Geographical variations of the associations between health interventions and all-cause under-five mortality in Uganda

  • BMC Public Health, Volume 19, No. 1, Year 2019

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Study Justification:
The study aims to assess the associations between health interventions and under-five mortality (U5M) in Uganda at both national and sub-national scales. This is important because national averages can hide regional disparities, and understanding these variations can guide control programs for targeted interventions. The study also aims to identify the interventions that have the greatest impact on reducing U5M at the sub-national level.
Highlights:
– The study found that interventions such as artemisinin-based combination therapy, initiation of breastfeeding within 1 hour of birth, intermittent preventive treatment, and access to insecticide-treated nets were associated with the highest reductions in U5M at the national level.
– The specific interventions associated with the largest reductions in U5M varied across different regions of Uganda. For example, in Central 2, Mid-Western, and South-West regions, access to insecticide-treated nets had the largest impact, while in Mid-North and West-Nile regions, improved source of drinking water was the key factor.
– Other interventions such as improved sanitation facilities, oral rehydration solution, and postnatal care were also found to have significant associations with U5M in specific regions.
Recommendations:
– The study recommends using sub-national estimates of the associations between health interventions and U5M to guide control programs for spatial targeting. This approach can help accelerate progress towards mortality-related Sustainable Development Goals.
– Policy makers should prioritize interventions that have been identified as having the greatest impact on reducing U5M in specific regions. This targeted approach can lead to more effective allocation of resources and better health outcomes.
Key Role Players:
– Ministry of Health: Responsible for implementing and coordinating health interventions at the national level.
– District Health Offices: Responsible for implementing and coordinating health interventions at the district level.
– Non-governmental Organizations (NGOs): Play a crucial role in implementing and supporting health interventions, especially at the community level.
– Community Health Workers: Provide frontline healthcare services and play a key role in delivering health interventions to the community.
Cost Items for Planning Recommendations:
– Training and capacity building for healthcare providers and community health workers.
– Procurement and distribution of health intervention supplies, such as insecticide-treated nets and oral rehydration solution.
– Monitoring and evaluation of the implementation and impact of health interventions.
– Health education and awareness campaigns to promote behavior change and uptake of interventions.
– Infrastructure development, such as improving access to clean water and sanitation facilities.
Please note that the cost items mentioned above are general categories and the actual costs will depend on the specific context and implementation strategies.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it is based on a study that utilized spatially explicit data and Bayesian geostatistical models to quantify associations between health interventions and under-five mortality at national and sub-national scales in Uganda. The study also employed Bayesian variable selection to identify the most important determinants of under-five mortality. However, to improve the evidence, the abstract could provide more information on the sample size, data collection methods, and statistical analysis techniques used in the study.

Background: To reduce the under-five mortality (U5M), fine-gained spatial assessment of the effects of health interventions is critical because national averages can obscure important sub-national disparities. In turn, sub-national estimates can guide control programmes for spatial targeting. The purpose of our study is to quantify associations of interventions with U5M rate at national and sub-national scales in Uganda and to identify interventions associated with the largest reductions in U5M rate at the sub-national scale. Methods: Spatially explicit data on U5M, interventions and sociodemographic indicators were obtained from the 2011 Uganda Demographic and Health Survey (DHS). Climatic data were extracted from remote sensing sources. Bayesian geostatistical Weibull proportional hazards models with spatially varying effects at sub-national scales were utilized to quantify associations between all-cause U5M and interventions at national and regional levels. Bayesian variable selection was employed to select the most important determinants of U5M. Results: At the national level, interventions associated with the highest reduction in U5M were artemisinin-based combination therapy (hazard rate ratio (HRR) = 0.60; 95% Bayesian credible interval (BCI): 0.11, 0.79), initiation of breastfeeding within 1 h of birth (HR = 0.70; 95% BCI: 0.51, 0.86), intermittent preventive treatment (IPTp) (HRR = 0.74; 95% BCI: 0.67, 0.97) and access to insecticide-treated nets (ITN) (HRR = 0.75; 95% BCI: 0.63, 0.84). In Central 2, Mid-Western and South-West, largest reduction in U5M was associated with access to ITNs. In Mid-North and West-Nile, improved source of drinking water explained most of the U5M reduction. In North-East, improved sanitation facilities were associated with the highest decline in U5M. In Kampala and Mid-Eastern, IPTp had the largest associated with U5M. In Central1 and East-Central, oral rehydration solution and postnatal care were associated with highest decreases in U5M respectively. Conclusion: Sub-national estimates of the associations between U5M and interventions can guide control programmes for spatial targeting and accelerate progress towards mortality-related Sustainable Development Goals.

Uganda is situated across the equator in East Africa. The country is bordered by the Democratic Republic of the Congo in the West, Kenya in the East, Rwanda in the South-West, Tanzania in the South and Sudan in the North. Uganda is a land-locked country with a surface area of 241,000 Km2. The country is divided into 15 regions, which are further partitioned into 116 districts. The population is approximately 44 million people; about half of the population are younger than 15 years, while children below the age of 5 account for approximately 20% [10]. All-cause child mortality data were obtained from women’s birth histories, available in the 2011 DHS, which was carried out between May and December, 2011. A representative sample of 10,086 households was selected for the 2011 DHS, using a stratified two-stage cluster design. In the first stage, 404 clusters were selected from a list of clusters for the 2009/2010 Uganda National Household Survey. The second stage involved selecting households from a complete listing of households in each cluster. Overall, 8674 women aged 15–49 years who were either permanent residents of the households or visitors who slept in the households the night before the survey were eligible to be interviewed on characteristics regarding their children. Mortality data were collected on 7878 children representing the number of children born in the period of 5 years preceding the date of the survey. The The DHS captures data relating to a number of health interventions, including malaria, micronutrients intake and treatments, the latter depending on whether drugs were taken in the previous night of the survey, 7 days, 2 weeks or 6 months prior to the survey. Such coverages may not reflect the extent of intervention utilization in the 5 years preceding the survey. Thus, to obtain representative estimates of intervention coverages for the period of 5 years preceding the 2011 DHS, we averaged health intervention coverages of the 2006 and 2011 DHS. The 2006 DHS collected data on malaria control interventions different from those in the 2011 DHS, that is, households with at least one insecticide-treated net (ITN), U5 sleeping under an ITN and indoor residual spraying (IRS). For consistency, interventions of the 2009 Uganda Malaria Indicator Survey (MIS) were utilized since they matched with those in the 2011 DHS. Health interventions considered in this paper comprise of malaria, WASH practices, reproductive health, breastfeeding, vaccinations, micronutrients supplementation and treatments of diseases. Coverage of health interventions was generated at the cluster level [7] because data on various interventions such as the vaccination status of dead children are not reported at an individual level in the DHS. Data at clusters were used to obtain intervention coverages at regions. Data on malaria interventions were collected by means of household questionnaires and included use and ownership of ITN and IRS. Standard guidelines of the Roll Back Malaria (RBM) were followed in the generation of malaria intervention coverage indicators [11]. The ITN use indicators derived in this analysis comprised the percentage of children U5 and the percentage of the population who slept under an ITN the night preceding the survey and the percentage of ITN used by the population in a household the previous night. The indicator on IRS coverage was generated as the percentage of households sprayed in the past 12 months. ITN ownership indicators included the percentage of households with at least one ITN, the percentage of households with one ITN for every two people and the percentage of the population with access to an ITN within their household. WASH interventions included the percentage of households with an improved source of drinking water, the percentage of households with improved sanitation facilities and the percentage of households with both water and soap/detergent at hand washing places. Data on the coverage of reproductive health, breastfeeding, vaccinations, micronutrients supplementation and treatment interventions were collected from all eligible women using a pretested questionnaire. The questionnaire comprised reproductive health interventions (the percentage of married women using any family planning method, percentage of pregnant mothers receiving antenatal care (ANC) from a skilled provider, the percentage of pregnant women making four or more ANC visits during their entire pregnancy, the percentage of women who received intermittent preventive treatment for malaria during pregnancy (IPTp), the percentage of births that took place with the assistance of a skilled provider and the percentage of newborns receiving first postnatal checkup from a skilled provider within 2 days after delivery, breastfeeding (the percentage of infants who started breastfeeding within 1 h of birth and the percentage of infants exclusively breastfed during the first 6 months after birth), vaccinations (the percentage of the last-born child fully protected against neonatal tetanus, the percentage of children vaccinated with BCG and measles, the percentage of children with complete vaccination of DPT and polio), micronutrients supplementation (the percentage of children receiving vitamin A supplements, the percentage of children receiving iron supplements in the past 7 days and the percentage of children living in households with iodized of salt) and treatments of diseases (the percentage of children with symptoms of acute respiratory infections (ARIs) who took antibiotics, the percentage of children with diarrhoea given fluid from oral rehydration solution (ORS) sachets or recommended home fluids (RHF), the percentage of children with diarrhoea given zinc sulphates, the percentage of children with fever during the 2 weeks prior to the survey and took ACT and those dewormed in the past 6 months). Interventions with coverage ≥95% and those lacking sufficient coverage (< 5%) within the regions were excluded from the analysis due to lack of variation in estimating their relation with mortality. These were the percentage of households sprayed with IRS in the past 12 months (%H_IRS, 7%), the percentage of pregnant mothers receiving ANC from a skilled provider (ANC provider, 95%), the percentage of children living in households with iodized salt (iodized salt; 99%) and the percentage of children with diarrhoea given zinc sulphates (zinc; 2%). Table 1 provides a list of health interventions assessed in the study. Health interventions, Uganda DHS 2006, 2009 and 2011 Environmental and climatic factors were obtained from remote sensing sources and aggregated at the cluster level. Temporal predictors such as land surface temperature (LST), rainfall and normalized difference vegetation index (NDVI) were averaged for the entire year of 2011. Land cover types were provided in 17 categories according to the International Global Biosphere Programme (IGBP) classification scheme and re-grouped into three categories, that is, urban, forest and crops. Distance to permanent water bodies was calculated based on the water category of the land cover data. Table 2 contains a list of environmental and climatic factors together with their spatio-temporal resolutions and data sources. Remote sensing data sourcesa na Not applicable; Land cover groups (forest, crops, urban); aLand cover data accessed in June 2011 and other data accessed in November 2013; bModerate Resolution Imaging Spectroradiometer (MODIS)/Terra, available at: http://modis.gsfc.nasa.gov/; lLand surface temperature (LST) day and night; mNormalized difference vegetation index Demographic and socioeconomic proxies, including maternal (education, literacy, residence, age at birth, early pregnancy termination, number of children born and working status) and child (sex, birth order, birth interval and mode of delivery) characteristics were incorporated in the analysis at an individual level and were captured using a household questionnaire. The household asset score was aggregated at the cluster level and considered in the analysis as a socioeconomic proxy for households’ socioeconomic status. A Bayesian geostatistical proportional hazards model assuming a baseline Weibull hazard function was fitted to quantify the associations between health interventions’ coverage and U5M, and to identify the most important interventions. The models were fitted to child-specific deaths and censoring times. Environmental, climatic, demographic and socioeconomic factors were included in the model as potential confounders. Spatial correlation between clusters was modelled by a Gaussian process with a covariance matrix measuring correlation between any pair of clusters by an exponential function of the distance between them. Our model assumed that the relation between health interventions and mortality varied across regions by including spatially varying coefficients to capture the interventions effect. Spatial dependence in the interventions’ effects was modelled by region-specific random effects assuming conditional autoregressive prior distributions. To identify the most important interventions and characteristics associated with the U5M, Bayesian geostatistical variable selection was used, adopting a stochastic search approach. The selection consisted of introducing a binary indicator parameter for each of socio-demographic, IRS and land cover variables with values defining the covariate-specific inclusion probability in the model. We assumed that the indicator arises from a Bernoulli prior distribution with probability defining the variable-specific inclusion probability in the model. We have chosen a spike and slab prior for the regression coefficients, which is a mixture of normals with mixing proportion equal to the inclusion probability. The spike component shrinks the regression coefficient to zero when the variable is excluded and the slab assumes a non-informative normal prior distribution when the variable has high inclusion probability (i.e., ≥ 50%). Environmental and climatic indicators (LST, NDVI, distance to permanent bodies and rainfall) were included or excluded in the model in a linear or categorical form. We introduced indicators with a multinomial prior distribution with three parameters corresponding to the probabilities of exclusion of a variable, inclusion in linear or categorical form. ITN coverage indicators were highly correlated with more than 85%. Hence, only one (or none) ITN indicator among those measuring ownership and one (or none) ITN indicator among those defining use was selected. The ITN indicator with the highest probability of inclusion in each category was included in the final model. Health intervention indicators were standardized and a separate model adjusting for possible confounders was fitted for each selected intervention. Maps were generated using ArcGIS version 10.5 (ESRI; Redlands, CA, USA). Descriptive data analysis was carried out in STATA version 14.0 (Stata Corporation; College Station, TX, USA). Bayesian variable selection and model fit were implemented in OpenBUGS 3.2.3 (Imperial College and Medical Research Council; London, UK). The effects of health interventions on U5M were summarized by posterior medians of their hazard rate ratios (HRR) and the corresponding 95% Bayesian credible intervals (BCI). An estimate is considered statistically significant if its 95% BCI excludes one. Details on the Bayesian geostatistical methods are provided in the Additional file 1.

The study titled “Geographical variations of the associations between health interventions and all-cause under-five mortality in Uganda” provides valuable insights into the associations between health interventions and under-five mortality rates at national and sub-national scales in Uganda. The study aims to guide control programs for spatial targeting and accelerate progress towards mortality-related Sustainable Development Goals.

Based on the findings of the study, several recommendations can be made to develop innovations that improve access to maternal health in Uganda:

1. Strengthening Artemisinin-Based Combination Therapy (ACT): Innovations can focus on improving the availability and accessibility of ACT for the treatment of malaria in pregnant women, as malaria during pregnancy can have adverse effects on maternal and child health.

2. Promoting Early Initiation of Breastfeeding: Innovations can focus on promoting breastfeeding education and support for mothers, ensuring that healthcare facilities have the necessary resources and infrastructure to support early initiation of breastfeeding.

3. Enhancing Access to Insecticide-Treated Nets (ITNs): Innovations can focus on improving the distribution and utilization of ITNs, particularly in regions where they have been identified as a key intervention.

4. Improving Water and Sanitation Facilities: Innovations can focus on improving access to clean water sources and sanitation facilities, particularly in areas with high mortality rates.

5. Strengthening Reproductive Health Services: Innovations can focus on improving the availability and quality of reproductive health services, ensuring that pregnant women have access to essential care and interventions.

6. Enhancing Postnatal Care: Innovations can focus on improving postnatal care services, including early identification and management of postpartum complications, as well as providing support and education to mothers on newborn care.

These recommendations can serve as a basis for developing innovative approaches to improve access to maternal health in Uganda. By targeting specific interventions and regions, these innovations can help reduce under-five mortality rates and contribute to the achievement of Sustainable Development Goals related to maternal and child health.
AI Innovations Description
The study titled “Geographical variations of the associations between health interventions and all-cause under-five mortality in Uganda” provides valuable insights into the associations between health interventions and under-five mortality rates at national and sub-national scales in Uganda. The study aims to guide control programs for spatial targeting and accelerate progress towards mortality-related Sustainable Development Goals.

Based on the findings of the study, several recommendations can be made to develop innovations that improve access to maternal health in Uganda:

1. Strengthening Artemisinin-Based Combination Therapy (ACT): The study found that ACT was associated with the highest reduction in under-five mortality at the national level. Innovations can focus on improving the availability and accessibility of ACT for the treatment of malaria in pregnant women, as malaria during pregnancy can have adverse effects on maternal and child health.

2. Promoting Early Initiation of Breastfeeding: The study identified early initiation of breastfeeding within 1 hour of birth as an intervention associated with a significant reduction in under-five mortality at the national level. Innovations can focus on promoting breastfeeding education and support for mothers, ensuring that healthcare facilities have the necessary resources and infrastructure to support early initiation of breastfeeding.

3. Enhancing Access to Insecticide-Treated Nets (ITNs): The study found that access to ITNs was associated with a significant reduction in under-five mortality in certain regions of Uganda. Innovations can focus on improving the distribution and utilization of ITNs, particularly in regions where they have been identified as a key intervention.

4. Improving Water and Sanitation Facilities: The study highlighted the importance of improved source of drinking water and improved sanitation facilities in reducing under-five mortality in specific regions. Innovations can focus on improving access to clean water sources and sanitation facilities, particularly in areas with high mortality rates.

5. Strengthening Reproductive Health Services: The study identified interventions such as antenatal care, intermittent preventive treatment for malaria during pregnancy (IPTp), and skilled assistance during childbirth as important factors associated with reduced under-five mortality in specific regions. Innovations can focus on improving the availability and quality of reproductive health services, ensuring that pregnant women have access to essential care and interventions.

6. Enhancing Postnatal Care: The study found that postnatal care was associated with a significant decrease in under-five mortality in certain regions. Innovations can focus on improving postnatal care services, including early identification and management of postpartum complications, as well as providing support and education to mothers on newborn care.

Overall, these recommendations can serve as a basis for developing innovative approaches to improve access to maternal health in Uganda. By targeting specific interventions and regions, these innovations can help reduce under-five mortality rates and contribute to the achievement of Sustainable Development Goals related to maternal and child health.
AI Innovations Methodology
To simulate the impact of the main recommendations on improving access to maternal health in Uganda, the following methodology can be used:

1. Data Collection: Collect data on the current status of maternal health interventions and under-five mortality rates in Uganda. This can be done through surveys, interviews, and existing data sources such as the Uganda Demographic and Health Survey (DHS).

2. Identify Target Regions: Based on the findings of the study, identify the regions in Uganda where the recommended interventions are most needed and likely to have the greatest impact on reducing under-five mortality rates.

3. Develop Baseline Indicators: Calculate baseline indicators for each recommended intervention in the target regions. This includes indicators such as the availability and accessibility of Artemisinin-Based Combination Therapy (ACT), early initiation of breastfeeding rates, access to Insecticide-Treated Nets (ITNs), water and sanitation facilities, and the availability and quality of reproductive health services and postnatal care.

4. Set Targets: Set specific targets for each intervention based on the desired improvements in access to maternal health. For example, the target could be to increase the availability of ACT in target regions by a certain percentage, or to improve early initiation of breastfeeding rates to a specific level.

5. Develop Intervention Strategies: Based on the recommendations from the study, develop intervention strategies to improve access to maternal health in the target regions. These strategies should be tailored to address the specific challenges and needs of each region.

6. Implement Interventions: Implement the intervention strategies in the target regions. This may involve working with local healthcare providers, community organizations, and government agencies to improve the availability and accessibility of ACT, promote breastfeeding education and support, distribute and promote the use of ITNs, improve water and sanitation facilities, strengthen reproductive health services, and enhance postnatal care.

7. Monitor and Evaluate: Continuously monitor and evaluate the implementation of the interventions and their impact on improving access to maternal health. This can be done through regular data collection, surveys, and monitoring and evaluation activities. Adjust the intervention strategies as needed based on the findings.

8. Measure Impact: Measure the impact of the interventions on improving access to maternal health by comparing the baseline indicators with the indicators after the interventions have been implemented. Calculate the changes in indicators and assess the overall impact on under-five mortality rates.

9. Disseminate Findings: Share the findings of the impact assessment with relevant stakeholders, including policymakers, healthcare providers, and community organizations. Use the findings to advocate for continued support and investment in improving access to maternal health in Uganda.

By following this methodology, it is possible to simulate the impact of the main recommendations from the study on improving access to maternal health in Uganda and assess their effectiveness in reducing under-five mortality rates.

Statistics:
Citations: 4
Authors: 6
Identifiers:
DOI: 10.1186/s12889-019-7636-x
Research Areas:
Community Interventions, Disparities, Environmental, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants
Study Countries:
Congo, Kenya, Multi-Countries, Rwanda, Sudan, Tanzania, Uganda
Study Design:
Cross Sectional Study, randomised-control-trial
Study Approach:
Quantitative
Participants Gender:
Female
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