ArticleIndoor air2021
Temporal variability of indoor dust concentrations of semivolatile organic compounds.
Article in Indoor air, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis 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
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Characterizing the Contribution of Indoor Residential Phthalate and Phthalate Alternative Dust Concentrations to Internal Dose in the US General Population: An Updated Systematic Review and Meta-Analysis.International journal of environmental research and public health · 2023Pooled it
- Article
- Exposure to per- and polyfluoroalkyl substances in residential settled dust and risk of childhood acute lymphoblastic leukemia.International journal of cancer · 2025Article
- Characterizing PMEnvironmental science & technology · 2024Article
- Silicone wristbands as personal passive sampling devices: Current knowledge, recommendations for use, and future directions.Environment international · 2022Review
- Emissions of Fungal Volatile Organic Compounds in Residential Environments and Temporal Emission Patterns: Implications for Sampling Methods.International journal of environmental research and public health · 2022Article
- Temporal Trends of Phenol, Paraben, and Triclocarban Exposure in California Pregnant Women during 2007-2014.Environmental science & technology · 2021Article
- Evaluating couch polyurethane foam for a potential passive sampler of semivolatile organic compounds.Chemosphere · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
The determinants of the temporal variability of indoor dust concentrations of semivolatile organic compounds (SVOCs) remain mostly unexplored. We examined temporal variability of dust concentrations and factors affecting dust concentrations for a wide range of SVOCs. We collected dust samples three times from 29 California homes during a period of 22 months and quantified concentrations of 47 SVOCs in 87 dust samples. We computed intraclass correlation coefficients (ICCs) using three samples collected within the same house. We calculated correlation coefficients (r) between two seasons with similar climate (spring and fall) and between two seasons with opposite climate (summer and winter). Among 26 compounds that were detected in more than 50% of the samples at all three visits, 20 compounds had ICCs above 0.50 and 6 compounds had ICCs below 0.50. For 19 out of 26 compounds, correlation coefficients between spring and fall (r = 0.48-0.98) were higher than those between summer and winter (r = 0.09-0.92), implying seasonal effects on dust concentrations. Our study showed that within-home temporal variability of dust concentrations was small (ICC > 0.50) for most SVOCs, but dust concentrations may vary over time for some SVOCs with seasonal variations in source rates, such as product use.
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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.