively, than living in homes < 20 min from an inpatient facility. No such association was found for outpatient facilities. The wet season (July–November) was associated with 1.28 (95% CI: 1.07, 1.53) higher under-5 mortality than the dry season (December–June), likely reflecting the malaria season.

Conclusions

Our results emphasize the importance of geographical proximity to health care, distinguish between inpatient and outpatient facilities, and also show a seasonal effect, probably driven by malaria.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11483-4.

Exploring the spatial-temporal distribution and evolution of population aging and social-economic indicators in China

Background

China is one of the world’s fastest-aging countries. Population aging and social-economic development show close relations. This study aims to illustrate the spatial-temporal distribution and movement of gravity centers of population aging and social-economic factors and thier spatial interaction across the provinces in China.

Methods

Factors of elderly population rate (EPR), elderly dependency ratio (EDR), per capita gross regional product (GRP_pc), and urban population rate (UPR) were collected. Distribution patterns were detected by using global spatial autocorrelation, Kernel density estimation, and coefficient of variation. Further, Arc GIS software was used to find the gravity centers and their movement trends yearly from 2002 to 2018. The spatial interaction between the variables was investigated based on bivariate spatial autocorrelation analysis.

Results

The results showed a larger variety of global spatial autocorrelation indexed by Moran’s I and stable trends of dispersion degree without obvious convergence in EPR and EDR. Furthermore, the gravity centers of the proportion of EPR and EDR moved northeastward. In contrast, the economic and urbanization factors showed a southwestward movement, which exhibited an reverse trend compared to population aging indicators. Moreover, the movement rates of EPR and EDR (15.12 and 18.75 km/year, respectively) were higher than that of GRP_pc (13.79 km/year) and UPR (6.89 km/year) annually during the study period. Further, the bivariate spatial autocorrelation variation is in line with the movement trends of gravity centers which showed a polarization trend of population aging and social-economic factors that the difference between southwest and northeast directions and exhibited a tendency to expand in China.

Conclusions

In sum, our findings revealed the difference in spatio-temporal distribution and variation between population aging and social-economic factors in China. It further indicates that the opposite movements of gravity centers and the change of the BiLISA in space which may result in the increase of the economic burden of the elderly care in northern China. Hence, future development policy should focus on the social-economic growth and distribution of old-aged supporting resources, especially in northern China.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11032-z.

Trends and projections of under-5 mortality in Bangladesh including the effects of maternal high-risk fertility behaviours and use of healthcare services

OBJECTIVE

This study examines trends and puts forward projections of under-5 mortality (U5M) in Bangladesh and identifies the effects of maternal high-risk fertility behaviours and use of healthcare services.

METHODS

Data from seven waves of the Bangladesh Demographic and Health Survey (1994-2014) were analyzed for trends and projections of U5M and a Chi-square (χ2) test was used to identify if there was any association with maternal high-risk fertility behaviours and use of healthcare services. A multivariate logistic regression model was used to determine the effects of fertility behaviors and healthcare usage on the occurrence of U5M adjusting with confounders.

RESULTS

U5M declined from 82.5 to 41.0 per 1000 livebirths during 1994-2014 and is projected to further reduce to 17.6 per 1000 livebirths by 2030. The study identified a noticeable regional variation in U5M with maternal high-risk fertility behaviours including age at birth <18 years (aOR: 1.84, 95% CI: 1.23-2.76) and birth interval <24 months (aOR: 1.56, 95% CI: 1.02-2.37) found to be significant determinants. There was a 39-53% decline in this rate of mortality among women that had used antenatal care services at least four times (aOR, 0.51, 95% CI: 0.27-0.97), delivery care (aOR, 0.47, 95% CI: 0.24-0.95), and had received postnatal care (aOR, 0.61, 95% CI: 0.41-0.91) in their last birth. Cesarean section was found to be associated with a 51% reduction in U5M (aOR, 0.49, 95% CI: 0.29-0.82) compared to its non-use.

CONCLUSION

The Sustainable Development Goals require a U5M rate of 25 per 1000 livebirths to be achieved by 2030. This study suggests that with the current trend of reduction, Bangladesh will achieve this target before the deadline. This study also found that maternal high-risk fertility behaviours and non-use of maternal healthcare services are very prevalent in some regions of Bangladesh and have increased the occurrence of U5M in those areas. This suggests therefore, that policies and programmes designed to reduce the pregnancy rates of women that are at risk and to encourage an increase in the use of maternal healthcare services are needed.

The influence of the municipal human development index and maternal education on infant mortality: an investigation in a retrospective cohort study in the extreme south of Brazil

Background

Infant mortality is considered an important and sensitive health indicator in several countries, especially in underdeveloped and developing countries. Most of the factors influencing infant mortality are interrelated and are the result of social issues. Therefore, this study performed an investigation of the influence of the MHDI and maternal education on infant mortality in a capital in the extreme south of Brazil.

Methods

It is a retrospective cohort study with data on births and deaths in the first year of life for the period of 2000–2017. The association between the independent variables and the outcome was done by bivariate analysis through simple Poisson regression. The variables that can potentially be considered confounding factors were used in a multiple Poisson regression for robust variances - adjusted model.

Results

The study included 317,545 children, of whom 3107 died. The medium MHDI showed associated with infant death in the first year of life. Maternal education, individually and jointly analyzed with the MHDI, showed association with the outcome of infant death in the first year of life, particularly for children of mothers with lower maternal education (p < 0.001). In relation to other related factors, maternal age; number of Prenatal Care Consultations; gestational age, weight, gender and Apgar Index (5th minute) of the newborn showed association with IM (p < 0.001).

Conclusions

The HDI is considered a good predictor of infant mortality by some authors and the analyzes of the present study also confirm an association of the medium MHDI and its low MHDIE component with infant mortality. In addition, it was maternal education with less than 8 years of study that that demonstrated a higher risk of death, revealing itself to be a social determinant with a relevant impact on infant mortality. Thus, it is possible to conclude that maternal education is available information, and it is superior to the MHDI to assess the infant mortality outcome.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-10226-9.

Exploring spatiotemporal distribution of under-five mortality in Ethiopia: further analysis of Ethiopian Demographic and Health Surveys 2000, 2005, 2011 and 2016

OBJECTIVE

The aim of this study was to explore spatiotemporal distribution of under-five mortality in Ethiopia using data from four (2000, 2005, 2011 and 2016) consecutive demographic and health surveys.

METHODS

A total of 41 498 children were included from four consecutive Ethiopian Demographic and Health Surveys. The geospatial analysis was conducted by using ArcGIS V.10.7 and saTScan V.9.6. Thus, spatial autocorrelation, hotspot analysis, spatial interpolation and spatial scan statistics were carried out for each survey separately to show the temporal pattern of geographically risk areas of under-five mortality in Ethiopia. Finally, the most under-five mortality rate (U5MR) risk areas in each survey period were mapped.

RESULTS

Under-five mortality was spatially clustered in Ethiopia (Moran's Index: 0.046-0.096, p<0.01). The Benishangul-Gumuz region was consistently at a higher risk in the last two decades. Additional hotspot areas were detected at Afar and Amhara (in 2000, 2005, 2016), at Gambala (in 2011) and the South Nation Nationality and People's (SNNP) Region (in 2016). Moreover, 160 primary clusters were identified. Of these, 85 clusters (log-likelihood ratio (LLR)=13.10, p<0.01) were from Benishangul-Gumuz and Amhara regions (in 2000); 67 clusters (LLR=12.93, p<0.01) were from Afar and Amhara regions (in 2005); 4 clusters (LLR=10.54, p<0.01) were from Benishangul-Gumuz region (in 2011); and another 4 clusters (LLR=11.85, p<0.01) were from Afar region (in 2016).

CONCLUSION

High-risk areas were detected mainly in the Benishangul-Gumuz and Afar regions. As a result, designing under-five population targeted intervention programmes in those high-risk geographical regions was vital to reduce under-five mortality in Ethiopia.

Spatial heterogeneity of the associations of economic and health care factors with infant mortality in China using geographically weighted regression and spatial clustering

Economic factors and health care resources are important influential factors of infant mortality. We aimed to examine prefecture-level spatial heterogeneity and clustering of the associations of economic and health care factors with infant mortality rates (IMR) in China. IMR data in 348 prefectures were calculated and adjusted, and economic and health care data were collected in each prefecture in China, 2010. Stepwise regression was used to select important variables, and geographically weighted regression (GWR) was applied to examine the spatial variations of the relationships between economic and health care factors and IMR. The k-means clustering was developed to elucidate the spatial clustering patterns of the GWR coefficients. The results showed that three important variables were selected in the multivariable regression model, including per capita income of rural residents, Engel's coefficient of rural residents, and proportion of government health expenditure. The GWR with these three variables revealed spatial heterogeneity of the associations between IMR and economic and health care factors; western China generally had higher GWR R-squares and stronger associations between IMR and all the three variables than the middle-eastern part of China. Based on the GWR coefficients, three distinct spatial clusters were identified. This study contributes new findings on the spatial heterogeneity of the associations between economic and health care factors and infant mortality rate in China, which calls for region-specific policies to reduce infant mortality in China.

Socioeconomic Inequalities in Child Malnutrition in Bangladesh: Do They Differ by Region?

Socioeconomic inequality in child malnutrition is well-evident in Bangladesh. However, little is known about whether this inequality differs by regional contexts. We used pooled data from the 2011 and 2014 Bangladesh Demographic and Health Survey to examine regional differences in socioeconomic inequalities in stunting and underweight among children under five. The analysis included 14,602 children aged 0–59 months. We used logistic regression models and the Concentration index to assess and quantify wealth- and education-related inequalities in child malnutrition. We found stunting and underweight to be more concentrated among children from poorer households and born to less-educated mothers. Although the poverty level was low in the eastern regions, socioeconomic inequalities were greater in these regions compared to the western regions. The extent of socioeconomic inequality was the highest in Sylhet and Chittagong for stunting and underweight, respectively, while it was the lowest in Khulna. Regression results demonstrated the protective effects of socioeconomic status (SES) on child malnutrition. The regional differences in the effects of SES tend to diverge at the lower levels of SES, while they converge or attenuate at the highest levels. Our findings have policy implications for developing programs and interventions targeted to reduce socioeconomic inequalities in child malnutrition in subnational regions of Bangladesh.

Socioeconomic inequality in maternal healthcare: An analysis of regional variation in Bangladesh

Socioeconomic inequality in the utilisation of maternal healthcare services is well-documented in Bangladesh. However, the spatial dimension of this inequality is largely unexplored in the literature. This study examined the regional variation of wealth-related inequality in the utilisation of maternal healthcare services using data from Bangladesh Demographic and Health Survey, 2014. The highest extent of pro-wealthy inequality was found in Chittagong and Sylhet for ANC services compared to Khulna and Rangpur where inequality was the lowest. Pro-wealthy inequality was the lowest in Rangpur while Dhaka and Barisal tended to have the greatest degree of inequality for delivery care services. Policy efforts aiming to tackle socioeconomic inequality in maternal healthcare should consider this spatial dimension of inequality in Bangladesh.