Infantmortality is the death of a child before completing the first year of age. The infant deaths number from every 1000 live births called infantmortalityrate. This rate can be taken as an indicator to measure the health care and well- being of the society . The most causes of infantmortality are birth defects, preterm, low birth weight, maternal complications of pregnancy and injuries such as suffocation [3, 6]. The infantmortality causes are significantly associated to structural factors like economic development, general living conditions, social wellbeing and the environment quality . In 2005 the United Nations stated in the human development report the most powerful indicator to capture the divergence in the human development is child mortality .
This study examines the factors that affect the rate of mortality among infants under one year of age using panel data sets from the World Bank’s World Development Indicator database from the year 2000 to 2009 from 53 African countries. Using a random effect model in a 2SLS analytical method, results obtained after correcting for endogeneity showed that fertility rate significantly affect infantmortalityrate in a positive way. Similarly, GDP per capita as a proxy for income, public health expenditure as a percentage of GDP, Prevalence of HIV and the participation of adult female in the labour force significantly affect infantmortalityrate. Furthermore, of all the explanatory variables used in the analysis, fertility rate and GDP per capita had the most impact on infantmortalityrate respectively. This study also confirms Chowdhury’s (1988) postulation that there is a dual causality between infantmortalityrate and fertility rate.
terms of per capita was the most important determinant of IMR. South Korea, Qatar, Singapore and Maldives spent the highest amount per capita on health in their regions and they also had the best IMR figures in their regions. Higher governmental spending determines that the section most vulnerable, the poor and the lower middle class can avail the benefits of affordable or subsidized health care. In the 1990s Italy privatized a significant portion of its healthcare delivery system the authors of an epidemiological study calculated the average rate of change in avoidable mortality rates in 19 of Italy's regions for a decade and concluded that public spending was significantly associated with reductions in avoidable mortality rates, while greater private sector spending was not. 19 In the present study Afghanistan, Myanmar, Yemen and Vietnam had the highest proportion of private spending as a percentage of total spending and also had the highest IMR in their regions. This indicates that when a good public health care system and infrastructure is not available or found wanting, then citizens have to depend on private health care which may not be always affordable and consequently results in poorer health outcomes. In a study on achieving the millennium developmental goals in India, the authors pointed out that poverty, low literacy, poor nutritional status , urban-rural divide and lower budgetary allocations are the reasons most responsible for high IMR and increasing governmental spending has started showing encouraging results. 20 A cross-country study in seven Pacific island countries evaluated the relationship between per capita health expenditure and health outcomes such as infantmortalityrate and the results provided strong evidence that per capita health expenditure
Infantmortalityrate (IMR) has been viewed as the vital index which can be used to measure the health level of a country or a district, and also can indirectly illustrate the economic development level of the country or district. In this paper, the authors 1) introduce three calculation methods of IMR and compare the differences among them; 2) calculate the IMR using one method above, and find the IMRs recorded in China Population Statistic Yearbook (CPSY) from National Statistics Institute and in China Health Statistic Yearbook from Ministry of National Hygiene are both overestimated; 3) point out three main reasons for this overestimation: firstly, confusion of methods of calculation and concepts, secondly, inconsistent statistical caliber among different yearbooks, thirdly, flaws within the registration system.
India shows wide variations of InfantMortality among its various states. There is a high infantmortalityrate in Rajasthan, Madhya Pradesh, Uttar Pradesh, Orissa and Bihar in comparison to the nation’s average. Rajasthan shows an alarming InfantMortalityrate. The decrease in infantmortality is very slow which shows that the implementation of various policies and programs is not being carried out efficiently in Rajasthan. Also there is an increase of the proportion of neonatal deaths.
Abstract: The idea of introducing extra parameters into the existing model in enhancing more flexibility is a giant stride in research. Transmutation map technique is one of the recent methods of introducing additional properties such as skewness, kurtosis and bimodality into the baseline distribution. In this article, a new exponentiated exponential distribution is developed using transmutation map. This model is referred to as exponentiated cubic transmuted exponential distribution (ECTED). The mathematical properties of the model which include survival function, hazard function, central and non- central moments, moment generating function and order statistics are established. The inherent parameters in the model are estimated using method of maximum likelihood estimation (MLE). The system of equations obtained is non-linear in parameters therefore non-linear optimization algorithms are implemented in R package. The distribution is used to model data on infantmortalityrate in Nigeria. The performance of the subject model is compared with its baseline exponential distribution (ED), transmuted exponential distribution (TED), exponentiated transmuted exponential distribution (ETED) and cubic transmuted exponential distribution (CTED) using Akaike Information criterion (AIC), Corrected Akaike Information criterion (AICC) and Bayesian Information criterion (BIC). It is hope that this will serve as an alternative distribution in modelling complex real life data arising from various fields of human endeavors.
The infantmortalityrate in North Sumatra has been declining since the 1970s. The trend of the decline can be seen in Table 1.2. The table clearly shows that the infantmortalityrate in North Sumatra (for both sexes) has declined from 120 per 1000 live births in 1971 to 89 per 1000 live births in 1980. Note should be taken here that Sumantri (1983) used the Trussell method, while CBS (1983) used the Brass method in estimating the infantmortalityrate. Accordingly, it is possible that the levels of estimation are slightly different. However, the overall IMR of 120 in 1971 was quite high. This might be due to error in the original publication, because the reasonable level of IMR should lay between 122 and 103. Substantial disparities can be observed between the IMR in urban as compared with rural areas. In 1980 the IMRs in rural areas were about one-third higher than those in urban areas.
countries with great diversities. India experienced notable mortality variation in all the age groups by the place of residence . So, it is imperative to estimate the mortality rates at the district level which will help the policy makers to assess the quality improvements related to the health services and will also assist in evaluating the programs and policy implications. In developing countries like India accurate estimation of infantmortalityrate at the sub-state level is a difficult task due to lack of comprehensive vital registration system. In such circumstances, researchers have to rely only on the indirect methods. One of the famous widely such methods is the Brass method pioneered by Brass (1964) , which is based on the information related to children ever born (CEB), child survival (CS) and total married woman reported in the age group of 15-49 years. Brass converted proportions of dead children that were ever born as reported by their mothers classified by various age groups of the reproductive period into the estimates of death probabilities before attaining definite childhood ages . He noticed that the link between the proportions of dead children with respect to mother’s age group (D(i) where i takes the values 1,2, 3,5,10,15 and 20 for the corresponding mother’s age group 15-19,20-24,… 45-49) and the life table measure is basically influenced by the age pattern of fertility. Brass also found a series of correspondence between the ages of the mothers and their children as shown in Table 1. But however, these matches are not exact and they rely upon the reproduction stories of those females who report about their births . In addition to this, Brass established a series of multipliers in order to adjust the specific reproductive stories for the mothers and also to convert the values of the proportion of children died into the estimates of the death probabilities before age x . The multipliers adopted by Brass have been further modified by Sullivan (1972) and Trusell (1975) (, ). However, Brass method is subjected to some fallacies. Such errors mainly derive from misreporting on the number of babies born and children dead; incorporation of stillbirths as births, and exclusion of living children who have moved away from their mother’s house, changes in the levels of fertility and also selective mortality amongst the mothers . Another drawback of this method it ignores the estimate of the death probabilities before reaching age 1 (q(1)) which is based on the mother age group 15-19. Regardless of these limitations, the method has found to have several _______________________
Whether or not IMR time series require logarithmic trans- formations has important implications for analyses of convergence of IMR both across countries and among sub-populations within countries. If IMR decline is expo- nential and requires a logarithmic transform, this implies more rapid IMR convergence. In contrast, if IMR decline is closer to linear, IMR convergence is expected to be slower. The shape of IMR declines also has implications for anal- yses of relative versus absolute gaps in IMR over time. Sup- pose IMR is declining in two populations called "A" and "B", and there is a gap so that B is higher than A. A rate ratio, B/A, is a measure of relative inequality, and a gap measure B-A is a measure of absolute inequality. There have been recent calls for researchers and policymakers to focus on relative gaps in health outcomes, including IMR, to assess health inequalities over time [9,10]. It is argued that absolute gaps in health outcomes such as IMR give a misleading impression of progress. Consider the extreme, and impossible, case that IMR declines are linear, as shown in Figure 1, Panel A. where population A obeys IMR A = A 0 - θ × Time and population B obeys IMR B = B 0 - θ × Time. Suppose there is a gap so that A 0 <B 0 . In this case, population A will approach zero first, driving the denominator of IMR A /IMR B to zero and the quotient to infinity. Researchers describing rate ratios in this era would be able to perpetually document how the IMR rate ratio each year was larger than it ever was before. This appears to be happening even now . If instead, the two populations have exponentially declining infant mor- tality rates, IMR A = exp(A 0 - θ × Time) and IMR B = exp(B 0 -
Mortality means finally death and the condition of being susceptible to death. It is generally used to indicate the end of life or death. Infantmortality is defined as the death of children under the age of one year. Infantmortalityrate is the death of children under the age of one year per 1000 live births. The death of children due to mortality may be used as a symbol of public health condition of those countries. As a result of these, children mortality effect also on the entire population disturbance. There are many factors that affect the child infantmortality like race and ethnicity, sanitation, culture, life style, education etc. The present study aimed to study the demographic profile of Todapur and Dasghara women and children in Delhi. The data were collected from Jat and Yadav dominated villages in different months of the year 2013-2014 from 900 households. The main focus of the interview was the ever-married women in the reproductive age group of 15 to 55 years and their children. The data was collected through interviews and observations. Data on reproductive history, vital events, family planning etc. was collected. The results revealed that 38.6% of people are original inhabitants of Todapur, 17.4% from Dasghara and the rest from Bihar state. The age at marriage is low that is 15 years. More than 5.3% of the women in the age group of 15 to 19 years have ever had a child. This is the cause of reproductive wastage. The crude death rate of the people of Todapur-Dasghara is 7.26 per 1000. The infantmortalityrate is 26.6 per 1000 live births. This study looks into the reasons for infantmortality, which would help to control or further reduce infantmortality in future.
From the Human Development Report of 2014, we calculated the product of infantmortalityrate, under-five mortalityrate, female adult mortalityrate, and male adult mortalityrate as a new measure of national health, the total mortalityrate or TMR, and the ratio of per capita health spending in purchasing power parity to inequality in life expectancy as a new measure of national health, the health spending per health inequality or Health/c/IneqLE. Of the 172 nations reporting sufficient data to evaluate these parameters, 52 were healthy (TMR < 1 billion). All healthy nations were rich (Health/c/IneqLE> 101). Of the 120 sick nations (TMR > 1 billion), 108 were poor (Health/c/IneqLE< 102). We conclude that Health/c/IneqLE> 101 is a necessary condition for national health. Twelve nations were rich but sick. None of these twelve had Health/c/IneqLE> 186. All nations with Health/c/IneqLE> 194 were healthy. We conclude that Health/c/IneqLE> 194 is a sufficient condition for national health. We recommend that efforts to improve human development be directed at increasing Health/c or decreasing IneqLE. Efforts to increase Health/c should increase per capita health spending and/or diminish population growth. Efforts to decrease IneqLE should enhance primary health care for the poor.
Over the last three decades fertility rate declines substantially all over the world. The aim of this study is to investigate the macroeconomic determinants of fertility rate decline in the South Asian countries. Data are taken from seven south Asian countries named Bangladesh, India, Sri-Lanka, Nepal, Pakistan, Bhutan and Maldives over the period of 1990-2015. Breusch-Pagan, Honda, King-Wu, Standardized Honda and Standardized King-Wu Lagrange Multiplier test confirm there exists cross-section effects. Hausman test confirms that fixed effect model is appropriate for empirical analysis for this study. But Breusch-Pagan LM test, Pesaran scaled LM test and Baltagi, Feng, and Kao bias-corrected scaled LM test confirm that there exist cross-sectional dependence in residuals. Therefore, Panel Corrected Standard Error (PCSE) model has been employed to get the unbiased estimators. Empirical results of PCSEmodel confirm that per capita GNI, Female labor force participation rate, Education, Infantmortalityrate, and urbanization have statistically significant impact on fertility rate in the south Asian countries. Empirical results reveal that increase of per capita GNI, female labor force participation rate, education, and urbanization will cause to decline fertility rate, while decline of infantmortalityrate will cause to decline it, which is in accordance with our theoretical expectation. Therefore, we expect that to control the population growth rate policy makers should take these factors under their consideration.
In historical demography and also in population studies of developing countries, infantmortality is often used as an indicator of the socioeconomic conditions of a population. Several studies show that the late decline in infantmortality in Italy, which caused a delayed demographic transition with respect to other European countries, was strongly connected to socioeconomic status (Manfredini and Pozzi 2004). After the unification of Italy, and indeed throughout the 1800s, the economic backwardness was clearly reflected in the high infantmortalityrate recorded throughout the country. With the dawning of the new century the dualism that pitted economically and socially progressive north-central Italy against a strongly penalized southern Italy progressively increased. As a result, high levels of infantmortality increasingly became the prerogative of the south (Caselli 1987; Pozzi 2000). The geography of infantmortality in Italy reflected the persistence of a strong relationship between socioeconomic development and infantmortality until the 1960s, when due to a higher frequency of low-weight and preterm births the most industrialized regions lost some of the advantages that the economic conditions and the best health care facilities should have ensured (Pinnelli 1989). In more recent decades, Italy has quickly recovered: infantmortality has reached values that are among the lowest in Europe and continue to decline throughout the country, although in the last years there has been a slowing down of this trend. Furthermore, geographical discontinuities, although still persistent, have reduced (ISTAT 2014).
The results further revealed the existence of unidirectional causality from manufacturing value-added to infantmortalityrate and gross secondary school enrolment rate. On the other hand, the study found the existence of unidirectional causality from the infantmortalityrate to the manufacturing output-GDP ratio. No causal relationship was found to exist between manufacturing output-GDP ratio and the other variables included in the manufacturing output- GDP equation. The above findings corroborate the earlier findings with respect to the impact of the infantmortalityrate and the gross secondary school enrolment ratio on the value-added in the manufacturing sector. The finding highlights the weakness of the country with respect to the provision of health infrastructure and human capital development. While the development of the manufacturing sector has resulted in the increased supply of domestic substitutes for the goods consumed by the educational and health sector, the reverse has not been the case with respect to the impact of both variables on the value-added in the manufacturing sector. This is reflected in the earlier mentioned inadequacy – qualitatively – of the nation’s stock of human capital in meeting the needs of the manufacturing sector, as well as the loss of productivity in the manufacturing sector caused by the loss of valuable man hours to health related issues.
In the year 1998-99 Kerala remains in the same position (16.3%) while Himachal Pradesh replaced Maharashtra and occupied second position (34.4%) and Maharashtra slipped to third position (43.7%). Uttar Pradesh, Madhya Pradesh and Rajasthan have performed worst in terms of infantmortalityrate with a figure of 86.7%, 86.1%, and 80.4% respectively. In the year 2005- 06 Kerala again performed well with a number of 15.2% followed by Tamil Nadu (30.4%) and Himachal Pradesh (36.1%). But Uttar Pradesh, Madhya Pradesh and Rajasthan have hardly been able to bring about much of a change in their positions in this regard.
Human deprivation index is a composite index based on the income, health and educational deprivations. For the analysis human deprivation index gives equal weightage for these three deprivations. There is lot of indicators for measuring these deprivations. For example, per capita income, percentage of population living below poverty line, unemployment, anaemia among children and mother, under+nourished children, infantmortalityrate, maternal mortalityrate, birth rate, death rate, immusation achievement, availability of health facilities, illiteracy, drop+out, student+teacher ratio, availability of educational facilities etc. But among these, very prominent, sensitive and effective indicators are selected for human deprivation index construction.
M uch of the information presented in this report of vital statistics for 1996 is good news. The infantmortalityrate (IMR) for the United States continued to decline in 1996 to the lowest level ever recorded, life expectancy at birth reached an all time high, the rate of births to teen mothers has decreased for the fifth consecutive year, use of early prenatal care continued to increase for all groups of women, the birth rate for unmarried women declined slightly, the death rate from human immunodeficiency virus (HIV) infection decreased sharply, and deaths among children and adolescents from injuries including homicides decreased.
The healthcare facilities in Pakistan present a very disappointing scenario. It is the outcome of extremely low expenditure on health over the last 60 years. Health expenditure in Pakistan remains at low band of 0.5-0.8 % of GNP during 1970-2007. In FY 2006-07health expenditure was only 0.6% of GNP, which was very low comparing with other developing countries. Not only the health expenditures are low but also delivery of available healthcare facilities is also inefficient. Moreover, primary healthcare and rural health services were ignored and the priority was given to hospitals, medical colleges and curative services in the urban areas. In Pakistan, infantmortalityrate was high at 77 per thousand live births; life expectancy was low at 65 years in 2006. Comparing the indicators in 2000, 85 per thousand
The lack of basic amenities and diverse sociocultural practices is also directly or indirectly responsible for affecting on the early life of childhood than the other demographic, environmental and genetic factors, etc. There is a high chance that most of the children within the same community and within the same family have the tendency of sharing common facilities in terms of household sanitation, educational, health care etc. As such, there is also need to study whether the child deaths are concentrated in the same communities. Thus, by taking the advantage of recent most NFHS 4 data having the clustering nature due to the sampling design, this study estimate the childhood mortality, i.e., neonatal mortalityrate (NMR), infantmortalityrate (IMR) and under-five mortality (U5M) among Schedule Castes, Schedule Tribes, Others Backward Classes and Others social group; and investigate differential in childhood mortality by social status that is, Schedule Castes, Schedule Tribes, Other Backward Classes and Others social group.
In recent years, the upward social mobility of females brought about by the wider availability of economic opportunities and their participation in the modern economic sectors have contributed to higher level of contraceptive use and fertility decline in Sri Lanka. Further in recent years the expansion of family planning programs, started from 1963 also has enabled the drop in the fertility rate (Sirisena, 1986, p.31). A number of socio-economic factors that contributed to the rapid decrease of fertility can be identified further. The rapid entry of more and more women in to the education and jobs, the growing living standards of women, the expansion of women's taking decisions making powers, rapidly decrease in the infantmortalityrate and specially the vast increase of long term expenses, on children are some of the important factors in this contest. With the rising cost of living, especially, the women who were engaged in education faced economic problems and as a solution to that a large number of them found employment. Today this rise of women's rate of employment has been increasing and this could be seen by the fall of the rate of unemployment of women. These changes increased female employment and also increase competition among females for employment. Due to high competition females had to wait for a long period of time in hope of employment. Therefore, they ended up getting married.