scholarly journals Health disparities in Russia at the regional and global scales

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Natalia Shartova ◽  
Vladimir Tikunov ◽  
Olga Chereshnya
Keyword(s):  
Health Status ◽  
Infant Mortality ◽  
Life Expectancy ◽  
Principal Component ◽  
Well Being ◽  
Spatial Inequality ◽  
Infant Mortality Rate ◽  
High Income Group ◽  
Life Expectancy At Birth ◽  
Regions Of Russia

Abstract Background The capacity for health comparisons, including the accurate comparison of indicators, is necessary for a comprehensive evaluation of well-being in places where people live. An important issue is the assessment of within-country heterogeneity for geographically extensive countries. The aim of this study was to assess the spatial and temporal changes in health status in Russia and to compare these regional changes with global trends. Methods The index, which considers the infant mortality rate and the male and female life expectancy at birth, was used for this purpose. Homogeneous territorial groups were identified using principal component analysis and multivariate ranking procedures. Trend analysis of individual indicators included in the index was also performed to assess the changes over the past 20 years (1990–2017). Results The study indicated a trend towards convergence in health indicators worldwide, which is largely due to changes in infant mortality. It also revealed that the trend of increasing life expectancy in many regions of Russia is not statistically significant. Significant interregional heterogeneity of health status in Russia was identified according to the application of typological ranking. The regions were characterized by similar index values until the mid-1990s. Conclusions The strong spatial inequality in health of population was found in Russia. While many regions of Russia were comparable to the countries in the high-income group in terms of GDP, the progress in health was less pronounced. Perhaps this can be explained by intraregional inequality, expressed by significant fluctuations in income levels. Trial registration Not applicable.

scholarly journals Mortality level and trend in South Africa and their Implications

2021 ◽  
pp. 53-62
Author(s):  
K. A. KYEI ◽  
P. GAVHI
Keyword(s):  
South Africa ◽  
Health Status ◽  
Infant Mortality ◽  
Life Expectancy ◽  
South African ◽  
Household Survey ◽  
Infant Mortality Rate ◽  
Critical Measure ◽  
Study Results ◽  
Credible Information

Mortality is a critical measure of population’s health and public health systems. Infant mortality, for example, indicates quality of life, accessibility to primary healthcare and the overall health status of a country. Reduction in infant mortality shows improvement in the health status. No credible information about mortality in South Africa because the two previous censuses’ data from Statistics South Africa (StatsSA) were not reliable, this study makes attempt to bridge the gap in the lack of knowledge. Th is study uses South African General Household Survey (SAGHS) data, to fi nd the level and trend of mortality and their implications. Data for the years, 2012, 2013 and 2015, have been used. Demographic and statistical methods, including an evaluation of data quality using UN joint score, and construction of model life tables. The results indicated that the infant mortality rate (IMR) was 43 per 1000 in 2012, 36 per 1000 in 2013 and 21 per 1000 in 2015. Th is study further indicated that the general health status of South African population improved marginally from 2012 to 2015 because the life expectancy in creas ed by 7 years for the males, and by 8 years for females, between those years. The study results that SAGHS data are reliable, mortality is decreasing with increasing life expectancy. The study recommends that more proactive measures need to be put in place to improve the health status of the population, especially the children because the IMR is still quite high and creates concerns.

scholarly journals The Determinants of Health Status: A Cross-Country Analysis

1994 ◽  
Vol 33 (4II) ◽  
pp. 745-758 ◽  
Author(s):  
Rehana Siddiqui ◽  
Mir Annice Mahmood
Keyword(s):  
Health Status ◽  
Life Expectancy ◽  
Human Resource Development ◽  
Labour Force ◽  
Infant Mortality Rate ◽  
General Level ◽  
Life Expectancy At Birth ◽  
Country Analysis ◽  
Cross Country ◽  
The Impact

An analysis of health status is an important aspect of human resource development. Improvements in health do not only improve the productivity of the labour force, but they also help to improve the impact of other forms of human capital formation, e.g. education. In most developing countries health status is difficult to determine as the question arises as to what measures should be used as indicators of health status. At a general level most of the demand or production function considerations are obtained by aggregating over the micro factors. I However, in the case of health status micro and macro measures may not be perfectly correlated; In most cross-country studies life expectancy at birth or the infant mortality rate are taken as indicators of health status. Other measures which can be used to indicate such improvements in health status are age and diseasespecifrc mortality or morbidity and life expectancy. However, the improvement in health status can be observed most obviously from increases in life expectancy which is a better measure for cross country comparison than age and diseasespecific mortality or morbidity, which are more difficult to compare at the international level.

DEMOGRAPHIC AND HEALTH PATTERNS IN A RURAL COMMUNITY FROM THE BASQUE AREA IN SPAIN (1800–1990)

2002 ◽  
Vol 34 (4) ◽  
pp. 541-558 ◽  
Author(s):  
MIGUEL A. ALFONSO SÁNCHEZ ◽  
VICTORIA PANERA MENDIETA ◽  
JOSÉ A. PEÑA ◽  
ROSARIO CALDERÓN
Keyword(s):  
Infant Mortality ◽  
Life Expectancy ◽  
Rural Community ◽  
Significant Proportion ◽  
Infant Mortality Rate ◽  
Effective Control ◽  
Malignant Neoplasms ◽  
Transitional Stage ◽  
Life Expectancy At Birth ◽  
Health Patterns

In this work, the evolution of demographic and health patterns in a Basque rural population from Spain is analysed, as they relate to progress in demographic and epidemiological transition. For this purpose, parochial record data on 13,298 births and 9215 deaths, registered during the 19th and 20th centuries (1800–1990), were examined. The study area is a rural community called Lanciego, which is located at the southern end of the Rioja Alavesa area (Alava Province, Basque Country). In Lanciego, demographic transition began in the final decade of the 19th century, when a definite, irreversible trend began towards a reduction in mortality. The decrease in the birth rate came later than that in the death rate, and did not start until the 1930s. The post-transitional stage seemed to be reached in the 1970s, when the birth and death rates showed values below 20 per 1000. Other characteristics observed for the post-transitional stage in Lanciego are: (i) very low rates of infant mortality achieved at the expense of effective control of exogenous mortality; (ii) the mortality curve by ages changes from a U-shape (typical of populations with a high infant mortality rate and low life expectancy at birth) to a J-shape more characteristic of modern societies where longevity and life expectancy are considerably higher; (iii) a certain level of over-mortality among women in the senior age group (>65); and (iv) a significant proportion of mortality in recent times (1970–90) resulting from cardiovascular diseases and malignant neoplasms (post-transition causes). This last point is in contrast with observations from the first four decades of the 20th century, when infectious diseases and respiratory ailments were determining factors in mortality among this population. The data provided by the study of the variation over time in demographic and health patterns indicate that reducing the risk of mortality is one of the most important preconditions for fertility decline.

Health Status, Government Health Expenditure and Economic Growth Nexus in India: A Toda–Yamamoto Causality Approach

2020 ◽  
pp. 097674792096340
Author(s):  
Avinash Kaur
Keyword(s):  
Economic Growth ◽  
Health Status ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Life Expectancy ◽  
Health Expenditure ◽  
Infant Mortality Rate ◽  
Government Health ◽  
The Government ◽  
Government Health Expenditure

This article attempts to examine the causal linkage among government health expenditure, health status and economic growth in India for the period from 1981–1982 to 2015–2016. The results of Johansen co-integration test indicate that government health expenditure, health status and economic growth have long-run relationship in India. The results of Toda–Yamamoto causality test showed that there existed unidirectional causal relationship running from government health expenditure to gross domestic product—GDP (economic growth); GDP (economic growth) to life expectancy; government health expenditure to infant mortality rate and infant mortality rate to life expectancy. On the other hand, there is no evidence showing causality in any direction between infant mortality rate to GDP (economic growth) and government health expenditure to life expectancy. The study strongly confirmed that the government health expenditure has an effect on GDP (economic growth) and infant mortality rate (which depicts health status) in India. The health outcomes, namely life expectancy and infant mortality rare, reveal unidirectional causality between them. Therefore, the study concludes that policymakers and the government should pay proper attention to the health sector in order to ultimately achieve economic growth in the country.

Issues of Convergence

2016 ◽  
pp. 119-143 ◽  
Author(s):  
Maniklal Adhikary ◽  
Melisha Khatun
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
Life Expectancy ◽  
Gross Domestic Product ◽  
Infant Mortality Rate ◽  
Domestic Product ◽  
Capita Gross Domestic Product ◽  
Life Expectancy At Birth ◽  
Per Capita ◽  
Conditional Beta

There is no point to disagree that inequality in recent time has come up as a growing social predicament in the world. This chapter endeavors to look into the issue of convergence in terms of per capita gross domestic product, infant mortality rate, life expectancy at birth and Human Development Index among eight member countries of South Asian Association of Regional Cooperation (SAARC) during the time frame 1990-2013. There has been an evidence of strong absolute beta divergence in terms of per capita gross domestic product and infant mortality rate. But the beta convergence in terms of life expectancy at birth and HDI has also been empirically evidenced. Strong evidence of conditional beta divergence conditioning on infant mortality rate exists in terms of PCGDP only for the time period 1990-1995. Sigma divergence implying dispersion among the countries in terms of PCGDP and IMR has risen over time. But sigma convergence has been found to exist for LEB and HDI.

scholarly journals Imbalance in Life Table: Effect of Infant Mortality on Lower Life Expectancy at Birth

2013 ◽  
Vol 5 (3) ◽  
pp. 479-488 ◽  
Author(s):  
A. M. Fazle Rabbi
Keyword(s):  
Developing Countries ◽  
Infant Mortality ◽  
Life Expectancy ◽  
Life Table ◽  
Surveillance System ◽  
Mortality Rates ◽  
Demographic Surveillance System ◽  
Infant Mortality Rate ◽  
Life Expectancy At Birth ◽  
Infant And Child Mortality

Life expectancy at birth is a well-known demographic measure of population longevity. Rationally, life expectancy at birth should be higher than life expectancy at any particular age. However, historically, lower life expectancy at birth is observed than that of age one, which diminishes the feature of life expectancy at birth as a prominent indicator of longevity. High infant and child mortality rates result in lower values of life expectancy at birth than at older ages. This imbalance in life table disappears only when the crossover occurs and it happens when the inverse of the infant mortality becomes equal to the life expectancy at age one. For Matlab Health and Demographic surveillance system of Bangladesh, life expectancy at age one is still higher than life expectancy at birth. Required infant mortality rate to achieve crossover suggests further decline in infant mortality for Matlab HDSS to attain crossover of life expectancy at birth and age one. Keywords: Life expectancies; Developing countries; Imbalance; Life table.  © 2013 JSR Publications. ISSN: 2070-0237 (Print); 2070-0245 (Online). All rights reserved.  doi: http://dx.doi.org/10.3329/jsr.v5i3.14105 J. Sci. Res. 5 (3), 479-488 (2013)

scholarly journals Center-peripheral differences in life expectancy in Russia: a regional analysis

2021 ◽  
Vol 7 (5) ◽  
pp. 63-83
Author(s):  
Alexey Shchur ◽  
Sergey Timonin
Keyword(s):  
Mortality Rate ◽  
Life Expectancy ◽  
Causes Of Death ◽  
Regional Analysis ◽  
Age Groups ◽  
Spatial Inequality ◽  
Steady Increase ◽  
Significant Heterogeneity ◽  
Life Expectancy At Birth ◽  
Regions Of Russia

Elevated mortality (compared with the West) and significant spatial differences in life expectancy are serious challenges facing Russia. The goals of improving Russians' health and increasing their life expectancy by reducing inequality in mortality between regions and settlements are closely intertwined with the goals of spatial development of Russia, aimed at reducing interregional differences in the quality of life. This paper presents an assessment of the scope and dynamics of changes in mortality differences between the ‘center’ and the ‘periphery’ in 67 regions of Russia, which are home to three-quarters of the country's population. The selected research period - 2003-2018 - is characterized by a steady increase in life expectancy at birth (LE) in Russia. Using unpublished data from Rosstat for cities, we estimated life expectancy at birth in 67 regional centers and in the rest of the regions (‘periphery’). Depending on the magnitude of the differences in LE and the dynamics, we identified 6 types of regions. For those regions with a LE gap between center and periphery larger than the average, the decomposition method was applied, which made it possible to determine the key age groups and causes of death responsible for such high differences. In 36 regions of Russia classified as types I-III, the center-peripheral gap exceeded the average Russian level, while only in six regions in 2003-18 was there a tendency towards a reduction in the size of this gap. The decomposition results showed that elevated mortality of males in the periphery is due to a higher mortality rate at working age from external causes of death, especially from traffic accidents, homicides and suicides, as well as from ‘alcoholic’ causes of death; females in the periphery suffer from higher mortality rate at older ages from chronic non-communicable diseases. Despite the seemingly ‘objective’ nature of the mortality differences between the center and the periphery (the advantage of the former being due to the socio-demographic characteristics of its residents and the educational structure of the population, as well as to selective migration), the positive experience of other countries shows that effective public health policies can substantially reduce the degree of spatial inequality in mortality even if significant heterogeneity in the level of socio-economic development remains.

scholarly journals Socioeconomic development and life expectancy relationship: evidence from the EU accession candidate countries

Genus ◽  
2020 ◽  
Vol 76 (1) ◽  
Author(s):  
Goran Miladinov
Keyword(s):  
Infant Mortality ◽  
Life Expectancy ◽  
Socioeconomic Development ◽  
Theoretical Background ◽  
Infant Mortality Rate ◽  
Gdp Per Capita ◽  
Pool Data ◽  
Eu Accession ◽  
Life Expectancy At Birth ◽  
Per Capita

AbstractThis paper investigates the effect of the socioeconomic development on life expectancy at birth as an indicator of mortality or longevity in five EU accession candidate countries (Macedonia, Serbia, Bosnia and Herzegovina, Montenegro, and Albania). Using aggregate time series pool data on an annual level from UN and World Bank databases for the period 1990–2017 and Full Information Maximum Likelihood model, it was found that this connection between the socioeconomic conditions and life expectancy at birth is a prerequisite for longer life in all these five countries. Our dependent variable was the life expectancy at birth, and the background exploratory variables for the socioeconomic development were GDP per capita and infant mortality rate. The main results are that higher values of GDP per capita and lower values of infant mortality levels lead to higher life expectancy at birth suggesting that longevity of people in these five countries is increasing. These results are supported by our theoretical background and research framework hypotheses.

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