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Article ; Online: A geospatial assessment of industrial releases and pediatric neuroblastic tumours at diagnosis: A retrospective case series.

Tambasco, Domenica / Franklin, Meredith / Harris, Shelley A / Tibout, Pauline / Doria, Andrea S

Archives of environmental & occupational health

2024 Volume 78, Issue 9-10, Page(s) 455–470

Abstract: Environmental risk factors associated with malignancy of pediatric neuroblastic tumours are not well-known and few studies have examined the relationship between industrial emissions and neuroblastic tumour diagnosis. A retrospective case series of 310 ... ...

Abstract	Environmental risk factors associated with malignancy of pediatric neuroblastic tumours are not well-known and few studies have examined the relationship between industrial emissions and neuroblastic tumour diagnosis. A retrospective case series of 310 patients was evaluated at a tertiary hospital in Toronto, Canada between January 2008, and December 2018. Data from the National Pollutant Release Inventory (NPRI) were used to estimate exposure for a dozen chemicals with known or suspected carcinogenicity or embryotoxicity. Comparative analysis and predictive logistic regression models for malignant versus benign neuroblastic tumours included variables for residential proximity, number, and type of industries, mean total emissions within 2 km, and inverse distance weighted (IDW) quantity of chemical-specific industrial emissions estimated within 10 and 50 km of cases. No significant difference was seen between malignant and benign cases with respect to the mean nearest residential distance to industry, the number or type of industry, or the mean total quantity of industrial emissions within a 2 km radius of residential location of cases. However, there were statistically significant differences in the interpolated IDW emissions of dioxins and furans released between 1993 and 2019 within 10 km. Concentrations were significantly higher in malignant neuroblastic tumours at 1.65 grams (g) toxic equivalent (TEQ) (SD 2.01 g TEQ) compared to benign neuroblastic tumours at 1.13 g TEQ (SD 0.84 g TEQ) (
MeSH term(s)	Child ; Humans ; Retrospective Studies ; Benzene ; Neoplasms ; Environmental Pollutants ; Dioxins
Chemical Substances	Benzene (J64922108F) ; Environmental Pollutants ; Dioxins
Language	English
Publishing date	2024-02-07
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2245323-4
ISSN	2154-4700 ; 1933-8244 ; 0003-9896
ISSN (online)	2154-4700
ISSN	1933-8244 ; 0003-9896
DOI	10.1080/19338244.2023.2291734
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Article ; Online: Zhong et al. Respond to "There's No Place Like Home".

Zhong, Charlie / Franklin, Meredith / Wang, Sophia S / Longcore, Travis

American journal of epidemiology

2022 Volume 191, Issue 9, Page(s) 1544–1545

Language	English
Publishing date	2022-05-10
Publishing country	United States
Document type	Journal Article ; Comment
ZDB-ID	2937-3
ISSN	1476-6256 ; 0002-9262
ISSN (online)	1476-6256
ISSN	0002-9262
DOI	10.1093/aje/kwac085
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Article: Exposure models for particulate matter elemental concentrations in Southern California

Yin, Xiaozhe / Franklin, Meredith / Fallah-Shorshani, Masoud / Shafer, Martin / McConnell, Rob / Fruin, Scott

Environment international. 2022 Apr. 12,

2022

Abstract: Due to a scarcity of routine monitoring of speciated particulate matter (PM), there has been limited capability to develop exposure models that robustly estimate component-specific concentrations that are able to capture small-scale spatial variability ... ...

Abstract	Due to a scarcity of routine monitoring of speciated particulate matter (PM), there has been limited capability to develop exposure models that robustly estimate component-specific concentrations that are able to capture small-scale spatial variability near sources. This paper presents the largest such study conducted in a single urban area. Using samples that were collected at 220 locations over two seasons, quasi-ultrafine (PM₀.₂), accumulation mode fine (PM₀.₂₋₂.₅), and coarse (PM₂.₅₋₁₀) particulate matter concentrations were used to develop spatiotemporal regression, random forest, extreme gradient boosting and neural network models that enabled predictions of 24 elemental components in eight Southern California communities. We used supervised variable selection of over 150 variables, largely from publicly available sources, including meteorological, roadway and traffic characteristics, land use, and dispersion model estimates of traffic emissions. PM components that have high oxidative potential (and potentially large health effects) or are otherwise important markers for major PM sources were the primary focus. We present results for copper, iron, and zinc (as non-tailpipe vehicle emissions); elemental carbon (diesel emissions); vanadium (ship emissions); calcium (soil dust); and sodium (sea salt). Spatiotemporal linear regression models with 17 to 36 predictor variables including meteorology; distance to different classifications of roads; intersections and off ramps within a given buffer distance; truck and vehicle traffic volumes; and near-roadway dispersion model estimates produced superior predictions over the machine learning approaches (cross validation R-squares ranged from 0.76 to 0.92). Our models are easily interpretable and appear to have more effectively captured spatial gradients in the metallic portion of PM than other comparably large studies, particularly near roadways for the non-tailpipe emissions. Furthermore, we demonstrated the importance of including spatiotemporally resolved meteorology in our models as it helped to provide key insights into spatial patterns and allowed us to make temporal predictions.
Keywords	calcium ; carbon ; copper ; dust ; environment ; iron ; land use ; meteorology ; particulates ; regression analysis ; roads ; sodium ; soil ; traffic ; urban areas ; vanadium ; zinc ; California
Language	English
Dates of publication	2022-0412
Publishing place	Elsevier Ltd
Document type	Article
Note	Pre-press version
ZDB-ID	554791-x
ISSN	1873-6750 ; 0160-4120
ISSN (online)	1873-6750
ISSN	0160-4120
DOI	10.1016/j.envint.2022.107247
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Article: Satellite-Derived PM2.5 Composition and Its Differential Effect on Children’s Lung Function

Chau, Khang / Franklin, Meredith / Gauderman, W. James

Remote Sensing. 2020 Mar. 23, v. 12, no. 6

2020

Abstract: Studies of the association between air pollution and children’s health typically rely on fixed-site monitors to determine exposures, which have spatial and temporal limitations. Satellite observations of aerosols provide the coverage that fixed-site ... ...

Abstract	Studies of the association between air pollution and children’s health typically rely on fixed-site monitors to determine exposures, which have spatial and temporal limitations. Satellite observations of aerosols provide the coverage that fixed-site monitors lack, enabling more refined exposure assessments. Using aerosol optical depth (AOD) data from the Multiangle Imaging SpectroRadiometer (MISR) instrument, we predicted fine particulate matter, PM 2.5 , and PM 2.5 speciation concentrations and linked them to the residential locations of 1206 children enrolled in the Southern California Children’s Health Study. We fitted mixed-effects models to examine the relationship between the MISR-derived exposure estimates and lung function, measured as forced expiratory volume in 1 second (FEV 1) and forced vital capacity (FVC), adjusting for study community and biological factors. Gradient Boosting and Support Vector Machines showed excellent predictive performance for PM 2.5 (test R 2 = 0.68) and its chemical components (test R 2 = –0.71). In single-pollutant models, FEV 1 decreased by 131 mL (95% CI: - 232 , - 35) per 10.7-µg/m 3 increase in PM 2.5 , by 158 mL (95% CI: - 273 , - 43) per 1.2-µg/m 3 in sulfates (SO 4 2 -), and by 177 mL (95% CI: - 306 , - 56) per 1.6-µg/m 3 increase in dust; FVC decreased by 175 mL (95% CI: - 310 , - 29) per 1.2-µg/m 3 increase in SO 4 2 - and by 212 mL (95% CI: - 391 , - 28) per 2.5-µg/m 3 increase in nitrates (NO 3 -). These results demonstrate that satellite observations can strengthen epidemiological studies investigating air pollution health effects by providing spatially and temporally resolved exposure estimates.
Keywords	aerosols ; air pollution ; child health ; children ; dust ; epidemiological studies ; health effects assessments ; image analysis ; lung function ; models ; nitrates ; particulates ; remote sensing ; satellites ; spectroradiometers ; sulfates ; support vector machines ; California
Language	English
Dates of publication	2020-0323
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2513863-7
ISSN	2072-4292
ISSN	2072-4292
DOI	10.3390/rs12061028
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Article ; Online: Predicting ambient PM

Enebish, Temuulen / Chau, Khang / Jadamba, Batbayar / Franklin, Meredith

Journal of exposure science & environmental epidemiology

2020 Volume 31, Issue 4, Page(s) 699–708

Abstract: Background: Accurately assessing individual ambient air pollution exposure is a crucial part of epidemiological studies looking at the adverse health effect of poor air quality. This is particularly challenging in developing countries with high levels ... ...

Abstract	Background: Accurately assessing individual ambient air pollution exposure is a crucial part of epidemiological studies looking at the adverse health effect of poor air quality. This is particularly challenging in developing countries with high levels of air pollution, mostly due to sparse monitoring networks with a lack of consistent data. Methods: We evaluated the performance of six different machine learning algorithms in predicting fine particulate matter (PM Results: Random forest (RF) and gradient boosting models performed the best with leave-one-location-out cross-validated R Conclusion: Our results provide evidence of the advantage and feasibility of machine learning approaches in predicting ambient PM
MeSH term(s)	Air Pollutants/analysis ; Air Pollution/analysis ; Cities ; Environmental Monitoring ; Humans ; Machine Learning ; Mongolia ; Particulate Matter/analysis
Chemical Substances	Air Pollutants ; Particulate Matter
Language	English
Publishing date	2020-08-03
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2218551-3
ISSN	1559-064X ; 1559-0631
ISSN (online)	1559-064X
ISSN	1559-0631
DOI	10.1038/s41370-020-0257-8
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Article ; Online: Estimating traffic noise over a large urban area: An evaluation of methods.

Fallah-Shorshani, Masoud / Yin, Xiaozhe / McConnell, Rob / Fruin, Scott / Franklin, Meredith

Environment international

2022 Volume 170, Page(s) 107583

Abstract: Unlike air pollution, traffic-related noise remains unregulated and has been under-studied despite evidence of its deleterious health impacts. To characterize population exposure to traffic noise, both acoustic-based numerical models and data-driven ... ...

Abstract	Unlike air pollution, traffic-related noise remains unregulated and has been under-studied despite evidence of its deleterious health impacts. To characterize population exposure to traffic noise, both acoustic-based numerical models and data-driven statistical approaches can generate estimates over large urban areas. The aim of this work is to formally compare the performances of the most common traffic noise models by evaluating their estimates for different categories of roads and validating them against a unique dataset of measured noise in Long Beach, California. Specifically, a statistical land use regression model, an extreme gradient boosting machine learning model (XGB), and three numerical/acoustic traffic noise models: the US Noise Model (FHWA-TNM2.5), a commercial noise model (CadnaA), and an open-source European model (Harmonoise) were optimized and compared. The results demonstrate that XGB and CadnaA were the most effective models for estimating traffic noise, and they are particularly adept at differentiating noise levels on different categories of road.
Language	English
Publishing date	2022-10-13
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	554791-x
ISSN	1873-6750 ; 0160-4120
ISSN (online)	1873-6750
ISSN	0160-4120
DOI	10.1016/j.envint.2022.107583
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Article ; Online: Exposure models for particulate matter elemental concentrations in Southern California.

Yin, Xiaozhe / Franklin, Meredith / Fallah-Shorshani, Masoud / Shafer, Martin / McConnell, Rob / Fruin, Scott

Environment international

2022 Volume 165, Page(s) 107247

Abstract: Due to a scarcity of routine monitoring of speciated particulate matter (PM), there has been limited capability to develop exposure models that robustly estimate component-specific concentrations. This paper presents the largest such study conducted in a ...

Abstract	Due to a scarcity of routine monitoring of speciated particulate matter (PM), there has been limited capability to develop exposure models that robustly estimate component-specific concentrations. This paper presents the largest such study conducted in a single urban area. Using samples that were collected at 220 locations over two seasons, quasi-ultrafine (PM
MeSH term(s)	Air Pollutants/analysis ; Air Pollution/analysis ; Environmental Monitoring/methods ; Particulate Matter/analysis ; Vehicle Emissions/analysis
Chemical Substances	Air Pollutants ; Particulate Matter ; Vehicle Emissions
Language	English
Publishing date	2022-04-18
Publishing country	Netherlands
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Extramural
ZDB-ID	554791-x
ISSN	1873-6750 ; 0160-4120
ISSN (online)	1873-6750
ISSN	0160-4120
DOI	10.1016/j.envint.2022.107247
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Article ; Online: Outdoor artificial light at night, air pollution, and risk of childhood acute lymphoblastic leukemia in the California Linkage Study of Early-Onset Cancers.

Zhong, Charlie / Wang, Rong / Morimoto, Libby M / Longcore, Travis / Franklin, Meredith / Rogne, Tormod / Metayer, Catherine / Wiemels, Joseph L / Ma, Xiaomei

Scientific reports

2023 Volume 13, Issue 1, Page(s) 583

Abstract: Acute lymphoblastic leukemia (ALL) is the most common type of cancer in children (age 0-14 years); however, the etiology remains incompletely understood. Several environmental exposures have been linked to risk of childhood ALL, including air pollution. ... ...

Abstract	Acute lymphoblastic leukemia (ALL) is the most common type of cancer in children (age 0-14 years); however, the etiology remains incompletely understood. Several environmental exposures have been linked to risk of childhood ALL, including air pollution. Closely related to air pollution and human development is artificial light at night (ALAN), which is believed to disrupt circadian rhythm and impact health. We sought to evaluate outdoor ALAN and air pollution on risk of childhood ALL. The California Linkage Study of Early-Onset Cancers is a large population-based case-control in California that identifies and links cancer diagnoses from the California Cancer Registry to birth records. For each case, 50 controls with the same year of birth were obtained from birth records. A total of 2,782 ALL cases and 139,100 controls were identified during 2000-2015. ALAN was assessed with the New World Atlas of Artificial Night Sky Brightness and air pollution with an ensemble-based air pollution model of particulate matter smaller than 2.5 microns (PM
MeSH term(s)	Child ; Female ; Humans ; Infant, Newborn ; Infant ; Child, Preschool ; Adolescent ; Light Pollution ; Air Pollution/adverse effects ; Risk Factors ; Particulate Matter/adverse effects ; Environmental Exposure/adverse effects ; Environmental Exposure/analysis ; Precursor Cell Lymphoblastic Leukemia-Lymphoma/epidemiology ; Precursor Cell Lymphoblastic Leukemia-Lymphoma/etiology ; California/epidemiology ; Air Pollutants/analysis
Chemical Substances	Particulate Matter ; Air Pollutants
Language	English
Publishing date	2023-01-11
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, P.H.S.
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-022-23682-z
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Article ; Online: Disparities in greenspace associated with sleep duration among adolescent children in Southern California.

Zhong, Charlie / Yin, Xiaozhe / Fallah-Shorshani, Masoud / Islam, Talat / McConnell, Rob / Fruin, Scott / Franklin, Meredith

Environmental epidemiology (Philadelphia, Pa.)

2023 Volume 7, Issue 4, Page(s) e264

Abstract: More than half of adolescent children do not get the recommended 8 hours of sleep necessary for optimal growth and development. In adults, several studies have evaluated effects of urban stressors including lack of greenspace, air pollution, noise, ... ...

Abstract	More than half of adolescent children do not get the recommended 8 hours of sleep necessary for optimal growth and development. In adults, several studies have evaluated effects of urban stressors including lack of greenspace, air pollution, noise, nighttime light, and psychosocial stress on sleep duration. Little is known about these effects in adolescents, however, it is known that these exposures vary by socioeconomic status (SES). We evaluated the association between several environmental exposures and sleep in adolescent children in Southern California. Methods: In 2010, a total of 1476 Southern California Children's Health Study (CHS) participants in grades 9 and 10 (mean age, 13.4 years; SD, 0.6) completed a questionnaire including topics on sleep and psychosocial stress. Exposures to greenspace, artificial light at night (ALAN), nighttime noise, and air pollution were estimated at each child's residential address, and SES was characterized by maternal education. Odds ratios and 95% confidence intervals (95% CIs) for sleep outcomes were estimated by environmental exposure, adjusting for age, sex, race/ethnicity, home secondhand smoke, and SES. Results: An interquartile range (IQR) increase in greenspace decreased the odds of not sleeping at least 8 hours (odds ratio [OR], 0.86 [95% CI, 0.71, 1.05]). This association was significantly protective in low SES participants (OR, 0.77 [95% CI, 0.60, 0.98]) but not for those with high SES (OR, 1.16 [95%CI, 0.80, 1.70]), interaction Conclusions: Residing in urban neighborhoods of greater greenness was associated with improved sleep duration among children of low SES but not higher SES. These findings support the importance of widely reported disparities in exposure and access to greenspace in socioeconomically disadvantaged populations.
Language	English
Publishing date	2023-08-01
Publishing country	United States
Document type	Journal Article
ISSN	2474-7882
ISSN (online)	2474-7882
DOI	10.1097/EE9.0000000000000264
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Article ; Online: The role of traffic noise on the association between air pollution and children's lung function.

Franklin, Meredith / Fruin, Scott

Environmental research

2017 Volume 157, Page(s) 153–159

Abstract: Although it has been shown that traffic-related air pollution adversely affects children's lung function, few studies have examined the influence of traffic noise on this association, despite both sharing a common source. Estimates of noise exposure ( ... ...

Abstract	Although it has been shown that traffic-related air pollution adversely affects children's lung function, few studies have examined the influence of traffic noise on this association, despite both sharing a common source. Estimates of noise exposure (L
MeSH term(s)	Adolescent ; Air Pollutants/toxicity ; Asthma/chemically induced ; Asthma/epidemiology ; California/epidemiology ; Child ; Child, Preschool ; Environmental Exposure ; Female ; Forced Expiratory Volume ; Humans ; Los Angeles/epidemiology ; Male ; Nitrogen Oxides/toxicity ; Noise, Transportation/adverse effects ; Vehicle Emissions/toxicity ; Vital Capacity
Chemical Substances	Air Pollutants ; Nitrogen Oxides ; Vehicle Emissions
Language	English
Publishing date	2017
Publishing country	Netherlands
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	205699-9
ISSN	1096-0953 ; 0013-9351
ISSN (online)	1096-0953
ISSN	0013-9351
DOI	10.1016/j.envres.2017.05.024
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