Spatial clustering and risk factors of infant mortality: district-level assessment of high-focus states in India

Exploring the distribution of risk factors for drop-out from Ponseti treatment for clubfoot across Bangladesh using geospatial cluster analysis

Clubfoot is a congenital anomaly affecting 1/1,000 live births. Ponseti casting is an effective and affordable treatment. About 75% of affected children have access to Ponseti treatment in Bangladesh, but 20% are at risk of drop-out. We aimed to identify the areas in Bangladesh where patients are at high or low risk for drop-out. This study used a cross-sectional design based on publicly available data. The nationwide clubfoot program: 'Walk for Life' identified five risk factors for drop-out from the Ponseti treatment, specific to the Bangladeshi setting: household poverty, household size, population working in agriculture, educational attainment and travel time to the clinic. We explored the spatial distribution and clustering of these five risk factors. The spatial distribution of children <5 years with clubfoot and the population density differ widely across the different sub-districts of Bangladesh. Analysis of risk factor distribution and cluster analysis showed areas at high risk for dropout in the Northeast and the Southwest, with poverty, educational attainment and working in agriculture as the most prevalent driving risk factor. Across the entire country, twenty-one multivariate high-risk clusters were identified. As the risk factors for drop-out from clubfoot care are not equally distributed across Bangladesh, there is a need in regional prioritization and diversification of treatment and enrolment policies. Local stakeholders and policy makers can identify high-risk areas and allocate resources effectively.

Prevalence, spatial distribution and determinants of infant mortality in Ethiopia: Findings from the 2019 Ethiopian Demographic and Health Survey

INTRODUCTION

Infant mortality declined globally in the last three decades. However, it is still a major public health concern in Ethiopia. The burden of infant mortality varies geographically with the highest rate in Sub-Saharan Africa. Although different kinds of literature are available regarding infant mortality in Ethiopia, an up to date information is needed to design strategies against the problem. Thus, this study aimed to determine the prevalence, show the spatial variations and identify determinants of infant mortality in Ethiopia.

METHODS

The prevalence, spatial distribution, and predictors of infant mortality among 5,687 weighted live births were investigated using secondary data from the Ethiopian Demographic and Health Survey 2019. Spatial autocorrelation analysis was used to determine the spatial dependency of infant mortality. The spatial clustering of infant mortality was studied using hotspot analyses. In an unsampled area, ordinary interpolation was employed to forecast infant mortality. A mixed multilevel logistic regression model was used to find determinants of infant mortality. Variables with a p-value less than 0.05 were judged statistically significant and adjusted odds ratios with 95 percent confidence intervals were calculated.

RESULT

The prevalence of infant mortality in Ethiopia was 44.5 infant deaths per 1000 live births with significant spatial variations across the country. The highest rate of infant mortality was observed in Eastern, Northwestern, and Southwestern parts of Ethiopia. Maternal age between 15&19 (adjusted odds ratio (AOR) = 2.51, 95% Confidence Interval (CI): 1.37, 4.61) and 45&49(AOR = 5.72, 95% CI: 2.81, 11.67), having no antenatal care follow-up (AOR = 1.71, 95% CI: 1.05, 2.79) and Somali region (AOR = 2.78, 95% CI: 1.05, 7.36) were significantly associated with infant mortality in Ethiopia.

CONCLUSION

In Ethiopia, infant mortality was higher than the worldwide objective with significant spatial variations. As a result, policy measures and strategies aimed at lowering infant mortality should be devised and strengthened in clustered areas of the country. Special attention should be also given to infants born to mothers in the age groups of 15-19 and 45-49, infants of mothers with no antenatal care checkups, and infants born to mothers living in the Somali region.

Improved Yet Unsafe: At the Light of NFHS-V

Following UNICEF’s analysis of National Family Health Survey-III Data (NFHS-III), it was opined that households with access to better sanitation and better access to improved water sources have much better infant survival rates than the others. Sahu et al. (2015, The Indian journal of medical research, 141(5), 709), Arun et al. (2017, International Conference on Cognitive Computing and Information Processing (pp. 81–92), Springer) and Tripathy and Mishra (2017, Journal of Tropical Pediatrics, 63(6), 431–439) supported these findings. However, Banerjee (2020a , Journal of Health Management, 22(1), 57–66), analysing NFHS-IV data, has vehemently criticised such findings and showed using regression with robust standard errors that improved access to better water sources leads to higher infant mortality. In another article published in the same year, Banerjee (2020b , Journal of Health Management, 22(3), 466–471) explained this paradox. Now with NFHS-V data coming out, time is apt to test the robustness of Banerjee’s findings (2002a). However, owing to the incomplete NFHS-V data published so far, unlike Banerjee (2002a) that has used data of 29 states, the present analysis is based on only 17 states. The findings support that the findings of Banerjee (2002a) were robust.

The effects of community clustering on under-five mortality in India: a parametric shared frailty modelling approach

The study of the effect of community clustering of under-five mortality has its implications in both research and policy. Studies have shown the contribution of community factors on under-five mortality. However, these studies did not account for censoring. We examine the presence of community dependencies and determine the risk factors of under-five mortality in India and its six state-regions by employing a Weibull hazard model with gamma shared frailty. We considered every possible way to ensure that the frailty models used in the study are not merely a consequence of how the data are organized rather than representing a substantive assumption about the source of the frailty. Data from the fourth round of the National Family Health Survey has been used. The study found that except for south India, children born in the same community in India and the other five state-regions shared similar characteristics of under-five mortality. The risk of under-five mortality decreased with an increase in mother’s schooling. Except for northern region, female births were less likely to die within first five years of life. We found a U-shaped relationship between preceding birth interval and under-five mortality. History of sibling’s death, multiple births and low-birthweight significantly increases the risk of under-five mortality in all the six state-regions. The Hindu–Muslim mortality gaps and Scheduled Caste or Tribe’s mortality disadvantage is diminishing. Since the factors associated with under-five mortality were not necessarily the same across the six state-regions of India, adopting a uniform approach in dealing with under-five mortality in India may not benefit all the regions equally.

Differential in infant, childhood and under-five death clustering among the empowered and non-empowered action group regions in India

Background

With 8,82,000 deaths in the under-five period, India observed varied intra-state and inter-regional differences across infant and child mortality in 2018. However, scarce literature is present to capture this unusual concentration of mortality in certain families by examining the association of the mortality risks among the siblings of those families along with various unobserved characteristics of the mother. Looking towards the regional and age differential in mortality, this paper attempts to provide evidence for the differential in mortality clustering among infants (aged 0–11 months), children (12–59 months) and under-five (0–59 months) period among mothers from the Empowered Action Group (EAG) and non-EAG regions of India.

Methods

The study used data from the National Family Health Survey (2015–16) which includes all the birth histories of 475,457 women aged 15–49 years. Bivariate and multivariate analyses were used to fulfil the objectives of the study. A two-level random intercept Weibull regression model was used to account for the unexplained mother (family) level heterogeneity.

Results

About 3.3% and 5.9% of infant deaths and 0.8% and 1.6% of childhood deaths were observed in non-EAG and EAG regions respectively. Among them, a higher percentage of infant and child death was observed due to the death of a previous sibling. There were 1.67 times [95% CI: 1.55–1.80] and 1.46 times [CI: 1.37–1.56] higher odds of infant and under-five mortality of index child respectively when the previous sibling at the time of conception of the index child was dead in the non-EAG regions. In contrast, the odds of death scarring (death of previous sibling scars the survival of index child) were 1.38 times [CI: 1.32–1.44] and 1.24 times [CI: 1.20–1.29] higher for infant and under-five mortality respectively in the EAG regions.

Conclusion

The extent of infant and child mortality clustering and unobserved heterogeneity was higher among mothers in the non-EAG regions in comparison to their EAG region counterparts. With the growing situation of under-five mortality clustering in non-EAG states, region-wise interventions are recommended. Additionally, proper care is needed to ameliorate the inter-family variation in mortality risk among the children of both EAG and non-EAG regions throughout their childhood.

Mapping changes in district level prevalence of childhood stunting in India 1998-2016: An application of small area estimation techniques

The four rounds of National Family Health Survey (NFHS) conducted during 1992-93, 1998-99, 2005-06 and 2015-16 is main source to track the health and development related indicators including nutritional status of children at national and state level in India. Except NFHS-4, first three rounds of NFHS were unable to provides district-level estimates of childhood stunting due to the insufficient sample sizes. The small area estimation (SAE) techniques offer a viable solution to overcome the problem of small sample size. Therefore, this study uses SAE techniques to derive district level prevalence of childhood stunting corresponding to NFHS-2 (1998-99). Study further estimated GIS maps, univariate Local indicator of spatial autocorrelation (LISA) and Moran's I to understand the trend in district level childhood stunting between NFHS-2 and NFHS-4. Estimates obtained by SAE techniques suggest that prevalence of childhood stunting ranges from 20.7% (95% CI: 18.8-22.7) in South Goa district of Goa to 64.4% (95%CI: 63.1-65.7) in Dhaulpur district of Rajasthan during 1998-99. The diagnostic measures used to validate the reliability of estimates obtained by SAE techniques indicate that the model-based estimates are reliable and representative at district level. Results of geospatial analysis indicates substantial reduction in childhood stunting between 1998 and 2016. Out of 640 district,about 81 district experience reduction of more than 50%. At the same time 60 district experience less than 10% of reduction between 1998 and 2016. Spatial clustering of childhood stunting remains same over the study period except few additional cluster in Maharashtra, Andhra and Meghalaya in 2016. The district level estimates obtained from this study might be helpful in framing decentralized policies and implementation of vertical programs to enhance the efficacy of various nutrition interventions in priority districts of the country.

Demystifying the Aquatic Paradox: The Infant Mortality in India

It is evident that better access to improved water sources will lead to the lessening of infant mortality rate (IMR). However, for India, such inference is ambiguous. There is a strong group of academicians such as Sahu et al. (2015) , Arun et al. (2017) and Tripathy and Mishra (2017) and organizations such as UNICEF that firmly believe that if access to the improved water sources can be improved, then there would be tremendous social welfare and much betterment to the IMR.

On the other hand, Banerjee et al. (2020) have refuted such claims and opined that access to improved water sources increases the IMR. The empirical validation of their claim has been flawless, but they are somewhat silent on why such a direct relationship between IMR and improved water source exists. They have made a comment based on assumptions that it might be complacency that develops with access to improved water sources that refrain the people to consider any type of water treatment before passing it to infants for drinking. Such a comment might be valid, but neither is it built upon a sound literature review nor does it stand on strong empirics. At this juncture, the present article tests the claim of Banerjee et al. (2020) based on pure empirics.

Factors explaining regional variation in under-five mortality in India: An evidence from NFHS-4

Although child mortality has declined in India, pronounced regional and socioeconomic inequality exists. The study examines the effects of individual- and community-level characteristics on under-five mortality and investigates the extent to which they affect regional variation. The study is based on Indian National Family and Health Survey 4, 2015-16 data. A two-level logistic regression model was performed to examine the effects of the socio-economic characteristics, and multivariate decomposition analysis was done to assess the contribution of factors in the inter-regional under-five mortality differentials. Regional variation in the selected variables is observed. For instance, the percentage of children with small childbirth size varied from 9.7% in the southern to 21.6% in the northeastern region. The percentage of poor households, low educated mothers, and childbirths delivered at home facility were higher in the central and eastern region compared to the southern region. The multilevel analysis shows that the region of residence explained 15.8% variance, and community-level characteristics alone could explain 25.3% variation in the risk of under-five deaths. The decomposition analysis indicates that the average number of excess deaths in the central and eastern regions is higher compared to the other regions. The compositional differences account for 50.9% of the under-five mortality gaps between the south and north region, 80.9% of the gap between the south and east, and 42.9% of the gap between the south and central region of India. Special attention and targeted action are needed to address the underlying causes of low birth weight of children in all the regions of India. Region-specific interventions might be priorities; for example, north, and central regions, need an economic and educational uplift, while infrastructural and economic policies should be prioritized for the northeastern region. Also, region-specific community-level interventions are needed to improve child survival in India.

Proximal and contextual correlates of childhood stunting in India: A geo-spatial analysis

BACKGROUND

Globally, India is home to every third child affected by stunting. While numerous studies have examined the correlates of childhood stunting (CS) in India, most of these studies have focused on examining the role of proximal factors, and the role of contextual factors is much less studied. This study presents a comprehensive picture of both proximal and contextual determinants of CS in India, expanding the current evidence base. The present study is guided by the WHO conceptual framework, which outlines the context, causes, and consequences of CS.

DATA AND METHODS

The study used exploratory spatial data analysis tools to analyse the spatial pattern and correlates of CS, using data from the fourth round (2015-16) of the National Family Health Survey (NFHS-4) and the 2011 Census of India.

RESULTS

The study findings reiterate that CS continues to be high in India, with several hot spot states and districts, and that children from the central and eastern region of the nation, namely, Bihar, Jharkhand, Madhya Pradesh, and Uttar Pradesh are particularly vulnerable. Our analysis has identified six risk factors-maternal short stature, large household size, closely spaced births, prevalence of hypertension among women, household poverty, open defecation, and extreme temperature-and four protective factors-female education, access to improved drinking water, dietary diversity among children, and iron and folic acid (IFA) supplementation during pregnancy.

CONCLUSIONS

The study highlights the need for investing in pre-conception care, addressing both demand- and supply-side barriers to increase the coverage of nutrition-specific interventions, implementing programmes to promote the intake of healthy foods from an early age, providing contraceptive counselling and services to unmarried and married adolescents and young women and men, and universalizing quality primary and secondary education that is inclusive and equitable to avert the burden of childhood stunting in India.

Improved yet Unsafe: An Aquatic Perspective of Indian Infant Mortality

Infant mortality rate (IMR) is an important development indicator and a vital component of millennium development goals (MDGs) set by United Nations Development Programme (UNDP). According to UNDP, so far India has only fared moderately in reducing IMR (Goal 4 of MDGs). India (32) ranks 144th among 196 countries regarding IMR as per the 2017 data availed from World Development Indicators. Its adjacent countries such as Bhutan (25.6), Bangladesh (26.9) and Nepal (27.8) have fared much better regarding infant survival. Numbers within the parentheses indicate the IMR of the respective country. The United Nations Children’s Fund (UNICEF) has identified that IMR among families with better access to improved drinking water sources and toilet is much lower than those bereft of the same. This inference has been drawn from National Family Health Survey 3 data (NFHS III). The present study investigates into the aforementioned relation analysing NFHS IV data. The result depicts that contrary to UNICEF’s findings, IMR increases with better accessibility to improved water sources. Further to this, the article shows that an additional aqua-related practice together with improved drinking water sources might lead to the betterment of IMR for India.

The persistent influence of caste on under-five mortality: Factors that explain the caste-based gap in high focus Indian states

OBJECTIVE

Although under-five mortality rate (U5MR) is declining in India, it is still high in a few selected states and among the scheduled caste (SC) and scheduled tribe (ST) population of the country. This study re-examines the association between caste and under-five deaths in high focus Indian states following the implementation of the country's National Rural Health Mission (NRHM) program. In addition, we aim to quantify the contribution of socioeconomic determinants in explaining the gap in under-five death risk between the SC/ST population and non-SC/ST population in high focus states in India.

DATA AND METHOD

Using data from the National Family Health Survey (NFHS), we calculated the U5MR by applying a synthetic cohort probability approach. We applied a binary logistic regression model to examine the association of under-five deaths with the selected covariates. Further, we used Fairlie's decomposition technique to understand the relative contribution of socioeconomic variables on under-five death risk between the caste groups.

FINDINGS

In high focus Indian states, the under-five mortality risk between well-off and deprived caste children has declined in the post-NRHM period, indicating a positive impact in terms of reducing caste-based inequalities in the high focus states. Despite the reduction in under-five death risk, children belonging to the SC population experience higher mortality rates than children belonging to the non-SC/ST population from 1992 to 2016. Both macro level (district level mortality rates) and individual (regression analysis) analyses showed that children belonging to SCs experience the highest likelihood of dying before their fifth birthday. A decomposition analysis revealed that 83% of the caste-based gap in the under-five deaths is due to the distribution of women's level of educational attainment and household wealth between the SC/ST and non-SC/ST population. Program indicators such as place of birth and number of antenatal care (ANC) visit also contributed significantly to widening caste-based gaps in U5MR.

CONCLUSION

The study indicates that there is still room to improve access to health facilities for mothers and children belonging to deprived caste groups in India. Continuous efforts to raise the level of maternal education and the economic status of people belonging to deprived caste groups should be pursued simultaneously.

Using spatial analysis and GIS to improve planning and resource allocation in a rural district of Bangladesh

The application of a geographic information system (GIS) in public health is relatively common in Bangladesh. However, the use of GIS for planning, monitoring and decision-making by local-level managers has not been well documented. This assessment explored how effectively local government health managers used maps with spatial data for planning, resource allocation and programme monitoring. The United States Agency for International Development-funded MaMoni Health Systems Strengthening project supported the introduction of the maps into district planning processes in 2015 and 2016. GIS maps were used to support the prioritisation of underserved unions (the lowest administrative units) and clusters of disadvantaged communities for the allocation of funds. Additional resources from local government budgets were allocated to the lowest performing unions for improving health facility service readiness and supervision. Using a mixed-methods approach, the project evaluated the outputs of this planning process. District planning reports, population-based surveys, local government annual expenditure reports and service availability and utilisation data were reviewed. The goal was to determine the degree to which district planning teams were able to use the maps for their intended purpose. Key informant interviews were conducted with upazila (subdistrict) managers, elected government representatives and service providers to understand how the maps were used, as well as to identify potential institutionalisation scopes. The project observed improvements in health service availability and utilisation in the highest priority unions in 2016. Quick processing of maps during planning sessions was challenging. Nevertheless, managers and participants expressed their satisfaction with the use of spatial analysis, and there was an expressed need for more web-based GIS both for improving community-level service delivery and for reviewing performance in monthly meetings. Despite some limitations, the use of GIS maps helped local health managers identify health service gaps, prioritise underserved unions and monitor results.

Continuities and changes in spatial patterns of under-five mortality at the district level in India (1991-2011)

Background

India has the largest number of under-five deaths globally, and large variations in under-five mortality persist between states and districts. Relationships between under-five mortality and numerous socioeconomic, development and environmental health factors have been explored at the national and state levels, but the possible spatial heterogeneity in these relationships has seldom been investigated at the district level. This study seeks to unravel local variation in key determinants of under-five mortality based on the 1991 and 2011 censuses.

Methods

Using geocoded district-level data from the last two census rounds (1991 and 2011) and ordinary least squares and geographically weighted regressions, we identify district-specific relationships between under-five mortality rate and a series of determinants for two periods separated by 20 years (1986–1987 and 2006–2007). To identify spatial groupings of coefficients, we perform a cluster analysis based on t-values of the geographically weighted regression.

Results

The geographically weighted regression analysis shows that relationships between the under-five mortality rate and factors for socioeconomic, development, and environmental health factors vary spatially in terms of direction, strength, and extent when considering: female literacy and labor force participation; share of scheduled castes and scheduled tribes; access to electricity; safe water and sanitation; road infrastructure; and medical facilities. This spatial heterogeneity is accompanied by significant changes over time in the roles that these factors play in under-five mortality. Important local determinants of under-five mortality in 2011 were female literacy, female labor force participation, access to sanitation facilities and electricity; while the key local determinants in 1991 were road infrastructure, safe water, and medical facilities. We identify six different clusters based on geographically weighted regression coefficients that broadly encompass the same districts in both periods; but these clusters do not follow the regional boundaries suggested by the previous studies. In particular, the high mortality states of India that are often typically classified as high focus states were classified into three different clusters based on the relationship of the factors associated with under-five mortality.

Conclusion

This study demonstrates the utility of combining geographically weighted regression and cluster analyses as a methodological approach to study local-level variation in public health indicators, and it could be applied in any country using aggregate-level information from census or survey data. Identifying local predictors of under-five mortality is important for designing interventions in specific districts. Additional reduction in under-five mortality will only be possible with intervention programs designed at the local level, which take into consideration local level determinants of under-five mortality.

Neonatal and under-five mortality rate in Indian districts with reference to Sustainable Development Goal 3: An analysis of the National Family Health Survey of India (NFHS), 2015-2016

Background and objective

India contributes the highest global share of deaths among the under-fives. Continuous monitoring of the reduction in the under-five mortality rate (U5MR) at local level is thus essential to set priorities for policy-makers and health professionals. In this study, we aimed to provide an update on district-level disparities in the neonatal mortality rate (NMR) and the U5MR with special reference to Sustainable Development Goal 3 (SDG3) on preventable deaths among new-borns and children under five.

Data and methods

We used recently released population-based cross-sectional data from the National Family Health Survey (NFHS) conducted in 2015–2016. We used the synthetic cohort probability approach to analyze the full birth history information of women aged 15–49 to estimate the NMR and U5MR for the ten years preceding the survey.

Results

Both the NMR and U5MR vary enormously across Indian districts. With respect to the SDG3 target for 2030 for the NMR and the U5MR, the estimated NMR for India for the period studied is about 2.4 times higher, while the estimated U5MR is about double. At district level, while 9% of the districts have already reached the NMR targeted in SDG3, nearly half (315 districts) are not likely to achieve the 2030 target even if they realize the NMR reductions achieved by their own states between the last two rounds of National Family Health Survey of India. Similarly, less than one-third of the districts (177) of India are unlikely to achieve the SDG3 target on the U5MR by 2030. While the majority of high-risk districts for the NMR and U5MR are located in the poorer states of north-central and eastern India, a few high-risk districts for NMR also fall in the rich and advanced states. About 97% of districts from Chhattisgarh and Uttar Pradesh, for example, are unlikely to meet the SDG3 target for preventable deaths among new-borns and children under age five, irrespective of gender.

Conclusions

To achieve the SDG3 target on preventable deaths by 2030, the majority of Indian districts clearly need to make a giant leap to reduce their NMR and U5MR.