scholarly journals PANEL DATA REGRESSION ANALYSIS FOR FACTORS AFFECTING INFANT MORTALITY RATE IN EAST JAVA 2013-2017

2021 ◽  
Vol 16 (3) ◽  
pp. 437
Author(s):  
Faishal Azhar Wardhana ◽  
Rachmah Indawati
Keyword(s):  
Panel Data ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Data Availability ◽  
Infant Mortality Rate ◽  
Complete Coverage ◽  
Cross Sectional ◽  
Panel Data Regression ◽  
Data Regression ◽  
The Government

ABSTRACTThe escalating infant mortality rate (IMR) in Indonesia has not been able to fulfill the target of Sustainable Development Goals (SDGs) that restrict the limit of IMR to just 12 of 1,000 live births. According to such fact, this research was designed as the application of panel data regression in an IMR case study of East Java from 2013–2017. Regression panel data enable research in describing cross-sectional and time series information. The variety of data availability in this method were capable of producing a high degree of freedom, allowing it to meet the prerequisites and statistical properties. This method was considered the most suitable one for analyzing the rising IMR. This research was classified as non-reactive research. All regencies/cities in East Java served as this study’s population. Data collection included K4 coverage, childbirth assistance, and KN complete coverage. The result of panel data regression showed a significant connection between K4 coverage (0.0230), childbirth assistance (p = 0.0105), and KN complete coverage (0.0205). Adjusted R-Square value was obtained with an amount of 80%, which means that all independent variables were able to explain the dependent one of that value, while the remaining were explained by other factors. This study can provide some suggestions to support IMR in East Java, including handling from the government or related pregnant families to support IMR on an ongoing basis. Keywords: panel data regression, IMR, K4, childbirth assistance, KN complete

scholarly journals Kepatuhan Ibu Nifas Dalam Pemanfaatan Buku KIA Terhadap Pencegahan Komplikasi Masa Nifas Di Kota TarakanKepatuhan Ibu Nifas Dalam Pemanfaatan Buku KIA Terhadap Pencegahan Komplikasi Masa Nifas Di Kota Tarakan

2021 ◽  
Vol 5 (2) ◽  
pp. 77-86
Author(s):  
Nur Indah Noviyanti ◽  
◽  
Gusrian Gusrian ◽  
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
Community Health Center ◽  
Sampling Technique ◽  
Infant Mortality Rate ◽  
Chi Square ◽  
Cross Sectional ◽  
The Government ◽  
The Right ◽  
Postpartum Mothers

Indonesia is currently still experienced problems related to the high maternal mortality rate (MMR) and infant mortality rate (IMR). So that the government makes efforts to reduce MMR and IMR. In this effort, in 1994 the government issued the MCH booklet, which is one of the strategies in reducing maternal and infant mortality rates, this strategy involves empowering the community, especially families and communities. In order to ensure the use of the MCH handbook in the community, the implementation of the MCH handbook is coordinated directly by the respective regional health offices. During the pandemic postpartum mothers find it difficult to access health facilities because of the right to service. Therefore, to increase mother's knowledge, both about early detection of complications, health education, health promotion, it is hoped that mothers can support them through the KIA book that every pregnant and postpartum mother has. This study aims to determine the relationship between postpartum mother’s adherence to the use of MCH book as an education to prevent complications in the Pandemic Era in the Sebengkok Community Health Center. This type of research used analytical research with cross sectional design. The population in this study were all postpartum mothers who were in the working area of the pusksemas Sebengkok from January to June 2020. The sampling technique in this study was purposive sampling. Based on the chi square test, the value of ρ = 0.011 was obtained, which shows ρ <α (0.05), which means that there is a relationship between postpartum mothers' knowledge of the use of the MCH book during the COVID-19 pandemic.

Determinants of Infant Mortality Rate in Malaysia: Evidence from Dynamic Panel Data Study

2019 ◽  
Vol 21 (4) ◽  
pp. 443-450
Author(s):  
Chor Foon Tang
Keyword(s):  
Panel Data ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Health Spending ◽  
Mortality Rates ◽  
Dynamic Panel Data ◽  
Infant Mortality Rate ◽  
Female Education ◽  
Dynamic Panel ◽  
Governance Quality

Understanding the factors associated with the infant mortality rate is essential as it may guide policymaking in efforts to alleviate the high incidence of infant mortality. The aim of this study is to explore the major determinants of the infant mortality rate with specific focus accorded to research and development (R&D) and governance quality. Our analysis utilizes unbalanced panel data from 122 countries from 2001 to 2013. Using the dynamic panel data generalized method of moments (GMM) estimator, we find that income, health spending, female education, technological progress and governance quality have significant negative impact on infant mortality rates. It can thus be surmised that policies to reduce infant mortality rates should focus upon improving the level of income, female education, health spending and governance quality, besides encouraging R&D activities.

scholarly journals Analisis Regresi Panel pada Pemodelan Tingkat Kematian Bayi di Provinsi Sulawesi Selatan

2020 ◽  
Vol 2 (2) ◽  
pp. 115
Author(s):  
Syafruddin Side ◽  
S. Sukarna ◽  
Raihana Nurfitrah
Keyword(s):  
Panel Data ◽  
Infant Mortality ◽  
Regression Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
Dummy Variable ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

Penelitian ini membahas mengenai estimasi parameter model regresi data panel pada pemodelan tingkat kematian bayi di Provinsi Sulawesi Selatan dari tahun 2014 sampai dengan 2015. Data yang digunakan adalah data sekunder dari Dinas Kesehatan Provinsi Sulawesi Selatan yang berupa jumlah kematian bayi, berat bayi lahir rendah, persalinan yang ditolong oleh tenaga kesehatan, penduduk miskin, bayi yang diberi ASI ekslusif dan rumah tangga berperilaku bersih sehat di seluruh Kabupaten/Kota di Provinsi Sulawesi Selatan tahun 2014-2016. Analisis data dilakukan dengan menggunakan penghitungan manual dan dengan menggunakan software EViews 9. Pembahasan dimulai dari melakukan estimasi parameter model regresi data panel, menentukan model regresi data panel terbaik, , menguji asumsi model regresi data panel, pengujian signifikansi parameter dan interpretasi model regresi. Dalam penelitian ini diperoleh kesimpulan yaitu estimasi model regresi data panel terbaik dengan pendekatan fixed effect model.Kata kunci:Regresi Data Panel, Kematian Bayi, Fixed Effect Model, Least Square Dummy Variable. This research discusses about parameter estimation of panel data regression model of infant mortality level modelling in South Sulawesi from 2014 to 2015. The data used were secondary data from Dinas Kesehatan Provinsi Sulawesi Selatan in the form of number of infant mortality, low weight of infant, childbirth rescued by health workers, poor population, infants who were given exclusive breast milk and household that behaves well in the whole district/town in South Sulawesi year 2014-2016. Data analysis was performed using the calculation manually and by using EViews 9 software. The discussion started from doing parameter estimation of panel data regression model, determining the best panel data regression model, testing the assumption of panel data regression model, testing the signification of parameter and interpretation of regression model. Conclusion of this research are the estimation of regression model is the best panel data regression model with fixed effects model approach.Keywords:Panel Data Regression, Infant Mortality, Fixed Effect Model, Least Square Dummy Variable.

scholarly journals Indonesian Clove Competitiveness and Competitor Countries in International Market

2020 ◽  
Vol 9 (1) ◽  
pp. 39-54
Author(s):  
Adnan Putra Pratama ◽  
Dwidjono Hadi Darwanto ◽  
Masyhuri Masyhuri
Keyword(s):  
Panel Data ◽  
Sri Lanka ◽  
Market Share ◽  
Secondary Data ◽  
International Market ◽  
Panel Data Regression ◽  
Data Regression ◽  
The World ◽  
The Government ◽  
Star Position

Trade liberalization is currently demanding every country to increase the competitiveness of its products. Indonesia as the largest clove producer in the world has a major competitor in the international market. This study aims to determine the competitiveness of Indonesia's clove exports and competing countries in the international market and determine the factors that affect its competitiveness. The data used in this study are secondary data from five major producing countries namely Indonesia, Madagascar, Tanzania, Sri Lanka, and Comoros during the period 2000-2017 sourced from UNComtrade, FAO and the World Bank. Competitiveness is measured by Revealed Comparative Advantage (RCA), Acceleration Ratio (AR) and Export Product Dynamic (EPD) while the factors that affect competitiveness are used panel data regression methods using E-Views software. The results showed that Indonesia had the lowest RCA index, the AR value showed Madagascar and Tanzania were able to capture market share in the international market and the EPD value showed that all countries occupied the rising star position except Sri Lanka in the falling star position. Panel data regression analysis results show that the market share and GDP variables significantly influence the competitiveness of the main clove producing countries while the production variables and export prices do not significantly influence the country's competitiveness. The government must dare to take policies to limit clove imports and increase exports.

scholarly journals FAKTOR-FAKTOR YANG MEMPENGARUHI PERBEDAAN BERAT BADAN LAHIR BAYI DI RSUD. Dr. M . YUNUS KOTA BENGKULU

2018 ◽  
Vol 8 (2) ◽  
pp. 143-151
Author(s):  
Meli Marisiantini
Keyword(s):  
Birth Weight ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Health Workers ◽  
Statistical Tests ◽  
Infant Mortality Rate ◽  
Dominant Factor ◽  
Low Birth Weight Infants ◽  
Caffeine Consumption ◽  
Cross Sectional

Nowadays, Infant Mortality Rate (IMR) is still high in Indonesia, it is about 32 per 1.000 livebirths, and low birth weight infants accounted for 34% as the major cause (SDKI, 2012). InDr.M.Yunus hospital at Bengkulu city, cases of LBW has increased from the preceding year,approximately 391 infants (14.4%) of 2713 childbirths. The purpose of this research is known thefactors which affect average of birth weight infants in C1 Midwifery room at Dr.M.Yunus Bengkulu in2013. The study design was observational descriptive with cross-sectional method which the populationare women who delivered in the maternity room at Dr.M.Yunus hospital, and also with accidentalsampling technique which samples are 48 respondents, data were processed using univariate andbivariate. The results of statistical tests showed there are influences of those factors to affect average ofbirth weight infant in Dr.M.Yunus hospital in 2013 and long-standing is the most dominant factor. It isexpected that health workers can be provide counseling to pregnant women in order to know the risks ifthe women have a bad lifestyle (exposure to cigarette smoke, caffeine consumption, and prolongedstanding) and also set the age for pregnancy planning.

scholarly journals Peningkatan Keberhasilan ASI Eksklusif Melalui Kegiatan Kelompok Pendukung Ibu

2015 ◽  
Vol 2 (1) ◽  
pp. 17
Author(s):  
Tri Budi Rahayu
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
Exclusive Breastfeeding ◽  
Research Method ◽  
Qualitative Approach ◽  
Infant Mortality Rate ◽  
Cross Sectional ◽  
Interview Technique ◽  
Depth Interview

Supporting the success of breastfeeding to improve the coverage of exclusive breastfeeding in order to lower the infant mortality rate (IMR) set out in 10 Langkah Menuju Keberhasilan Menyusui (LMKM) policy. One of the steps taken is strive for the establishment of Kelompok Pendukung Ibu (KP-Ibu). This study aims to explain the results of the Kelompok Pendukung Ibu (KP-Ibu) in improving the success of exclusive breastfeeding. Cross-sectional research method with qualitative approach using in-depth interview technique. The results showed there is still one group that the level of attendance <80%. It is motivated by: 1) There are some KP-Ibu motivator who are less active because the husband follows the work out of town and do not feel confident because it has not had the experience of breastfeeding; 2) Non-availability of props, tools limited to the manual / guideline; 3) Monitoring and mentoring have not done regularly every 3 months.

scholarly journals Infant Mortality in Rural and Post-Conflict Areas in South Kivu, Eastern DR Congo: A Cross-Sectional Study 

2021 ◽  
Author(s):  
Gaylord Ngaboyeka ◽  
Espoir Malembaka ◽  
Pacifique Lyabayungu ◽  
Samuel Lwamushi ◽  
Aimé Cikomola ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
Cross Sectional Study ◽  
Infant Mortality Rate ◽  
Sectional Study ◽  
Dr Congo ◽  
Cross Sectional ◽  
Factors Associated ◽  
Post Conflict ◽  
South Kivu

Abstract Background: The infant mortality rate in the province of South Kivu remains one of the highest in the Democratic Republic of Congo (DR Congo). The aim of this study is to estimate this mortality by identifying the associated factors in the health zones of Walungu and Miti-Murhesa, rural and post-conflict health zones of South Kivu, eastern DR Congo.Methods: We conducted a cross-sectional study in two post-conflict rural health zones, Miti-Murhesa and Walungu, between July 2016 and September 2017. Our study population consisted of women giving birth from two aforementioned areas during the period of study in which a structured questionnaire assessing the survival of the child resulting from the previous pregnancy was administered. Qualitative variables were described as counts and proportions and quantitative variables as means or medians depending on their distribution. To determine the factors associated with child survival, simple and multivariate logistic regression models were constructed. The materiality threshold was set at 5%. Results: The infant mortality rate is 49.7 ‰ in the two study areas overall and specifically 52.6 ‰ in Miti-Murhesa and 46.56 ‰ in Walungu. The factors associated with this mortality were the age of the mother under 20 years old [adjusted odds ratio ( ORa) = 2.3, 95% CI : 1.1-4.5 ; p = 0.022], household size greater than or equal to 7 people [( ORa = 3.7 ; 95% CI : 1.9-7.3 ; p <0.001 )], prematurity [( ORa = 25.5 ; 95% CI : 9.9-65.4 ; p < 0.001)], home birth [( ORa = 1.9 ; 95% CI : 1.3-2.9 ; p = 0.001)], the inter-reproductive space less than 12 months [( ORa = 5.3 ; ORa : 3.3-8.5 ; P < 0.001 )], not using LLINs [( ORa = 2.2 ; 95% CI : 1.4-3.3 ; P < 0.001 )].Conclusion: Infant mortality in the post-crisis rural area of South Kivu remains high although it is relatively low compared to the national average (58 ‰). However, efforts still need to be made in order to hope to achieve the Sustainable Development Goals.

scholarly journals ANALYSIS OF FACTOR AFFECTING INFANT MORTALITY RATE (IMR) IN EAST JAVA USING MULTIPLE LINEAR REGRESSION

2020 ◽  
Vol 9 (1) ◽  
pp. 69
Author(s):  
Weike Retno Palupi ◽  
Lailatul Khusnul Rizki
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Secondary Data ◽  
Medical Personnel ◽  
Equation Model ◽  
Infant Mortality Rate ◽  
P Value ◽  
The Government

Infant Mortality Rate (IMR) is one of the important indicators in public health. Indonesia still has a relatively high IMR compared to the neighboring countries. Based on the Indonesian Demographic Health Survey (IDHS) in 2012, IMR in East Java reached 25.50 deaths per 1000 births. IMR decline occurred during 2012 to 2015. Achievement depends on the factors that influence it. This study aims to create a model of IMR based on maternal and external factors in East Java. The method used was a non-reactive study using 38 districts/cities as sample units in East Java, which came from Central Bureau of Statistics secondary data in 2015. Statistical analysis used multiple linear regression. The results showed the independent variables together affected the IMR (p-value = 0,000 <0.05), but partially influenced by the age of the first married mother (p-value = 0,000 <0.05) and the helper delivery of non-medical personnel (p-value = 0.014 <0.05). The conclusion of this study is the regression equation model for IMR in East Java in 2015, which is IMR = 1,064 + 1,319 * (age of first marriage) + 0.439 * (helper of non-medical births). Suggestions for the Government of East Java Province to implement strategies so that infant mortality cases can be reduced.

Reflections on Microfinance

2019 ◽  
pp. 188-207
Author(s):  
Sovik Mukherjee ◽  
Ramesh Chandra Das
Keyword(s):  
Economic Development ◽  
Panel Data ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Poverty Alleviation ◽  
Poverty Reduction ◽  
Poverty Line ◽  
Infant Mortality Rate ◽  
Self Sufficiency ◽  
Socio Economic Development

Microfinance has become the latest buzzword in the credit markets where it shoulders the responsibility of alleviating poverty coupled with socio-economic development. Dealing with microfinance coupled with the issue of poverty reduction, the first concern is to handle the twin objectives of poverty alleviation and achievement of financial self-sufficiency, which are often at loggerheads. To begin with, the present chapter constructs a five-dimensional human poverty index (HPI) in terms of the rate of unemployment, state wise illiteracy rate, state-wise infant mortality rate, state-wise percentage of population below the poverty line, and the percentage of population not having an access to electricity for the states across India. Thus, this will serve as an index for the extent of poverty. Consequently, a fall in the value of the index actually implies poverty alleviation. This empirical model does not justify the hypothesis that “microfinance reduces poverty” at the macro level using cross-state panel data for India.

scholarly journals Understanding State-Level Variations in the US Infant Mortality: 2000 to 2015

2018 ◽  
Vol 36 (12) ◽  
pp. 1271-1277
Author(s):  
Alireza Ebrahimvandi ◽  
Niyousha Hosseinichimeh ◽  
Jay Iams
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
State Level ◽  
Infant Mortality Rate ◽  
Cross Sectional ◽  
Explanatory Variables ◽  
Infant Deaths ◽  
Factors Associated ◽  
Effect Regression ◽  
Causes Of Mortality

Objective To exploit state variations in infant mortality, identify diagnoses that contributed to reduction of the infant mortality rate (IMR), and examine factors associated with preterm-related mortality rate (PMR). Study Design Using linked birth-infant deaths files, we examined patterns in the leading causes of IMR. We compared these rates at both national and state levels to find reduction trends. Creating a cross-sectional time series of states' PMR and some explanatory variables, we implemented a fixed-effect regression model to examine factors associated with PMR at the state level. Results We found substantial state-level variations in changes of the IMR (range =  − 2.87–2.08) and PMR (−1.77–0.67). Twenty-one states in which the IMR declined more than the national average of 0.99 (6.89–5.90) were labeled as successful. In the successful states, we found reduction in the PMR accounted for the largest decline in the IMR—0.90 fewer deaths. Changes in the other subgroups of leading causes did not differ significantly in successful and unsuccessful states. Conclusion Trends in the causes of mortality are heterogeneous across states. Although its impact is not large, reducing the percentage of pregnant women with inadequate care is one of the mechanisms through which the PMR decrease.

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