ArticleEnvironmental health insights2015
Using Machine Learning to Estimate Global PM2.5 for Environmental Health Studies.
Article in Environmental health insights, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Air Pollution (Particulate Matter) Exposure and Associations with Depression, Anxiety, Bipolar, Psychosis and Suicide Risk: A Systematic Review and Meta-Analysis.Environmental health perspectives · 2019Pooled it
- A systematic review of data mining and machine learning for air pollution epidemiology.BMC public health · 2017Pooled it
- Durational effect of ambient air pollution on hospital admissions of schizophrenia: a time series analysis.Social psychiatry and psychiatric epidemiology · 2025Article
- Article
- "Urban-Satellite" estimates in the ABCD Study: Linking Neuroimaging and Mental Health to Satellite Imagery Measurements of Macro Environmental Factors.medRxiv : the preprint server for health sciences · 2024Article
- The links between microclimatic and particulate matter concentration in a multi-storey car parking: a case study iran.Journal of environmental health science & engineering · 2022Article
- Air Pollution, Foreign Direct Investment, and Mental Health: Evidence From China.Frontiers in public health · 2022Article
- Explaining the Association Between Urbanicity and Psychotic-Like Experiences in Pre-Adolescence: The Indirect Effect of Urban Exposures.Frontiers in psychiatry · 2022Article
- Will Smog Cause Mental Health Problems? Indication from a Microsurvey of 35 Major Cities in China.International journal of environmental research and public health · 2021Article
- Integration of air quality model with GIS for the monitoring of PM2.5 from local primary emission at a rural site.Environmental monitoring and assessment · 2021Article
- Autonomous Learning of New Environments with a Robotic Team Employing Hyper-Spectral Remote Sensing, Comprehensive In-Situ Sensing and Machine Learning.Sensors (Basel, Switzerland) · 2021Article
- Ensemble averaging based assessment of spatiotemporal variations in ambient PMAtmospheric environment (Oxford, England : 1994) · 2020Article
- An association between air pollution and daily most frequently visits of eighteen outpatient diseases in an industrial city.Scientific reports · 2020Article
- Using Machine Learning for the Calibration of Airborne Particulate Sensors.Sensors (Basel, Switzerland) · 2019Article
- Using machine learning to understand the temporal morphology of the PMEnvironmental monitoring and assessment · 2019Article
- Time-series analysis of satellite-derived fine particulate matter pollution and asthma morbidity in Jackson, MS.Environmental monitoring and assessment · 2019Article
- Association of Air Pollution Exposure With Psychotic Experiences During Adolescence.JAMA psychiatry · 2019Article
- PMInternational journal of biological sciences · 2019Article
- A Deep CNN-LSTM Model for Particulate Matter (PMSensors (Basel, Switzerland) · 2018Article
- The relationship between fine particulate matter (PMInternational archives of occupational and environmental health · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
With the increasing awareness of health impacts of particulate matter, there is a growing need to comprehend the spatial and temporal variations of the global abundance of ground-level airborne particulate matter (PM2.5). Here we use a suite of remote sensing and meteorological data products together with ground based observations of PM2.5 from 8,329 measurement sites in 55 countries taken between 1997 and 2014 to train a machine learning algorithm to estimate the daily distributions of PM2.5 from 1997 to the present. We demonstrate that the new PM2.5 data product can reliably represent global observations of PM2.5 for epidemiological studies. An analysis of Baltimore schizophrenia emergency room admissions is presented in terms of the levels of ambient pollution. PM2.5 appears to have an impact on some aspects of mental health.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.