scholarly journals Child Mortality Estimation: Consistency of Under-Five Mortality Rate Estimates Using Full Birth Histories and Summary Birth Histories

PLoS Medicine ◽  
2012 ◽  
Vol 9 (8) ◽  
pp. e1001296 ◽  
Author(s):  
Romesh Silva
Keyword(s):  
Mortality Rate ◽  
Child Mortality ◽  
Under Five ◽  
Mortality Estimation

scholarly journals Logistic Regression Additive Model: Application to Tanzania Demographic and Health Survey Data

2017 ◽  
Vol 10 (1) ◽  
pp. 294-302 ◽  
Author(s):  
W.J. Dlamini ◽  
S.F. Melesse ◽  
H.G. Mwambi
Keyword(s):  
Mortality Rate ◽  
Survey Data ◽  
Child Mortality ◽  
Additive Model ◽  
Well Being ◽  
Additive Models ◽  
Cluster Sampling ◽  
African Region ◽  
Under Five ◽  
Number Of Children

Background:The well-being of a child reflects household, community and national involvement on family health. Currently, the global under-five child mortality rate is falling faster compared to any time in the past two decades. However, the progress remained insufficient to match the Millennium Development Goal 4 targets especially in the Sub-Saharan African region.Objective:This study aims to visualize and identify factors associated with under-five child mortality in Tanzania, which is essential for formulating appropriate health program and policies.Methods:The survey data used for this paper was taken from 2011-2012 Tanzania HIV/AIDS and Malaria Indictor Survey. The study utilizes statistical model that accommodate a response, which is dichotomous and account for non-linear relationship between binary response and independent variable. Generalized additive models was adopted for the analysis. The sample was selected using stratified, two-stage cluster sampling that gave a sample size of 10494 mothers. The model was fitted using proc gam in statistical analysis software version 9.3.Results:The results showed that human immunodeficiency virus status of the mother and breastfeeding were associated with under-five child mortality. Furthermore, the results also indicated that under-five child mortality had a quadratic pattern relationship with the number of children ever born, the number of children alive, the number of children five or under in a household and child birth order number.Conclusion:Based on the study, our findings confirmed that under-five mortality is a serious problem in the Tanzania. Therefore, there is a need to intensify child health interventions to reduce the under-five mortality rate even further with the development of policies and programs to reduce under-five child mortality.

scholarly journals Predictive analytics framework for accurate estimation of child mortality rates for Internet of Things enabled smart healthcare systems

2020 ◽  
Vol 16 (5) ◽  
pp. 155014772092889 ◽  
Author(s):  
Muhammad Islam ◽  
Muhammad Usman ◽  
Azhar Mahmood ◽  
Aaqif Afzaal Abbasi ◽  
Oh-Young Song
Keyword(s):  
Mortality Rate ◽  
Child Mortality ◽  
Death Rate ◽  
Predictive Analytics ◽  
Healthcare Systems ◽  
Data Sets ◽  
Demographic Health Survey ◽  
Live Births ◽  
Under Five ◽  
Smart Healthcare

Globally, under-five child mortality is a substantial health problem. In developing countries, reducing child mortality and improving child health are the key priorities in health sectors. Despite the significant reduction in deaths of under-five children globally, developing countries are still struggling to maintain an acceptable mortality rate. Globally, the death rate of under-five children is 41 per 1000 live births. However, the death rate of children in developing nations like Pakistan and Ethiopia per 1000 live births is 74 and 54, respectively. Such nations find it very challenging to decrease the mortality rate. Data analytics on healthcare data plays a pivotal role in identifying the trends and highlighting the key factors behind the children deaths. Similarly, predictive analytics with the help of Internet of Things based frameworks significantly advances the smart healthcare systems to forecast death trends for timely intervention. Moreover, it helps in capturing hidden associations between health-related variables and key death factors among children. In this study, a predictive analytics framework has been developed to predict the death rates with high accuracy and to find the significant determinants that cause high child mortality. Our framework uses an automated method of information gain to rank the information-rich mortality variables for accurate predictions. Ethiopian Demographic Health Survey and Pakistan Demographic Health Survey data sets have been used for the validation of our proposed framework. These real-world data sets have been tested using machine learning classifiers, such as Naïve Bayes, decision tree, rule induction, random forest, and multi-layer perceptron, for the prediction task. It has been revealed through our experimentation that Naïve Bayes classifier predicts the child mortality rate with the highest average accuracy of 96.4% and decision tree helps in identifying key classification rules covering the factors behind children deaths.

scholarly journals Determinants of Under-five Child Mortality: Evidence from Bangladesh Multiple Indicator Cluster Survey (MICS) 2019

2021 ◽  
Author(s):  
Md. Momin Islam ◽  
Farha Musharrat Noor ◽  
Md. Rokibul Hasan ◽  
Mohammad Ahsan Udddin
Keyword(s):  
Risk Factors ◽  
Mortality Rate ◽  
Child Mortality ◽  
Proportional Hazard ◽  
Under Five ◽  
Cluster Survey ◽  
Cox Proportional Hazard ◽  
Multiple Indicator Cluster Survey ◽  
Multiple Indicator ◽  
Child Mortality Rate

Abstract Background: Every year millions of under-five children die due to different causes and some of those death could be prevented by proper awareness or taking steps. Though under-five child mortality rate has reduced by a remarkable rate for last decade in Bangladesh, the rate is still high to reach the expected level of Sustainable Development Goals (SDGs). Methods: The main aim of this study was to find out the socioeconomic and demographic determinants of under-five child mortality in Bangladesh. Nationally representative cross-sectional secondary data from the Multiple Indicator Cluster Survey (MICS) 2019, Bangladesh had been used in this study. Outcome variable was under-five child survival status (alive or dead). Kaplan–Meier log-rank test and Cox Proportional Hazard (PH) model with 95% confidence interval (CI) were fitted to identify associated risk factors for under-five child mortality. This analysis was performed by using STATA version 16.Results: The study showed that among 5112 under-five children, 170 (3.3%) were dead. Cox proportional hazard model revealed that mother’s education [secondary (HR: 0.53, 95%CI: (0.30, 0.94), p=0.03), higher (HR: 0.41, 95% CI: (0.21, 0.81), p=0.01)], higher birth order [HR: 1.43, 95% CI: (1.13, 1.89), p=0.007], size of child at birth [HR: 2.28, 95% CI: (1.22, 4.26), p=0.009], taking antenatal care [HR: 0.77, 95% CI: (0.52, 1.15), p= 0.091] had a significant effect on child mortality. Under-five child mortality rate was varied among division and highest mortality rate was found in Sylhet [HR: 2.13, 95% CI: (0.99, 4.55), p=0.054]. Conclusions: This study identified potential risk factors for under-five child mortality, which would help the policy makers to take proper steps as community-based educational programs for mother’s and public health interventions focused on birth to reduce under-five child mortality rate in Bangladesh.

scholarly journals Newborns and Under-5 Mortality in Ethiopia: The Necessity to Revitalize Partnership in Post-COVID-19 Era to Meet the SDG Targets

2021 ◽  
Vol 12 ◽  
pp. 215013272199688
Author(s):  
Yonas Getaye Tefera ◽  
Asnakew Achaw Ayele
Keyword(s):  
Child Mortality ◽  
Millennium Development Goals ◽  
Sustainable Development Goals ◽  
National Plan ◽  
Health Targets ◽  
The Sustainable Development ◽  
Live Births ◽  
Mortality Estimation ◽  
Development Goals ◽  
Children Under 5

The Sustainable Development Goals (SDGs) were adopted during the United Nations meeting in 2015 to succeed Millennium Development Goals. Among the health targets, SDG 3.2 is to end preventable deaths of newborns and children under 5 years of age by 2030. These 2 targets aim to reduce neonatal mortality to at least as low as 12 per 1000 live births and under-5 mortality to at least as low as 25 per 1000 live births. Ethiopia is demonstrating a great reduction in child mortality since 2000. In the 2019 child mortality estimation which is nearly 5 years after SDGs adoption, Ethiopia’s progress toward reducing the newborns and under-5 mortality lie at 27 and 50.7 per 1000 live births, respectively. The generous financial and technical support from the global partners have helped to achieve such a significant reduction. Nevertheless, the SDG targets for newborns and under-5 mortality reduction are neither attained yet nor met the national plan to achieve by the end of 2019/2020. The partnership dynamics during COVID-19 crisis and the pandemic itself may also be taken as an opportunity to draw lessons and spur efforts to achieve SDG targets. This urges the need to reaffirm a comprehensive partnership and realignment with other interconnected development goals. Therefore, collective efforts with strong partnerships are required to improve the determinants of child health and achieving SDG target reduction until 2030.

scholarly journals Association between household air pollution and child mortality in Myanmar using a multilevel mixed-effects Poisson regression with robust variance

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Juwel Rana ◽  
Rakibul M. Islam ◽  
Md Nuruzzaman Khan ◽  
Razia Aliani ◽  
Youssef Oulhote
Keyword(s):  
Air Pollution ◽  
Child Mortality ◽  
Survey Design ◽  
Household Air Pollution ◽  
P Value ◽  
Middle Income ◽  
Under Five ◽  
Middle Income Countries ◽  
Relative Risks ◽  
Clean Cookstoves

AbstractHousehold air pollution (HAP) from solid fuel use (SFU) for cooking is a major public health threat for women and children in low and middle-income countries. This study investigated the associations between HAP and neonatal, infant, and under-five child mortality in Myanmar. The study consisted of 3249 sample of under-five children in the households from the first Myanmar Demographic and Health Survey 2016. Fuel types and levels of exposure to SFU (no, moderate and high) were proxies for HAP. We estimated covariate-adjusted relative risks (aRR) of neonatal, infant, and under-five child mortality with 95% confidence intervals, accounting for the survey design. The prevalence of SFU was 79.0%. The neonatal, infant, and under-five child mortality rates were 26, 45, and 49 per 1000 live births, respectively. The risks of infant (aRR 2.02; 95% CI 1.01–4.05; p-value = 0.048) and under-five mortality (aRR 2.16; 95% CI 1.07–4.36; p-value = 0.031), but not neonatal mortality, were higher among children from households with SFU compared to children from households using clean fuel. Likewise, children highly exposed to HAP had higher risks of mortality than unexposed children. HAP increases the risks of infant and under-five child mortality in Myanmar, which could be reduced by increasing access to clean cookstoves and fuels.

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