scholarly journals Air pollution control efficacy and health impacts: A global observed study from 2000 to 2016

2020 ◽  
Author(s):  
Chunlei Han ◽  
Rongbin Xu ◽  
Yajuan Zhang ◽  
Wenhua Yu ◽  
Shanshan Li ◽  
...  
Keyword(s):  
Air Pollution ◽  
Mortality Rate ◽  
Pollution Control ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Infant Mortality Rate ◽  
Gdp Per Capita ◽  
Air Pollution Control ◽  
Control Efficacy ◽  
Per Capita

AbstractBackgroundPM2.5 concentrations vary between countries with similar CO2 emissions, possibly due to differences in air pollution control efficacy. However, no indicator of the level of air pollution control efficacy has yet been developed. We aimed to develop such an indicator, and to evaluate its global and temporal distribution and its association with country-level health metrics.MethodA novel indicator, ground level population-weighted average PM2.5 concentration per unit CO2 emission per capita (PM2.5/CO2, written as PC in abbreviation), was developed to assess country-specific air pollution control efficacy. We estimated and mapped the global average distribution of PC and PC changes during 2000–2016 across 196 countries. Pearson correlation coefficients and Generalized Additive Mixed Model (GAMM) were used to evaluate the relationship between PC and health metrics.ResultsPC varied by country with an inverse association with the economic development. PC showed an almost stable trend globally from 2000 to 2016 with the low income groups increased. The Pearson correlation coefficients between PC and life expectancy at birth (LE), Infant-mortality rate (IMR), Under-five mortality rate (U5MR) and logarithm of GDP per capita (LPGDP) were –0.566, 0.646, 0.659, –0.585 respectively (all P-values <0.001). Compared with PM2.5 or CO2, PC could explain more variation of LE, IMR and U5MR. The association between PC and health metrics was independent of GDP per capita.ConclusionsPC might be a good indicator for air pollution control efficacy and was related to important health indicators. Our findings provide a new way to interpret health inequity across the globe from the point of air pollution control efficacy.

scholarly journals 209Novel indicator of air pollution control efficacy: analysis of 196 countries from 2000 to 2016

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Chunlei Han
Keyword(s):  
Air Pollution ◽  
Pollution Control ◽  
Co2 Emission ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Gdp Per Capita ◽  
Air Pollution Control ◽  
Control Efficacy ◽  
Per Capita ◽  
Pm2.5 Concentration

Abstract Background PM2.5 concentration is different with the same CO2 emission across countries, which might because of different air pollution control efficacy. But there is no indicator to reflect the level of air pollution control efficacy in previous studies. We aimed to develop such an indicator, and to evaluate its global and temporal distribution and its association with country-level health metrics. Methods A novel indicator, PM2.5 concentration per unit per capita CO2 emission (PC), was developed to show the air pollution control efficacy. We estimated and mapped the global average distribution of PC and PC changes during 2000-2016 of 196 countries for the first time. Gini coefficient was used to show the inequity of PC among different countries. Pearson correlation coefficients and Generalized Additive Mixed Model (GAMM) were used to evaluate the relationship between PC and health metrics. Results PC varied by country with an inverse association with GDP per capita. PC showed a declining trend globally from 2000 to 2016. The most remarkable decreases were observed for countries in Central Africa like Chad, Democratic Republic of Congo and Niger, then China and India. The international inequality of PC has also decreased. The Pearson correlation coefficients between PC and life expectancy at birth (LE), Infant-mortality rate (IMR), Under-five mortality rate (U5MR) and logarithm of GDP per capita(LPGDP) were -0.566, 0.646, 0.659,-0.585 respectively(all P-values &lt;0.05). Compared with PM2.5 and CO2, PC could explain more variation of LE, IMR and U5MR. Conclusions PC might be a good indicator of air pollution control efficacy and was related to important health indicators. Our findings provide a new way to interpret health equity across the globe from the point of air pollution control efficacy. Key messages air pollution, climate change, health equity, air pollution control efficacy our study developed a novel air pollution control efficacy indicator named PM2.5 concentration per unit per capita CO2 emission (PC). In the context of global climate change, PC is a good indicator to deal with air pollution for policymakers.

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.

Commanding the “Be Fruitful and Multiply” Directive: Reproductive Ethics, Law, and Policy in Israel

2010 ◽  
Vol 19 (3) ◽  
pp. 363-371 ◽  
Author(s):  
DANIEL SPERLING
Keyword(s):  
Exchange Rate ◽  
Mortality Rate ◽  
Life Expectancy ◽  
Developed Countries ◽  
Infant Mortality Rate ◽  
Gdp Per Capita ◽  
Reproductive Ethics ◽  
Live Births ◽  
Law And Policy ◽  
Per Capita

As of June 2009, Israel’s population was 7,424,400 people, 5,604,900 of which were Jewish, 1,502,400 were Arabs, and approximately 317,200 had no religion or are non-Arab Christians. Established in 1948, Israel is a highly urban and industrialized country. Its gross domestic product (GDP) per capita (based on exchange rate) is US$23,257, positioning it among the European developed countries. Life expectancy is 79 years for males and 82 years for females, with infant mortality rate of 4 cases per 1,000 live births. Of Israel’s GDP, 7.7% is spent on health.

scholarly journals Air pollution control efficacy and health impacts: A global observational study from 2000 to 2016

2021 ◽  
pp. 117211
Author(s):  
Chunlei Han ◽  
Rongbin Xu ◽  
Yajuan Zhang ◽  
Wenhua Yu ◽  
Zhongwen Zhang ◽  
...  
Keyword(s):  
Air Pollution ◽  
Observational Study ◽  
Pollution Control ◽  
Health Impacts ◽  
Air Pollution Control ◽  
Control Efficacy

scholarly journals Exploring Correlations of COVID-19 Mortality Rates with Development Variables: The Case of Northeast India

2021 ◽  
pp. 93-99
Author(s):  
Bidyutt Bikash Hazarika ◽  
Debajyoti Dutta Saikia ◽  
Bidyut Bikash Boruah ◽  
Amrit Kumar Nath
Keyword(s):  
Mortality Rate ◽  
Study Design ◽  
Pearson Correlation ◽  
Health Spending ◽  
Correlation Coefficients ◽  
Correlation Study ◽  
Cross Sectional ◽  
North East ◽  
District Hospitals ◽  
Per Capita

Aim: This paper explores the correlation of the Covid-19 mortality rate with some other developmental variables. This study also attempts to highlight the state-wise variability in mortality rate in the Northeastern region of India. Study Design: The study focuses on eight Northeastern states, correlating the Covid-19 mortality rate and other development (or socio-economic) variables. This study focuses on the region of North East India because there have been few investigations on Covid-19 in the region. This study follows a cross-sectional study design. Duration of the Study: The study was conducted and completed around three months. Methodology: The nature of the correlation between the mortality rate of Covid-19 and the other variables is determined by using the Karl Pearson correlation approach. We began by performing a correlation study and calculating the correlation coefficients. Results: The results demonstrate that all independent variables adversely correlate with the Covid-19 mortality rate. Except for the number of doctors in district hospitals and health spending per capita, which have a moderate negative correlation with the predicted variable, all explanatory factors have a weak negative connection with the death rate. Surprisingly, both the NSDP per Capita and the case positivity rate have negative findings. Another major issue in the findings is that none of the factors statistically link with mortality. Conclusion: This research shows that the more a state's socio-economic infrastructures, notably its health infrastructures, are developed, the lower the mortality rate in a pandemic will be.

scholarly journals Socioeconomic Determinants of Infant Mortality Rate in Asean: A Panel Data Analysis

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Vita Kartika Sari ◽  
Dwi Prasetyani
Keyword(s):  
Health Status ◽  
Panel Data ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Health Expenditure ◽  
Strong Influence ◽  
Mortality Rates ◽  
Infant Mortality Rate ◽  
Gdp Per Capita ◽  
Per Capita

The infant mortality rate indicates the health status of a country. Previous studies have proven that socioeconomic factors have a significant influence on infant mortality rates in both developed and developing countries. Further studies on infant mortality rates are useful for public service strategic policy in the health sector. The main purpose of this study was to analyze the socioeconomic factors influencing infant mortality rates in ASEAN based on panel data estimates for 2000-2017. The dependent variable for this study was infant mortality rate, while the independent variables were health expenditure, female labor force, maternal fertility rate, and GDP per capita. The authors concluded that the main cause of infant mortality in ASEAN is care during delivery. Other influencing factors include family health status, maternal education level, and socio-economic inequality. This study found that the size of the female workforce has a strong influence on increasing the infant mortality rate in ASEAN. The fertility rate also had a strong influence on increasing infant mortality rate in ASEAN, while GDP per capita had a negative influence on infant mortality rate.  Health expenditure is proven to have no effect on the increase of infant mortality rates in ASEAN.

scholarly journals Investigating the Causality Between Remittances, Infant Mortality, and Economic Growth in India: A Cointegration and Vector Error Correction Model Analysis

2021 ◽  
Vol 13 (3) ◽  
pp. 21
Author(s):  
Hassan Rashid ◽  
Miguel D. Ramirez
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
Mortality Rates ◽  
Infant Mortality Rate ◽  
Gdp Per Capita ◽  
Series Data ◽  
Real Gdp ◽  
Long Run ◽  
Real Gdp Per Capita ◽  
Per Capita

The main objective of this paper is to analyze the impact of remittances on human development as measured by infant mortality rates and real GDP per capita in India using time series data for the 1975-2018 period. By employing the Zivot-Andrews single-break unit root test and cointegration analysis using the Johansen procedure, a stable long-run relationship is found among the variables. Consequently, by estimating a VECM with dummy variables, results indicate that, in the long run, both remittances and real GDP per capita have a negative and significant impact on infant mortality rates in India. With infant mortality rate as a dependent variable, the adjustment coefficient for the cointegrating vector is negative and significant as the theory predicts. A Granger Block causality test is also conducted, and results indicate that remittances do not Granger cause real GDP and infant mortality rate; however, it is found that infant mortality rate and real GDP per capita Granger cause remittances. Policy implications are discussed.

Empirical analysis of factors influencing the public health expenditure in Malaysia

2018 ◽  
Vol 6 (3) ◽  
pp. 1
Author(s):  
Kok Wooi Yap ◽  
Doris Padmini Selvaratnam
Keyword(s):  
Public Health ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Health Expenditure ◽  
Price Index ◽  
Infant Mortality Rate ◽  
Public Health Expenditure ◽  
The Public ◽  
Empirical Results ◽  
Per Capita

This study aims to investigate the determinants of public health expenditure in Malaysia. An Autoregressive Distributed Lag (ARDL) approach proposed by Pesaran & Shin (1999) and Pesaran et al. (2001) is applied to analyse annual time series data during the period from 1970 to 2017. The study focused on four explanatory variables, namely per capita gross domestic product (GDP), healthcare price index, population aged 65 years and above, as well as infant mortality rate. The bounds test results showed that the public health expenditure and its determinants are cointegrated. The empirical results revealed that the elasticity of government health expenditure with respect to national income is less than unity, indicating that public health expenditure in Malaysia is a necessity good and thus the Wagner’s law does not exist to explain the relationship between public health expenditure and economic growth in Malaysia. In the long run, per capita GDP, healthcare price index, population aged more than 65 years, and infant mortality rate are the important variables in explaining the behaviour of public health expenditure in Malaysia. The empirical results also prove that infant mortality rate is significant in influencing public health spending in the short run. It is noted that macroeconomic and health status factors assume an important role in determining the public health expenditure in Malaysia and thus government policies and strategies should be made by taking into account of these aspects.

Measuring Effectiveness Of Economic Growth On Reducing Infant Mortality Rate In Tamilnadu

2019 ◽  
Vol 118 (4) ◽  
pp. 129-141
Author(s):  
Mr. Y. EBENEZER
Keyword(s):  
Economic Growth ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Negative Relationship ◽  
Infant Mortality Rate ◽  
Domestic Product ◽  
Per Capita ◽  
The Impact ◽  
Adf Test ◽  
Bound Test

                   This paper deals with economic growth and infant mortality rate in Tamilnadu. The objects of this paper are to test the relationship between Per capita Net State Domestic Product and infant mortality rate and also to measure the impact of Per capita Net State Domestic Product on infant mortality rate in Tamil Nadu. This analysis has employed the ADF test and ARDL approach. The result of the study shows that IMR got reduced and Per capita Net State Domestic Product increased during the study period. This analysis also revealed that there is a negative relationship between IMR and the economic growth of Tamilnadu. In addition, ARDL bound test result has concluded that per capita Net State Domestic Product of Tamilnadu has long run association with IMR.

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