ReviewCurrent environmental health reports2017
Recent Approaches to Estimate Associations Between Source-Specific Air Pollution and Health.
Review in Current environmental health reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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
8 citing papers in PubMed.
- Attribution of Health Hazards to Sources of Air Pollution Based on Networks of Sensors and Emission Inventories.Sensors (Basel, Switzerland) · 2025Article
- Association between annual concentration of air pollutants and incidence of metabolic syndrome among Korean adults: Korean Genome and Epidemiology Study (KoGES).Environmental health : a global access science source · 2025Article
- A review of common statistical methods for dealing with multiple pollutant mixtures and multiple exposures.Frontiers in public health · 2024Review
- Source-specific contributions of particulate matter to asthma-related pediatric emergency department utilization.Health information science and systems · 2021Article
- Article
- [Combined effects of different environmental factors on health: air pollution, temperature, green spaces, pollen, and noise].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2020Review
- Source-Apportioned PM2.5 and Cardiorespiratory Emergency Department Visits: Accounting for Source Contribution Uncertainty.Epidemiology (Cambridge, Mass.) · 2019Article
- Statistical Approaches to Address Multi-Pollutant Mixtures and Multiple Exposures: the State of the Science.Current environmental health reports · 2017Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purpose of reviewEstimating health effects associated with source-specific exposure is important for better understanding how pollution impacts health and for developing policies to better protect public health. Although epidemiologic studies of sources can be informative, these studies are challenging to conduct because source-specific exposures (e.g., particulate matter from vehicles) often are not directly observed and must be estimated. We reviewed recent studies that estimated associations between pollution sources and health to identify methodological developments designed to address important challenges. RECENT
findingsNotable advances in epidemiologic studies of sources include approaches for (1) propagating uncertainty in source estimation into health effect estimates, (2) assessing regional and seasonal variability in emissions sources and source-specific health effects, and (3) addressing potential confounding in estimated health effects. Novel methodological approaches to address challenges in studies of pollution sources, particularly evaluation of source-specific health effects, are important for determining how source-specific exposure impacts health.
Indexed as
Identifiers
28108914What OpenQuestion holds
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.