scholarly journals Case Study in the COVID-19 Pandemic: Stunting, Low Birth Weight, Maternal Mortality and Infant Mortality in Semarang, Central Java-Indonesia

2021 ◽  
pp. 10-22
Author(s):  
Sulistiyowati . ◽  
Ika Pantiawati ◽  
Evina Widianawati ◽  
Slamet Isworo
Keyword(s):  
Birth Weight ◽  
Infant Mortality ◽  
Low Birth Weight ◽  
Maternal Mortality ◽  
Child Mortality ◽  
Maternal Death ◽  
Secondary Data ◽  
Central Java ◽  
Analysis Strategy ◽  
Quantitative Descriptive

Background and Objective: Stunting, low birth weight, maternal death, and child mortality have all become public health issues in recent years, particularly in Semarang, Indonesia. Simultaneously, the COVID-19 pandemic is spreading. Between the years 2019 and 2021. Methods: The Semarang City Health Service's secondary data analysis strategy was combined with a quantitative descriptive research methodology in this study. To evaluate numerical patterns in stunting, low birth weight, maternal death, and infant mortality in the data, simple regression were utilized. Results: According to the findings, the trend of stunting (modeling results y = 35,236 x + 361.77) and maternal mortality (modeling results 0.0218x+1.2921) increased between 2019 and 2021, whereas the trend of low birth weight (modeling results y = - 0.5425x+60.008) and child mortality (modeling results y = -0.0028x+ 2.202) decreased. The number of low birth weight has the lowest trend value, while the stunting rate has the greatest. Conclusion: Stunting rates increased, the low birth weight dropped, maternal mortality increased, and child mortality decreased in Semarang. The conditions of the Covid-19 epidemic have at least influenced this condition.

scholarly journals Trends in Infant mortality rate and mortality for neonates born at less than 32 weeks and with very low birth weight

2011 ◽  
Vol 19 (4) ◽  
pp. 977-984 ◽  
Author(s):  
René Mauricio Barría-Pailaquilén ◽  
Yessy Mendoza-Maldonado ◽  
Yohana Urrutia-Toro ◽  
Cristian Castro-Mora ◽  
Gema Santander-Manríquez
Keyword(s):  
Birth Weight ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Low Birth Weight ◽  
Causes Of Death ◽  
Very Low Birth Weight ◽  
Secondary Data ◽  
Mortality Rates ◽  
Infant Mortality Rate ◽  
Year 2000

The aim of the study was to assess the trend of the infant mortality rate between 1990-2004 and the neonatal mortality between 2000-2005 in infants born at less than 32 weeks of gestational age or with very low birth-weight. Based on secondary data, infant mortality rate and by its component for Valdivia city were compared with national indicators. Mortality at <32 weeks and <1500g was calculated, establishing causes of death and evaluating its relation with specific interventions, such as the use of surfactant and antenatal corticoids. Since the year 2000, infant mortality rates have stopped their decrease in comparison to the preceding decade and the gap between national and local rates before 2000 was drastically reduced. Mortality at <32 weeks and <1500g varied between 88‰ and 200‰ of liveborns, emphasizing respiratory distress as the main cause of death. The use of corticoids and surfactant was in line with reductions in mortality rates.

scholarly journals Determinants of neonatal and post-neonatal mortality in the City of São Paulo

2003 ◽  
Vol 6 (4) ◽  
pp. 345-358 ◽  
Author(s):  
Carla Jorge Machado ◽  
Kenneth Hill
Keyword(s):  
Birth Weight ◽  
Infant Mortality ◽  
Prenatal Care ◽  
Low Birth Weight ◽  
Neonatal Mortality ◽  
Child Mortality ◽  
Infant Death ◽  
Neonatal Death ◽  
Apgar Scores ◽  
The City

INTRODUCTION: Child Mortality (mortality of children less than five years) has declined considerably in the developing world in the 1990s, but the Infant Mortality has declined less. Therefore, to further reduce child mortality it is important to understand the determinants of neonatal and post-neonatal mortality. MATERIAL AND METHODS: We probabilistically matched 209628 live births and 3842 infant death records from the City of São Paulo, birth cohort of 1998. Data came from SINASC and SIM. We then used logistic regression to analyze the following risk factors of neonatal and post-neonatal mortality: birth weight, gestational age, Apgar scores at 1 and 5 minutes, delivery mode, plurality, sex, maternal education, maternal age, number of prior losses, prenatal care, race, parity and community development. RESULTS AND CONCLUSION: Infants of older mothers were less likely to die in the neonatal period; infants of adolescent mothers were more likely to die in both periods. Parities four or higher increased the likelihood of post-neonatal death. Cesarean delivery was not found to be associated with infant mortality. Low number of prenatal care visits, low birth weight, preterm birth and low Apgar scores were associated with neonatal death; Low number of prenatal care visits, low birth weight, and low Apgar scores were associated with post-neonatal death. Finally, having a mother live in a highest developed community decreased the likelihood of infant death, suggesting that unmeasured factors are behind such association.

scholarly journals Hubungan Paritas Dengan Berat Badan Lahir Rendah (BBLR)

2021 ◽  
Vol 1 (1) ◽  
pp. 49
Author(s):  
Elis Fatmawati ◽  
Dwi Retno Wati
Keyword(s):  
Birth Weight ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Low Birth Weight ◽  
Statistical Tests ◽  
Secondary Data ◽  
Sampling Technique ◽  
Infant Mortality Rate ◽  
Determining Factors ◽  
Analytical Research

One of the indicators that determine a country's health status is the high and low number of the Infant Mortality Rate (IMR). Meanwhile, the incidence of Low Birth Weight (LBW) is one of the main determining factors that contribute to the Infant Mortality Rate (IMR). Many factors cause an increase in the number of IMR, one of which is parity. This study aims to determine the relationship between parity and low birth weight (LBW) in Cendrawasih Dobo Hospital, Aru Islands Regency.This study uses analytical research with a "retrospective" research design. The dependent variable is parity and the independent variable is LBW. The population in this study were all mothers who had LBW in Cendrawasih Dobo Hospital, Aru Islands Regency in 2020 as many as 42 mothers with LBW babies. Sampling using a total sampling technique. The study was conducted from July 1 to August 31, 2020, using secondary data, and analyzed using the Spearman Ranks statistical test.The results showed that almost half of the primiparous mothers gave birth to LBW babies, namely 15 babies (35.7%) and most of the multipara mothers gave birth to 22 LBW babies (52.4%). Based on the results of statistical tests using Spearman Rho with = 0.05) the value of count (0.470) > r table (0.257) then H1 is accepted, H0 is rejected, this means that there is a parity relationship with low birth weight (LBW).There were that not only high parity has the potential for LBW births, but even low parity has the potential to occur LBW births considering that there are many factors that can influence it, not only in terms of maternal parity. Health agencies can make efforts to prevent the occurrence of LBW by improving the quality of health services.

Pengaruh Perawatan Metode Kanguru (PMK) terhadap Pencegahan Hipotermi pada Bayi Baru Lahir

2020 ◽  
Vol 2 (2) ◽  
pp. 66-71
Author(s):  
Parti ◽  
Sumiati Malik ◽  
Nurhayati
Keyword(s):  
Birth Weight ◽  
Infant Mortality ◽  
Low Birth Weight ◽  
Health Workers ◽  
Kangaroo Mother Care ◽  
Infant Mortality Rate ◽  
P Value ◽  
Low Birth Weight Infants ◽  
Low Birth Weight Babies ◽  
Before And After

Most causes of infant death are problems that occur in newborn/neonatal (0-28 days old), Low Birth Weight Babies (LBW) is one of the factors which has a contribution to infant mortality, especially in the neonatal period. Infant Mortality Rate (IMR) is a benchmark in determining the degree of public health, both at the National and Provincial levels. This study aimed to determine the effect of the Kangaroo Mother Care Method (KMC) on the prevention of hypothermia in low birth weight infants at Morowali District Hospital in 2019. The type of research used was a quasi-experiment. The population is all low birth weight babies born from May to July 2019. The sample in this study was all newborns with low birth weight born from May to July 2019, totaling 30 babies. There is a difference (influence) on the baby's body temperature before and after KMC with a p-value=0,000. The kangaroo mother care can continue to be affiliated considering its benefits for both infants and mothers, as well as increasing the ability of health workers in conducting KMC so that they can provide in-house training for mothers to be carried out at home.

scholarly journals PERBANDINGAN MODEL REGRESI BINOMIAL NEGATIF BIVARIAT DENGAN MODEL GEOGRAPHICALLY WEIGHTED NEGATIVE BINOMIAL BIVARIAT REGRESSION (GWNBBR) PADA KASUS ANGKA KEMATIAN BAYI DAN KEMATIAN IBU DI JAWA TENGAH

2022 ◽  
Vol 10 (4) ◽  
pp. 488-498
Author(s):  
Yashmine Noor Islami ◽  
Dwi Ispriyanti ◽  
Puspita Kartikasari
Keyword(s):  
Infant Mortality ◽  
Maternal Mortality ◽  
Count Data ◽  
Poisson Regression ◽  
Negative Binomial ◽  
Poor People ◽  
Significant Variable ◽  
Central Java ◽  
Observation Area ◽  
Bivariate Regression

Infant mortality (0-11 months) and maternal mortality (during pregnancy, childbirth, and postpartum) are significant indicators in determining the level of public health. Central Java Province which has 35 regencies/cities is included in the top five regions with the highest number of infant and maternal mortality in Indonesia. The data characteristics of the number of infants and maternal mortality are count data. Therefore, the Poisson Regression method can be used to analyze the factors that influence the number of infants and maternal mortality. In Poisson regression analysis, there must be a fulfilled assumption, called equidispersion. Frequently, the variance of count data is greater than the mean, which is known as the overdispersion. The research, binomial negative bivariate regression is used as a solutions to overcome the problem of overdispersion in poisson regression. This method produce a global model. In reality, the geographical, socio-cultural, and economic conditions of each region will be different. This illustrates the effect of spatial heterogeneity, so it needs to be developed into Geographically Weighted Negative Binomial Bivariate Regression (GWNBBR). The model of GWNBBR provides weighting based on the position or distance from one observation area to another. Significant variables for modeling infant mortality cases included the percentage of obstetric complications treated (X1), the percentage of infants who were exclusively breastfed (X3), and the percentage of poor people (X5). Significant variable for modeling maternal mortality cases is the percentage of poor people (X5). Based on the AIC value, GWNBBR model is better than binomial negatif bivariat regression model because it has a smaller AIC value. 

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