Approximation of the Cox survival regression model by MCMC Bayesian Hierarchical Poisson modelling of factors associated with childhood mortality in Nigeria

  • Scientific Reports, Volume 11, No. 1, Year 2021

listen audio

Study Justification:
– The study was conducted to address the need for more pragmatic approaches to achieve sustainable development goals on childhood mortality reduction.
– The study aimed to examine the influence of where children live and the censoring nature of children survival data, which is a scarce area of research.
Study Highlights:
– The study used data from the 2018 Nigeria Demographic and Health Survey (NDHS) and included a total sample of 33,924 under-five children.
– The study employed MCMC Bayesian hierarchical Poisson regression models as approximations of the Cox survival regression model.
– The study identified compositional and contextual factors associated with under-five and infant mortality in Nigeria.
– The study found that factors such as maternal education, multiple births, low birthweight, short birth interval, household poverty, healthcare access, community illiteracy level, and rural population proportion were associated with higher risks of infant and under-five mortality.
– The study revealed that state-level and neighborhood-level factors explained a significant portion of the variation in infant and under-five mortality rates.
Recommendations for Lay Reader and Policy Maker:
– The study highlights the importance of addressing compositional and contextual factors in reducing childhood mortality in Nigeria.
– Policy makers should focus on improving maternal education, reducing poverty, promoting access to healthcare, and addressing community illiteracy levels to reduce infant and under-five mortality rates.
– The study emphasizes the need for targeted interventions in states and neighborhoods with higher mortality rates.
– The findings of the study can guide policy makers in developing evidence-based strategies to achieve sustainable development goals related to childhood mortality reduction.
Key Role Players:
– Researchers and statisticians for data analysis and modeling.
– Public health experts and policymakers for interpreting and implementing the study findings.
– Government agencies and non-governmental organizations for implementing interventions and programs based on the study recommendations.
– Community leaders and healthcare providers for community-level engagement and implementation of interventions.
Cost Items for Planning Recommendations:
– Funding for research and data analysis.
– Budget for implementing interventions and programs targeting maternal education, poverty reduction, healthcare access, and community literacy improvement.
– Resources for monitoring and evaluation of interventions.
– Budget for capacity building and training of healthcare providers and community leaders.
– Allocation of resources for data collection and surveillance to monitor progress in reducing childhood mortality rates.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a study that used secondary data from a nationally representative survey. The study used a multistage, stratified sampling design and collected information on a large sample size of under-five children. The study also implemented appropriate statistical techniques for analysis. However, the abstract does not provide information on potential limitations or biases in the data collection or analysis. To improve the evidence, the abstract could include a discussion of the limitations of the secondary data, such as potential biases in sampling or measurement errors. Additionally, the abstract could provide more details on the statistical methods used and any assumptions made in the analysis.

The need for more pragmatic approaches to achieve sustainable development goal on childhood mortality reduction necessitated this study. Simultaneous study of the influence of where the children live and the censoring nature of children survival data is scarce. We identified the compositional and contextual factors associated with under-five (U5M) and infant (INM) mortality in Nigeria from 5 MCMC Bayesian hierarchical Poisson regression models as approximations of the Cox survival regression model. The 2018 DHS data of 33,924 under-five children were used. Life table techniques and the Mlwin 3.05 module for the analysis of hierarchical data were implemented in Stata Version 16. The overall INM rate (INMR) was 70 per 1000 livebirths compared with U5M rate (U5MR) of 131 per 1000 livebirth. The INMR was lowest in Ogun (17 per 1000 live births) and highest in Kaduna (106), Gombe (112) and Kebbi (116) while the lowest U5MR was found in Ogun (29) and highest in Jigawa (212) and Kebbi (248). The risks of INM and U5M were highest among children with none/low maternal education, multiple births, low birthweight, short birth interval, poorer households, when spouses decide on healthcare access, having a big problem getting to a healthcare facility, high community illiteracy level, and from states with a high proportion of the rural population in the fully adjusted model. Compared with the null model, 81% vs 13% and 59% vs 35% of the total variation in INM and U5M were explained by the state- and neighbourhood-level factors respectively. Infant- and under-five mortality in Nigeria is influenced by compositional and contextual factors. The Bayesian hierarchical Poisson regression model used in estimating the factors associated with childhood deaths in Nigeria fitted the survival data.

This study used secondary data from 2018 NDHS, which is cross-sectional in design and nationally representative14. The DHS uses a multistage, stratified sampling design (state, clusters, and households) with the clusters (neighbourhoods) as the primary sampling unit. Eligible mothers living in households were interviewed. Sampling weights were generated to account for unequal selection probabilities as well as for non-response because the surveys were not self-weighting. With weights applied, survey findings represent the target populations. Information on households, sexual and reproductive health was collected from women aged 15–49 years within the selected households. Moreover, the DHS collects the birth history of all women interviewed. We, therefore, used the “child recode data” which contains all follow-up information on all children born to the interviewed women within five years preceding the survey. Information on a total sample of 33,924 under-five children was included in the analysis. The setting is Nigeria which comprises 36 states and the Federal capital territory (FCT), Abuja. The states are distributed across six geopolitical regions; North-East (NE), North-West (NW), North-Central (NC), South-East (SE), South-South (SS), and South-West (SW). The states are hereafter referred to as 36 + 1 states. The population characteristics in each of the geopolitical regions and states are relatively homogeneous and they share similar socio-cultural characteristics. Also, health-related characteristics such as access to healthcare, environment, housing characteristics are similar within the regions and states. Publicly available data from the DHS was used for the analysis. Before each interview, informed consents were obtained from the participants to participate in the survey. DHS survey protocol has consistent procedures with the standards for ensuring the protection of respondents’ confidentiality and privacy. While no further approval was required for us, we obtained permission to use the data from the data owners (ICF Macro, US). Originally, ethical approval for the survey was sought from ICF institutional review board. The data is available at dhsprogram.com. Written and signed informed consent was obtained from each parent and/or legal guardians of the children who participated in the study were told that the interviews have minimal risks and potential benefits and that information will be collected anonymously and held confidentially. The full details can be found at http://dhsprogram.com. All methods for data collection and data analysis were carried out following relevant guidelines and regulations on the protection of participants’ data.

Based on the provided information, it seems that the study focused on analyzing factors associated with childhood mortality in Nigeria using Bayesian hierarchical Poisson regression models. The study utilized secondary data from the 2018 Nigerian Demographic and Health Survey (NDHS), which is a nationally representative cross-sectional survey.

In terms of potential innovations to improve access to maternal health based on this study, here are some recommendations:

1. Strengthening Maternal Education: The study found that children with none or low maternal education had higher risks of infant and under-five mortality. Implementing innovative programs and interventions to improve maternal education can contribute to better maternal health outcomes and reduce childhood mortality.

2. Enhancing Birthweight and Birth Interval: The study identified low birthweight and short birth intervals as risk factors for infant and under-five mortality. Innovations that focus on improving prenatal care, nutrition, and family planning services can help address these risk factors and improve maternal and child health.

3. Addressing Healthcare Access Challenges: The study highlighted the importance of healthcare access in reducing childhood mortality. Innovative approaches such as mobile health clinics, telemedicine, and community health workers can help overcome barriers to accessing healthcare, especially in remote or underserved areas.

4. Targeting Poorer Households: The study found that children from poorer households had higher risks of infant and under-five mortality. Innovative strategies that address socioeconomic inequalities, such as conditional cash transfer programs or microfinance initiatives, can help improve access to healthcare and reduce maternal and child mortality.

5. Promoting Community Literacy and Health Education: The study indicated that high community illiteracy levels were associated with increased risks of infant and under-five mortality. Innovative interventions that focus on improving community literacy and health education can empower individuals and communities to make informed decisions about maternal and child health.

It’s important to note that these recommendations are based on the information provided and should be further explored and tailored to the specific context and needs of Nigeria’s maternal health system.
AI Innovations Description
The study you described focuses on identifying factors associated with childhood mortality in Nigeria and used data from the 2018 Nigeria Demographic and Health Survey (NDHS). The study employed a Bayesian hierarchical Poisson regression model to approximate the Cox survival regression model. The findings of the study revealed several compositional and contextual factors that are associated with infant and under-five mortality in Nigeria.

To improve access to maternal health, based on the findings of this study, the following recommendations can be considered:

1. Enhance maternal education: The study found that children with none or low maternal education had higher risks of infant and under-five mortality. Therefore, investing in education programs for women, particularly in areas with low literacy rates, can help improve maternal health outcomes.

2. Improve healthcare access: The study identified that children from households with difficulties in accessing healthcare facilities had higher mortality risks. Efforts should be made to improve the availability and accessibility of healthcare services, especially in rural areas, by establishing more healthcare facilities and ensuring transportation infrastructure.

3. Address birth-related factors: The study highlighted that multiple births, low birthweight, and short birth intervals were associated with increased mortality risks. Implementing interventions to promote healthy pregnancies, such as prenatal care, nutrition programs, and family planning services, can help reduce these risks.

4. Reduce poverty and improve living conditions: The study found that children from poorer households had higher mortality risks. Addressing poverty and improving living conditions can positively impact maternal health outcomes. This can be achieved through social welfare programs, economic empowerment initiatives, and poverty reduction strategies.

5. Strengthen community health education: The study indicated that high community illiteracy levels were associated with increased mortality risks. Implementing community-based health education programs can help raise awareness about maternal health, promote healthy behaviors, and empower communities to take proactive measures to improve maternal and child health.

It is important to note that these recommendations are based on the findings of the study you described. Implementing these recommendations would require collaboration among various stakeholders, including government agencies, healthcare providers, non-governmental organizations, and communities.
AI Innovations Methodology
Based on the provided description, it seems that the study focuses on identifying factors associated with childhood mortality in Nigeria and approximating the Cox survival regression model using MCMC Bayesian Hierarchical Poisson modeling. The study utilized secondary data from the 2018 Nigeria Demographic and Health Survey (NDHS), which is a nationally representative cross-sectional survey.

To improve access to maternal health based on the findings of this study, the following innovations and recommendations can be considered:

1. Strengthening maternal education: The study found that children with none or low maternal education had higher risks of infant and under-five mortality. Implementing programs that promote and support maternal education can improve maternal health knowledge and practices, leading to better health outcomes for both mothers and children.

2. Enhancing healthcare access: The study identified factors such as spouses deciding on healthcare access and difficulties in reaching healthcare facilities as contributors to higher mortality risks. Innovations that improve access to healthcare, such as mobile health clinics, telemedicine, or community health worker programs, can help overcome geographical barriers and ensure timely access to maternal healthcare services.

3. Addressing socio-economic disparities: The study revealed that children from poorer households had higher mortality risks. Implementing interventions that address socio-economic disparities, such as income support programs, targeted healthcare subsidies, or livelihood improvement initiatives, can help alleviate financial barriers to accessing maternal healthcare.

4. Promoting birth spacing and family planning: The study found that short birth intervals were associated with increased mortality risks. Encouraging the use of family planning methods and promoting birth spacing can help reduce the risks associated with closely spaced pregnancies and improve maternal and child health outcomes.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could involve the following steps:

1. Define the indicators: Identify specific indicators that reflect access to maternal health, such as the proportion of pregnant women receiving antenatal care, the proportion of births attended by skilled health personnel, or the maternal mortality ratio.

2. Collect baseline data: Gather data on the selected indicators before implementing the recommendations. This can be done through surveys, health facility records, or existing data sources.

3. Implement the recommendations: Introduce the recommended innovations and interventions aimed at improving access to maternal health. This could involve implementing educational programs, establishing new healthcare facilities or services, or implementing policies to address socio-economic disparities.

4. Monitor and collect data: Continuously monitor the implementation of the recommendations and collect data on the selected indicators. This can be done through routine data collection systems, surveys, or targeted evaluations.

5. Analyze the data: Analyze the collected data to assess the impact of the recommendations on the selected indicators. This can involve comparing the baseline data with the post-intervention data and conducting statistical analyses to determine any significant changes.

6. Evaluate the impact: Evaluate the impact of the recommendations on improving access to maternal health by assessing changes in the selected indicators. This evaluation can help identify the effectiveness of the implemented innovations and inform future decision-making.

By following this methodology, policymakers and stakeholders can assess the potential impact of the recommended innovations on improving access to maternal health and make informed decisions regarding their implementation.

Statistics:
Authors: 4
Identifiers:
DOI: 10.1038/s41598-021-92606-0
Research Areas:
Community Interventions, Disparities, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants
Study Countries:
Nigeria
Study Design:
Cohort Study, Cross Sectional Study, Grounded Theory
Study Approach:
Quantitative
Participants Gender:
Female
Partagez ceci :
Facebook
Twitter
LinkedIn
WhatsApp
Email