Life expectancy, GDP and health spending per capita

How's Life? ◽  
2011 ◽  
Keyword(s):  
Life Expectancy ◽  
Health Spending ◽  
Per Capita

scholarly journals Biologic medicine inclusion in 138 national essential medicines lists

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Raphaël Kraus ◽  
Rae S. M. Yeung ◽  
Nav Persaud
Keyword(s):  
Life Expectancy ◽  
Health Spending ◽  
Essential Medicines ◽  
Care Needs ◽  
Biologic Dmards ◽  
Rheumatologic Diseases ◽  
Conventional Dmards ◽  
Country Characteristics ◽  
Essential Medicines Lists ◽  
Per Capita

Abstract Background Essential medicines lists (EMLs) are intended to reflect the priority health care needs of populations. We hypothesized that biologic disease-modifying antirheumatic drugs (DMARDs) are underrepresented relative to conventional DMARDs in existing national EMLs. We aimed to survey the extent to which biologic DMARDs are included in EMLs, to determine country characteristics contributing to their inclusion or absence, and to contrast this with conventional DMARD therapies. Methods We searched 138 national EMLs for 10 conventional and 14 biologic DMARDs used in the treatment of childhood rheumatologic diseases. Via regression modelling, we determined country characteristics accounting for differences in medicine inclusion between national EMLs. Results Eleven countries (7.97%) included all 10 conventional DMARDs, 115 (83.33%) ≥5, and all countries listed at least one. Gross domestic product (GDP) per capita was associated with the total number of conventional DMARDs included (β11.02 [95% CI 0.39, 1.66]; P = 0.00279). Among biologic DMARDs, 3 countries (2.2%) listed ≥10, 15 (10.9%) listed ≥5, and 47 (34.1%) listed at least one. Ninety-one (65.9%) of countries listed no biologic DMARDs. European region (β1 1.30 [95% CI 0.08, 2.52]; P = 0.0367), life expectancy (β1–0.70 [95% CI -1.22, − 0.18]; P = 0.0085), health expenditure per capita (β1 1.83 [95% CI 1.24, 2.42]; P < 0.001), and conventional DMARDs listed (β1 0.70 [95% CI 0.33, 1.07]; P < 0.001) were associated with the total number of biologic DMARDs included. Conclusion Biologic DMARDs are excluded from most national EMLs. By comparison, conventional DMARDs are widely included. Countries with higher health spending and longer life expectancy are more likely to list biologics.

scholarly journals COVID-19 Mortality Rate and Its Incidence in Latin America: Dependence on Demographic and Economic Variables

2021 ◽  
Vol 18 (13) ◽  
pp. 6900
Author(s):  
Javier Cifuentes-Faura
Keyword(s):  
Latin America ◽  
Mortality Rate ◽  
Population Density ◽  
Life Expectancy ◽  
Latin American ◽  
Positive Influence ◽  
Death Rates ◽  
Per Capita ◽  
Latin American Countries ◽  
Quality Infrastructure

The pandemic caused by COVID-19 has left millions infected and dead around the world, with Latin America being one of the most affected areas. In this work, we have sought to determine, by means of a multiple regression analysis and a study of correlations, the influence of population density, life expectancy, and proportion of the population in vulnerable employment, together with GDP per capita, on the mortality rate due to COVID-19 in Latin American countries. The results indicated that countries with higher population density had lower numbers of deaths. Population in vulnerable employment and GDP showed a positive influence, while life expectancy did not appear to significantly affect the number of COVID-19 deaths. In addition, the influence of these variables on the number of confirmed cases of COVID-19 was analyzed. It can be concluded that the lack of resources can be a major burden for the vulnerable population in combating COVID-19 and that population density can ensure better designed institutions and quality infrastructure to achieve social distancing and, together with effective measures, lower death rates.

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 Global improvements in Years of Good Life since 1950

2021 ◽  
Author(s):  
Erich Striessnig ◽  
Claudia Reiter ◽  
Anna Dimitrova
Keyword(s):  
Life Expectancy ◽  
Good Life ◽  
Composite Index ◽  
Well Being ◽  
Gdp Per Capita ◽  
World Population ◽  
Aggregate Level ◽  
Recent Past ◽  
Cognitive Limitations ◽  
Per Capita

Human well-being at the national aggregate level is typically measured by GDP per capita, life expectancy or a composite index such as the HDI. A more recent alternative is the Years of Good Life (YoGL) indicator presented by Lutz et al. (2018; 2021). YoGL represents a refinement of life expectancy in which only those person-years in a life table are counted that are spent free from material (1), physical (2) or cognitive limitations (3), while being subjectively perceived as satisfying (4). In this article, we present the reconstruction of YoGL to 1950 for 140 countries. Since life expectancy – as reported by the UN World Population Prospects in fiveyearly steps – forms the basis of our reconstruction, the presented dataset is also available on a five-yearly basis. In addition, like life expectancy, YoGL can be flexibly calculated for different sub-populations. Hence, we present separate YoGL estimates for women and men. Due to a lack of data, only the material dimension can be reconstructed based directly on empirical inputs since 1950. The remaining dimensions are modelled based on information from the more recent past.

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