Evidence map›Paper›PMID 34475494›Full record

ReviewJournal of exposure science & environmental epidemiology2022

Does evidence support measuring spore counts to identify dampness or mold in buildings? A literature review.

Mark J Mendell, Rachel I Adams

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of exposure science & environmental epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Mark J MendellCalifornia Department of Public Health, Richmond, CA, USA. mmendell@cdph.ca.gov.ORCID http://orcid.org/0000-0001-7194-7654
Rachel I AdamsCalifornia Department of Public Health, Richmond, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo identify dampness or mold (D/M) in buildings, investigators generally inspect for observable D/M indicators, the presence of which justifies remediation. Investigators may also use microbiological measurement and interpretation strategies with uncertain scientific support.

objectiveWe assessed available evidence supporting uses of spore counts, the microbiological measurement most commonly used to assess D/M.

methodsWe reviewed published studies assessing relationships between spore counts and observable D/M, across buildings with different observable D/M levels.

resultsPenicillium/Aspergillus counts were consistently elevated in damp vs. reference (dry or outdoor) locations. Total spore counts provided a weaker, less consistent signal. The most detailed published analysis could distinguish groups of damp homes but not individual damp homes. SIGNIFICANCE: Evidence did not validate current interpretations of spore count data for identifying single damp homes. Thus, such interpretations rest primarily on professional judgment. An additional series of informative but ineligible articles demonstrated an unconventional, more powerful "statistically based" comparison of multiple indoor vs. outdoor spore counts for identifying elevated indoor spores (and assumed D/M). Findings suggest that validation of enhanced spore trap approaches, including more samples indoors and outdoors plus statistically based comparisons of specific fungal groups, may allow evidence-based microbial identification of probable dampness in individual buildings.

Indexed as

Air Pollution, IndoorAir MicrobiologyColony Count, MicrobialEnvironmental MonitoringFungiHousingHumansSpores, FungalFungiHousingIndoor air pollutionMoistureSpore trapsWater damage

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.