Factors Affecting Infant Mortality Rate in India: An Analysis of Indian States

2016 ◽  
pp. 707-719 ◽  
Author(s):  
Vijayakumar Suriyakala ◽  
M. G. Deepika ◽  
Jyotishi Amalendu ◽  
Gupta Deepa
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
Infant Mortality Rate ◽  
Indian States ◽  
Factors Affecting

scholarly journals Factors Affecting Fertility – New Evidence from Malaysia

2017 ◽  
Vol 36 (36) ◽  
pp. 7-20
Author(s):  
Atif Awad ◽  
Ishak Yussof
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
Negative Impact ◽  
Positive Impact ◽  
Infant Mortality Rate ◽  
Fertility Rates ◽  
Short Term ◽  
Factors Affecting ◽  
Distributed Lag ◽  
Education And Employment

Abstract This research paper investigates long and short term determinants of fertility rates in Malaysia based on basic macroeconomic variables for the period 1980-2014 using Auto Regressive Distributed Lag (ARDL) method. The study reveals that over a long term period, all the selected variables (GDP, infant mortality rate, females’ education and employment) have had significant and negative impact on total fertility rates. Whilst during the short term period, only the infant mortality rate has had a positive impact. Since population growth is partly determined by fertility rates, efforts to increase population in Malaysia should consider factors that affect those rates.

scholarly journals FACTORS AFFECTING INFANT MORTALITY RATE IN KARANGASEM, BALI

2019 ◽  
Vol 4 (1) ◽  
pp. 12-15
Author(s):  
Ni Luh Putu Suciptawati ◽  
Ni Luh Putu Suciptawati ◽  
Made Asih ◽  
Kartika Sari ◽  
I G A M Srinadi
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
Linear Model ◽  
Birth Spacing ◽  
Linear Analysis ◽  
Infant Mortality Rate ◽  
Categorical Variables ◽  
Factors Affecting ◽  
Explanatory Variables ◽  
Log Linear

The purpose of this study was to determine the factors that influence the infant mortality rate in Karangasem, Bali. The method used in this research is the Log Linier model. In the Log linear model analyze relationship pattern among group of categorical variables which include an association of two or more variables, either simultaneously or partially. A Patterned relationship between variables can be seen from the interaction between variables. Log linear analysis does not distinguish between explanatory variables and response variables. The population in this study was all babies born in Karangasem in 2015 that is as many as 7,895 babies with live birth status and as many as 7,835 babies and 60 infants died. As a sample, 100 babies were taken, of which 60 were live and 40 died. The results show that infant mortality is affected by infant weight, how old the mother during childbirth, and interaction between birth spacing and infant weight  

Analysis of Infant Mortality Rate in Indian States

2017 ◽  
Vol 19 (2) ◽  
pp. 334-339
Author(s):  
Pragati Jain ◽  
Prerna Jain
Keyword(s):  
Health Status ◽  
Mortality Rate ◽  
Infant Mortality ◽  
State Level ◽  
Health Indicators ◽  
Rate Of Change ◽  
Infant Mortality Rate ◽  
Indian States ◽  
The Status ◽  
The Government

The aim of this research is to explore the status of infant mortality at the state level, rate of change over the study period (1981–2011) and regional variation in infant mortality rate (IMR) and present a case as to how health status can be improved through targeting goals as in the case of IMR by the health planners and policymakers. The achievement of each of the 15 states on the basis of IMR is examined on the basis of divergence reduction. Sigma and beta absolute convergence measures used to determine the nature of change in the degree of regional inequality in IMR show positive results in achieving regional convergence. This confirms that the government policy and programmes to control and reduce IMR have been successful. IMR is frequently questioned as a measure of health status as infant mortality turns out to be the main focus of health policy; however, the entire population’s health possibly will be ignored in achieving the policy targets. However, the brighter side to it is that the entire gamut of health indicators can be targeted in a phased manner to achieve the overall improvement in the health status.

Factors Affecting Reports of Neonatal Deaths in United States and Elsewhere

PEDIATRICS ◽  
1970 ◽  
Vol 45 (6) ◽  
pp. 1042-1042
Author(s):  
Laurance N. Nickey
Keyword(s):  
United States ◽  
Mortality Rate ◽  
Infant Mortality ◽  
The United States ◽  
Mortality Rates ◽  
Infant Mortality Rate ◽  
Factors Affecting ◽  
Neonatal Deaths ◽  
American Academy Of Pediatrics

Again, I have read that the United States' infant mortality rate is "a disgrace and totally unacceptable," that the Nation's infant mortality rate is 21.7 per 1000 live births, and that there are 12 countries which have lower infant mortality rates than the United States. I would very much like to challenge the Editorial Board of Pediatrics and the American Academy of Pediatrics to help clarify this somewhat mysterious but often quoted figure. I would like to see in print an authoritative report outlining the criteria for neonatal death as used in this country and its several states, and also the countries that are commonly listed in the forefront, in so far as infant mortality rates are concerned.

Perbandingan Linieritas Dalam Pendeteksian Faktor-Faktor Yang Mempengaruhi Angka Kematian Bayi Di Provinsi Aceh

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Desfira Ahya ◽  
Inas Salsabila ◽  
Miftahuddin
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
Linear Model ◽  
Health Workers ◽  
Additive Model ◽  
Infant Mortality Rate ◽  
Mortality Data ◽  
Important Indicator ◽  
Penalized Spline ◽  
Aceh Province

Angka Kematian Bayi/ Infant Mortality Rate (IMR) merupakan indikator penting dalam mengukur keberhasilan pengembangan kesehatan. Nilai IMR juga dapat digunakan untuk mengetahui tingkat kesehatan ibu, kondisi kesehatan lingkungan dan secara umum, tingkat pengembangan sosio-ekonomi masyarakat. Penelitian ini bertujuan untuk memperoleh model IMR terbaik menggunakan tiga pendekatan: Model Linear, Model Linear Tergeneralisir dan Model Aditif Tergeneralisir dengan basis P-spline. Sebagai tambahan, berdasarkan model tersebut akan terlihat variabel yang mempengaruhi tingkat kematian bayi di provinsi Aceh. Penelitian ini menggunakan data jumlah kematian bayi di tahun 2013-2015. Data dalam penelitian ini diperoleh dari Profil Kesehatan Aceh. Hasil menunjukkan bahwa model terbaik dalam menjelaskan angka kematian bayi di provinsi Aceh tahun 2013-2015 ialah Model Linear Tergeneralisir dengan basis P-spline menggunakan parameter penghalusan 100 dan titik knots 8. Faktor yang sangat mempengaruhi angka kematian ialah jumlah pekerja yang sehat.   Infant mortality rate (IMR) is an important indicator in measuring the success of health development. IMR also can be used to knowing the level of maternal health, environmental health conditions and generally the level of socio-economic development in community. This research aims to get the best model of infant mortality data using three approaches: Linear Model, Generalized Linear Model and Generalized Additive Model with Penalized Spline (P-spline) base. In addition, based on the model can be seen the variables that affect to infant mortality in Aceh Province. This research uses data number of infant mortality in Aceh Province period 2013-2015. The data in this research were obtained from Aceh’s Health Profile. The results show that the best model can be explain infant mortality rate in Aceh Province period 2013-2015 is GAM model with P-spline base using smoothing parameter 100 and knots 8. Factor that high effect to infant mortality is number of health workers.

Empirical analysis of factors influencing the public health expenditure in Malaysia

2018 ◽  
Vol 6 (3) ◽  
pp. 1
Author(s):  
Kok Wooi Yap ◽  
Doris Padmini Selvaratnam
Keyword(s):  
Public Health ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Health Expenditure ◽  
Price Index ◽  
Infant Mortality Rate ◽  
Public Health Expenditure ◽  
The Public ◽  
Empirical Results ◽  
Per Capita

This study aims to investigate the determinants of public health expenditure in Malaysia. An Autoregressive Distributed Lag (ARDL) approach proposed by Pesaran & Shin (1999) and Pesaran et al. (2001) is applied to analyse annual time series data during the period from 1970 to 2017. The study focused on four explanatory variables, namely per capita gross domestic product (GDP), healthcare price index, population aged 65 years and above, as well as infant mortality rate. The bounds test results showed that the public health expenditure and its determinants are cointegrated. The empirical results revealed that the elasticity of government health expenditure with respect to national income is less than unity, indicating that public health expenditure in Malaysia is a necessity good and thus the Wagner’s law does not exist to explain the relationship between public health expenditure and economic growth in Malaysia. In the long run, per capita GDP, healthcare price index, population aged more than 65 years, and infant mortality rate are the important variables in explaining the behaviour of public health expenditure in Malaysia. The empirical results also prove that infant mortality rate is significant in influencing public health spending in the short run. It is noted that macroeconomic and health status factors assume an important role in determining the public health expenditure in Malaysia and thus government policies and strategies should be made by taking into account of these aspects.

Measuring Effectiveness Of Economic Growth On Reducing Infant Mortality Rate In Tamilnadu

2019 ◽  
Vol 118 (4) ◽  
pp. 129-141
Author(s):  
Mr. Y. EBENEZER
Keyword(s):  
Economic Growth ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Negative Relationship ◽  
Infant Mortality Rate ◽  
Domestic Product ◽  
Per Capita ◽  
The Impact ◽  
Adf Test ◽  
Bound Test

                   This paper deals with economic growth and infant mortality rate in Tamilnadu. The objects of this paper are to test the relationship between Per capita Net State Domestic Product and infant mortality rate and also to measure the impact of Per capita Net State Domestic Product on infant mortality rate in Tamil Nadu. This analysis has employed the ADF test and ARDL approach. The result of the study shows that IMR got reduced and Per capita Net State Domestic Product increased during the study period. This analysis also revealed that there is a negative relationship between IMR and the economic growth of Tamilnadu. In addition, ARDL bound test result has concluded that per capita Net State Domestic Product of Tamilnadu has long run association with IMR.

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