scholarly journals Nexus Between Foreign Direct Investment Inflow, Renewable Energy Consumption, Ambient Air Pollution, and Human Mortality: A Public Health Perspective From Non-linear ARDL Approach

2022 ◽  
Vol 9 ◽  
Author(s):  
Muhammad Haroon Shah ◽  
Sultan Salem ◽  
Bilal Ahmed ◽  
Irfan Ullah ◽  
Alam Rehman ◽  
...  
Keyword(s):  
Air Pollution ◽  
Foreign Direct Investment ◽  
Renewable Energy ◽  
Direct Investment ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Series Data ◽  
Human Mortality ◽  
Ardl Approach ◽  
Non Linear

A huge foreign direct investment (FDI) inflow has been witnessed in China, though on the one hand, it brings a significant contribution to economic growth. On the other hand, it adversely affects the ambient air pollution that may affect human mortality in the country. Renewable energy (RE) usage meets the country's energy needs with no adverse effect on the environment. Therefore, this study is trying to empirically analyze the effect of FDI inflow on human morality and RE consumption in China. We used time-series data for 1998–2020 and applied a non-linear ARDL approach for the estimations. The empirical outcomes suggest that FDI inflow positively affects mortality and RE. There is also unidirectional causality running from RE and pollution to mortality. In addition, the relationship among the variable verifies the existence of a non-linear relationship. The government needs policy guidelines to further boost FDI inflow due to its positive aspects. However, to reduce the negative effect on the environment and human morality, the extensive usage of RE should be adopted. Indeed, proper legislation for foreign firms might be a good step toward quality environmental and longevity of human health in society.

scholarly journals The association between ambient air pollution and scarlet fever in Qingdao, China, 2014-2018: a quantitative analysis

2020 ◽  
Author(s):  
Xiaowen Hu ◽  
Tao Wei ◽  
Yalin Han ◽  
Jing Jia ◽  
Bei Pan ◽  
...  
Keyword(s):  
Air Pollution ◽  
Scarlet Fever ◽  
Mixed Model ◽  
Linear Time ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Lag Effects ◽  
Distributed Lag ◽  
Non Linear ◽  
Air Pollutions

Abstract Background: We conducted a distributed lag non-linear time series analysis to quantify the association between air pollution and scarlet fever in Qingdao city during 2014-2018. Methods: A generalized additive Mixed Model (GAMM) combined with a distributed lag non-linear model (DLNM) was applied to quantify the distributed lag effects of air pollutions on scarlet fever, with daily incidence of scarlet fever as the dependent variable and air pollutions as the independent variable adjusted for potential confounders. Results: A total of 6,316 cases of scarlet fever were notified, and there were 376 days occurring air pollution during the study period. Scarlet fever was significantly associated with air pollutions at a lag of 7 days with different RRs of air pollution degrees (1.172, 95%CI: 1.038-1.323 in mild air pollution; 1.374, 95%CI: 1.078-1.749 in moderate air pollution; 1.610, 95%CI: 1.163-2.314 in severe air pollution; 1.887, 95%CI: 1.163-3.061 in most severe air pollution). Conclusions: Our findings show that air pollution is positively associated with scarlet fever in Qingdao, and the risk of scarlet fever could be increased along with the degrees of air pollution. It contributes to developing strategies to prevent and reduce health impact from scarlet fever and other non-vaccine-preventable respiratory infectious diseases in air polluted areas.

scholarly journals The association between ambient air pollution and scarlet fever in Qingdao, China, 2014-2018: a quantitative analysis

2020 ◽  
Author(s):  
Xiaowen Hu ◽  
Tao Wei ◽  
Yalin Han ◽  
Jing Jia ◽  
Bei Pan ◽  
...  
Keyword(s):  
Air Pollution ◽  
Scarlet Fever ◽  
Mixed Model ◽  
Linear Time ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Lag Effects ◽  
Distributed Lag ◽  
Non Linear ◽  
Air Pollutions

Abstract Background: We conducted a distributed lag non-linear time series analysis to quantify the association between air pollution and scarlet fever in Qingdao city during 2014-2018. Methods: A generalized additive Mixed Model (GAMM) combined with a distributed lag non-linear model (DLNM) was applied to quantify the distributed lag effects of air pollutions on scarlet fever, with daily incidence of scarlet fever as the dependent variable and air pollutions as the independent variable adjusted for potential confounders. Results: A total of 6,316 cases of scarlet fever were notified, and there were 376 days occurring air pollution during the study period. Scarlet fever was significantly associated with air pollutions at a lag of 7 days with different RRs of air pollution degrees (1.172, 95%CI: 1.038-1.323 in mild air pollution; 1.374, 95%CI: 1.078-1.749 in moderate air pollution; 1.610, 95%CI: 1.163-2.314 in severe air pollution; 1.887, 95%CI: 1.163-3.061 in most severe air pollution). Conclusions: Our findings show that air pollution is positively associated with scarlet fever in Qingdao, and the risk of scarlet fever could be increased along with the degrees of air pollution. It contributes to developing strategies to prevent and reduce health impact from scarlet fever and other non-vaccine-preventable respiratory infectious diseases in air polluted areas.

scholarly journals Nexus between foreign direct investment, foreign aid, foreign remittance and economic growth in Bangladesh: Analysis of association

IIUC Studies ◽  
2020 ◽  
Vol 16 ◽  
pp. 77-98
Author(s):  
Shah Asadullah Mohd. Zobair ◽  
Myne Uddin
Keyword(s):  
Economic Growth ◽  
Foreign Direct Investment ◽  
Foreign Aid ◽  
Direct Investment ◽  
Time Series Data ◽  
Competent Authority ◽  
Series Data ◽  
Ardl Approach ◽  
Negative Role ◽  
Effective Use

This study aims at exploring time series data of economic growth indicator and foreign inflow of fund to Bangladesh to investigate the nature of impact of such fund inflows on economic growth. In this regard data has been collected from World Bank data base for a period ranging from 1976 to 2017. The analysis is conducted by using the ARDL approach. The study identified foreign direct investment as a crucial external factor for growth of Bangladeshi economy. But another two mentionable ways of fund inflow such as foreign aid and remittance are found to play negative role in this regard. Along with these findings, this study recommends that the competent authority of Bangladesh should focus on creating more investment friendly environment to attract and ensure continual of foreign investment. Additionally, the study also claims for proper action to ensure effective use of policy and rules to make the best use of foreign aid and ensure enhanced capital formation of the foreign remittance. IIUC Studies Vol.16, December 2019: 77-98

scholarly journals The association between ambient air pollution and scarlet fever in Qingdao, China, 2014–2018: a quantitative analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Fachun Jiang ◽  
Tao Wei ◽  
Xiaowen Hu ◽  
Yalin Han ◽  
Jing Jia ◽  
...  
Keyword(s):  
Air Pollution ◽  
Scarlet Fever ◽  
Mixed Model ◽  
Linear Time ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Lag Effects ◽  
Distributed Lag ◽  
Non Linear ◽  
Air Pollutions

Abstract Background We conducted a distributed lag non-linear time series analysis to quantify the association between air pollution and scarlet fever in Qingdao city during 2014–2018. Methods A distributed lag non-linear model (DLNM) combined with a generalized additive mixed model (GAMM) was applied to quantify the distributed lag effects of air pollutions on scarlet fever, with daily incidence of scarlet fever as the dependent variable and air pollutions as the independent variable adjusted for potential confounders. Results A total of 6316 cases of scarlet fever were notified, and there were 376 days occurring air pollution during the study period. Scarlet fever was significantly associated with air pollutions at a lag of 7 days with different relative risk (RR) of air pollution degrees [1.172, 95% confidence interval (CI): 1.038–1.323 in mild air pollution; 1.374, 95% CI 1.078–1.749 in moderate air pollution; 1.610, 95% CI 1.163–2.314 in severe air pollution; 1.887, 95% CI 1.163–3.061 in most severe air pollution]. Conclusions Our findings show that air pollution is positively associated with scarlet fever in Qingdao, and the risk of scarlet fever could be increased along with the degrees of air pollution. It contributes to developing strategies to prevent and reduce health impact from scarlet fever and other non-vaccine-preventable respiratory infectious diseases in air polluted areas.

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