Happier countries, longer lives: an ecological study on the relationship between subjective sense of well-being and life expectancy

2017 ◽  
Vol 26 (2) ◽  
pp. 36-40 ◽  
Author(s):  
Grahame F. Evans ◽  
Elsayed Z. Soliman
Keyword(s):  
Life Expectancy ◽  
Gross Domestic Product ◽  
Ecological Footprint ◽  
Economic Status ◽  
Pearson Correlation ◽  
Strong Relationship ◽  
Well Being ◽  
Domestic Product ◽  
Highly Correlated ◽  
The Relationship

The relationship between sense of well-being and longevity is not well-established across populations of varying levels of socioeconomic status. We sought to examine the relationship between happiness, or subjective sense of well-being and life expectancy using data from 151 countries. This analysis is based on the 2012 Happy Planet Index project conducted by the Center of Well-Being of the New Economics Foundation, based in the United Kingdom. Well-being data for each country were taken from responses to the ‘Ladder of Life’ question in the 2012 Gallup World Poll in which participants were asked to rate their quality of life on a scale from 1 (worst possible life) to 10 (best possible life). Life expectancy and gross domestic product data were taken from the 2011 United Nations records. Ecological footprint data were taken from Global Footprint Network records. Subjective sense of well-being was highly correlated with life expectancy (Pearson correlation r = 0.71, p < 0.0001). In a multivariable linear regression model adjusted for gross domestic product, ecological footprint, and population, each 1 unit of the well-being scale was associated with an increase in life expectancy of 4.0 years (95% confidence interval = 2.7–5.3). In conclusion, better sense of well-being has a strong relationship with life expectancy regardless of economic status or population size, suggesting that governments should foster happiness in order to support long-living populations.

Assessing the impact of marine production manufacturing on gross domestic product indicators

2018 ◽  
Vol 3 (4) ◽  
pp. 338-353 ◽  
Author(s):  
Faris ALshubiri
Keyword(s):  
Gross Domestic Product ◽  
Pearson Correlation ◽  
Statistical Significance ◽  
Strong Relationship ◽  
Ordinary Least Squares ◽  
Coastal Ecosystems ◽  
Domestic Product ◽  
Content Type ◽  
Gcc Countries ◽  
The Impact

Purpose This paper aims to assess and empirically analyze the impact of marine production manufacturing on gross domestic product (GDP) indicators as a comparative study in Gulf Cooperation Council (GCC) countries. Design/methodology/approach This study used analytical quantitative approaches to assess the impact of marine production manufacturing on GDP between GCC countries over the period from 2007 to 2015. The data were collected from Global Competitiveness Reports during 2006-2016 and from Food and Agriculture Organization of the United Nations, FAO 2015 reports. Findings The results show that Saudi Arabia country has the highest production of marine while Bahrain country is the lowest in GCC. The results of ordinary least squares test show that marine production has a statistical significance on GDP indicators as Pearson correlation matrix shows a strong relationship between all variables. Practical implications The main conclusion is that GCC countries must adopt a regional strategy to support maritime activities, especially in the light of green environmental fluctuations. Integrated management plans are also needed to protect vital coastal ecosystems while allowing economic growth and ensuring a better quality of life for all coastal populations. Comprehensive and collaborative leadership provides effective long-term management of coastal ecosystems in the GCC. In addition, GCC countries have high competition with each other for their market share in the global export-based marine production manufacturing. Originality/value This paper is the first to present most wealthy GCC countries in terms of marine production manufacturing. Marine production manufacturing introduces to create a new competitive market that generates distinctive internal capabilities for survival and growth in international markets.

Abstract P360: Hypertension Treatment Rates And Health Worker Density: An Analysis Of Worldwide Data

Circulation ◽  
2014 ◽  
Vol 129 (suppl_1) ◽  
Author(s):  
Rajesh Vedanthan ◽  
Mondira Ray ◽  
Valentin Fuster ◽  
Ellen Magenheim
Keyword(s):  
Gross Domestic Product ◽  
Health Worker ◽  
World Bank ◽  
Domestic Product ◽  
Hypertension Treatment ◽  
Treatment Rate ◽  
Capita Gross Domestic Product ◽  
The World ◽  
Per Capita ◽  
The Relationship

Introduction: Hypertension is the leading global risk for mortality and its prevalence is increasing in many low- and middle-income countries. Hypertension treatment rates are low worldwide, potentially in part due to insufficient human resources. However, the relationship between health worker density and hypertension treatment rates is unknown. Objective: To conduct an econometric analysis of the relationship between health worker density and hypertension treatment rates worldwide. Methods: Hypertension treatment rates were collected from published reports between 1980 and 2010. Data on health worker (physician and nurse) density were obtained from the World Health Organization (WHO). Data for potential confounding variables--per capita gross domestic product, hospital bed density, burden of infectious diseases, land area and urban population--were obtained from WHO and World Bank databases. Potential interaction by per capita gross domestic product was evaluated. Multivariable logistic-logarithmic regression analysis was performed using Stata. Results: Full data were available from 146 countries spanning all World Bank income classification categories. Health worker density was significantly associated with hypertension treatment rate in the unadjusted model (beta = 0.23; p < 0.005). In the fully adjusted model, the association remained positive but was not statistically significant (beta = 0.30; p = 0.078) (Figure). Hypertension treatment rates were more strongly related to physician than nurse density (beta = 0.21 vs 0.08; p = 0.10 vs 0.49). Conclusion: Hypertension treatment rates across the world appear to be related to health worker density, although the relationship does not achieve strict statistical significance. Our results suggest that a 10% increase in health worker density is associated with a 2-3% increase in hypertension treatment rate. Given the global burden of hypertension and other chronic diseases, WHO guidelines for health workforce staffing may need to be reconsidered.

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 Spelling Scoring Metrics in Malay Language: An Investigation among Young Spellers

2018 ◽  
Vol 8 (12) ◽  
pp. 1622
Author(s):  
Swee Gek Tang ◽  
Julia Ai Cheng Lee ◽  
Jecky Misieng
Keyword(s):  
Primary Schools ◽  
Word Reading ◽  
Strong Relationship ◽  
Phonological Coding ◽  
Correct Letter ◽  
Highly Correlated ◽  
The Relationship

The aim of this study was to investigate the relationship among three spelling scoring metrics, namely, words spelled correctly (WSC), correct letter sequences (CLS), and phonological coding (PC) in Malay language. The relationship between spelling measure and word reading measure was studied. There were 866 Primary 1 (Grade 1 equivalent) students from 11 randomly selected public primary schools in Kuching, Sarawak Malaysia who participated in this study. The study showed that the scores from each scoring metric were highly correlated to each other. There was a strong relationship between each spelling outcome to word reading.

scholarly journals An analysis of the relationship of inflation and unemployment to the gross domestic product (gdp) in zimbabwe

2014 ◽  
Vol 1 (3) ◽  
pp. 156-162
Author(s):  
Tendai Makoni
Keyword(s):  
Time Series ◽  
Gross Domestic Product ◽  
Cointegration Test ◽  
Domestic Product ◽  
Long Run ◽  
Causality Tests ◽  
Granger Causality Tests ◽  
Relationship Of ◽  
The Relationship ◽  
Yearly Data

The time series yearly data for Gross Domestic Product (GDP), inflation and unemployment from 1980 to 2012 was used in the study. First difference of the logged data became stationary as suggested by the time series plots. Johansen Maximum Likelihood Cointegration test indicated a long-run relationship among the variables. Granger Causality tests suggested unidirectional causality between inflation and GDP, implying that GDP is Granger caused by inflation in Zimbabwe. Another unidirectional causality was noted between unemployment and inflation. The causality between unemployment and inflation imply that unemployment do affect GDP indirectly since unemployment influences inflation which in turn positively affect GDP.

The Relationship Between Climate Change and Financial Stability

2021 ◽  
pp. 118-133
Author(s):  
Joan Mwihaki Nyika
Keyword(s):  
Climate Change ◽  
Risk Management ◽  
Gross Domestic Product ◽  
Financial Stability ◽  
Domestic Product ◽  
Financial Systems ◽  
Financial Firms ◽  
Climate Risk Management ◽  
Liability Risks ◽  
The Relationship

Climate change is the greatest challenge of the modern day with the capacity to destabilize global financial systems and socioeconomic welfare. This chapter explores the uncertainties posed by climate change, its effects on the economy, the risks associated with the phenomenon, and approaches to manage them through risk management. Using documented evidence, climate change is shown to result in gross domestic product reductions; physical, transition, and liability risks that result to systemic financial problems characterized by liquidation of companies, losses for, and closure of financial firms and their intermediaries; and inability of investors to pay debts. Climate risk management is proposed as a solution to adapt to climate change and reduce its associated risks.

Invisible Hand or Ecological Footprint? Comparing Social Versus Environmental Impacts of Recent Economic Growth

2019 ◽  
pp. 108602661988511 ◽  
Author(s):  
Gregory M. Mikkelson
Keyword(s):  
United States ◽  
Economic Growth ◽  
Public Policy ◽  
Gross Domestic Product ◽  
Natural Environment ◽  
Ecological Footprint ◽  
Well Being ◽  
The United States ◽  
Invisible Hand ◽  
Key Indicators

This study examines changes in some key indicators among 66 countries on six continents over a 56-year period, to compare the power of economic growth to improve human health and income distribution with its tendency to degrade the natural environment. The results indicate that growth depletes and pollutes nature far more than it benefits society. This suggests that public policy should shift toward enhancement of individual and social well-being in ways more direct and effective, and less ecologically damaging, than reliance on overall growth in gross domestic product. I illustrate this implication with a degrowth scenario for the United States to 2050 that draws on the empirical results for the period 1961 to 2016. And I consider certain reforms in the management and governance of organizations to implement such a scenario.

scholarly journals Economic Crisis in Europe: Panel Analysis of Inflation, Unemployment and Gross Domestic Product Growth Rates

2017 ◽  
Vol 9 (10) ◽  
pp. 145 ◽  
Author(s):  
Bibi Rouksar-Dussoyea ◽  
Ho Ming-Kang ◽  
Raja Rajeswari ◽  
Benjamin Chan Yin-Fah
Keyword(s):  
Gross Domestic Product ◽  
Growth Rates ◽  
Fixed Effects ◽  
Domestic Product ◽  
Panel Analysis ◽  
Causality Test ◽  
Data Set ◽  
Gross Domestic Product Growth ◽  
European Crisis ◽  
The Relationship

This panel analysis study is conducted to examine the relationship between inflation rates (CPI) and unemployment rates (HUR) with the Gross Domestic Product growth rates (GDP), before and after the 2008 European crisis. Quarterly data for 18 consecutive years and six sample countries from Europe (Austria, France, Germany, Greece, Hungary and United Kingdom) have been considered in the panel. In order to get a more profound understanding of the impacts of the European crisis on the relationship between the variables, the panel data set has been classified into 3 separate panels, such that Panel 1 (1999Q1-2007Q4) represents before-crisis panel, Panel 2 (2008Q1-2016Q4) represents the during/after crisis panel and lastly, Panel 3 (1999Q1-2016Q4) represents the long-run panel. Panel 1 is subject to the Fixed Effects with LSDV model, whereby four out of the six countries are significant, and CPI and HUR are insignificant predictors of the GDP. Both Panel 2 and Panel 3 are subject to the Two-way Random Effects model, whereby both CPI and HUR have negative significant effect on GDP. Granger Causality test has also been carried out to determine whether causality is present among variables, based on each panel.

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