Impact of air pollution in Mymensingh city of Bangladesh: focusing peoples’ perception

2021 ◽  
Vol 31 (3) ◽  
pp. 154-163
Author(s):  
MA Mondol ◽  
M Hossain ◽  
S Sultana ◽  
MA Islam ◽  
P Biswas
Keyword(s):  
Air Pollution ◽  
Family Size ◽  
Significant Relationship ◽  
Air Pollutants ◽  
Correlation Coefficients ◽  
Educational Qualification ◽  
Independent Variables ◽  
Study Sites ◽  
The Impact ◽  
The Relationship

The present study was conducted to investigate the impact of air pollution in some selected areas of Mymensingh city. The relationship between independent variables (age, educational qualification, family size and communication exposure) with the basic idea and impact of air pollution (dependent variable) was investigated in this study. To conduct the study, two hundred (200) respondents were selected randomly from four study sites under Mymensingh city. Pearson's product-moment correlation coefficients were analyzed to examine the relationship between the concerned variables. The findings revealed that 87.5% people have basic idea and 12.5% people have no idea about air pollution. About half (46%) of the peoples had high impact, 34% had medium and 20% had low impact because of air pollution. Out of four independent variables, three variables such as educational qualification and communication exposure had positive and significant relationship, age had negative but significant relationship and family size had non-significant relationship with their perception and awareness of air pollution. Further assessment on different air pollutants in the study area may explore the original status of air pollution and their impact on environment as well as on livelihood. Progressive Agriculture 31 (3): 154-163, 2020

scholarly journals People’s perception and awareness on air pollution in rural and urban areas of Mymensingh Sadar upazila

2018 ◽  
Vol 29 (1) ◽  
pp. 22-32
Author(s):  
R Sarker ◽  
M Yeasmin ◽  
MA Rahman ◽  
MA Islam
Keyword(s):  
Air Pollution ◽  
Family Size ◽  
Significant Relationship ◽  
Rural Areas ◽  
Urban Areas ◽  
Correlation Coefficients ◽  
Educational Qualification ◽  
Independent Variables ◽  
Rural And Urban Areas ◽  
The Relationship

The present study was conducted to investigate peoples’ perception level and awareness of air pollution in some selected areas of Mymensingh sadar upazila. The relationship of independent variables (age, educational qualification, family size, residence and communication exposure) with the peoples’ perception level and awareness of air pollution (dependent variable) was done to understand the objectives of the study. Six Hundreds (600) respondents were selected randomly from six study sites under Mymensingh sadar upazila for collecting data during the period of Jan 2016-April, 2017. Pearson’s product-moment correlation coefficients were computed to examine the relationship between the concerned variables. The findings revealed that about half (46.67 percent) of the peoples had medium perception and awareness, 31.67 percent had low and 21.67 percent had high perception and awareness about air pollution. In rural areas, 43.33 percent respondents had low, 50.00 percent had medium and only 6.67 percent had high perception and awareness of air pollution. In urban areas, 20.00 percent respondents had low, 43.33 percent had medium and 36.67 percent had high perception and awareness of air pollution. Majority of the respondents (93.33 percent) were lacking of proper awareness of air pollution in rural areas while 63.33 percent in urban areas. Out of five independent variables, three variables such as educational qualification, residence and communication exposure had positive and significant relationship, age had negative and significant relationship and family size had no relationship with their perception and awareness of air pollution.Progressive Agriculture 29 (1): 22-32, 2018

scholarly journals The modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo, China

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Rui Zhang ◽  
Yujie Meng ◽  
Hejia Song ◽  
Ran Niu ◽  
Yu Wang ◽  
...  
Keyword(s):  
Air Pollution ◽  
High Temperature ◽  
Air Pollutants ◽  
Meteorological Data ◽  
Effect Of Temperature ◽  
Distributed Lag ◽  
Modification Effect ◽  
Incidence Risk ◽  
The Impact ◽  
The Relationship

Abstract Background Although exposure to air pollution has been linked to many health issues, few studies have quantified the modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo, China. Methods The data of daily incidence of influenza and the relevant meteorological data and air pollution data in Ningbo from 2014 to 2017 were retrieved. Low, medium and high temperature layers were stratified by the daily mean temperature with 25th and 75th percentiles. The potential modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo was investigated through analyzing the effects of air pollutants stratified by temperature stratum using distributed lag non-linear model (DLNM). Stratified analysis by sex and age were also conducted. Results Overall, a 10 μg/m3 increment of O3, PM2.5, PM10 and NO2 could increase the incidence risk of influenza with the cumulative relative risk of 1.028 (95% CI 1.007, 1.050), 1.061 (95% CI 1.004, 1.122), 1.043 (95% CI 1.003, 1.085), and 1.118 (95% CI 1.028, 1.216), respectively. Male and aged 7–17 years were more sensitive to air pollutants. Through the temperature stratification analysis, we found that temperature could modify the impacts of air pollution on daily incidence of influenza with high temperature exacerbating the impact of air pollutants. At high temperature layer, male and the groups aged 0–6 years and 18–64 years were more sensitive to air pollution. Conclusion Temperature modified the relationship between air pollution and daily incidence of influenza and high temperature would exacerbate the effects of air pollutants in Ningbo.

Relationship between Air Pollutants and Visibility in Shanghai during 2006-2010

2014 ◽  
Vol 675-677 ◽  
pp. 314-317
Author(s):  
Dan Xue ◽  
Qian Liu
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Air Pollutants ◽  
Correlation Coefficients ◽  
Mean Value ◽  
Secondary Pollutants ◽  
The Mean ◽  
The Relationship

Air pollution has been deteriorated seriously in Shanghai as a result of urbanization and modernization. Visibility reduction is the most apparent symptom of air pollution. This paper aims to describe the characteristics of visibility and air pollutants in Shanghai, and to investigate the relationship between them. Visibility in Shanghai was higher in summer and lower in winter. The mean value of visibility during 2006-2010 was 17.8km. Air pollution in Shanghai was also serious. In 2010, Shanghai got the relative better air quality compared with the former four years. Air pollutants and visibility were negatively correlated. SO2 and NO2 had higher correlation coefficients with visibility than PM10. This suggested that the visibility in Shanghai was mainly due to secondary pollutants.

scholarly journals Relationship Between Air Pollution and the Concentration of Nitric Oxide in the Exhaled Air (FeNO) in 8–9-Year-Old School Children in Krakow

2021 ◽  
Vol 18 (13) ◽  
pp. 6690
Author(s):  
Marta Czubaj-Kowal ◽  
Ryszard Kurzawa ◽  
Henryk Mazurek ◽  
Michał Sokołowski ◽  
Teresa Friediger ◽  
...  
Keyword(s):  
Nitric Oxide ◽  
Air Pollution ◽  
Air Pollutants ◽  
Primary Schools ◽  
Significant Relationships ◽  
Exhaled Air ◽  
Nitric Oxide Concentration ◽  
Positive Correlations ◽  
The Impact ◽  
The Relationship

The consequences of air pollution pose one of the most serious threats to human health, and especially impact children from large agglomerations. The measurement of nitric oxide concentration in exhaled air (FeNO) is a valuable biomarker in detecting and monitoring airway inflammation. However, only a few studies have assessed the relationship between FeNO and the level of air pollution. The study aims to estimate the concentration of FeNO in the population of children aged 8–9 attending the third grade of public primary schools in Krakow, as well as to determine the relationship between FeNO concentration and dust and gaseous air pollutants. The research included 4580 children aged 8–9 years who had two FeNO measurements in the winter–autumn and spring–summer periods. The degree of air pollution was obtained from the Regional Inspectorate of Environmental Protection in Krakow. The concentration of pollutants was obtained from three measurement stations located in different parts of the city. The FeNO results were related to air pollution parameters. The study showed weak but significant relationships between FeNO and air pollution parameters. The most significant positive correlations were found for CO8h (r = 0.1491, p < 0.001), C6H6 (r = 0.1420, p < 0.001), PM10 (r = 0.1054, p < 0.001) and PM2.5 (r = 0.1112, p < 0.001). We suggest that particulate and gaseous air pollutants impact FeNO concentration in children aged 8–9 years. More research is needed to assess the impact of air pollution on FeNO concentration in children. The results of such studies could help to explain the increase in the number of allergic and respiratory diseases seen in children in recent decades.

scholarly journals The relationship between air pollutants and COVID-19 cases and its implications for air quality in Jakarta, Indonesia

2021 ◽  
Vol 11 (1) ◽  
pp. 93-100
Author(s):  
Muhammad Rendana ◽  
Leily Nurul Komariah
Keyword(s):  
Air Pollution ◽  
Air Pollutants ◽  
Large Scale ◽  
Control Method ◽  
Pollution Index ◽  
Ambient Air ◽  
World Health ◽  
Air Pollution Index ◽  
The Impact ◽  
The Relationship

World Health Organization (WHO) has announced that COVID-19 as a global pandemic and public health emergency. Previous studies have revealed that COVID-19 was an infectious disease and it could remain viable in ambient air for hours. Therefore, this study aims to examine the correlation between air pollutants (PM2.5, PM10, CO, SO2, NO2 and O3) and COVID-19 spread in Jakarta, Indonesia. Furthermore, this study also evaluates the impact of large-scale social restriction (LSSR) on air pollution index (API). Result of study found that air pollution index of PM2.5, PM10, CO, SO2 and NO2 decreased by 9.48%, 15.74%, 29.17%, 6.26% and 18.34% during LSSR period. While, for O3 showed an increase by 4.06%. Another result also found significantly positive correlations of SO2, CO and PM2.5 with COVID-19 cases. An exposure to SO2, CO and PM2.5 has driven the area become vulnerable for COVID-19 infection. Our findings indicated that the relationship between air pollutants and COVID-19 spread could provide a new notion for precaution and control method of COVID-19 outbreak.

Air pollution increases the risk of pulmonary embolism: a meta-analysis

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Huangtai Miao ◽  
Xiaoying Li ◽  
Xiao Wang ◽  
Shaoping Nie
Keyword(s):  
Air Pollution ◽  
Pulmonary Embolism ◽  
Air Pollutants ◽  
Respiratory Diseases ◽  
Web Of Science ◽  
Meta Analysis ◽  
Inclusion Criteria ◽  
Increased Risk ◽  
The Impact ◽  
The Relationship

Abstract Objectives Air pollution can lead to many cardiovascular and respiratory diseases, but the impact of air pollution on pulmonary embolism is still uncertain. We conducted a meta-analysis to assess the relationship between air pollution and pulmonary embolism. Content We searched PubMed, EMBASE, Web of Science, and the Cochran Library for citations on air pollutants (carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone and particulate matter) and pulmonary embolism. A total of nine citations met the inclusion criteria. There is no evidence of bias. CO, SO2, PM10 and PM2.5 had no significant effect on the occurrence of pulmonary embolism. NO2 and O3 can increase the risk of pulmonary embolism to a small extent. Summary This meta-analysis suggests that some air pollutants are associated with an increased risk of pulmonary embolism. Outlook Reducing air pollution and improving air quality can effectively reduce the risk of pulmonary embolism.

scholarly journals The Impact of the Synergistic Effect of Temperature and Air Pollutants on Chronic Lung Diseases in Subtropical Taiwan

2021 ◽  
Vol 11 (8) ◽  
pp. 819
Author(s):  
Da-Wei Wu ◽  
Szu-Chia Chen ◽  
Hung-Pin Tu ◽  
Chih-Wen Wang ◽  
Chih-Hsing Hung ◽  
...  
Keyword(s):  
Air Pollution ◽  
Lung Disease ◽  
Air Pollutants ◽  
Lung Diseases ◽  
Environmental Parameters ◽  
Effect Of Temperature ◽  
Cross Sectional ◽  
Chronic Lung Diseases ◽  
The Impact ◽  
The Relationship

Previous studies have suggested an association between air pollution and lung disease. However, few studies have explored the relationship between chronic lung diseases classified by lung function and environmental parameters. This study aimed to comprehensively investigate the relationship between chronic lung diseases, air pollution, meteorological factors, and anthropometric indices. We conducted a cross-sectional study using the Taiwan Biobank and the Taiwan Air Quality Monitoring Database. A total of 2889 participants were included. We found a V/U-shaped relationship between temperature and air pollutants, with significant effects at both high and low temperatures. In addition, at lower temperatures (<24.6 °C), air pollutants including carbon monoxide (CO) (adjusted OR (aOR):1.78/Log 1 ppb, 95% CI 0.98–3.25; aOR:5.35/Log 1 ppb, 95% CI 2.88–9.94), nitrogen monoxide (NO) (aOR:1.05/ppm, 95% CI 1.01–1.09; aOR:1.11/ppm, 95% CI 1.07–1.15), nitrogen oxides (NOx) (aOR:1.02/ppm, 95% CI 1.00–1.05; aOR:1.06/ppm, 95% CI 1.04–1.08), and sulfur dioxide (SO2) (aOR:1.29/ppm, 95% CI 1.01–1.65; aOR:1.77/ppm, 95% CI 1.36–2.30) were associated with restrictive and mixed lung diseases, respectively. Exposure to CO, NO, NO2, NOx and SO2 significantly affected obstructive and mixed lung disease in southern Taiwan. In conclusion, temperature and air pollution should be considered together when evaluating the impact on chronic lung diseases.

Capital Structure and Earnings per Share: An Empirical Analysis of Indian Corporate Sector

2015 ◽  
Vol 5 (3) ◽  
Author(s):  
Harvinder Singh Mand ◽  
Manjit Singh
Keyword(s):  
Capital Structure ◽  
Empirical Analysis ◽  
Corporate Sector ◽  
Independent Variables ◽  
Earnings Per Share ◽  
Panel Data Regression ◽  
Data Regression ◽  
The Impact ◽  
The Relationship ◽  
The Empirical Analysis

This paper intends to measure the impact of capital structure on EPS (earnings per share) in Indian corporate sector. Fifteen control variables along with capital structure have been selected to know their impact on EPS. Panel data regression has been applied to establish the relationship among dependent and independent variables. It is found from the empirical analysis that the relation of capital structure with EPS has been statistically insignificant in Indian corporate sector among all specific industries except telecommunication industry. The results are consistent with Modigliani-Miller approach.

scholarly journals Be Aware of Burnout! The Role of Changes in Academic Burnout in Problematic Facebook Usage among University Students

2021 ◽  
Vol 18 (15) ◽  
pp. 8055
Author(s):  
Katarzyna Tomaszek ◽  
Agnieszka Muchacka-Cymerman
Keyword(s):  
Regression Coefficient ◽  
Population Sample ◽  
Cross Sectional ◽  
Academic Burnout ◽  
Independent Variables ◽  
Social Motive ◽  
Explained Variance ◽  
The Impact ◽  
The Relationship

Most previous research has examined the relationship between FB addiction and burnout level by conducting cross-sectional studies. Little is known about the impact of changes in burnout on FB addiction in an educational context. Through a two-way longitudinal survey of a student population sample (N = 115), this study examined the influence of changes in academic burnout over time and FB motives and importance (measured at the beginning and the end of the semester) on FB intrusion measured at the end of the academic semester. The findings show that: (1) increases in cynicism and in FB motives and importance significantly predicted time2 FB intrusion; (2) FB importance enhanced the prediction power of changes in the academic burnout total score, exhaustion and personal inefficacy, and reduced the regression coefficient of changes in cynicism; (3) the interaction effects between FB social motive use and changes in academic burnout, as well as between FB importance and personal inefficacy and exhaustion, accounted for a significant change in the explained variance of time2 FB intrusion. About 20–30% of the variance in time2 FB intrusion was explained by all the examined variables and by the interactions between them. The results suggest that changes in academic burnout and FB motives and importance are suppressive variables, as including these variables in the regression model all together changed the significance of the relationship between independent variables and FB intrusion.

scholarly journals A Student’s Guide to the Classification and Operationalization of Variables in the Conceptualization and Design of a Clinical Study: Part 1

2021 ◽  
Vol 43 (2) ◽  
pp. 177-179 ◽  
Author(s):  
Chittaranjan Andrade
Keyword(s):  
Clinical Study ◽  
Significant Relationship ◽  
Research Experience ◽  
Process Variables ◽  
Know How ◽  
Independent Variables ◽  
Cause And Effect ◽  
Confounding Variables ◽  
Dependent Variables ◽  
The Relationship

Students without prior research experience may not know how to conceptualize and design a study. This article explains how an understanding of the classification and operationalization of variables is the key to the process. Variables describe aspects of the sample that is under study; they are so called because they vary in value from subject to subject in the sample. Variables may be independent or dependent. Independent variables influence the value of other variables; dependent variables are influenced in value by other variables. A hypothesis states an expected relationship between variables. A significant relationship between an independent and dependent variable does not prove cause and effect; the relationship may partly or wholly be explained by one or more confounding variables. Variables need to be operationalized; that is, defined in a way that permits their accurate measurement. These and other concepts are explained with the help of clinically relevant examples.

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