Resampled Cox Proportional Hazards Models for Infant Mortality at the Kigali University Teaching Hospital (original) (raw)
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Cox Proportional Hazards Models for Infant Mortality at the Kigali University Teaching Hospital
2019
Statistical analysis supports two major findings: 1) parents under 20 years of age indicate a relatively higher risk of infant death, and 2) abnormality in the newborn's head and weight indicates a relatively higher risk of infant mortality. Recommendations include avoidance of pregnancy until after age 20 and clinically recommended nutrition for the mother during pregnancy to decrease the risk of infant mortality.
BMC Pediatrics, 2020
Background The Infant Mortality Rate (IMR) in Sub-Saharan Africa (SSA) remains the highest relatively to the rest of the world. In the past decade, the policy on reducing infant mortality in SSA was reinforced and both infant mortality and parental death decreased critically for some countries of SSA. The analysis of risk to death or attracting chronic disease may be done for helping medical practitioners and decision makers and for better preventing the infant mortality. Methods This study uses popular statistical methods of re-sampling and one selected model of multiple events analysis for measuring the survival outcomes for the infants born in 2016 at Kigali University Teaching Hospital (KUTH) in Rwanda, a country of SSA, amidst maternal and child’s socio-economic and clinical covariates. Dataset comprises the newborns with correct information on the covariates of interest. The Bootstrap Marginal Risk Set Model (BMRSM) and Jackknife Marginal Risk Set Model (JMRSM) for the availab...
International journal of MCH and AIDS, 2017
The Newborn Survival Case study in Rwanda provides an analysis of the newborn health and survival situation in the country. It reviews evidence-based interventions and coverage levels already implemented in the country; identifies key issues and bottlenecks in service delivery and uptake of services by community/beneficiaries, and provides key recommendations aimed at faster reduction in newborn mortality rate. This study utilized mixed method research including qualitative and quantitative analyses of various maternal and newborn health programs implemented in the country. This included interviewing key stakeholders at each level, field visits and also interviewing beneficiaries for assessment of uptake of services. Monitoring systems such as Health Management Information Systems (HMIS), maternal and newborn death audits were reviewed and data analyzed to aid these analyses. Policies, protocols, various guidelines and tools for monitoring are already in place however, implementatio...
2013
This further analysis examines levels trends and determinants of neonatal mortality in Rwanda using data from the 2000 2005 and 2010 Rwanda Demographic and Health Surveys (RDHS). The analysis begins with estimates of the neonatal mortality rate (NMR) overall and within each category of selected potential predictors of neonatal death in the five years preceding each survey. Multivariate log probability models are then used to determine whether key indicators are independently associated with neonatal mortality in Rwanda after adjusting for socio-demographic factors that could confound the association. Finally multivariate decomposition procedures are used to determine the extent to which each selected indicator contributes to the observed reduction in neonatal mortality. Between 2000 and 2010 a dramatic decline in under-five mortality in Rwanda was accompanied by a more modest reduction in the NMR. The improvement in the NMR was largely concentrated in rural areas where coverage of m...
A 12 Years Neonatal Mortality Rate and Its Predictors in Eastern Ethiopia
Global Pediatric Health, 2021
Introduction. Surviving and thriving of newborn is essential to ending extreme poverty. However, the surviving and thriving of new born is depends on where neonates are born. The true feature of neonatal mortality rate and trends is not well known in the study area. Thus, we aimed to estimate a neonatal mortality incidence in each year, and determine factors associated though pregnancy observation cohort study in Eastern Ethiopia. Methods. The study was conducted in Kersa Health Demographic Surveillance System (KHDSS) among 36 kebeles. We extracted all events (38 541 live birth and 776 neonatal death) occurred between January 1, 2008 and December 30, 2019. Neonatal mortality rate was presented by neonatal death per 1000 live birth with 95% confidence interval in each years, and trends of neonatal morality was described with line regression. Cox proportional regression model was used to assess predictors and presented with an adjusted hazard ratio (AHR) and 95% CI. Results. The estim...
1998
The levels of infant and child mortality in Indonesia have declined considerably since the 1960s, although the decline has not been as rapid as observed in some neighbouring countries. In the last decade, information for estimating infant and child mortality in Indonesia was very limited and as a consequence only indirect estimation techniques were employed. These techniques, however, were inadequate for analysing the effects of the social determinants of infant and child mortality. The reliability and validity of Indonesian data are not good, particularly the quality of age reporting of deceased children. To estimate infant and child mortality using survey data, methods which utilise reports of all recent births are more ‘efficient’ than methods using only a portion of these. Cox regression, which utilises the life table concept, maximises the inclusion of cases in the analysis, and thus is preferred as a means of efficiently exploiting survey data to offset weaknesses of misreport...
Family Medicine & Primary Care Review , 2022
Background. Infant mortality is a salient indicator for appraising the quality of the healthcare infrastructures of a country. To achieve the sustainable development goal, the infant mortality rate should be reduced to the indicated level. On account of this, it is requisite to point out the associated factors of infant mortality and provide action plans for monitoring them. Objectives. This study aimed to discover the prevalence of infant mortality and assess how different factors influence infant mortality in 24 developing countries by utilising the latest Demographic and Health Survey (DHS) data. Material and methods. This study used a mixed-method design to assemble cross-sectional studies to integrate data from 24 other countries due to the widening perspective of infant mortality. Descriptive analysis, binary logistic regression model, random-effect meta-analysis and forest plot have been used for the analyses. Results. The binary logistic regression model for Bangladesh revealed that a higher education level of fathers (OR: 0.344, 95% CI: 0.147; 0.807), being 2 nd born or above order infant (OR: 0.362, 95% CI: 0.248; 0.527), undergoing antenatal care (ANC) (OR: 0.271, 95% CI: 0.192; 0.382 for 1-4 visits) and undergoing postnatal care (PNC) (OR: 0.303, 95% CI: 0.216; 0.425) were statistically significant determinants of lowering infant death. While carrying multiple foetuses (OR: 6.634, 95% CI: 3.247; 13.555) was shown to be a risk factor of infant mortality. The most significant factors influencing infant mortality for developing countries were the number of foetuses (OR: 0.193, 95% CI: 0.176; 0.213), undergoing ANC (OR: 0.356, 95% CI: 0.311; 0.407), undergoing PNC (OR: 0.302, 95% CI: 0.243; 0.375) and the size of the children (OR: 0.653, 95% CI: 0.588; 0.726). Conclusions. In this study, the number of the foetuses, undergoing ANC and PNC, mother's education, fathers' education and size of the children were the most significant factors affecting infant mortality in developing countries. Thusly, anticipation and control projects need to be taken considering the outcome of this study to reduce the infant mortality.
Obstetrics and Gynecology International
Background. Uganda is one of the countries in the Sub-Saharan Africa with a very high maternal mortality ratio estimated at 336 deaths per 100,000 live births. We aimed at exploring the main factors affecting maternal death and designing a predictive model for estimation of the risk of dying at admission at a major referral hospital in northern Uganda. Methods. This was a retrospective matched case-control study, carried out at Lacor Hospital in northern Uganda, including 130 cases and 336 controls, from January 2015 to December 2019. Multivariate logistic regression was used to estimate the net effect of the associated factors. A cumulative risk score for each woman based on the unstandardised canonical coefficients was obtained by the discriminant equation. Results. The average maternal mortality ratio was 328 per 100,000 live births. Direct obstetric causes contributed to 73.8% of maternal deaths; the most common were haemorrhage (42.7%), sepsis (24.0%), hypertensive disorders (1...
Determination of Infant and Child Mortality in Kenya Using Cox-Proportional Hazard Model
American Journal of Theoretical and Applied Statistics, 2015
One of the Millennium Development Goals is the reduction of infant and child mortality by two-thirds by year 2015. To achieve this goal, efforts need be concentrated at identifying cost-effective strategies as many international agencies have advocated for more resources to be directed to health sector. One way of doing this is to identify the important factors that affect infant and child mortality. This study is necessary because, Infant and child mortality is one of the most important sensitive indicators of the social economic and health status of a community. This is because more than any other age group of a population, infants and children survival depends on the socioeconomic condition of their environment. This study addresses factors affecting infant and child mortality in Kenya. The main objective of the paper is to determine the effect of socioeconomic and demographic variables on infant and child mortality. Childhood mortality from the, KDHS 2008-09 data, was analyzed in two age periods: mortality from birth to the age of 12 months, referred to as "infant mortality" and mortality from the age of 12 months to the age of 60 months, referred to as "child mortality". Data from Kenya Demographic and Health Survey (KDHS 2008-09) was collected by use of questionnaires, after carrying out a two-stage cluster sampling design. The Cox regression survival analysis was used to compute relative risk of the socioeconomic and demographic variables, on infant and child mortality. The study revealed that the socioeconomic and demographic factors affect both infant and child mortality. The relative risks were higher for infant's mortality as compared to child's mortality. The place of birth has the greatest impact on infant mortality. The study recommends policy makers and programme managers in the child health sector to formulate appropriate strategies to improve the situation, of children less than five years in Kenya, by creating awareness on these factors and improving on them.
Multiple Events Model for the Infant Mortality at Kigali University Teaching Hospital
The Open Public Health Journal
Introduction: The present study applies multiple events survival analysis to infant mortality at the Kigali University Teaching Hospital (KUTH) in Rwanda. Materials and Methods: The primary dataset consists of newborns from KUTH recorded in the year 2016 and in the current paper, a complete case analysis was used. Two events per subject were modeled namely death and the occurrence of at least one of the following conditions that may also cause long-term death to infants such as severe oliguria, severe prematurity, very low birth weight, macrosomia, severe respiratory distress, gastroparesis, hemolytic, trisomy, asphyxia and laparoschisis. Covariates of interest include demographic covariates namely the age and the place of residence for parents; clinical covariates for parents include obstetric antecedents, type of childbirth and previous abortion. Clinical covariates for babies include APGAR, gender, number of births at a time, weight, circumference of the head, and height. Results...