scholarly journals 1374 Risk Factors for Neonatal Mortality Rate

2012 ◽  
Vol 97 (Suppl 2) ◽  
pp. A391-A391
Author(s):  
M. Kosim ◽  
A. N. Radityo ◽  
T. Taufan-Prasetya ◽  
S. Gatot-Irawan
Keyword(s):  
Risk Factors ◽  
Mortality Rate ◽  
Neonatal Mortality ◽  
Neonatal Mortality Rate

scholarly journals Infant mortality: comparison between two birth cohorts from Southeast and Northeast, Brazil

2004 ◽  
Vol 38 (6) ◽  
pp. 773-779 ◽  
Author(s):  
Valdinar S Ribeiro ◽  
Antônio A M Silva ◽  
Marco A Barbieri ◽  
Heloisa Bettiol ◽  
Vânia M F Aragão ◽  
...  
Keyword(s):  
Risk Factors ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Neonatal Mortality ◽  
Protective Factor ◽  
Infant Mortality Rate ◽  
Northeast Brazil ◽  
Birth Cohorts ◽  
Neonatal Mortality Rate ◽  
Live Births

OBJECTIVE: To obtain population estimates and profile risk factors for infant mortality in two birth cohorts and compare them among cities of different regions in Brazil. METHODS: In Ribeirão Preto, southeast Brazil, infant mortality was determined in a third of hospital live births (2,846 singleton deliveries) in 1994. In São Luís, northeast Brazil, data were obtained using systematic sampling of births stratified by maternity unit (2,443 singleton deliveries) in 1997-1998. Mothers answered standardized questionnaires shortly after delivery and information on infant deaths was retrieved from hospitals, registries and the States Health Secretarys' Office. The relative risk (RR) was estimated by Poisson regression. RESULTS: In São Luís, the infant mortality rate was 26.6/1,000 live births, the neonatal mortality rate was 18.4/1,000 and the post-neonatal mortality rate was 8.2/1,000, all higher than those observed in Ribeirão Preto (16.9, 10.9 and 6.0 per 1,000, respectively). Adjusted analysis revealed that previous stillbirths (RR=3.67 vs 4.13) and maternal age <18 years (RR=2.62 vs 2.59) were risk factors for infant mortality in the two cities. Inadequate prenatal care (RR=2.00) and male sex (RR=1.79) were risk factors in São Luís only, and a dwelling with 5 or more residents was a protective factor (RR=0.53). In Ribeirão Preto, maternal smoking was associated with infant mortality (RR=2.64). CONCLUSIONS: In addition to socioeconomic inequalities, differences in access to and quality of medical care between cities had an impact on infant mortality rates.

scholarly journals Early neonatal mortality rate and the risk factors in Wangaya hospital

2016 ◽  
Vol 48 (5) ◽  
pp. 306
Author(s):  
Made Lndah Nastiti Utami Budha ◽  
Wayan Retayasa ◽  
Made Kardana
Keyword(s):  
Risk Factors ◽  
Birth Weight ◽  
Mortality Rate ◽  
Neonatal Mortality ◽  
Gestational Age ◽  
Neonatal Death ◽  
Early Neonatal Death ◽  
Neonatal Mortality Rate ◽  
Early Neonatal Mortality ◽  
Early Neonatal Mortality Rate

Background The first week of life of a neonate is a critical period.In Asia, early neonatal mortality rate remains high.Objective To investigate early neonatal mortality rate and the riskfactors in Wangaya Hospital.Methods A cross sectional study was carried out retrospectivelyon neonates registered at Perinatology Unit, Wangaya HospitalDenpasar, Bali since January 2006. The study was done fromOctober to November 2007. Data was obtained from medicalrecord, analyzed as univariate using chi-square test or Fisher'sexact test and multivariate logistic regression analysis model.Results Early neonatal mortality rate in Wangaya Hospital was 38.7per 1000 livebirths. Univariate analyses showed that there werefive significant risk factors of early neonatal death, i.e., respiratorydistress, asphyxia, birth weight less than 2500 grams, sepsis, andgestational age less than 3 7 weeks. Multivariate analysis showedthat those five variables were significant as risk factors of earlyneonatal death i.e., OR (95% confidence interval) for respiratorydistress: 16.8 (3.7 to 76.6)], asphyxia: 13.5 (6.1 to 29.9)], birthweight <2500 grams: 8.1 (3.3 to 19.9)], sepsis: 7.3 (3.1 to 17.1),and gestational age <37 weeks: 3.5 (1.6 to 7.8)].Conclusions Early neonatal mortality rate in Wangaya Hospitalremains high. Respiratory distress, asphyxia, birth weight <2500gram, sepsis, and gestational age <37 weeks were independent riskfactors of early neonatal death.

scholarly journals Maternal Risk Factors for Perinatal Mortality

2013 ◽  
Vol 26 (2) ◽  
pp. 86-91
Author(s):  
Nusrat Ara Yousuf ◽  
Ismat Ara Yousuf ◽  
Noor Uddin Talukder ◽  
Afroza Kutubi ◽  
Parveen Akhter Shamsun Nahar ◽  
...  
Keyword(s):  
Risk Factors ◽  
Mortality Rate ◽  
Neonatal Mortality ◽  
Perinatal Mortality ◽  
Prospective Clinical Study ◽  
Maternal Risk Factors ◽  
Neonatal Mortality Rate ◽  
College Hospital ◽  
Total Birth ◽  
Maternal Risk

Objective: This prospective clinical study was designed on maternal risk factors for perinatal  mortality.Material and Methods: This is cross sectional study conducted in the Department of Obstetrics  & Gynae and Department of pediatrics Sylhet M A G Osmani Medical College Hospital, Sylhet, during the period from 1st July 2008 – 30th June 2009. Here study population were all fresh & macerated stillborn & early neonatal death cases during the study period. For  convenience sampling total 100 cases were studied for this study during the study period.Results: During this period 8398 deliveries were done & there were 715 perinatal deaths. In Sylhet region neonatal mortality rate is higher (53 /1000 total birth) than our national neonatal  mortality rate (37/1000 total birth) (BDHS, 2007). From this study it was revealed that most  important maternal risk factor for perinatal mortality was pre-eclampsia, eclampsia and obstructed labour.Conclusion: Perinatal mortality rate serves as the most sensitive index of maternal and neonatal care. DOI: http://dx.doi.org/10.3329/bjog.v26i2.13786 Bangladesh J Obstet Gynaecol, 2011; Vol. 26(2) : 86-91  

scholarly journals Comparison of Factors Associated with the Neonatal Mortality Rate in Fars Province before and after Implementing the Health Section Evolution: A Retrospective Cross-Sectional Study

2021 ◽  
Author(s):  
Khalil Alimohammadzadeh ◽  
Farshad Falahati ◽  
Hassan Karami ◽  
Hamidreza Parsa ◽  
Maryam Shirvani Shiri ◽  
...  
Keyword(s):  
Risk Factors ◽  
Mortality Rate ◽  
Neonatal Mortality ◽  
Cross Sectional Study ◽  
P Value ◽  
Fars Province ◽  
Neonatal Mortality Rate ◽  
Cross Sectional ◽  
Factors Associated ◽  
Before And After

Background: The neonatal period or the first 28 days after birth is a critical and vulnerable time for a child period, and the mortality rate is high due to the severe problems which might happen during this period. The goal of this study was to compare the risk factors associated with the neonatal mortality rate (NMR) before and after the implementation of the health sector evolution plan (HSEP) in Fars Province, Iran. Methods: This study was a retrospective cross-sectional study. This research was conducted using the census method, and 275951 newborns’ files were studied. Variables are expressed as percentage and frequency. The chi-square test and Fisher tests was used to measure the significance level of variables. A multivariate logistic regression model was also used to estimate the odds ratio of neonatal mortality and risk factors associated with neonatal mortality. All statistical tests were performed bilaterally with P-value < 0.05 considered as significant. All tests were conducted using the software SPSS19. Results: After HSEP, risk factors of pregnancy and delivery complications were significantly reduced, and abnormalities were significantly increased (P-value < 0.001). Using multivariate logistic regression analysis, the risk of death is nine times more in gestational age below 37 weeks compared to gestational age over 37 weeks. The chances of neonatal mortality among neonates weighing less than 1000 grams are much more, and it is about 140 times more than normal weight (over 2500 grams). There was not a significant relationship between the chance of neonatal mortality and the implementation of HSEP (P-value > 0.05). Conclusion: Neonates with abnormal weight and premature neonates had the highest chance of death. Therefore, the prevention of preterm labor and low-birth-weight infants are essential factors in reducing neonatal mortality. This study suggests that improved health service quality is determinative to decrease neonatal mortality rate.

IMPACT OF NEONATAL INTENSIVE CARE

PEDIATRICS ◽  
1996 ◽  
Vol 97 (2) ◽  
pp. 215-215
Author(s):  
Student
Keyword(s):  
Intensive Care ◽  
Birth Weight ◽  
Mortality Rate ◽  
Neonatal Mortality ◽  
Neonatal Intensive Care ◽  
Neonatal Mortality Rate ◽  
Total Reduction ◽  
Weight Groups

Neonates who weighed &gt; 1.5 kg at birth were the major contributors to the overall reduction in the neonatal mortality rate (NMR); approximately two thirds of total reduction in the NMR between 1960 and 1980 and 52.6% of the total reduction between 1980 and 1986 occurred in the &gt; 1.5-kg birth weight groups.

The Mortality of Extremely Premature Infants and the Impact on the Overall Neonatal Mortality Rate [20C]

2016 ◽  
Vol 127 ◽  
pp. 31S
Author(s):  
Horatio S. Falciglia ◽  
William K. Brady ◽  
Ronald Merkel ◽  
Vickie Glover ◽  
Angela N. Fellner
Keyword(s):  
Mortality Rate ◽  
Neonatal Mortality ◽  
Premature Infants ◽  
Neonatal Mortality Rate ◽  
The Impact

scholarly journals Density Estimation of Neonatal Mortality Rate Using Empirical Bayes Deconvolution with Poisson Distributed Surrogate in Central Java Province Indonesia

2020 ◽  
pp. 206-212
Author(s):  
Fevi Novkaniza ◽  
Khairil Anwar Notodiputro ◽  
I Wayan Mangku ◽  
Kusman Sadik
Keyword(s):  
Mortality Rate ◽  
Neonatal Mortality ◽  
Density Estimation ◽  
Poisson Distribution ◽  
Empirical Bayes ◽  
Prior Density ◽  
Neonatal Mortality Rate ◽  
Neonatal Deaths ◽  
Central Java ◽  
Central Java Province

This article is concerned with the density estimation of Neonatal Mortality Rate (NMR) in Central Java Province, Indonesia. Neonatal deaths contribute to 73% of infant deaths in Central Java Province. The number of neonatal deaths for 35 districts/municipalities in Central Java Province is considered as Poisson distributed surrogate with NMR as the rate of Poisson distribution. It is assumed that each number of neonatal deaths by district/municipality in Central Java Province were realizations of unobserved NMR, which come from unknown prior density. We applied the Empirical Bayes Deconvolution (EBD) method for estimating the unknown prior density of NMR based on Poisson distributed surrogate. We used secondary data from the Health Profiles of Central Java Province, Indonesia, in 2018. The density estimation of NMR by the EBD method showed that the resulting prior estimate is relatively close to the Gamma distribution based on Poisson surrogate. This is implying that the suitability of the obtained prior density estimation as a conjugate prior for Poisson distribution.

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