Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

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

Abstract

Background

To 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.

Objective

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

Methods

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

Results

Penicillium/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.

This is a preview of subscription content, access via your institution

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Fig. 1: Results reported by Baxter et al. [13], in Figure 3 in that article, showing that the interquartile range for indoor spore counts in moldy homes completely exceeded the interquartile ranges for both clean homes and outdoors.
Fig. 2

References

  1. WHO Regional Office for Europe. World Health Organization guidelines for indoor air quality: dampness and mould. Bonn, Germany; 2009.

  2. Mendell MJ, Mirer AG, Cheung K, Tong M, Douwes J. Respiratory and allergic health effects of dampness, mold, and dampness-related agents: a review of the epidemiologic evidence. Environ Health Perspect. 2011;119:748–56.

    CAS  Article  Google Scholar 

  3. Tischer C, Hohmann C, Thiering E, Herbarth O, Müller A, Henderson J, et al. Meta-analysis of mould and dampness exposure on asthma and allergy in eight European birth cohorts: an ENRIECO initiative. Allergy. 2011;66:1570–9.

    CAS  Article  Google Scholar 

  4. Mendell MJ, Adams RI. The challenge for microbial measurements in buildings. Indoor Air. 2019;29:523–6.

    Article  Google Scholar 

  5. Kanchongkittiphon W, Mendell MJ, Gaffin JM, Wang G, Phipatanakul W. Indoor environmental exposures and asthma exacerbation: an update to the 2000 review by the Institute of Medicine. Environ Health Perspect. 2015;123:6–20.

    Article  Google Scholar 

  6. AIHA. Planning and Conducting a Survey. In: Dillon HK, Heinsohn PA, Miller JD, editors. Field guide for the determination of biological contaminants in environmental samples. 2nd ed. Fairfax, VA: American Industrial Hygiene Association; 2005. p. 47–91.

  7. Spicer RC, Gangloff HJ. Differences in detection frequency as a bioaerosol data criterion for evaluating suspect fungal contamination. Build Environ. 2010;45:1304–11.

    Article  Google Scholar 

  8. Major JL, Boese GW. Cross section of legislative approaches to reducing indoor dampness and mold. J Public Health Manag Pract. 2017;23:388.

    Article  Google Scholar 

  9. AIHA. Sampling Design Strategy. In: Prezant B, Miller JD, Weekes DM, editors. Recognition, evaluation, and control of indoor mold. 1st ed. Fairfax, VA: American Industrial Hygiene Association; 2008. p. 129–38.

  10. ACGIH. Bioaerosols: assessment and control. Cincinnati, OH: American Conference of Governmental Industrial Hygienists; 1999.

  11. Johnson D, Thompson D, Clinkenbeard R, Redus J. Professional judgment and the interpretation of viable mold air sampling data. J Occup Environ Hyg. 2008;5:656–63.

    Article  Google Scholar 

  12. AIHA. Sampling Methods. In: Prezant B, Miller JD, Weekes DM, editors. Recognition, evaluation, and control of indoor mold. 1st ed. Fairfax, VA: American Industrial Hygiene Association; 2008. p. 139–52.

  13. Baxter DM, Perkins JL, McGhee CR, Seltzer JM. A regional comparison of mold spore concentrations outdoors and inside “clean” and “mold contaminated” Southern California buildings. J Occup Environ Hyg. 2005;2:8–18.

    Article  Google Scholar 

  14. AIHA. Laboratory Analytical Methods. In: Prezant B, Miller JD, Weekes DM, editors. Recognition, evaluation, and control of indoor mold. 1st ed. Fairfax, VA: American Industrial Hygiene Association; 2008. p. 153–70.

  15. Meng J, Barnes C, Rosenwasser L.Children’s Mercy Center for Environmental Health Identity of the fungal species present in the homes of asthmatic children. Clin Exp Allergy. 2012;42:1448–58.

    CAS  Article  Google Scholar 

  16. Institute of Medicine. Damp indoor spaces and health. Washington, D.C.: National Academies Press; 2004.

  17. Robertson LD, Brandys R. A multi-laboratory comparative study of spore trap analyses. Mycologia. 2011;103:226–31.

    CAS  Article  Google Scholar 

  18. Reponen T, Singh U, Schaffer C, Vesper S, Johansson E, Adhikari A, et al. Visually observed mold and moldy odor versus quantitatively measured microbial exposure in homes. Sci Total Environ. 2010;408:5565–74.

    CAS  Article  Google Scholar 

  19. Garrett MH, Rayment PR, Hooper MA, Abramson MJ, Hooper BM. Indoor airborne fungal spores, house dampness and associations with environmental factors and respiratory health in children. Clin Exp Allergy. 1998;28:459–67.

    CAS  Article  Google Scholar 

  20. Li D-W, Kendrick B. Indoor aeromycota in relation to residential characteristics and allergic symptoms. Mycopathologia. 1995;131:149–57.

    CAS  Article  Google Scholar 

  21. Rao CY, Riggs MA, Chew GL, Muilenberg ML, Thorne PS, Van Sickle D, et al. Characterization of airborne molds, endotoxins, and glucans in homes in New Orleans after Hurricanes Katrina and Rita. Appl Environ Microbiol. 2007;73:1630–4.

    CAS  Article  Google Scholar 

  22. Barnes CS, Dowling P, Van Osdol T, Portnoy J. Comparison of indoor fungal spore levels before and after professional home remediation. Ann Allergy Asthma Immunol. 2007;98:262–8.

    Article  Google Scholar 

  23. Jones R, Recer G, Hwang S, Lin S. Association between indoor mold and asthma among children in Buffalo, New York. Indoor Air. 2011;21:156–64.

    CAS  Article  Google Scholar 

  24. Hegarty B, Pan A, Haverinen-Shaughnessy U, Shaughnessy R, Peccia J. DNA sequence-based approach for classifying the mold status of buildings. Environ Sci Technol. 2020;54:15968–75.

    CAS  Article  Google Scholar 

  25. Lei Y, Yao Z, He D. Automatic detection and counting of urediniospores of Puccinia striiformis f. sp. tritici using spore traps and image processing. Sci Rep. 2018;8:13647.

    Article  Google Scholar 

  26. Cho S, Cox‐Ganser J, Park JH. Observational scores of dampness and mold associated with measurements of microbial agents and moisture in three public schools. Indoor Air. 2016;26:168–78.

    CAS  Article  Google Scholar 

  27. Adams RI, Chen W, Kumagai K, Macher JM, Mendell MJ. Relating measured moisture of gypsum board to estimated water activity using moisture meters. Build Environ. 2019;147:284–98.

    Article  Google Scholar 

  28. Mendell MJ, Kumagai K. Observation–based metrics for residential dampness and mold with dose–response relationships to health: a review. Indoor Air. 2017;27:506–17.

    CAS  Article  Google Scholar 

  29. Solomon GM, Hjelmroos-Koski M, Rotkin-Ellman M, Hammond SK. Airborne mold and endotoxin concentrations in New Orleans, Louisiana, after flooding, October through November 2005. Environ Health Perspect. 2006;114:1381–6.

    CAS  Article  Google Scholar 

  30. Chew GL, Wilson J, Rabito FA, Grimsley F, Iqbal S, Reponen T, et al. Mold and endotoxin levels in the aftermath of Hurricane Katrina: a pilot project of homes in New Orleans undergoing renovation. Environ Health Perspect. 2006;114:1883–9.

    CAS  Article  Google Scholar 

  31. Foto M, Vrijmoed LL, Miller JD, Ruest K, Lawton M, Dales RE. A comparison of airborne ergosterol, glucan and Air-O-Cell data in relation to physical assessments of mold damage and some other parameters. Indoor Air. 2005;15:257–66.

    CAS  Article  Google Scholar 

  32. Spicer RC, Gangloff HJ. Bioaerosol data distribution: probability and implications for sampling in evaluating problematic buildings. Appl Occup Environ Hyg. 2003;18:584–90.

    Article  Google Scholar 

  33. Spicer RC, Gangloff HJ. Verifying interpretive criteria for bioaerosol data using (bootstrap) Monte Carlo techniques. J Occup Environ Hyg. 2008;5:85–93.

    Article  Google Scholar 

  34. Spicer RC, Gangloff HJ. Permutation/randomization-based inference for environmental data. Environ Monit Assess. 2016;188:147.

    Article  Google Scholar 

  35. Spicer RC, Gangloff HJ. Implications of error rates associated with numerical criteria for airborne fungal data. Proc Indoor Air. 2011;2011:398–404.

    Google Scholar 

  36. Ernst MD. Permutation methods: a basis for exact inference. Stat Sci. 2004;19:676–85.

    Article  Google Scholar 

  37. Miller JD, Haisley PD, Reinhardt JH. Air sampling results in relation to extent of fungal colonization of building materials in some water‐damaged buildings. Indoor Air. 2000;10:146–51.

    CAS  Article  Google Scholar 

  38. Vesper SJ, Varma M, Wymer LJ, Dearborn DG, Sobolewski J, Haugland RA. Quantitative polymerase chain reaction analysis of fungi in dust from homes of infants who developed idiopathic pulmonary hemorrhaging. J Occup Environ Med. 2004;46:596–601.

    Article  Google Scholar 

Download references

Acknowledgements

We wish to thank Ian Cull for comments on our draft manuscript, Daniel Baxter for permission to reproduce a figure from his prior publication, and R. C. Spicer for discussions about his methods. This research was supported entirely by the California Department of Public Health.

Author information

Authors and Affiliations

Authors

Contributions

MJM contributed to the original concept of this article, helped conduct the literature review, synthesized the findings, and was the primary writer. RIA contributed to the original concept of this article, conducted the literature review, contributed to writing the initial draft, and reviewed the final drafts.

Corresponding author

Correspondence to Mark J. Mendell.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Mendell, M.J., Adams, R.I. Does evidence support measuring spore counts to identify dampness or mold in buildings? A literature review. J Expo Sci Environ Epidemiol 32, 177–187 (2022). https://doi.org/10.1038/s41370-021-00377-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41370-021-00377-7

Keywords

  • Fungi
  • Moisture
  • Water damage
  • Housing
  • Indoor air pollution
  • Spore traps

Search

Quick links