PM10
Re: PM10
2024 May 9
Residential exposure to air pollution and incidence of leukaemia in the industrial area of Viadana, Northern Italy
https://pubmed.ncbi.nlm.nih.gov/38734295/
Conclusions: This was the first study investigating the link between ambient formaldehyde exposure and leukaemia incidence in the general population. The evidence presented suggests an association, although it remains inconclusive, and a potential significance of emissions related to industrial activities in the district. Further research is warranted in larger populations incorporating data on other potential risk factors.
Residential exposure to air pollution and incidence of leukaemia in the industrial area of Viadana, Northern Italy
https://pubmed.ncbi.nlm.nih.gov/38734295/
Conclusions: This was the first study investigating the link between ambient formaldehyde exposure and leukaemia incidence in the general population. The evidence presented suggests an association, although it remains inconclusive, and a potential significance of emissions related to industrial activities in the district. Further research is warranted in larger populations incorporating data on other potential risk factors.
https://www.eboro.cz
Re: PM10
2024 May 9
Air pollutants, genetic susceptibility, and incident schizophrenia in later life: A prospective study in the UK Biobank
https://pubmed.ncbi.nlm.nih.gov/38734111/
Conclusion: This large-scale, prospective cohort study conveys the first-hand evidence that long-term air pollution exposure could elevate schizophrenia incidence in later life, especially for individuals with higher genetic risks. The findings highlight the importance of improving air quality for preventing the late-onset schizophrenia in an aging era, especially among those with high genetic risks.
Air pollutants, genetic susceptibility, and incident schizophrenia in later life: A prospective study in the UK Biobank
https://pubmed.ncbi.nlm.nih.gov/38734111/
Conclusion: This large-scale, prospective cohort study conveys the first-hand evidence that long-term air pollution exposure could elevate schizophrenia incidence in later life, especially for individuals with higher genetic risks. The findings highlight the importance of improving air quality for preventing the late-onset schizophrenia in an aging era, especially among those with high genetic risks.
https://www.eboro.cz
Re: PM10
2024 May 11
Associations between exposure to various air pollutants and risk of metabolic syndrome: a systematic review and meta-analysis
https://pubmed.ncbi.nlm.nih.gov/38733545/
Conclusion: The findings of this study demonstrate a significant association between exposure to fine particulate matter (PM1, PM2.5, PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and the incidence of metabolic syndrome (MetS). Moreover, the results suggest that air pollution exposure could potentially contribute to the development of MetS in humans.
Associations between exposure to various air pollutants and risk of metabolic syndrome: a systematic review and meta-analysis
https://pubmed.ncbi.nlm.nih.gov/38733545/
Conclusion: The findings of this study demonstrate a significant association between exposure to fine particulate matter (PM1, PM2.5, PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and the incidence of metabolic syndrome (MetS). Moreover, the results suggest that air pollution exposure could potentially contribute to the development of MetS in humans.
https://www.eboro.cz
Re: PM10
2024 May 13
Relationship Between Air Pollutants and the Incidence of Epistaxis in Yangzhou
https://pubmed.ncbi.nlm.nih.gov/38738381/
Conclusion: Epistaxis in the Yangzhou area is more common in males, mostly occurs in 0 to 17 years old, with seasonal. There was also a positive correlation between the incidence of epistaxis and air pollutants in Yangzhou.
Relationship Between Air Pollutants and the Incidence of Epistaxis in Yangzhou
https://pubmed.ncbi.nlm.nih.gov/38738381/
Conclusion: Epistaxis in the Yangzhou area is more common in males, mostly occurs in 0 to 17 years old, with seasonal. There was also a positive correlation between the incidence of epistaxis and air pollutants in Yangzhou.
https://www.eboro.cz
Re: PM10
2024 May 10
Relationship of long-term exposure to air pollutant mixture with metabolic-associated fatty liver disease (MAFLD) and subtypes: A retrospective cohort study of the employed population of Southwest China
https://pubmed.ncbi.nlm.nih.gov/38744043/
Conclusions: Air pollutant mixture was associated with MAFLD, particularly the lean MAFLD subtype. CO played a pivotal role in both overall and overweight/obesity MAFLD, whereas SO42- were associated with lean MAFLD.
Relationship of long-term exposure to air pollutant mixture with metabolic-associated fatty liver disease (MAFLD) and subtypes: A retrospective cohort study of the employed population of Southwest China
https://pubmed.ncbi.nlm.nih.gov/38744043/
Conclusions: Air pollutant mixture was associated with MAFLD, particularly the lean MAFLD subtype. CO played a pivotal role in both overall and overweight/obesity MAFLD, whereas SO42- were associated with lean MAFLD.
https://www.eboro.cz
Re: PM10
2024 May 18
Association between long-term exposure to air pollution and diabetic retinopathy: Evidence from the Fujian Eye Study
https://pubmed.ncbi.nlm.nih.gov/38763052/
Conclusions: These findings showed that long-term exposure to ambient particulate matter and NO2 was associated with a high DR risk in Fujian province, where ambient air pollution is relatively low.
Association between long-term exposure to air pollution and diabetic retinopathy: Evidence from the Fujian Eye Study
https://pubmed.ncbi.nlm.nih.gov/38763052/
Conclusions: These findings showed that long-term exposure to ambient particulate matter and NO2 was associated with a high DR risk in Fujian province, where ambient air pollution is relatively low.
https://www.eboro.cz
Re: PM10
2024 May 21
Long- and Intermediate-Term Ambient Particulate Pollution Is Associated with Increased Osteoarthritis Risk: A Population-Based Prospective Analysis
https://pubmed.ncbi.nlm.nih.gov/38771144/
Abstract
Recent studies found the intrusion and retention of exogenous fine particles into joints, but epidemiological data for long- and intermediate-term exposure associations are scare. Here, all urban working, retired employee, and rural residents (16.78 million) in Beijing from January 1, 2011 to December 31, 2019 were included to investigate the effects of long- and intermediate-term ambient particulate exposure on development of osteoarthritis. We identified 1,742,067 participants as first-visit patients with osteoarthritis. For each interquartile range increase in annual PM2.5 (23.32 μg/m3) and PM10 (23.92 μg/m3) exposure concentration, the pooled hazard ratios were respectively 1.238 (95% CI: 1.228, 1.249) and 1.178 (95% CI: 1.168, 1.189) for first osteoarthritis outpatient visits. Moreover, age at first osteoarthritis outpatient visits significantly decreased by 4.52 (95% CI: 3.45 to 5.40) days per μg/m3 for annual PM2.5 exposure at below 67.85 μg/m3. Finally, among the six constituents analyzed, black carbon appears to be the most important component associated with the association between PM2.5 exposure and the three osteoarthritis-related outcomes.
Long- and Intermediate-Term Ambient Particulate Pollution Is Associated with Increased Osteoarthritis Risk: A Population-Based Prospective Analysis
https://pubmed.ncbi.nlm.nih.gov/38771144/
Abstract
Recent studies found the intrusion and retention of exogenous fine particles into joints, but epidemiological data for long- and intermediate-term exposure associations are scare. Here, all urban working, retired employee, and rural residents (16.78 million) in Beijing from January 1, 2011 to December 31, 2019 were included to investigate the effects of long- and intermediate-term ambient particulate exposure on development of osteoarthritis. We identified 1,742,067 participants as first-visit patients with osteoarthritis. For each interquartile range increase in annual PM2.5 (23.32 μg/m3) and PM10 (23.92 μg/m3) exposure concentration, the pooled hazard ratios were respectively 1.238 (95% CI: 1.228, 1.249) and 1.178 (95% CI: 1.168, 1.189) for first osteoarthritis outpatient visits. Moreover, age at first osteoarthritis outpatient visits significantly decreased by 4.52 (95% CI: 3.45 to 5.40) days per μg/m3 for annual PM2.5 exposure at below 67.85 μg/m3. Finally, among the six constituents analyzed, black carbon appears to be the most important component associated with the association between PM2.5 exposure and the three osteoarthritis-related outcomes.
https://www.eboro.cz
Re: PM10
2024 May 7
Air pollution and mortality for cancer of the respiratory system in Italy: an explainable artificial intelligence approach
https://pubmed.ncbi.nlm.nih.gov/38774048/
Abstract
Respiratory system cancer, encompassing lung, trachea and bronchus cancer, constitute a substantial and evolving public health challenge. Since pollution plays a prominent cause in the development of this disease, identifying which substances are most harmful is fundamental for implementing policies aimed at reducing exposure to these substances. We propose an approach based on explainable artificial intelligence (XAI) based on remote sensing data to identify the factors that most influence the prediction of the standard mortality ratio (SMR) for respiratory system cancer in the Italian provinces using environment and socio-economic data. First of all, we identified 10 clusters of provinces through the study of the SMR variogram. Then, a Random Forest regressor is used for learning a compact representation of data. Finally, we used XAI to identify which features were most important in predicting SMR values. Our machine learning analysis shows that NO, income and O3 are the first three relevant features for the mortality of this type of cancer, and provides a guideline on intervention priorities in reducing risk factors.
Air pollution and mortality for cancer of the respiratory system in Italy: an explainable artificial intelligence approach
https://pubmed.ncbi.nlm.nih.gov/38774048/
Abstract
Respiratory system cancer, encompassing lung, trachea and bronchus cancer, constitute a substantial and evolving public health challenge. Since pollution plays a prominent cause in the development of this disease, identifying which substances are most harmful is fundamental for implementing policies aimed at reducing exposure to these substances. We propose an approach based on explainable artificial intelligence (XAI) based on remote sensing data to identify the factors that most influence the prediction of the standard mortality ratio (SMR) for respiratory system cancer in the Italian provinces using environment and socio-economic data. First of all, we identified 10 clusters of provinces through the study of the SMR variogram. Then, a Random Forest regressor is used for learning a compact representation of data. Finally, we used XAI to identify which features were most important in predicting SMR values. Our machine learning analysis shows that NO, income and O3 are the first three relevant features for the mortality of this type of cancer, and provides a guideline on intervention priorities in reducing risk factors.
https://www.eboro.cz
Re: PM10
2024 May 21
Association between ambient air pollution and dry eye symptoms among Chinese individuals during the COVID-19 pandemic: A national-based study
https://pubmed.ncbi.nlm.nih.gov/38777047/
Conclusion: The association between ambient air pollutants and DES may have been mitigated during the pandemic due to increased time spent indoors. Despite this, our findings support the deleterious health impact of air pollutants. Future urban planning should plan industrial zones further away from residential areas.
Association between ambient air pollution and dry eye symptoms among Chinese individuals during the COVID-19 pandemic: A national-based study
https://pubmed.ncbi.nlm.nih.gov/38777047/
Conclusion: The association between ambient air pollutants and DES may have been mitigated during the pandemic due to increased time spent indoors. Despite this, our findings support the deleterious health impact of air pollutants. Future urban planning should plan industrial zones further away from residential areas.
https://www.eboro.cz
Re: PM10
2024 May 22
Association of outdoor air and noise pollution with unprovoked seizures and new onset epilepsy: A systematic review and meta-analysis
https://pubmed.ncbi.nlm.nih.gov/38776166/
Association of outdoor air and noise pollution with unprovoked seizures and new onset epilepsy: A systematic review and meta-analysis
https://pubmed.ncbi.nlm.nih.gov/38776166/
https://www.eboro.cz
Re: PM10
2024 May 23
University of Pavia, 27100 Pavia, Italy
Continuous Markov Models for Analyzing the Effect of Environmental Personal Exposure on Multiple Sclerosis Progression
Abstract
Multiple sclerosis (MS) is an inflammatory autoimmune demyelinating disorder of the central nervous system, leading to progressive functional impairments. Predicting disease progression with a probabilistic and time-dependent approach might help suggest interventions for a better management of the disease. Recently, there has been increasing focus on the impact of air pollutants as environmental factors influencing disease progression. This study employs a Continuous-Time Markov Model (CMM) to explore the impact of air pollution measurements on MS progression using longitudinal data from MS patients in Italy between 2013 and 2022. Preliminary findings indicate a relationship between air pollution and MS progression, with pollutants like Particulate Matter with a diameter of 10 micrometers (PM10) or 2.5 micrometers (PM2.5), Nitrogen Dioxide (NO2), and Carbon Monoxide (CO) showing potential effects on disease activity.
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Second trimester / O3 .. time ...O3 +PM2,5+Gene, (CCSVI RRMS) + Life Style (stres, ..) = MS - perhaps .. - Petr75
University of Pavia, 27100 Pavia, Italy
Continuous Markov Models for Analyzing the Effect of Environmental Personal Exposure on Multiple Sclerosis Progression
Abstract
Multiple sclerosis (MS) is an inflammatory autoimmune demyelinating disorder of the central nervous system, leading to progressive functional impairments. Predicting disease progression with a probabilistic and time-dependent approach might help suggest interventions for a better management of the disease. Recently, there has been increasing focus on the impact of air pollutants as environmental factors influencing disease progression. This study employs a Continuous-Time Markov Model (CMM) to explore the impact of air pollution measurements on MS progression using longitudinal data from MS patients in Italy between 2013 and 2022. Preliminary findings indicate a relationship between air pollution and MS progression, with pollutants like Particulate Matter with a diameter of 10 micrometers (PM10) or 2.5 micrometers (PM2.5), Nitrogen Dioxide (NO2), and Carbon Monoxide (CO) showing potential effects on disease activity.
------------------------------
Second trimester / O3 .. time ...O3 +PM2,5+Gene, (CCSVI RRMS) + Life Style (stres, ..) = MS - perhaps .. - Petr75
https://www.eboro.cz
Re: PM10
2024 May 23
Effect of fine particulate matter exposure on gestational diabetes mellitus risk: a retrospective cohort study
https://pubmed.ncbi.nlm.nih.gov/38783609/
Conclusions: Our study results suggest that PM2.5 exposure during preconception and the first and second trimesters increases the risk of GDM, with the preconception period appearing to be the critical window for PM2.5 exposure.
Effect of fine particulate matter exposure on gestational diabetes mellitus risk: a retrospective cohort study
https://pubmed.ncbi.nlm.nih.gov/38783609/
Conclusions: Our study results suggest that PM2.5 exposure during preconception and the first and second trimesters increases the risk of GDM, with the preconception period appearing to be the critical window for PM2.5 exposure.
https://www.eboro.cz
Re: PM10
2024 May 24
Association of exposure to ambient air pollutants with cognitive performance and dementia risk and the mediating role of pulmonary function: Evidence from the UK Biobank
https://pubmed.ncbi.nlm.nih.gov/38784975/
Conclusion: Mixed air pollution may impact cognitive function, with PF (pulmonary function) potentially mediating this relationship.
Association of exposure to ambient air pollutants with cognitive performance and dementia risk and the mediating role of pulmonary function: Evidence from the UK Biobank
https://pubmed.ncbi.nlm.nih.gov/38784975/
Conclusion: Mixed air pollution may impact cognitive function, with PF (pulmonary function) potentially mediating this relationship.
https://www.eboro.cz
Re: PM10
2024 Apr 28
Decadal Trends in Ambient Air Pollutants and Their Association with COPD and Lung Cancer in Upper Northern Thailand: 2013-2022
https://pubmed.ncbi.nlm.nih.gov/38787100/
Decadal Trends in Ambient Air Pollutants and Their Association with COPD and Lung Cancer in Upper Northern Thailand: 2013-2022
https://pubmed.ncbi.nlm.nih.gov/38787100/
https://www.eboro.cz