Association of Changes in Air Quality With Incident Asthma in Children in California, 1993-2014

Garcia, Erika; Berhane, Kiros; Islam, Talat; McConnell, Rob; Urman, Robert; Chen, Zhanghua; Gilliland, Frank D.

doi:10.1001/jama.2019.5357

Cited by 139 publications

(110 citation statements)

References 37 publications

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“…Other significant differences were found between grids without monitors and grids with monitors for poverty percent and population density for all case and control groups (all p's ≤ 0.05). Monitor-No 6.0 (5.9-6.1) * 6.0 (6.0-6.1) * 6.4 (6.3-6.5) * 6.4 (6.3-6.4) * 4 Significant difference between no monitor versus monitor within poverty, p ≤ 0.05. 5 Significant difference between no monitor versus monitor within population density (Population, L 10 ), p ≤ 0.05.…”

Section: Cases and Controlsmentioning

confidence: 99%

“…The adverse effects of PM 2.5 on the respiratory-cardiovascular system have been repeatedly confirmed [1][2][3][4][5][6][7][8][9][10][11][12]. Epidemiologic studies that assess exposure risk to different ambient PM 2.5 concentration levels have relied on the U.S. Environmental Protection Agency's (EPA) network of ground-based ambient air pollutant monitors [4,[13][14][15][16]. Ambient air monitors are not equally spatially distributed, and most make measurements every 3 or 6 days [13,[16][17][18].…”

Section: Introductionmentioning

confidence: 99%

“…Significance was evaluated with the Chi Square test: * = p ≤ 0.05; † = p ≤ 0.01 3. Significant age group differences between ED asthma cases and IP asthma cases, p ≤ 0.01 4. Significant age group differences between ED asthma controls and IP asthma controls, p ≤ 0.01 5.…”

mentioning

confidence: 99%

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Contribution of Satellite-Derived Aerosol Optical Depth PM2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland

et al. 2020

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The fine particulate matter baseline (PMB), which includes PM 2.5 monitor readings fused with Community Multiscale Air Quality (CMAQ) model predictions, using the Hierarchical Bayesian Model (HBM), is less accurate in rural areas without monitors. To address this issue, an upgraded HBM was used to form four experimental aerosol optical depth (AOD)-PM 2.5 concentration surfaces. A case-crossover design and conditional logistic regression evaluated the contribution of the AOD-PM 2.5 surfaces and PMB to four respiratory-cardiovascular hospital events in all 99 12 km 2 CMAQ grids, and in grids with and without ambient air monitors. For all four health outcomes, only two AOD-PM 2.5 surfaces, one not kriged (PMC) and the other kriged (PMCK), had significantly higher Odds Ratios (ORs) on lag days 0, 1, and 01 than PMB in all grids, and in grids without monitors. In grids with monitors, emergency department (ED) asthma PMCK on lag days 0, 1 and 01 and inpatient (IP) heart failure (HF) PMCK ORs on lag days 01 were significantly higher than PMB ORs. Warm season ORs were significantly higher than cold season ORs. Independent confirmation of these results should include AOD-PM 2.5 concentration surfaces with greater temporal-spatial resolution, now easily available from geostationary satellites, such as GOES-16 and GOES-17.In urban areas, PMB gives more "weight" to PM 2.5 monitor readings than CMAQ PM 2.5 model predictions. In rural areas, CMAQ PM 2.5 model predictions exert more influence than PM 2.5 monitor readings on PMB, since there are fewer monitors or no monitors. Ambient air monitors are usually found in urban areas. In the last 15 years, PMB has turned out to be a more representative PM 2.5 concentration surface, compared to the interpolation of PM 2.5 monitor data, as a method to resolve spatial gaps between ambient air monitors [16,18,22]. CDC subsequently incorporated PMB into its Environmental Public Health Tracking (EPHT) network of state and New York City partners [16,18,22,26]. To date, PMB has been used by federal and state epidemiologists completing EPHT projects in different parts of the US [16,18,22,26].Within this decade, the availability and use of satellite AOD data have become more routine [6,16,[27][28][29][30][31]. Newer generation satellite instruments measure AOD with increased temporal accuracy and finer spatial resolution [27,[32][33][34][35][36][37]. AOD is a unitless measure of the scattering and absorption of visible light by aerosols (particles) in the atmosphere [38][39][40]. AOD data are, by definition, actual physical measurements, an improvement over CMAQ PM 2.5 model predictions. Once AOD unitless measurements have been calibrated with actual PM 2.5 readings from on-the-ground ambient air monitors, it is then possible to utilize the derived AOD-PM 2.5 concentration readings to estimate actual ambient PM 2.5 concentration in areas where there are no on-the-ground air monitors. The relationship between AOD measurements and on-the-ground measurements of PM 2.5 concentration readings has b...

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Section: Cases and Controlsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Contribution of Satellite-Derived Aerosol Optical Depth PM2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland

et al. 2020

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“…On average, approximately 25-30% of PM 2.5 in the region is attributed to primary vehicle emissions and~15% to other mobile sources, as well as a similar contribution from stationary sources (e.g., industrial facilities) [9,10]. Children are particularly vulnerable to the adverse impacts of ambient air pollution, in part due their rapid growth, developmental vulnerability, greater exposure to air pollutants compared with adults, and immature immune systems [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Youth Engaged Participatory Air Monitoring: A ‘Day in the Life’ in Urban Environmental Justice Communities

Johnston

Juarez

Navarro³

et al. 2019

IJERPH

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Air pollution in Southern California does not impact all communities equally; communities of color are disproportionately burdened by poor air quality and more likely to live near industrial facilities and freeways. Government regulatory monitors do not have the spatial resolution to provide air quality information at the neighborhood or personal scale. We describe the A Day in the Life program, an approach to participatory air monitoring that engages youth in collecting data that they can then analyze and use to take action. Academics partnered with Los Angeles-based youth environmental justice organizations to combine personal air monitoring, participatory science, and digital storytelling to build capacity to address local air quality issues. Eighteen youth participants from four different neighborhoods wore portable personal PM2.5 (fine particles <2.5 µm in diameter) monitors for a day in each of their respective communities, documenting and mapping their exposure to PM2.5 during their daily routine. Air monitoring was coupled with photography and videos to document what they experienced over the course of their day. The PM2.5 exposure during the day for participants averaged 10.7 µg/m3, although the range stretched from <1 to 180 µg/m3. One-third of all measurements were taken <300 m from a freeway. Overall, we demonstrate a method to increase local youth-centered understanding of personal exposures, pollution sources, and vulnerability to air quality.

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“…The prevalence of asthma has been increasing worldwide for at least three decades, without any definite reason. Recent evidence suggested that this increase of asthma cases might be linked to urban air pollution, with the fact that more and more people are attracted to living in cities [1][2][3][4][5]. According to the WHO, 30% of all child deaths before the age of 5 were due to asthma caused by polluted air (http://www.who.int/mediacentre/news/releases/2017/pollution-child-death/en/).…”

Section: Introductionmentioning

confidence: 99%

Immunologic and Non-Immunologic Mechanisms Leading to Airway Remodeling in Asthma

Fang

Sun

Roth

2020

IJMS

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Asthma increases worldwide without any definite reason and patient numbers double every 10 years. Drugs used for asthma therapy relax the muscles and reduce inflammation, but none of them inhibited airway wall remodeling in clinical studies. Airway wall remodeling can either be induced through pro-inflammatory cytokines released by immune cells, or direct binding of IgE to smooth muscle cells, or non-immunological stimuli. Increasing evidence suggests that airway wall remodeling is initiated early in life by epigenetic events that lead to cell type specific pathologies, and modulate the interaction between epithelial and sub-epithelial cells. Animal models are only available for remodeling in allergic asthma, but none for non-allergic asthma. In human asthma, the mechanisms leading to airway wall remodeling are not well understood. In order to improve the understanding of this asthma pathology, the definition of “remodeling” needs to be better specified as it summarizes a wide range of tissue structural changes. Second, it needs to be assessed if specific remodeling patterns occur in specific asthma pheno- or endo-types. Third, the interaction of the immune cells with tissue forming cells needs to be assessed in both directions; e.g., do immune cells always stimulate tissue cells or are inflamed tissue cells calling immune cells to the rescue? This review aims to provide an overview on immunologic and non-immunologic mechanisms controlling airway wall remodeling in asthma.

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Association of Changes in Air Quality With Incident Asthma in Children in California, 1993-2014

Cited by 139 publications

References 37 publications

Contribution of Satellite-Derived Aerosol Optical Depth PM2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland

Contribution of Satellite-Derived Aerosol Optical Depth PM2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland

Youth Engaged Participatory Air Monitoring: A ‘Day in the Life’ in Urban Environmental Justice Communities

Immunologic and Non-Immunologic Mechanisms Leading to Airway Remodeling in Asthma

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