Do Indoor Molds in Nonindustrial Environments

Epidemiologic Reviews Copyright © 2002 by the Johns Hopkins Bloomberg School of Public Health All rights reserved

Vol. 24, No. 2 Printed in U.S.A. DOI: 10.1093/epirev/mxf009

Do Indoor Molds in Nonindustrial Environments Threaten Workers’ Health? A Review of the Epidemiologic Evidence

Henrik A. Kolstad1,2, Charlotte Brauer2, Martin Iversen3, Torben Sigsgaard4, and Sigurd Mikkelsen2 1

Department of Occupational Medicine, Aarhus University Hospital, Aarhus, Denmark. Department of Occupational Medicine, Glostrup Hospital, University of Copenhagen, Denmark. 3 Department of Lung Diseases, Aarhus University Hospital, Aarhus, Denmark. 4 Institute of Environmental and Occupational Medicine, Aarhus University, Aarhus, Denmark. 2

Received for publication February 21, 2000; accepted for publication November 21, 2001.

Abbreviations: CFU, colony-forming units; CI, confidence interval.

INTRODUCTION

Since the early 1980s, mucosal, skin, and respiratory symptoms, in addition to general symptoms such as fatigue and headache, have been related to the indoor climate of nonindustrial workplaces. Mold growth has been suggested as a causal factor because the health complaints frequently have been related to indicators of microbial contamination: visible signs of mold growth, moisture, and water damage (1). Molds refer to growing colonies of different species of fungi. Fungi are nonphotosynthetic plant bodies that are ubiquitous in nature and decompose organic material. The species differ in size, but most are about 10 µm in diameter. Fungi are able to grow at a relative humidity of between 75 percent and 95 percent at normal room temperature. Fungi reproduce by spores that spread by air, depending on climatic factors, activity in the surrounding environment, and physiologic properties of the individual species (2, 3). Growing fungi may produce metabolites to protect a nutrient source from bacteria. Mycotoxins are metabolites that are able to initiate a toxic response in vertebrates when ingested, inhaled, or otherwise absorbed. Mold antigens may induce an immunoglobulin E–mediated response (4, 5). β-(1,3)-D-glucan is a polyglucose structure of mold cell walls that can induce inflammatory reactions through a specific receptor (6, 7). Ergosterol is the primary membrane sterol of filamentous fungi, and extracellular polysaccharides are stable carbohydrates secreted during fungal growth. At present, there is no evidence for a pathogenic role of ergosterol or extracellular polysaccha-

rides in allergic or inflammatory reactions to fungal components (8). High-level exposure to airborne mold spores may cause allergic alveolitis (e.g., farmer’s lung) (9). Aerosols from air humidifiers heavily contaminated by bacteria, algae, or molds may cause inhalation fever (humidifier fever) (10). Single cases of occupational asthma have been attributed to mold exposure (11, 12), and asthma severity has been associated with outdoor mold spore levels in children and adolescents (13). Mold-contaminated food and feed have been held responsible for serious cases of poisoning in humans and livestock (14). It was discussed recently whether mycotoxins may be responsible for cases of acute idiopathic pulmonary hemorrhage in infants (15, 16). Among employees of nonindustrial workplaces with visible signs of mold growth, moisture, or water damage, there has been an increasing concern about possible health effects. This review evaluates this concern based on present epidemiologic literature. Recently, the topic was partly reviewed by Husman, Verhoeff and Burge, and Peat and Dickerson (17–19). However, they focused mainly on the health effects in children, which may not be relevant for the adult working population (20). Furthermore, several studies assessing mold exposure in the sick building syndrome were included to only a limited extent. This is a systematic review of reports on health effects related to mold growth (or indicators of mold growth) in nonindustrial work sites. Since comparable mold exposure is seen in dwellings, studies that related adult health effects to exposure at home were also reviewed (21).

Reprint requests to Dr. Henrik Kolstad, Department of Occupational Medicine, Aarhus University Hospital, Norrebrogade 44, DK-8000 Aarhus C, Denmark (e-mail: [email protected]).

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204 Kolstad et al. INDOOR MOLDS IN NONINDUSTRIAL ENVIRONMENTS

To assess the possible health effects of indoor molds, characterization of the presence and the degree of exposure is crucial. Use of questionnaire information on visible signs or the characteristic smell of molds or dampness is a simple method, but it gives little information about the degree of exposure and involves a risk of reporting bias (22). Inspection by surveyors can provide a standardized assessment of mold growth in terms of the area affected (23). Settlement plates, dust samples, and air samples can be used to determine viable mold spores. However, these methods have limitations concerning determination of concentrations of viable mold spores in the air representative of time-weighted exposure (24). Settlement plates have failed to adequately collect small spores and have shown little reproducibility, with average coefficients of variance of about 30 percent regarding the number of colony-forming units (CFUs) (2, 25). Dust sampling has resulted in coefficients of variance of between 11 percent and 27 percent (CFU/g dust), and the mean agreement for species isolated has varied from 37 percent to 60 percent (26). Comparable figures have been reported for air sampling (25). Viable mold counts may represent only a minor fraction of the total number of fungal particles in indoor air because of different survival rates and difficulties in detecting them on growth agar medium. Nonviable and viable spores can contain allergens and mycotoxins, and it may be of importance also to assess the total number of spores (viable and nonviable), even if a high correlation has been found between viable and total mold counts (27). Levels of β-(1,3)-D-glucan, ergosterol, and extracellular polysaccharides may be other appropriate measures of fungal biomass, even if only measures of extracellular polysaccharides provide information on the fungal species (8). Coefficients of variance of 25 percent and 16 percent have been reported for measurements of β-(1,3)-D-glucan and extracellular polysaccharides, respectively, while relative standard deviations for determining ergosterol have ranged from 5 percent to 27 percent (8, 28, 29). Total airborne mold counts (viable and nonviable) of 667– 570,000 spores/m3 have been reported in dwellings (30, 31). Table 1 presents viable mold exposure levels expressed as CFU per cubic meter (only limited data exist for the other parameters) and shows considerable variation, ranging from 0 to 450,000 CFU/m3, between studies. Furthermore, counts differ by season, and there is a tendency toward higher counts at lower latitudes (in Asia). Generally, viable spore counts are higher outdoors than indoors. Significantly higher counts were reported in buildings with signs of mold growth or dampness than in reference buildings (32–34); however, no or small differences in mold levels have also been shown (21, 23, 25, 30, 35–37). During remediation of moldy buildings (homes or nonindustrial workplaces), mold exposure levels may increase significantly (38). The predominant mold genera are Penicillium, Cladosporium, and Aspergillus indoors as well as outdoors in all parts of the world. Fungi such as Trichoderma and Stachybotrys, which require high water activity (aw >0.90–0.95) for growth, are infrequent, but high exposure levels may be seen

(34). Stachybotrys has been identified more frequently in buildings with mold problems (32, 39, 40). LITERATURE SEARCH AND STUDY QUALITY EVALUATION

MEDLINE (National Institutes of Health, Bethesda, Maryland) (1968–June 2000) and NIOSHTIC (National Institute for Occupational Safety and Health Technical Information Center; database provided by SilverPlatter Information Ltd., London, United Kingdom) (1977–June 2000) were searched to identify human peer-reviewed studies published in English that related adult health effects to mold exposure in nonindustrial indoor environments. Additional snowball searches were conducted of the bibliographies in the original papers identified initially. A total of 47 articles were identified. The articles were initially classified as 1) case or cluster reports and 2) analytical studies in populations with no concerns about possible mold-related health effects. The analytical studies were then scored according to six quality parameters, as follows (score value in parentheses): 1) design: cross-sectional (0), longitudinal (1); 2) participation rate: 0.05)# (dryness, smarting, or irritation)

0.76 (p < 0.05)# (dryness, itching, or blushing of skin or hands)

Teeuw et al., 1994 (69)

2

—‡ (congestion)

—‡ (dryness)

—‡ (dryness)

—‡ (dryness)

Menzies et al., 1998 (62)

5

Norbäck et al., 2000 (64)

4

—‡ (congestion, discharge, itching or sneezing)

Wan and Li, 1999 (70)

3

0.96 (0.82, 1.11) (congestion or discharge)

—‡ (headache, fatigue or malaise) 1.98 (1.19, 3.29) (congestion)

1.08 (0.65, 1.78) (cough, dryness, irritation, itching, soreness)

0.87 (0.54, 1.42) (dryness, irritation, or soreness)

0.78 (0.47, 1.29) (dryness, irritation, itching)

Mixed organs

—‡ (dryness or irritation of eyes, nose, or throat)

1.04 (0.63, 1.71) (fatigue)

—‡ (rash or dryness)

—‡ (irritation, discharge, or cough affecting eyes, nose, or throat)

—‡ (sick building syndrome)** 0.46 (0.17, 1.20) (lethargy or fatigue)

—‡ (headache)

Total molds ¶ —‡ (nasal irritation, congestion or discharge; cough or difficulty in breathing)

β(1,3)-D-glucan 1.03 (0.92, 1.14) (dryness, irritation, itching, soreness)

1.04 (0.93, 1.16) (dryness, irritation, or itching)

0.89 (0.76, 1.04) (dryness, irritation, or itching

1.26 (1.05, 1.51) (lethargy or fatigue)

* For studies reporting several symptoms for each organ specified, the most prevalent were selected (61, 70, 82). † Defined as onset of one or more symptoms (fatigue, headache, drowsiness, dizziness, shortness of breath, nausea or vomiting, skin dryness or rash, or eye, nose, or throat irritation) at least twice weekly while in the building. ‡ No statistically significant association; estimates not presented in the article. § Crude odds ratio derived from the original data. ¶ Airborne mold levels except in the study by Gyntelberg et al. (59) that reported dust levels and Skov et al. (67) and Menzies et al. (62) that reported both air and dust levels. # Correlation coefficient. ** Defined as at least one general symptom every month and at least one mucosal and one dermatologic symptom every week.

tive measures of bronchial hyperresponsiveness or nasal mucosal parameters, but the studies were few (35, 64, 80). In children, asthma also has been related to signs of mold growth or dampness (18, 19). Epidemiol Rev 2002;24:203–217

The studies provide no consistent evidence that quantitative measures of total or viable indoor molds, β-(1,3)-Dglucan, or specific mold species are associated with asthma disease, asthma-related symptoms, or bronchial hyperre-

214 Kolstad et al.

sponsiveness. These findings are in line with the fact that the impact of mold exposure on asthma in adults is largely unknown (85), even if single cases of occupational mold asthma have been reported (11, 12). In addition, nose, throat, eye, and skin symptoms; fatigue; headache; or objective nasal parameters were not associated with specific measures of fungal biomass. The discrepancies in these results may suggest that the quantitative measures of mold exposure were inappropriate, that detection levels in the quantitative studies were insufficient, or that these studies were flawed because of bias. The latter aspect also pertains to the studies relying on qualitative signs of mold growth or dampness. We discuss these aspects one at a time. Appropriateness of quantitative measures of mold exposure

In the studies reviewed, four principally different measures of molds in air or dust were used: total viable mold counts, total mold counts (viable and nonviable), β-(1,3)-Dglucan level, and specific mold species (qualitative or quantitative). Air and dust are the media relevant to examine; dermal absorption or ingestion of surface-contaminated material is not expected to play a significant role, and no difference in exposure-effect relations was observed when exposure assessment was based on air or dust samples. However, one may question the appropriateness of using viable mold counts as the measure of exposure since higher levels generally are not observed in buildings characterized by mold growth or water damage compared with nonproblem buildings or outdoor air (21, 23, 25, 30, 35–37). This question may also apply to total mold counts; however, for this measure, data are limited. β-(1,3)-D-glucan levels have been associated with signs of mold growth in the indoor environment (70). Thus, it may be that the measures of exposure applied do not provide a sufficient characterization of mold exposure. On the other hand, they all reflect the extent of molds from recent and current sources in air or dust and are therefore expected to relate to human health effects if a causal effect of indoor molds is present. Even if molds are obvious causal candidates for the health effects reported by subjects working or living in buildings with signs of mold growth or dampness, there are also other candidates, for example, house dust mites. House dust mites, similar to molds, prefer a humid environment and are welldocumented causes of allergic airway disease. Furthermore, house dust mites were related to asthmatic symptoms in the study by Björnsson et al. (in contrast to mold counts) (31) but not in the study by Wan and Li (70). Inhalation of bacterial particles could also, at least partly, explain some of the symptoms, since endotoxin exposure determines the severity of asthma in people allergic to house dust mites (86); however, the studies reviewed do not provide consistent evidence for this hypothesis (31, 61, 64, 70).

Detection level of the quantitative studies

The lack of any consistent association between levels of mold exposure and health effects may be due to nondifferential misclassification, since a limited number of mold measurements often were used to classify exposure levels for several workers in large buildings (61, 63–65, 67) or sampling time was brief (70). This limitation may have attenuated real associations, since mold levels show significant variability (25). If there is a threshold level for mold-related health effects, it may be that the populations in the quantitative studies were exposed below this level. However, no stronger exposureeffect associations were seen in the few studies reviewed with the highest average exposure levels (>1,000 CFU/m3) (61, 73). Bias in the quantitative studies

It is expected that subjects with mucosal or respiratory symptoms take precautions to avoid exposures in their dwellings or leave workplaces that have mold and moisture problems. Thus, in cross-sectional studies, which was the preferred design of all but two of the studies reviewed, a possible relation between mold exposure and health effects may be underestimated (87). However, since it is expected that such selection bias would affect studies classifying exposure according to signs of mold growth more than those relying on quantitative measures, this possibility can hardly explain the discrepancy in the results of the studies reviewed. It is also unlikely with respect to other aspects of study quality, because no systematic deficit in overall quality (design, participation, confounder control, exposure-effect assessment, outcome specificity) was seen for the quantitative studies compared with those relying on qualitative exposure data. Discrepancies in results could also be seen if generally lower exposure levels were found compared with the qualitative studies. However, this possibility was not supported by the two studies by Björnsson et al. and Norbäck et al. that characterized the same population by both qualitative and quantitative exposure information (31, 80). Bias in the qualitative studies

The major limitation of the reviewed studies relying on self-reports of exposure is the inherent risk of information bias. Pirhonen et al. illustrated this limitation by observing that associations between self-reported home exposures and symptoms disappeared when subjects who had symptoms that could hardly be explained by indoor exposures were excluded from the analyses (81). Others have provided strong evidence of a significant effect of recall bias in studies of health effects due to indoor climate (22, 88), but not all have (82). Researchers’ independent observations of indoor mold growth may to some extent counter this bias, but not in studies with symptoms as the health outcome; symptoms, by definition, are self-reported, and mold growth visible to surveyors is also expected to be visible to study subjects. The Epidemiol Rev 2002;24:203–217

Indoor Molds and Health 215

studies that relied on reviewers’ observations of exposure showed results comparable to those relying on self-reports. Case and cluster reports

A high proportion of the studies reviewed were initiated because of concerns about mold-related health effects in the study populations. These studies may generate important hypotheses. However, they do not form a solid basis for assessing causal effects (89), even if an external, nonexposed reference population is included (39, 40, 50, 51, 54, 56, 57). Thus, in this review, these studies were considered less important than the analytical studies. On the other hand, these studies may provide important information from extreme exposure situations rarely encountered in systematic studies. The reports by Bernstein et al. and Kolmodin et al. of cases of organic dust toxic syndrome (now known as toxic pneumonitis or inhalation fever) and allergic alveolitis following high-level airborne mold exposure (5 × 103 CFU/m3 and 106 CFU/m3, respectively) (43, 45) are in accordance with cause-effect relations well documented among farmers and in cases of exposure to humidifiers highly contaminated by microbes (9, 10).

places be kept clean, well maintained, and dry. Nonetheless, we will be cautious before ascribing asthma; nose, eye, and skin symptoms; fatigue; or headache to mold exposure in our patients’ nonindustrial workplaces. However, these health problems more often are reported by adults working or living in buildings that have signs of indoor mold growth and dampness. To elucidate possible causal mechanisms, further studies should probably focus on populations experiencing larger mold exposure contrasts than those encountered in nonindustrial environments. Alternative measures are recommended to characterize buildings that have signs of mold growth and dampness. They may relate to molds and their metabolic products such as mycotoxins, but other factors should also be considered, as well as more appropriate exposure assessment strategies. Newly developed objective methods to determine inflammation, such as acoustic rhinometry, nasal lavage, tear fluid sampling, induced sputum, and condensed breath, will be needed in order to study exposure-response relations and to avoid reporting bias in this area of low exposure. The low exposure situation also leads to the need for good control for confounders and exposures outside the buildings studied.

A possible mode of action

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