scholarly journals Living Longer with Disability: Economic Implications for Healthcare Sustainability

2021 ◽  
Vol 13 (8) ◽  
pp. 4467
Author(s):  
Alessandro Danovi ◽  
Stefano Olgiati ◽  
Alessandro D’Amico
Keyword(s):  
Life Expectancy ◽  
Health Expenditure ◽  
The United States ◽  
The European Union ◽  
Negative Consequences ◽  
Total Health Expenditure ◽  
Economic Implications ◽  
Life Expectancy At Birth ◽  
Per Capita ◽  
Global Increase

This work focuses on the economic implications of the relationship between life expectancy, the number of years lost to disability and per-capita total health expenditure. The primary goal of the paper is to identify and plot the correlation between healthcare expenditure and the global increase in life expectancy, in order to assess if, and how, the way longer average lifespans are achieved affects healthcare sustainability. Datasets regarding the United States, the European Union and the five largest emerging healthcare systems (i.e., Brazil, the Russian Federation, India, China and South Africa) were obtained from the Institute for Health Metrics and Evaluation and the WHO Health Expenditure Statistics Repository. All analysis was performed on 2017 data. The results of the analysis showed the number of years lost to disability to be a linear function of life expectancy at birth (male R2 = 0.61; female R2 = 0.47), and per-capita total health expenditure to be an exponential function of the number of years lost to disability (male R2 = 0.60; female R2 = 0.65). This implies that improving life expectancy via social policies bears negative consequences in terms of healthcare sustainability, unless the number of years lost to disability is reduced too. Further studies should narrow the sample of countries and causes of years lost due to disability, to better inform future policy efforts.

scholarly journals Global Inequality in Life Expectancies: What Role Does Income Inequality Play?

2020 ◽  
Author(s):  
Nirajana Banerjee ◽  
Ritojeet Basu ◽  
Ananya De ◽  
Monalisa Poali
Keyword(s):  
Income Inequality ◽  
Life Expectancy ◽  
Gini Coefficient ◽  
Capita Income ◽  
Health Expenditure ◽  
Global Inequality ◽  
Life Expectancy At Birth ◽  
Choropleth Maps ◽  
Per Capita ◽  
Over Time

Context: Life expectancy best helps to capture the health and well-being of a population. However, wide differences are seen in life expectancies across different countries and at different points of time.Research objective: This study examines trends in global inequalities in Life Expectancy at birth between countries from 1960 to 2017, and studies how income inequality affects inequality in life expectancy.Data and methodology: Life expectancy at birth is the main variable under study. We have also used data on GDP per capita at purchasing power parity, Health Expenditure per capita and Government Expenditure on health per capita. Six measures of inequality have been used, primary being the Gini coefficient. We have divided the countries into four groups according to the World Bank Classification Scheme, and have used graphs, choropleth maps and Moran’s I for statistical analysis. The causal relationship between inequality in Life Expectancy and per capita GDP is examined using reduced form regression models.Findings: The life expectancy at birth shows a steadily rising trend. The choropleth maps indicate considerable spatial variations in life expectancy, which are stable over time. There is a decline in the global inequality in life expectancy over time. Moreover, the decomposition analysis for the Gini coefficient shows that in any year, the between groups inequality is more important than the within groups inequality. This is corroborated by the decomposition of Gini over time. We infer from the devised regression models that there is a positive association between per capita income inequality and inequality in life expectancy. The regressions point out evidence that inequality in lifespan and inequality in per capita income can be explained in terms of inequality in health expenditure.

Effects of Economic and Population Factors on Health Expenditures: Special Case of Pakistan

2018 ◽  
Vol 6 (2) ◽  
Author(s):  
Tanzeela Yaqoob ◽  
Rahat Bibi ◽  
Junaid S. Siddiqui
Keyword(s):  
Growth Rate ◽  
Life Expectancy ◽  
Gross Domestic Product ◽  
Health Expenditure ◽  
Population Growth Rate ◽  
Birth Rate ◽  
Crude Birth Rate ◽  
Health Expenditures ◽  
Total Health Expenditure ◽  
Life Expectancy At Birth

<p>This paper aims to explore the factors affecting the health care expenditures of Pakistan by employing the Multivariate techniques for the annual data series from 1960 to 2010 .The variables we considered are Gross Domestic Product (GDP) as an economic indicator, Population of age 65 and above (P≥65), Population of age 0 to 14 (P(0-14)), Life expectancy at Birth (LE), Crude Birth rate (CBR) and population growth rate (GR) as population indicator and Total Health Expenditure (THE) as an influencing factor. Multiple regression considering Total Health Expenditure (THE) is applied as dependent on the variables mentioned above. Since Variance Inflation Factor (VIF) for all independent variables are very high, the smallest VIF is around 11 goes up to 65. The results obtained by Principal components reveal the effect of population structure and the age factor effect oppositely on Total Health Expenditures (THE). Factor Analysis suggests that the behavior of Health Expenditures is common with Gross Domestic Product (GDP), population of age 65 and above (P≥65) and life expectancy at Birth (LE) in Pakistan while population of age 0 to 14 (P (0-14)), population growth rate (GR) and Crude Birth rate (CBR) are moving in opposite direction i.e. as GDP, P≥65 and LE of Pakistan increases P (0-14), GR and CBR will decreases.</p>

scholarly journals Health Expenditure and Its Human Capital Determinants in Iran

2020 ◽  
Author(s):  
Ahmad MOAYEDFARD ◽  
Salar GHORBANI ◽  
Sara EMAMGHOLIPOUR SEFIDDASHTI
Keyword(s):  
Human Capital ◽  
Life Expectancy ◽  
Health Expenditure ◽  
Positive Impact ◽  
Least Square ◽  
Gdp Per Capita ◽  
Literacy Rate ◽  
Life Expectancy At Birth ◽  
Per Capita ◽  
Watson Statistic

Background: Human capital is an effective variable on the health condition of a society and its changing changes health expenditure as the proxy of health. This study aimed to investigate the relationship between human capital determinants and health expenditure. Methods: An empirical model was used with 7 variables included gender parity (GPI) index, literacy rate, life expectancy at birth, GDP per capita, physician per capita, and hospital’s bed as the independent variable and health expenditure as depended variable. After unit root test of data by using Zivot-Andrews method, the model was estimated by ordinary least square (OLS) method. Result: GPI had the negative and significant impact on health expenditure. Literacy had the positive and significant impact on depended variable. In addition, GDP per capita and life expectancy had positive and significant on health expenditure. Hospital bed and physician per capita did not have the significant relationship with health expenditure.  The value of R-squared and Durbin-Watson statistic were 0.99 and 1.95 respectively, which showed good model fit. Conclusion: literacy rate and GPI index as the proxy of human capital had the different impact on health expenditure. The first had positive and the latter had negative. GDP per capita had the positive impact that showed health was a normal good.

Healthcare of Mexico

2020 ◽  
pp. 76-80
Author(s):  
Elena Vladimirovna Frolova
Keyword(s):  
Life Expectancy ◽  
Mexico City ◽  
The United States ◽  
World Health ◽  
Average Life ◽  
Average Life Expectancy ◽  
Large Cities ◽  
Life Expectancy At Birth ◽  
The World ◽  
Per Capita

Mexico is the largest Spanish-speaking state in North America that borders the United States on one side, and Guatemala and Belize on the other. The country is home to more than 120 million people, in terms of population Mexico ranks 10th. Many Mexicans prefer to live in large cities (for example, every 5th inhabitant of the country lives in the capital of Mexico City, and Mexico City itself is the second largest city in the world), but there are many villages and fishing villages scattered along the coast. The level of medical care in large metropolitan areas and small settlements varies greatly. Mexico was ranked 21st in the 2018 Bloomberg World Health System Performance Index. This ranking, which allows assessing healthcare systems, was based on three key indicators: average life expectancy at birth, government spending on health as a percentage of GDP per capita, and the cost of health services per capita. However, in terms of life expectancy, Mexico ranks only 80th in the world (the average life expectancy in this country was 75 years in 2018).

scholarly journals Controversial advertising of medicines. A comparison between Poland and the United States

2018 ◽  
Vol 21 (5) ◽  
pp. 67-79
Author(s):  
Marta Makowska
Keyword(s):  
United States ◽  
Prescription Drugs ◽  
The United States ◽  
The European Union ◽  
Negative Consequences ◽  
Direct To Consumer ◽  
Law And Ethics ◽  
The Us ◽  
The Law ◽  
Direct To Consumer Advertising

For many years, the subject of aggressive marketing campaigns conducted by pharmaceutical companies has been raised in Poland. Drug ads are everywhere, on television, the radio, magazines and on the Internet. Therefore, it is extremely important is to ensure both their legal and ethical dimension. This article will present the differences between direct-to-consumer advertising of medicines in Poland and in the US. The dissimilarities result mainly from differences in legislation. In Poland, the law is much stricter than in the US. For example, in the United States companies are allowed to advertise prescription drugs directly to patients. In the whole of the European Union, and thus in Poland, it is strictly prohibited. The article will also present other regulations existing in Poland and in the United States and it will compare them. It will offer examples of violations of the law and ethics in the advertising of medicine in both countries. Lastly, it will briefly outline the negative consequences of unacceptable pharmaceutical marketing.

scholarly journals An Association of Total Health Expenditure with GDP and Life Expectancy

2017 ◽  
Vol 1 (2) ◽  
pp. AU7-AU12 ◽  
Author(s):  
Sojib Bin Zaman ◽  
Naznin Hossain ◽  
Varshil Mehta ◽  
Shuchita Sharmin ◽  
Shakeel Ahmed Ibne Mahmood
Keyword(s):  
Developing Countries ◽  
Life Expectancy ◽  
Gross Domestic Product ◽  
Health Expenditure ◽  
Health Spending ◽  
Domestic Product ◽  
Fiscal Year ◽  
Total Health Expenditure ◽  
Registration System ◽  
Individual Level

Introduction: Gradual  total health expenditure (THE) has become a major concern. It is not only the increased THE, but also its unequal growth in  overall economy, found among the developing countries. If increased life expectancy is considered as a leverage for an individual’s investment in health services, it can be  expected that as the life expectancy increases, tendency of health care investment will also experience a boost up. Objective: The aim of the present study was to explore and identify the association of healthcare expenditure with the life expectancy and Gross Domestic Product (GDP) in developing countries, especially that of Bangladesh. Methodology: Data were retrospectively collected from “Health Bulletin 2011” and “Sample Vital Registration System 2010” of Bangladesh considering the fiscal year 1996 to fiscal year 2006. Using STATA, multivariable logistic regression was performed to find out the association of total health expenditure with GDP and life expectancy. Results: A direct relationship between GDP and total health expenditure was found through analysing the data. At the individual level, income  had a direct influence on health spending. However, there was no significant relationship between total health expenditure with increased life expectancy. Conclusion: The present study did not find any association between life expectancy and total health expenditure. However, our analysis found out that total health expenditure is more sensitive to gross domestic product rather than life expectancy.

scholarly journals SARS-COV-2 Vaccines: What Indicators are Associated with the Worldwide Distribution of the First Doses

2021 ◽  
Vol 58 ◽  
pp. 004695802110601
Author(s):  
Marcos Felipe Falcão Sobral ◽  
Brigitte Renata Bezerra de Oliveira ◽  
Ana Iza Gomes da Penha Sobral ◽  
Marcelo Luiz Monteiro Marinho ◽  
Gisleia Benini Duarte ◽  
...  
Keyword(s):  
Population Density ◽  
Life Expectancy ◽  
Human Development ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
The United States ◽  
Gdp Per Capita ◽  
Reproduction Rate ◽  
Worldwide Distribution ◽  
Per Capita

The present study aimed to identify the factors associated with the distribution of the first doses of the COVID-19 vaccine. In this study, we used 9 variables: human development index (HDI), gross domestic product (GDP per capita), Gini index, population density, extreme poverty, life expectancy, COVID cases, COVID deaths, and reproduction rate. The time period was until February 1, 2021. The variable of interest was the sum of the days after the vaccine arrived in the countries. Pearson’s correlation coefficients were calculated, and t-test was performed between the groups that received and did not receive the immunizer, and finally, a stepwise linear regression model was used. 58 (30.4%) of the 191 countries received the SARS-CoV-2 vaccine. The countries that received the most doses were the United States, China, the United Kingdom, and Israel. Vaccine access in days showed a positive Pearson correlation HDI, GDP, life expectancy, COVID-19 cases, deaths, and reproduction rate. Human development level, COVID-19 deaths, GDP per capita, and population density are able to explain almost 50% of the speed of access to immunizers. Countries with higher HDI and per capita income obtained priority access.

scholarly journals Black and White Differences in Life Expectancy in 4 US States, 1969-2013

2019 ◽  
Vol 134 (6) ◽  
pp. 634-642 ◽  
Author(s):  
Jay S. Kaufman ◽  
Corinne A. Riddell ◽  
Sam Harper
Keyword(s):  
New York ◽  
Life Expectancy ◽  
Racial Differences ◽  
State Level ◽  
Decomposition Methods ◽  
The United States ◽  
Future Research ◽  
Age Group ◽  
Life Expectancy At Birth ◽  
Racial Gap

Objectives: Racial differences in mortality in the United States have narrowed and vary by time and place. The objectives of our study were to (1) examine the gap in life expectancy between white and black persons (hereinafter, racial gap in life expectancy) in 4 states (California, Georgia, Illinois, and New York) and (2) estimate trends in the contribution of major causes of death (CODs) to the racial gap in life expectancy by age group. Methods: We extracted data on the number of deaths and population sizes for 1969-2013 by state, sex, race, age group, and 6 major CODs. We used a Bayesian time-series model to smooth and impute mortality rates and decomposition methods to estimate trends in sex- and age-specific contributions of CODs to the racial gap in life expectancy. Results: The racial gap in life expectancy at birth decreased in all 4 states, especially among men in New York (from 8.8 to 1.1 years) and women in Georgia (from 8.0 to 1.7 years). Although few deaths occurred among persons aged 1-39, racial differences in mortality at these ages (mostly from injuries and infant mortality) contributed to the racial gap in life expectancy, especially among men in California (1.0 year of the 4.3-year difference in 2013) and Illinois (1.9 years of the 6.7-year difference in 2013). Cardiovascular deaths contributed most to the racial gap in life expectancy for adults aged 40-64, but contributions decreased among women aged 40-64, especially in Georgia (from 2.8 to 0.5 years). The contribution of cancer deaths to inequality increased in California and Illinois, whereas New York had the greatest reductions in inequality attributable to cancer deaths (from 0.6 to 0.2 years among men and from 0.2 to 0 years among women). Conclusions: Future research should identify policy innovations and economic changes at the state level to better understand New York’s success, which may help other states emulate its performance.

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