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Institute of Medicine (US) Committee on Damp Indoor Spaces and Health. Damp Indoor Spaces and Health. Washington (DC): National Academies Press (US); 2004.

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Damp Indoor Spaces and Health.

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3Exposure Assessment


Assessments of exposure to environmental agents in indoor air play a central role in epidemiologic studies that seek to characterize population risks, in screening studies aimed at identifying individuals at risk, and in interventions designed to reduce risk. Because of the central importance of exposure assessment, there is a need to understand the strengths and limitations of the approaches that are available to assess exposures in those contexts. Indoor dampness may be associated with some respiratory health effects (Chapter 5), and a causal role for microorganisms has been suggested. However, the specific roles of infectious and noninfectious microorganisms and their components in diseases related to indoor environments are poorly understood. The lack of knowledge regarding the role of microorganisms in the development and exacerbation of those diseases is due largely to the lack of valid quantitative exposure-assessment methods and knowledge of which specific microbial agents may primarily account for the presumed health effects. In most studies, exposure is assessed by means of questionnaires, and relatively few studies have attempted to measure exposure to microorganisms.

Indoor environments contain a complex mixture of live (viable) and dead (nonviable) microorganisms, fragments thereof, toxins, allergens, microbial volatile organic compounds (MVOCs), and other chemicals. Sensitive and specific methods are available for the quantification of some biologic agents, such as endotoxins, but not for others. Many of the newly developed methods—for example, measurement of microbial agents, such as β(1→3)-glucans or fungal extracellular polysaccharides (EPSs)—have not been well validated and are not commercially available. Even for some well-established methods, such as the Limulus amebocyte lysate (LAL) assay for measuring bacterial endotoxins, substantial variations in exposure assessment between laboratories have been demonstrated (Chun et al., 2000; Reynolds et al., 2002; Thorne et al., 1997). It is known that the conditions of storage and transport of bioaerosol samples and extraction of dust samples may affect the activity of some biologic agents, such as endotoxins, and thus their measured concentrations, but those conditions are not often addressed (Douwes et al., 1995; Duchaine et al., 2001; Thorne et al., 1994). Finally, there may be biologic agents whose health effects have not been identified. Microbial exposure assessment in the indoor environment is therefore associated with large uncertainties, which potentially result in large measurement errors and biased exposure–response relationships.

This chapter focuses on exposure assessment of microorganisms and microbial agents that occur in damp indoor environments. It discusses issues related to dampness in general only briefly.



Two classes of exposure measures can be distinguished: the theoretically ideal (and typically unknown) risk-relevant exposure metric (ERR) that represents the individual breathing-zone concentration of an agent of interest over a period that is relevant to the risk of developing the health outcome of interest and the practical and available exposure surrogate that correlates to some extent with the ERR. When used without qualification in this report, exposure refers to surrogate exposure measures.

The ERR is the theoretical measure of exposure that best represents the risk of adverse health consequences. Researchers often do not know enough about the specific pathogenesis of indoor-related diseases to identify the appropriate ERR confidently. One possible ERR for the exacerbation of asthma, for example might be a short-term average that captures peak agent exposures in the breathing zone immediately before the exacerbation. Relevant averaging times might range from about 20 min to 48 hours.

Direct exposure surrogates include personal monitoring involving the measurement of agent concentrations with monitors carried by individual subjects. These offer more proximal measures of individual exposure than do the indirect approaches, but usually at the expense of sample size or ability to characterize long-term exposures. Indirect measures include environmental area monitoring (airborne or dust sampling), recall questionnaires, real-time diaries, and biologic response markers (IgG against fungal antigens, for example). These approaches tend to be more practical in largescale studies and often are better suited to long-term exposure characterization than are direct measures.

Exposure Mechanisms

Inhalation is usually presumed to be the most important mechanism of exposure to fungi and other dampness-related microbial agents in indoor environments. It is also generally believed that the most harmful agents are within particles, such as fungal spores; however, although this has been the general assumption, recent studies have identified hyphal fragments (Górny et al., 2002) and dust (Englehart et al., 2002) as potential carriers of harmful agents. This section briefly discusses the process of exposure; it focuses on exposures to fungal spores, but the same exposure mechanisms and associated questions apply to other microbial particles of similar size.

Fungal growth occurs on indoor surfaces—including surfaces in heating, ventilating, and air-conditioning systems—and an inhalation exposure to a fungal spore requires that the spore be initially aerosolized at the site of growth and transported to the inhaled parcel of air. Some fungi actively (forcibly) discharge spores into the air (Burge, 2000). In other cases, the initial aerosolization is likely to be caused by indoor air movements or physical disturbances caused by people. After initial aerosolization, a spore may be transported by air motion to the inhaled air parcel.

Most fungal spores have aerodynamic diameters of 2–10 µm (American Thoracic Society, 1997) and deposit quickly on indoor surfaces because of gravitational settling. For example, a 10-µm particle with unit density will fall 1 meter in 5.5 minutes in still air, and a 5-µm particle will fall 1 meter in 21 minutes (Hinds, 1982). Because the deposition rates of these large particles caused by gravitational settling exceed typical ventilation and filtration rates in houses,2 most spores deposit on indoor surfaces after aerosolization. The deposition of spores is confirmed by their detection in dust samples taken from a broad array of indoor surfaces, including surfaces that are too dry to support fungal growth.

Once deposited, spores can be resuspended by disturbances, such as walking and cleaning. Thus, the inhalation-exposure process for fungal spores (and other microbial particles of similar size) may be largely a consequence of resuspension. Thatcher and Layton (1995) have shown that resuspension occurs predominantly for particles larger than 1 µm and that the amount of resuspension increases with particle size. In experiments, such activities as walking, sitting, and house-cleaning increased air concentrations of 5- to 10-µm particles by a factor of 1.5–11. The surface properties of spores may affect their adherence to surfaces and the probability of their resuspension. There is evidence that human activities, including particle resuspension, cause a “personal cloud” of particles, whereby people's exposures to particles exceed those indicated by measurements at a fixed location (Özkaynak et al., 1996). The same personal cloud would be expected for fungal spores. The spores that deposit on surfaces can also be transported to other locations by tracking, for example, sticking to shoes and then detaching at another location.

Many of the above comments also apply to the process of inhalation exposure to fungal spores that are transported to the indoors from outdoors. Those spores can be brought into a building with outdoor air by natural ventilation through open windows and by air infiltration through unintentional cracks and holes in the building envelope and can be tracked in by people and pets. Once they are inside, the processes of spore settling, resuspension, and tracking would be expected to influence inhalation exposures as they do exposure to fungal spores from indoor sources.

Because spores and other components of molds are present on indoor surfaces and people have contact with these surfaces, exposures to fungal agents may occur through dermal contact and transport of lipid-soluble chemicals through the skin. In addition, incidental ingestion of fungal constituents on surfaces and in household dust may occur as a consequence of hand-to-mouth activity. Exposures via dermal contact or ingestion are known to be important for some chemicals and for lead. Infants are generally affected more than adults because of their contact with floors and their high level of hand-to-mouth activity. However, the significance of those routes of exposure to indoor fungi and other dampness-related microbial pollutants is not known.

In summary, the entire process of fungal-spore aerosolization, transport, deposition, resuspension, and tracking, all of which determine inhalation exposure, is poorly understood. A better understanding of the process would enable a better assessment of exposures and might elucidate better means of reducing them. The significance of exposures to fungi in normal indoor environments through dermal contact and ingestion is also not well understood.


Dose is the amount of an agent that is absorbed or deposited in the body of an exposed organism at a given time (NRC, 1991). Internal dose is the amount of an agent that is absorbed into the body, whereas biologically effective dose is the amount of an agent or its metabolites that interacts with a target site.

The primary determinants of where an inhaled gas, such as an MVOC, makes contact with the respiratory system are its solubility and reactivity. Reactive gases tend to reach the upper respiratory system. The primary determinant of deposition of airborne particles is the aerodynamic particle diameter (dae). Aerodynamic particle diameter, as distinct from physical diameter, determines the motion of particles in air. The dae of a particle is defined as the diameter of the unit density sphere that has the same terminal settling velocity as the particle of interest (ICRP, 1994). Particles with dae larger than 15 µm are captured preferentially (but not exclusively) in the upper respiratory tract (nose and throat). Particles with dae of 2.5–15 µm enter the lungs but tend to deposit in the upper conducting airways, where their mass and high velocities favor inertial impaction. Because they lack inertia, smaller particles move with the inhaled air stream into the alveolar region, where they may or may not deposit. The fraction of particles that deposit in the deep lung increases with decreasing dae below 0.5 µm because of the high diffusion constants of very small particles.

The role of particle density in determining dae is critical. A spherical particle with a physical diameter of 16 µm but a density of 0.1 will behave aerodynamically like a 5-µm water droplet. That property helps to explain the ability of large-diameter, low-density pollen grains to penetrate and deposit in the lung. Once deposited in the lungs, airborne agents may react with biomolecules, be absorbed into the blood, or be cleared from the lungs. From the viewpoint of indoor-related symptoms and diseases, the relevant sites and nature of interactions between inhaled agents and the human body remain uncertain, and this uncertainty limits our ability to define biologically effective dose in this context. It is important to note that all measures of dose, like those of exposure, can be viewed as surrogates of the theoretical risk-relevant dose measure.


Several strategies are available for exposure assessment conducted for risk-assessment purposes.4 In epidemiology, questionnaires are the most commonly-used instrument for gathering exposure information (for example, by asking about the presence of dampness or visible mold in the home). For individual patients with suspected indoor-related health problems, a home visit by an occupational hygienist with experience in this field may be the method of choice. Alternatively, personal or environmental monitoring can be used to measure agents of interest in the home. The latter approach has the potential to result in a more valid and accurate exposure assessment; however, this depends heavily on the chosen sampling strategy, which in turn depends on many factors, including

  • Specific disease or symptoms.
  • Acute vs chronic health outcomes (for example, disease exacerbation vs disease development).
  • Population vs patient-based approach.
  • Suspected exposure variation in time and space and between controls and cases.
  • Available methods to measure individual agents.
  • Costs of sampling and analyses.

For indoor-associated health problems, many exposures have to be considered because it is often not clear which specific microorganisms or agents cause symptoms or diseases. In fact, studies are often conducted with the specific aim of assessing which exposures may contribute to the development of symptoms. However, in practice, the funding and availability of methods of measuring specific agents (many methods are not commercially available and are applied only in research settings) severely limit the potential to measure all agents of interest.

Settled Dust vs Airborne Measurements

Indoor exposure assessment may use air or surface sampling or both. Swab samples can be taken, but they have limited value in quantitative exposure assessment and are usually used only as a diagnostic tool to characterize whether buildings have dampness- or mold-related problems (see Chapter 6).

In most studies, dust samples from dust reservoirs, such as living-room and bedroom floors and mattresses, are collected for analysis of microbial content (with or without prior sieving or extraction). A theoretical advantage of settled-dust sampling is the presumed time integration that occurs in the deposition of bioaerosols on surfaces. Surface sampling may thus be the method of choice for assessing the association between exposure and the development of chronic conditions, such as asthma. The method is fast, easy, and inexpensive, using only a vacuum cleaner and filters or nylon sampling bags to collect dust, so it is particularly useful in large epidemiologic studies (focusing on chronic diseases), in which airborne measurements often are not feasible. One example in which this method is widely applied is the routine measurement of settled dust allergens. Allergen concentrations are usually expressed in units of allergen per gram of dust.

One limitation of the common practice of reporting concentrations of allergen or specific microbial agents per gram of dust collected should be noted: by dividing by total amount of dust collected, this expression of exposure does a poor job of characterizing the total burden of a specific agent in a building. For example, homes A and B could have the same amount of an agent (fungal allergen, endotoxin, viable microorganisms, or the like) per gram of dust by the conventional measure, whereas home A might have 10 times more dust than home B, so the average exposure of occupants of home A could be 10 times that of occupants of home B. For exposure-assessment purposes, it may therefore be more accurate to express exposure as floor-dust concentration per square meter sampled than as concentration per gram of sampled dust.

It is critical that surface sampling procedures be standardized so that sample results can be compared between sampling sessions. This requires standardization with regard to the selection of the sampling location, the technique of vacuuming, vacuum suction and the duration of sampling. Provided that sampling procedures are standardized, sampling of settled dust is reproducible as has been demonstrated for samples taken repeatedly over time (Heinrich et al., 2003).

Although surface sampling has advantages in many situations (particularly when a proxy of long-term average exposure is required), airborne measurements may be more desirable in others. Airborne measurements allow fluctuations in exposure to be assessed over the course of a week, a day or even hours; this can be essential in studying acute adverse effects such as daily lung-function changes with such metrics as FEV1 (forced expiratory volume in 1 sec) or PEF (peak expiratory flow). Airborne sampling is also likely to capture the more appropriate dust fraction; that is, inhalable particles. Chew et al. (2003) propose that reservoir dust and air sampling represent different types of potential exposure to residents, suggesting that collection of both air and dust samples may be essential. However, airborne concentrations of specific agents are generally low in the residential indoor environment, and for many laboratory-based methods analytic sensitivity is not sufficient, so short-term airborne sampling is impossible for most agents. “Aggressive air sampling” has been suggested to overcome the problem of low indoor-air concentrations under “routine” conditions (IOM, 1993; Rylander, 1999; Rylander et al., 1992). Aggressive sampling involves activities intended to encourage the generation of biologic aerosols during sampling by agitating floor dust with devices that mimic people walking on carpets (Buttner et al., 2002) or by rapping on ventilation ducts (Dillon et al., 1999). Its usefulness in exposure assessment, however, is not clear. Viable microorganisms in the air can be identified with great sensitivity, provided that one is able to capture them alive and select a medium that can support their growth so that they can be measured under normal circumstances with methods for airborne sampling. However, sampling of viable microorganisms in the air with culture techniques will provide at best a “snapshot” of current exposure, given the high variability of microbial concentrations, the episodic nature of emissions from some microbial agents, and the relatively short sampling time allowed for this method. Thus, assessing the “true exposure” (ERR) requires many samples and is not possible in most population studies.

In summary, airborne measurements may be a good indicator of exposure from a theoretical point of view, particularly for assessing acute short-term exposures, but detection problems limit their use for most biological agents in practice. Surface sampling is often the only alternative. When long-term exposures are being assessed, surface sampling may have an additional advantage over airborne measurements in that airborne measurements require a much larger number of samples to be taken because of the expected large variation in airborne concentrations. Nonetheless, it should be stressed that surface sampling is crude and is expected to yield a poor surrogate of airborne concentrations and the theoretical risk-relevant dose measure. Results of surface sampling as a measure of exposure should be interpreted with caution (Chew et al., 1996).

Personal vs Area Sampling

Assuming that airborne sampling is the desirable choice in a particular situation, personal measurements best represent the current airborne ERR. Therefore, personal sampling is preferred to area sampling. Modern sampling equipment is now sufficiently light and small to use for personal sampling, and several studies of chemical air pollution have demonstrated its feasibility in both the indoor and outdoor environments (Janssen et al., 1999, 2000). However, practical constraints may make personal sampling impossible: it might be too cumbersome for the study subjects, or there might be no portable equipment to make the desired measurements (such as measurements of viable microorganisms).

If personal sampling is not possible, area sampling can be applied to reconstruct personal exposure with the “microenvironmental model” approach.5 The microenvironmental model of human exposure is widely accepted for environmental exposure assessment (Sexton and Ryan, 1988). In that model, exposure of a person to an airborne agent is defined as the time-weighted average of agent concentrations encountered as the person passes through a series of microenvironments. However, exposures to microbial agents—such as particulate allergens, endotoxins, and fungal spores—often occur episodically because of inadvertent disturbance and resuspension of reservoirs of biologic agents by human activities (vacuum cleaning, handling of bedding, and the like) or because of mold blooms. Those episodic exposure patterns are not likely to be accurately captured by environmental area samplers. In addition, it is practically impossible to measure all the relevant microenvironments. Given those uncertainties, personal sampling is, despite some practical problems, a preferred method.

When, Where, and How Often to Sample

To the extent to which it is possible, samples should be taken to represent ERR at the appropriate time. In the case of acute effects, exposure measurements taken shortly (up to 8 or 12 hours) before the effects take place would clearly be the most useful. However, it is not always possible to collect such information. Personal sampling is preferable, but if it cannot be performed, ambient sampling can be conducted where the person in question spends the most time. If air sampling is impossible for the reasons mentioned above, settled-dust samples can be taken in the same areas.

The case of chronic effects is more complicated because ideally exposure should be assessed before the occurrence of the effects and preferably at the time that is biologically most relevant, that is, when the exposure is thought to be the most problematic (such as when fungi are releasing spores) or when subjects are most susceptible to exposure. That is possible only in longitudinal cohort studies, and even then it often is not clear when people are most susceptible to the exposure of interest, although it is generally assumed that early childhood is the most relevant period for allergens. Cohort studies, however, are time-consuming and expensive. Most often, case-control studies are conducted; in these studies, exposure can be assessed only retrospectively. Settled-dust sampling (which is reviewed in Macher, 2001a,b) may be the best option because microbial agents in house dust appear to be relatively stable over long periods, and current concentrations may be a reasonable proxy for past exposures, assuming that the subjects have not moved homes or substantially changed the home conditions. It is not clear which sampling site best represents exposure; therefore, often a combination of bedroom and living-room floor dust samples and mattress dust samples is taken, sometimes including samples from the kitchen floor.

For risk-assessment purposes, measures of exposure need to be both accurate and precise so that the effect of exposure on disease can be estimated with minimal bias and maximal efficiency. Therefore, exposure must be assessed with a minimal measurement error. Precision can be gained (that is, measurement error can be reduced) by increasing the number of samples taken in each home. In population studies, repeated sampling within the home as a proxy for within-subject variation in exposure is particularly effective for exposures that are known to vary widely in the home relative to the variation observed between homes. If the within-home variation is smaller than the between-home variability, however, repeated sampling will not significantly reduce the measurement error, and one or a few samples will be sufficient. If within- and between-home variations are known (from previous surveys or pilot studies, for example), the number of samples required to obtain a given reduction in risk-estimate bias can be computed in the manner described by Cochran (1968). A within-home to between-home variance ratio of 3:1 to 4:1—which is not uncommon in airborne sampling of viable microorganisms—implies that 27–36 samples per home are required to estimate the average exposure reliably for an epidemiologic study with no more than a 10% bias in the relationship between some health end point and the exposure (Heederik and Attfield, 2000; Heederik et al., 2003).

Studies that include repeated measurements are scarce, so within-home and between-home variation cannot be accurately assessed. However, data are available on some agents. For example, it is well known that the concentration of total airborne viable fungi varies widely within a building even over very short periods (Hunter et al., 1988; Verhoeff et al., 1994). Viable mold counts in house-dust samples taken from the same location within a 6-week interval also showed very poor reproducibility (Verhoeff et al., 1994). In the same study, the variation in isolated genera and species between duplicate samples was even more substantial, with a very high within-home to between-home variance ratio of 3:1 to 4:1. More recently, that was confirmed in another study focusing on dustborne concentrations (Chew et al., 2001). It was demonstrated further that measurements of markers of fungal exposure in house dust, such as fungal EPSs were more reproducible, with an estimated within-home to between-home variance ratio of only 0.5:1. The estimated within-home variation of β(1→3)-glucans and total culturable fungi was similar to the between–home variations, with ratios close to 1:1. Endotoxin concentrations in house dust in 20 homes in the United States measured repeatedly during a period of 12 months were significantly correlated (r = 0.76 for bed dust and 0.40 for bedroom-floor dust); this suggests average to good reproducibility for this measure (Park et al., 2000). In addition, a much larger study in Germany involving repeated dust sampling in 745 homes with a median interval of 7 months between first and second sampling periods showed that allergen (mite and cat) and endotoxin concentrations were well correlated over time, with crude correlation coefficients of 0.65–0.75 for the allergens and 0.59 for endotoxins (Heinrich et al., 2003). Viable-spore counts were, however, very poorly correlated—a correlation coefficient of only 0.06. On the basis of that limited experience, within-home variability of indoor-air concentrations of biologic agents are expected to be generally high and within-home variability of concentrations of these components in settled house dust generally low (compared with between-home variation). An exception is viable microorganisms, the concentration of which is highly variable in both indoor air and settled dust.

Little is known about spatial variation—that is, variation in concentrations between sampling locations at the same site, such as, in the case of surface sampling, on the same floor or bed. For example, studies have shown that house dust mite and cat allergen distribution is highly variable in settled dust (Hirsch et al., 1998; Loan et al., 2003). Expression as allergen mass did not reduce this variability (Hirsch et al., 1998). Isolated sampling of settled dust thus does not necessarily characterize the total burden of a specific agent in a building. However, in the case of floor dust, samples taken from the center of the room (as is commonly done in studies) have been shown to yield concentrations very similar to the mean concentration level for the whole floor, indicating that a single sample taken in this manner may be representative (Loan et al., 2003). Similar studies for other microbial agents have not yet been conducted.

Thus, because only sparse data are available on variation in exposure to biologic agents in the home environment, it is not possible to recommend how many samples should be taken to produce an accurate assessment of the ERR. However, there is a strong suggestion that airborne concentrations are characterized by high variability over time, an indication that one sample per home is unlikely to be sufficient even when acute health effects are being considered, because variations in exposure occur over very short periods. Measurements of specific microbial agents in house dust generally appear to vary less and seem stable even over relatively long periods (up to 12 months and perhaps even longer), so one or a few samples may be sufficient. If only one floor sample is to be collected, research suggests that it be taken from the center of the floor (in front of a couch or a chair); for mattresses, the whole mattress should be sampled. Although measurements of dust can be more precise, it is not clear how well they represent airborne exposure. Measurements of viable microorganisms vary greatly over time regardless of whether they are sampled in air or in floor or bed dust, and many samples might be required.

In most circumstances, the only reason to go to the expense to measure specific taxa or the presence of glucan, ergosterol and the like is for the purposes of research into the health effects of exposure to those agents. However, persons experiencing health outcomes with suspected or established links to a specific agent (aspergillosis, for example) may gain useful information from a more detailed characterization. Testing in those circumstances could be used to identify problematic environments and inform remediation decisions.


Measurement of microorganisms relies on collection of a sample into or onto solid, liquid, or agar media and then microscopic, microbiologic, biochemical, immunochemical, or molecular biologic analysis (Eduard and Heederik, 1998). Two distinctly different approaches are used for evaluation of microbial exposure: culture-based and nonculture methods.

Culture-Based Methods

Exposure to microorganisms in the indoor environment can be studied by counting culturable propagules in settled-dust samples. Alternatively, airborne exposure can be studied with various devices for microbial bioaerosol sampling (these are reviewed at length by Eduard and Heederik, 1998). There are three standard methods of active sampling of airborne culturable bioaerosols (Heederik et al., 2003):

  • Impactor methods. With impactor sampling, bioaerosols moving in the air stream pass through a round jet or a slit to a culture medium. Multistage devices allow some size discrimination by sequentially increasing the velocity through the jet and decreasing the jet-to-plate spacing.
  • Liquid impinger methods. Liquid impingers collect microorganisms by directing the air stream into a liquid collection fluid. Bacteria, viruses, and fungal spores are retained in the collection fluid and can subsequently be plated onto appropriate culture media or evaluated with other analytical techniques, although some re-entrainment and losses occur (Grinshpun et al., 1997; Willeke et al., 1988).
  • Air filtration methods. Several sampling methods in common use rely on filtration to collect bioaerosols from a sampled air volume. After sampling, filters are agitated or sonicated in a solution. The solution is then serially diluted and plated on culture media or examined with other analytical techniques (biotechnology-based, immunological, or chemical assay, for example).

After sample collection (either airborne or from surfaces), bacterial growth media is incubated at a defined temperature for 3 days while fungal growth media may require incubation of 10 days. Colonies are counted and identified manually or with the aid of image-analysis techniques (reviewed in Eduard and Heederik, 1998). Concentrations are expressed as colony-forming units (CFUs) per sampled cubic meter of air or, in the case of surface sampling, per gram of sampled dust or per square meter.

Counting of culturable microorganisms has some serious drawbacks, including poor reproducibility; selection toward certain species because of chosen culture media, temperature, and the like; and the fact that dead microorganisms, cell debris, and microbial components are not detected although they may have toxic or allergenic properties. In addition, good methods for personal air sampling of culturable microorganisms are not available, and, although air concentrations usually vary widely in time, air sampling during a period of more than 15 minutes is often not possible and repeated sampling may be difficult logistically. But counting of culturable microorganisms is potentially a very sensitive technique that can identify many species.

Traditionally used culture methods to assess concentrations of culturable microorganisms in indoor air or settled dust have proved to be of little use for quantitative exposure assessment. They usually provide qualitative, rather than quantitative, information that can be important in risk assessment in that not all fungal and bacterial species pose the same hazard. A more extensive review of culture-based methods is available in the American Conference of Industrial Hygienists (ACGIH) publication “Bioaerosols, Assessment and Control” (1999).

Nonculture Methods

Nonculture methods enumerate organisms without regard to viability. Microorganisms in dust samples can be stained with a fluorochrome, such as acridine orange, and counted with an epifluorescence microscope (Thorne et al., 1994). Taxonomic classification of microorganisms is limited because little detail can be observed. Scanning electron microscopy (SEM) can also be used and allows better determination (Eduard et al., 1988; Karlsson and Malmberg, 1989) but it is expensive. Simple light microscopy may be used to count microorganisms, but counting is based only on morphologic recognition, which may result in large measurement errors. Bacteria collected with impingers or filters can be counted using flow cytometry after staining with 4',6-diamino-2-phenylindole (DAPI) or with fluorescent in situ hybridization (FISH) (Lange et al., 1997).

The main advantages of microscopy or flow cytometry are that both dead and living microorganisms are counted, selection effects are reduced, personal air sampling is possible, and sampling time can be varied over a wide range. Disadvantages include laborious and complicated procedures, high costs per sample, unknown validity, no detection of possibly relevant toxic or allergenic components or cell debris, and few possibilities of determination of microorganisms. Eduard and Heederik (1998) have published a more extensive review on microscopy and flow-cytometry methods for counting nonculturable microorganisms; the ACGIH (1999) review is another valuable reference for these methods.

Little or no experience is available with the more recently developed and more advanced nonculture based methods (scanning electron and epifluorescence microscopy, and flow cytometry, for example) in the nonindustrial indoor environment so the usefulness of these methods in indoor risk assessment is unknown.


Instead of counting culturable or nonculturable microbial propagules, constituents or metabolites of microorganisms can be measured as a surrogate of microbial exposure. Toxic components (for example, from mycotoxins) or proinflammatory components (from endotoxins) can be measured, but nontoxic molecules may also serve as markers of large groups of microorganisms or of specific microbial genera or species. The use of advanced methods, such as polymerase chain reaction (PCR) technologies and immunoassays, have opened new avenues for detection and speciation regardless of whether the organisms are culturable (Buttner et al., 2001; Cruz-Perez et al., 2001a,b).

Markers for assessment of fungal biomass include ergosterol measured by gas chromatography-mass spectrometry (GCMS) (Miller and Young, 1997) and fungal EPSs measured with specific enzyme immunoassays (Douwes et al., 1999), which allow partial identification of the mold genera present. Volatile organic compounds produced by fungi may be suitable markers of fungal growth (Dillon et al., 1996). Other agents, such as β(1→3)-glucans (Aketagawa et al., 1993; Douwes et al., 1996) and bacterial endotoxins are being measured on the basis of their toxic potency. Endotoxins are measured with an LAL assay prepared from blood cells of the horseshoe crab, Limulus polyphemus (Bang, 1956). Analytical chemistry methods for measurement of lipopolysaccharides (LPSs) have also been developed by using GCMS (Sonesson et al., 1988, 1990); however, these methods require special LPS extraction procedures and have not been widely used. Three methods for measuring β(1→3)-glucans have been described, of which one is based on the LAL assay (Aketagawa et al., 1993) and two are enzyme immunoassays (Douwes et al., 1996; Milton et al., 2001). Finally, PCR techniques have been developed for the identification of specific species of bacteria and fungi (Alvarez et al., 1994; Haugland et al., 1999; Khan and Cerniglia, 1994). Application of quantitative PCR for analysis of environmental samples that contain microorganisms is still under development (Buttner et al., 2001; Cruz-Perez et al., 2001a,b).

A number of methods—including GC, GCMS, high-performance liquid chromatography (HPLC), capillary electrophoresis, thin-layer chromatography, enzyme-linked immunosorbent assays (ELISA), and cell-culture cytotoxicity testing—have been described to measure a large number of mycotoxins. Recent advances in technology have given laboratories the ability to test for specific mycotoxins without using cost-prohibitive GC or HPLC techniques. One source indicates that surface, bulk, food and feeds, and air samples can be analyzed relatively inexpensively for the following mycotoxins: aflatoxin; ochratoxin; trichothecenes, including T-2 toxin; fumonisins; deoxynivalenol or DON (vomitoxin); satratoxins; verrucarins; zearalenone; citrinin; alternariol; gliotoxin; patulin; and sterigmatocystin (Adler, 2002).

Most of the methods for measuring microbial constituents (an exception is the method for measuring bacterial endotoxins and some mycotoxins) are in an experimental phase and have not yet been routinely applied in epidemiologic studies or are not commercially available. Important advantages of those methods include the stability of most of the measured components, which allows longer sampling times for airborne measurements and frozen storage of samples before analysis; the use of standards in most of the methods; and the enhanced possibility of testing for reproducibility.


Antibody-based immunoassays, particularly ELISA, are widely used for the measurement of aeroallergens and allergens in settled dust in buildings. To date, the house dust mite allergens Der p 1, Der f 1, and Der p/f 2 have been most widely investigated, and the methods have been well described (Platts-Mills and Chapman, 1987; Platts-Mills and de Weck, 1989; Price et al., 1990). Methods for measuring fungal allergens are not widely available, primarily because fungal allergen production in nature is highly variable and depends on many factors, including substrate and temperature. The variability makes it difficult to develop specific antibody-based immunoassays that detect the relevant fungal allergens in a specific environment.


Signs and Measurements of Dampness, Moisture, or Mold

Humans are poor humidity sensors, but some signs of inappropriate moisture can be directly perceived. Such perceptions are the basis of most epidemiologic studies, in which data on moisture conditions are collected by questionnaire. Questions are typically formulated to seek information on whether leaks, floods, wet basements, window condensation, visible fungal growth, or moldy odors are present. However, there is considerable variation in how the questions are framed. In some studies, the dampness indicator is limited to recent experience, such as “presence of damp stains or mold growth on indoor surfaces in last 2 years” (Brunekreef, 1992); others record experience with building dampness over the subjects' lifetimes. Assessment of dampness may also be classified according to specific building environments circumstances, for example, “Have you previously or do you currently notice moisture stains in the structures of your home?” (Pirhonen et al., 1996). Some have collected information about specific areas, such as “mold in a child's bedroom” or the living room. In many cases, the questions are collapsed into broader categories of dampness (Kilpeläinen et al., 2001; Yang et al., 1998). Table 3-1 provides examples of the studies. It should be noted that reporting bias may be a source of error in such research. Dales and colleagues (1997) report that under some conditions allergy patients may be more likely than nonallergic people to report visible fungal growth. However, other studies have demonstrated that such bias is unlikely (Verhoeff et al., 1995; Zock et al., 2002).

TABLE 3-1. Dampness Definitions and Associated Environmental Assessments in Selected Cross-Sectional and Analytic Epidemiologic Studies in Which “Dampness” Was a Key Risk Factor in Health Outcomes.


Dampness Definitions and Associated Environmental Assessments in Selected Cross-Sectional and Analytic Epidemiologic Studies in Which “Dampness” Was a Key Risk Factor in Health Outcomes.

Moisture conditions in buildings may be best discovered through direct observation and inspection. Home inspectors are known to rely on smell to supplement visual inspection. Among the items typically included in an inspection report are presence of mold, water stains, evidence of leaks or flooding, current leaks, crawl space conditions, attic sheathing condition, and overall stoutness or dilapidation of the building. Characterization of rainwater discharge and management is also necessary, given the importance and prevalence of foundation leakage to the overall moisture balance of a building. In one of the earlier studies of building dampness, Platt et al. (1989) trained surveyors to assess dampness by severity and type, mold by severity and location, and details of building structure. Air samples were also taken from rooms, and spore counts were estimated and fungi identified where possible. Koskinen et al. (1999) reported a study in which civil engineers recorded signs of leakage, presence of moist spots, detachment of paint or other surface material, and deformation of wood or discoloration and then categorized the findings into “moisture absent” or “moisture present.” Mohamed and colleagues (1995) described a study in Nairobi, Kenya, in which interviewers assessed the home with a standardized checklist; many of the homes lacked solid floors. Results of those and other studies will probably encourage others to provide more information about dampness in buildings in developing countries.

Attempts to quantify building characteristics with engineering protocols have been limited to a few epidemiologic studies. One of the most comprehensive attempts to describe dampness in relation to both indoor and outdoor characteristics has been reported by Jedrychowski and Flak (1998). Williamson et al. (1997) also applied an extensive assessment protocol to assess building dampness. Surveyors measured spot temperatures and relative humidity outdoors and in each room of the dwelling. An electronic resistance moisture meter was also used to measure dampness just above skirting-board height in the rooms. Dampness was coded as 0 (<10%), 1 (11–25%), 2 (26–50%), 3 (51–75%), or 4 (>75%) and the scores were summed for a total dampness score. The presence and severity of visible mold growth on each wall were graded subjectively on a four-point scale: 0 = absent, 1 = trace, 2 = obvious but localized, and 3 = obvious and widespread. Dwellings with a total mold score of 3 or more were classified as having significant mold contamination.


For biologic agents, very few biomarkers of exposure or dose have been identified, and their validity for exposure assessment in the indoor environment is often not known. Adducts formed by aflatoxins and ochratoxins as they damage DNA, RNA, and proteins can be measured from the body fluids of exposed persons (Bechtel, 1989; Sabbioni and Wild, 1991). They reflect repair activity more than they reflect degree of exposure, however, and do not accurately quantify exposure. But DNA adducts do indicate past presence of and damage to nucleic acids and constitute a limited biomarker of exposure, effect, and susceptibility (Miraglia et al., 1996). A 2003 study in rats suggested that measurement of stachylysin (a proteinaceous hemolysin) in serum with an ELISA technique could be used as a biomarker of exposure to Stachybotrys chartarum (Van Emon et al., 2003). However, although the method is sensitive and specific, it is not clear whether it is useful for quantitatively assessing indoor exposures to that mold. The same is true of the measurement of trichothecene mycotoxins in serum (Croft et al., 2002).

To the committee's knowledge, no other direct methods for measuring biologic agents or metabolites thereof in blood or urine have been described. IgG antibodies in serum have been suggested as an indirect marker of recent occupational exposure to fungi (Burrell and Rylander, 1981; Eduard et al., 1992), but little is known about the quantitative relation between serum IgG and airborne exposure. A few studies involving children and school indoor environments suggested that the correlation between IgG and mold exposure is poor (Immonen et al., 2002; Taskinen et al., 2002).

IgE and inflammatory markers in blood, sputum, nasal-lavage fluid, and exhaled breath condensate have been suggested as biomarkers of exposure (Hirvonen et al., 1999; Roponen et al., 2001, 2003), but these are more appropriately addressed as markers (or intermediates) of effect since they indicate susceptible persons and play a major role in the pathophysiological events leading to symptoms and disease. Therefore, they should not be considered markers of exposure.

Predictive Exposure Models

If the factors that explain the variation in indoor microbial exposure were known, mathematical models could be developed to predict exposure in homes where no exposure measurements were taken, provided that valid information on determinants of exposure were available. Various studies demonstrate that home and occupant characteristics assessed by questionnaire (such as age of building, presence of pets in the home, type of carpet, type of heating and ventilation, and damp or mold spots) are associated with indoor microbial exposures (Bischof et al., 2002; Douwes et al., 1998, 1999; Gehring et al., 2001). However, not all studies find housing characteristics to be predictive (Wood et al., 1988, for example), and the explained variance is too small to predict exposure reliably on the basis of these factors. Therefore, no such predictive models can now be used to assess exposure to biologic agents in the indoor environment accurately.


This section briefly discusses reported indoor concentrations of some biologic agents. However, the concentrations should be interpreted with caution because the studies used different sampling and analytic procedures that potentially could result in large differences in exposure assessment.


The concentrations of viable fungi in indoor environments are usually a few to several thousand CFUs per cubic meter of air. Those concentrations are highly variable and depend on such factors as climate and season; type, construction, age, and use of the building; and ventilation rate. The observed concentrations also depend on the sampling and analytic methods used. Table 3-2 summarizes fungal concentrations that have been observed in buildings in different countries; these data should be interpreted with caution because of the methodologic limitations described above, and they cannot be used as reference values.

TABLE 3-2. Reported Concentrations of Airborne Bacteria in Indoor Air in Selected Studies.


Reported Concentrations of Airborne Bacteria in Indoor Air in Selected Studies.


Relatively few studies have reported concentrations of bacteria in indoor air. The problems of accurate exposure assessment discussed for fungi also apply to measurements of airborne bacteria. New methods focusing on quantification of bacterial biomass with chemical markers (Szponar and Larsson, 2000, 2001) or, more specifically, DNA-based methods (Macneil et al., 1995) will probably help to solve some of these limitations. For some airborne pathogens, specific methods based on gene-amplification reactions have been developed (Pena et al., 1999), but applications of DNA-based methods for larger-scale analyses of airborne bacteria still need more validation.

The reported concentrations of viable bacteria in indoor air are summarized in Table 3-2. Usually, the total concentrations measured on standard media are reported, and few studies have characterized the bacterial flora of indoor air. Table 3-3 shows a rough summary of those bacteria found and indicates that gram-positive cocci usually dominate the airborne bacterial flora. Again, the data in these tables cannot be used as reference values.

TABLE 3-3. Bacterial Types Found in Different Indoor Environments.


Bacterial Types Found in Different Indoor Environments.


Endotoxin concentrations measured within particular nonindustrial indoor spaces vary widely, from a few to several thousand endotoxin units6 (EU) per milligram of house dust (Table 3-4). Concentrations measured as EU per square meter vary even more widely. However, ranges of endotoxin concentrations reported by researchers appear to vary only moderately between studies regardless of the geographic area. That is remarkable, considering that analytic methods applied in those studies were not standardized. Only a few studies have focused on airborne concentrations in the indoor environment. Park et al. (2000) reported a mean airborne endotoxin concentration of 0.64 EU/m3 measured in 15 homes in Boston, Massachusetts (and mean dust endotoxin concentrations of 44–105 EU/mg), indicating that time-weighted mean exposures are very low compared with the work environment, where airborne endotoxin concentrations can range from several tens to thousands of endotoxin units per cubic meter (Douwes et al., 2002).

TABLE 3-4. Overview of Epidemiologic Studies Indicating Adverse or Protective Effects on Respiratory Health Related to Indoor Endotoxin Exposure.


Overview of Epidemiologic Studies Indicating Adverse or Protective Effects on Respiratory Health Related to Indoor Endotoxin Exposure.


Methods used to analyze β(1→3)-glucans in environmental (settled or airborne) dust samples have not been standardized and are therefore not comparable across studies. In Sweden and Switzerland, typical exposures in buildings with mold problems ranged from about 10 to more than 100 ng/m3 according to an LAL assay of β(1→3)-glucans in airborne dust samples that were generated by rigorous agitation of settled dust in those buildings (Rylander, 1999). Exposures in buildings that had no obvious mold problems were close to 1 ng/m3. In the Netherlands and Germany, mean β(1→3)-glucans concentrations in house dust determined with a specific enzyme immunoassay were highly comparable at around 1,000–2,000 µg/g of dust and 500–1,000 µg/m2 (Chew et al., 2001; Douwes et al., 1996, 1998, 2000; Gehring et al., 2001). Samples were also taken in homes that were not selected specifically on the basis of mold problems and were analyzed in the same laboratory with identical procedures. No airborne samples were taken.


No health-based recommended exposure limits for indoor biologic agents exist, and this makes the interpretation of exposure difficult, particularly in case studies. Strategies to evaluate exposure data (either quantitatively or qualitatively) should include comparison of exposure data with background concentrations or, better, a comparison of exposures between symptomatic and nonsymptomatic subjects. A quantitative evaluation involves comparing exposures, whereas a qualitative evaluation could consist of comparing species or genera of microorganisms in different environments. Because of differences in climatic and meteorological conditions and differences in measurement protocols used in various studies (viable versus non-viable microorganism sampling, sampler type, analysis, and so on), reference material from the literature can seldom be used. Thus, to draw valid conclusions, it is important in each study to include measurements in indoor environments of subjects without symptoms. Furthermore, interpretations of airborne sampling should be based on multiple samples because space–time variability in the environment is high. Finally, the proper interpretation of exposure results requires detailed information about sampling and analytic procedures (including quality control) and knowledge of the potential problems associated with those procedures.

It is not possible to reach a general conclusion on whether total fungal counts represent a meaningful measure of exposure for indoor-related health effects. In cases where health outcomes have established links to a specific agent or microorganism, it is appropriate to focus on measurement of that agent or microorganism. If, on the other hand, agents such as β(1→3)-glucans are involved, then a total fungi count may be a relevant measure as almost all fungi contain β(1→3)-glucans. Given the present state of knowledge, it may be appropriate to make both specific and total fungi measures when this is possible.

Further, it is currently not clear whether fungal counting methods do a better job of characterizing a person's or population's true exposure than the traditionally-applied culture methods: this is largely dependent on the aim of the study, the specific health outcome(s) of interest, and the nature and source of the exposure. For some health outcomes—those involving allergic sensitization, for example—the identity of the microbial agent may be as important as the amount of agent present. These gaps in the knowledge base create a potential for misinterpretation and misuse of results that must be kept in mind whenever sampling is conducted. More research is needed to further our understanding of which exposure assessment methods are most relevant in assessing health risks from indoor exposures. General recommendations with regard to exposure assessment methods for the purpose of risk assessment can therefore not be given, particularly since indoor-related symptoms or diseases may be caused by multiple exposures.


Based on the review of the papers, reports and other information presented in this chapter, the committee has reached the following findings and recommendations, and has identified the following research needs regarding exposure assessment for damp indoor environments.

  • The evaluation of exposure characterization results should, whenever possible, be based on:
    • —Comparison of exposure data with background concentrations or, better, a comparison of exposures between symptomatic and nonsymptomatic subjects.
    • —Multiple samples, because space–time variability in the environment is high.
    • —Detailed information about sampling and analytic procedures (including quality control) and knowledge of the potential problems associated with those procedures.
  • The lack of knowledge regarding indoor microbial exposures and related health problems is due primarily to a lack of valid quantitative methods for assessing exposure.
  • There are several methods for measuring and characterizing fungal populations, but methods for assessing human exposure to fungal agents are poorly developed. Part of the difficulty is related to the large number of fungal species that are measurable indoors and the fact that fungal allergen content and toxic potential varies among species and among morphologic forms within species. In addition, the most common methods for fungal assessment—counting cultured colonies and identifying and counting spores—have variable and uncertain relationships to allergen, toxin, and irritant content of exposures.
  • Existing exposure assessment methods for fungal and other microbial agents need rigorous validation and further refinement to make them more suitable for large-scale epidemiologic studies. This includes standard ization of protocols for sample collection, transport of samples, extraction procedures, and analytical procedures and reagents. Such work should result in concise, internationally accepted protocols that will allow measurement results to be compared both within and across studies.
  • Research is needed to develop improved exposure assessment methods, particularly methods based on nonculture techniques and techniques for measuring constituents of microorganisms—allergens, endotoxins, β(1→3)-glucans, fungal extracellular polysaccharides (EPSs), fungal spores, other particles and emissions of microbial origin. These needs include:
    • —Further improvement of light and portable personal airborne exposure measurement technology.
    • —More rapid development of measurement methods for specific microorganisms that use DNA-based and other technology.
    • —Rapid and direct-reading assays for bioaerosols for the immediate evaluation of potential health risks.
  • Application of the new or improved methods will allow more valid exposure assessment of microorganisms and their components, which should facilitate more-informed risk assessments.


  • Åberg N, Sundell B, Eriksson B, Hesselmar B, Åberg B. 1996. Prevalence of allergic diseases in school children in relation to family history, upper respiratory infections, and residential characteristics. Allergy 51(4):232–237. [PubMed: 8792919]
  • ACGIH (American Conference of Governmental Industrial Hygienists). 1999. Bioaerosols: Assessment and Control. Macher JM, editor. , ed. Cincinnati, OH: American Conference of Governmental Industrial Hygienists.
  • Adler CM. 2002. Mycotoxins: characteristics, sampling methods, and limitations. ENVIRO-CHECK, Inc. Winter 2002–2003. http://www​.envirocheckonline​.com/docs/mycotoxins.pdf. accessed June 16, 2003.
  • Aketagawa J, Tanaka S, Tamura H, Shibata Y, Sait H. 1993. Activation of limulus coagulation factor G by several (1→3)-β-D-glucans: comparison of the potency of glucans with identical degree of polymerization but different conformations. Journal of Biochemistry 113:683–686. [PubMed: 8370664]
  • Alvarez AJ, Buttner MP, Toranzos GA, Dvorsky EA, Toro A, Heikes TB, Mertikas-Pifer LE, Stetzenbach LD. 1994. Use of solid-phase PCR for enhanced detection of airborne micro-organisms. Applied Environmental Microbiology 60:374–376. [PMC free article: PMC201317] [PubMed: 8117092]
  • American Thoracic Society. 1997. American Thoracic Society Workshop, Achieving Healthy Indoor Air. American Journal of Respiratory and Critical Care Medicine 156(Supplement 3):534–564.
  • Andriessen J, Brunekreef B, Roemer W. 1998. Home dampness and respiratory health status in European children. Clinical and Experimental Allergy 28:1191–1200. [PubMed: 9824385]
  • Bang FB. 1956. A bacterial disease of Limulus polyphemus. Bulletin of the John Hopkins Hospital 98:325–350. [PubMed: 13316302]
  • Bechtel DH. 1989. Molecular dosimetry of hepatic aflatoxin B1-DNA adduct: linear correlation with hepatic cancer risk. Regulatory Toxicology and Pharmacology 10(1):74–81. [PubMed: 2505337]
  • Bischof W, Koch A, Gehring U, Fahlbusch B, Wichmann HE, Heinrich J. 2002. Predictors of high endotoxin concentrations in the settled dust of German homes. Indoor Air 12:2–9. [PubMed: 11951708]
  • Braun-Fahrländer C, Riedler J, Herz U, Eder W, Waser M, Grize L, Maisch S, Carr D, Gerlach F, Bufe A, Lauener RP, Schierl R, Renz H, Nowak D, von Mutius E, Allergy and Endotoxin Study Team. 2002. Environmental exposure to endotoxin and its relation to asthma in school-age children. New England Journal of Medicine 347(12):869–877. [PubMed: 12239255]
  • Brunekreef B. 1992. Damp housing and adult respiratory symptoms. Allergy 47(5):498–502. [PubMed: 1485653]
  • Brunekreef B, Groot B, Rijcken B, Hoek G, Steenbekkers A, de Boer A. 1992. Reproducibility of childhood respiratory symptom questions. The European Respiratory Journal 5(8): 930–935. [PubMed: 1426200]
  • Burge HA. 2000. The fungi. In: Indoor Air Quality Handbook. JD Spengler, editor; , JM Samet, editor; , JF McCarthy, editor. , eds. New York: McGraw-Hill.
  • Burge HA, Pierson DL, Groves TO, Strawn KF, Mishra SK. 2000. Dynamics of airborne fungal populations in a large office building. Current Microbiology 40:10–16. [PubMed: 10568797]
  • Burrell R, Rylander R. 1981. A critical review of the role of precipitins in hypersensitivity pneumonitis. European Journal of Respiratory Diseases 62(5):332–343. [PubMed: 7047184]
  • Buttner MP, Cruz-Perez P, Stetzenbach LD. 2001. Enhanced detection of surface-associated bacteria in indoor environments by quantitative PCR. Applied Environmental Microbiology 67(6):2564–2570. [PMC free article: PMC92908] [PubMed: 11375164]
  • Buttner MP, Cruz-Perez P, Stetzenbach LD, Garrett PJ, Lutke AE. 2002. Measurement of airborne fungal spore dispersal from three types of flooring materials. Aerobiologia 18(1):1–11.
  • Chew GL, Muilenberg ML, Gold D, Burge HA. 1996. Is dust sampling a good surrogate for exposure to airborne fungi? Journal of Allergy and Clinical Immunology 97:419.
  • Chew GL, Douwes J, Doekes G, Higgins KM, Strien R, Spithoven J, Brunekreef B. 2001. Fungal extracellular polysaccharides, β(1→3)-glucans, and culturable fungi in repeated sampling of house dust. Indoor Air 11:171–178. [PubMed: 11521501]
  • Chew GL, Rogers C, Burge HA, Muilenberg ML, Gold DR. 2003. Dustborne and airborne fungal propagules represent a different spectrum of fungi with differing relations to home characteristics. Allergy 58(1):13–20. [PubMed: 12580801]
  • Chun DT, Chew V, Bartlett K, Gordon T, Jacobs RR, Larsson BM, Larsson L, Lewis DM, Liesivuori J, Michel O, Milton DK, Rylander R, Thorne PS, White EM, Brown ME. 2000. Preliminary report on the results of the second phase of a round-robin endotoxin assay study using cotton dust. Applied Occupational and Environmental Hygiene 15: 152–157. [PubMed: 10712070]
  • Cochran WG. 1968. Errors of measurement in statistics. Technometrics 10:637–666.
  • Croft WA, Jastromski BM, Croft AL, Peters HA. 2002. Clinical confirmation of trichothecene mycotoxicosis in patient urine. Journal of Environmental Biology 23(3):301–320. [PubMed: 12597576]
  • Cruz-Perez P, Buttner MP, Stetzenbach LD. 2001. a. Specific detection of Aspergillus fumigatus in pure culture using quantitative polymerase chain reaction. Molecular and Cellular Probes 15:81–88. [PubMed: 11292325]
  • Cruz-Perez P, Buttner MP, Stetzenbach LD. 2001. b. Specific detection of Stachybotrys chartarum in pure culture using quantitative polymerase chain reaction. Molecular and Cellular Probes 15:129–138. [PubMed: 11352593]
  • Cuijpers CE, Swaen GM, Wesseling G, Sturmans F, Wouters EF. 1995. Adverse effects of the indoor environment on respiratory health in primary school children. Environmental Research 68(1):11–23. [PubMed: 7729382]
  • Curtis L, Ross M, Persky V, Scheff P, Wadden R, Ramakrishnan V, Hryhorczuk D. 2000. Bioaerosol concentrations in the quad cities 1 year after the Mississippi river floods. Indoor and Built Environment 9(1):35–43.
  • Dales RE, Miller D. 1999. Residential fungal contamination and health: microbial cohabitants as covariates. Environmental Health Perspectives 107(Supplement 3):481–483. [PMC free article: PMC1566221] [PubMed: 10423391]
  • Dales RE, Burnett R, Zwanenburg H. 1991. Adverse health effects among adults exposed to home dampness and molds. American Review of Respiratory Disease 143(3):505–509. [PubMed: 2001058]
  • Dales RE, Miller D, McMullen E. 1997. Indoor air quality and health: validity and determinants of reported home dampness and moulds. International Journal of Epidemiology 26:120–125. [PubMed: 9126511]
  • Dillon HK, editor; , Heinsohn PA, editor; , Miller JD, editor. , eds. 1996. Field Guide for the Determination of Biological Contaminants in Environmental Samples. Fairfax, VA: American Industrial Hygiene Association.
  • Dillon HK, Miller JD, Sorenson WG, Douwes J, Jacobs RR. 1999. A review of methods applicable to the assessment of mold exposure to children. Environmental Health Perspectives 107(Supplement 3):473–480. [PMC free article: PMC1566225] [PubMed: 10423390]
  • Douwes J, Versloot P, Hollander A, Heederik D, Doekes G. 1995. Influence of various dust sampling and extraction methods on the measurement of airborne endotoxin. Applied Environmental Microbiology 61:1763–1769. [PMC free article: PMC167439] [PubMed: 7646014]
  • Douwes J, Doekes G, Montijn R, Heederik D, Brunekreef B. 1996. Measurement of β(1→3)-glucans in the occupational and home environment with an inhibition enzyme immunoassay. Applied Environmental Microbiology 62:3176–3182. [PMC free article: PMC168113] [PubMed: 8795207]
  • Douwes J, Doekes G, Heinrich J, Koch A, Bischof W, Brunekreef B. 1998. Endotoxin and β(1→3)-glucan in house dust and the relation with home characteristics: a pilot study in 25 German houses . Indoor Air 8:255–263.
  • Douwes J, van der Sluis B, Doekes G, van Leusden F, Wijnands L, van Strien R, Verhoeff A, Brunekreef B. 1999. Fungal extracellular polysaccharides in house dust as a marker for exposure to fungi: relations with culturable fungi, reported home dampness and respiratory symptoms. Journal of Allergy and Clinical Immunology 103:494–500. [PubMed: 10069885]
  • Douwes J, Zuidhof A, Doekes G, van der Zee S, Wouters I, Boezen HM, Brunekreef B. 2000. (1→3)-β-D-glucan and endotoxin in house dust and peak flow variability in children. American Journal of Respiratory and Critical Care Medicine 162:1348–1354. [PubMed: 11029343]
  • Douwes J, Pearce N, Heederik D. 2002. Does bacterial endotoxin prevent asthma? Thorax 57:86–90. [PMC free article: PMC1746164] [PubMed: 11809997]
  • Duchaine C, Thorne PS, Mériaux A, Grimard Y, Whitten P, Cormier Y. 2001. Comparison of endotoxin exposure assessment by bioaerosol impinger and filter sampling methods. Applied Environmental Microbiology 67(6):2775–2780. [PMC free article: PMC92938] [PubMed: 11375194]
  • Eduard W, Heederik D. 1998. Methods for quantitative assessment of airborne levels of noninfectious micro-organisms in highly contaminated work environments. American Industrial Hygiene Association Journal 59:113–127. [PubMed: 9487665]
  • Eduard W, Sandven P, Johansen BV, Bruun R. 1988. Identification and quantification of mould spores by scanning electron microscopy (SEM): analysis of filter samples collected in Norwegian saw mills. Annals of Occupational Hygiene 31(Supplement 1):447–455.
  • Eduard W, Sandven P, Levy F. 1992. Relationships between exposure to spores from Rhizopus microsporus and Paecilomycetes variotti and serum IgG antibodies in wood trimmers. International Archives of Allergy and Immunology 97:274–282. [PubMed: 1597347]
  • Englehart S, Loock A, Skutlarek D, Sagunski H, Lommel A, Färber H, Exner M. 2002. Occurrence of toxigenic Aspergillus versicolor isolates and sterigmatocystin in carpet dust from damp indoor environments. Applied and Environmental Microbiology 68(8): 3886–3890. [PMC free article: PMC124040] [PubMed: 12147486]
  • Engvall K, Norrby C, Norbäck D. 2001. Asthma symptoms in relation to building dampness and odour in older multifamily houses in Stockholm. International Journal of Tuberculosis and Lung Disease 5(5):468–477. [PubMed: 11336279]
  • Evans J, Hyndman S, Stewart-Brown S, Smith D, Petersen S. 2000. An epidemiological study of the relative importance of damp housing in relation to adult health. Journal of Epidemiology and Community Health 54:677–686. [PMC free article: PMC1731738] [PubMed: 10942447]
  • Gehring U, Douwes J, Doekes G, Koch A, Bischof W, Wichmann HE, Heinrich J. 2001. β(1→3)-glucan in house dust of German homes related to culturable mold spore counts, housing and occupant characteristics. Environmental Health Perspectives 109:139–144. [PMC free article: PMC1240633] [PubMed: 11266323]
  • Gehring U, Bischof W, Fahlbusch B, Wichmann HE, Heinrich J. 2002. House dust endotoxin and allergic sensitization in children. American Journal of Respiratory and Critical Care Medicine 166(7):939–944. [Erratum: American Journal of Respiratory and Critical Care Medicine (2003) 167(1):91.] [PubMed: 12359650]
  • Gereda JE, Leung DYM, Thatayatikom A, Streib JE, Price MR, Klinnert MD, Liu AH. 2000. Relation between house-dust endotoxin exposure, type 1 T-cell development, and allergen sensitization in infants at high risk of asthma. Lancet 355(9216):1680–1683. [PubMed: 10905243]
  • Górny RL, Reponen T, Willeke K, Schmechel D, Robine E, Boissier M, Grinshpun SA. 2002. Fungal fragments as indoor air biocontaminants. Applied and Environmental Microbiology 68(7):3522–3531. [PMC free article: PMC126767] [PubMed: 12089037]
  • Grinshpun SA, Willeke K, Ulevicius V, Juozaitiis A, Terzieva S, Donnelly J, Stelma GA, Brenner K. 1997. Effect of impaction, bounce and reaerosolization on collection efficiency of impingers. Aerosol Science and Technology 26(4):326–342.
  • Haugland RA, Heckman JL, Wymer LJ. 1999. Evaluation of different methods for the extraction of DNA from fungal conidia by quantitative competitive PCR analysis. Journal of Microbiological Methods 37(2):165–176. [PubMed: 10445315]
  • Heederik D, Attfield M. 2000. Characterization of dust exposure for the study of chronic occupational lung disease—a comparison of different exposure assessment strategies. American Journal of Epidemiology 151(10):982–990. [PubMed: 10853637]
  • Heederik D, Douwes J, Thorne PS. 2003. Biological Agents—evaluation. In: Modern Industrial Hygiene. J Perkins, editor. , ed. Cincinnati, OH: ACGIH.
  • Heinrich J, Hölscher B, Douwes J, Richter K, Koch A, Bischof W, Fahlbusch B, Kinne R, Wichmann HE. 2003. Reproducibility of allergen, endotoxin and fungi measurements in the indoor environment. Journal of Exposure Analysis and Environmental Epidemiology 13:152–160. [PubMed: 12679795]
  • Hinds WC. 1982. Aerosol Technology. New York: John Wiley and Sons.
  • Hirsch T, Kuhlisch E, Soldan W, Leupold W. 1998. Variability of house dust mite allergen exposure in dwellings. Environmental Health Perspectives 106(10):659–664. [PMC free article: PMC1533191] [PubMed: 9755142]
  • Hirvonen MR, Ruotsalainen M, Roponen M, Hyvärinen A, Husman T, Kosma V-M, Komulainen H, Savolainen K, Nevalainen A. 1999. Nitric oxide and proinflammatory cytokines in nasal lavage fluid associated with symptoms and exposure to moldy building microbes. American Journal of Respiratory and Critical Care Medicine 160:1943–1946. [PubMed: 10588610]
  • Hu F, Persky V, Flay B, Phil D, Richardson PH. 1997. An epidemiological study of asthma prevalence and related factors amoung young adults. Journal of Asthma 34(1):67–76. [PubMed: 9033442]
  • Hunter CA, Grant C, Flannigan B, Bravery AF. 1988. Mould in buildings: the air spora of domestic dwellings. International Biodeterioration & Biodegradation 24:81–101.
  • Hyvärinen A, Reponen T, Husman T, Nevalainen A. 2001. Comparison of indoor air quality in mold problem and reference buildings in subarctic climate. Central European Journal of Public Health 9(3):133–139. [PubMed: 11505735]
  • ICRP (International Commission on Radiological Protection). 1994. ICRP 66: Human Respiratory Tract Model for Radiological Protection. Annals of the ICRP 24(1–3). [PubMed: 7726471]
  • Immonen J, Laitinen S, Taskinen T, Pekkanen J, Nevalainen A, Korppi M. 2002. Mould-specific immunoglobulin G antibodies in students from moisture and mould-damaged schools: a 3-year follow-up study. Pediatric Allergy and Immunology 13:125–128. [PubMed: 12000485]
  • IOM (Institute of Medicine). 1993. Indoor Allergens: Assessing and Controlling Adverse Health Effects, Washington, DC: National Academy Press. [PubMed: 25144066]
  • IOM. 2000. Clearing the Air: Asthma and Indoor Air Exposures. Washington, DC: National Academy Press. [PubMed: 25077220]
  • Jaakkola MS, Nordman H, Piipari R, Uitti J, Laitinen J, Karjalainen A, Hahtola P, Jaakkola JJ. 2002. Indoor dampness and molds and development of adult-onset asthma: a population-based incident case-control study. Environmental Health Perspectives 110(5): 543–547. [PMC free article: PMC1240846] [PubMed: 12003761]
  • Jaffal AA, Banat IM, El Mogleth AA, Nsanze H, Bener A, Ameen AS. 1997. Residential indoor airborne microbial populations in the United Arab Emirates. Environment International 23(4):529–533.
  • Janssen NAH, Hoek G, Harssema G, Brunekreef B. 1999. Personal exposure to fine particles in children correlates closely with ambient fine particles. Archives of Environmental Health 54:95–101. [PubMed: 10094286]
  • Janssen NAH, de Hartog JJ, Hoek G, Brunekreef B, Lanki T, Timonen KL, Pekkanen J. 2000. Personal exposure to fine particulate matter in elderly subjects: relation between personal, indoor, and outdoor concentrations. Journal of the Air & Waste Management Association 50:1133–1143. [PubMed: 10939207]
  • Jedrychowski W, Flak E. 1998. Separate and combined effects of the outdoor and indoor air quality on chronic respiratory symptoms adjusted for allergy among preadolescent children. International Journal of Occupational Medicine and Environmental Health 11(1):19–35. [PubMed: 9637993]
  • Karlsson K, Malmberg P. 1989. Characterization of exposure to molds and actinomycetes in agricultural dusts by scanning electron microscopy, fluorescence microscopy and the culture method. Scandinavian Journal of Work, Environment, and Health 15:353–359. [PubMed: 2678431]
  • Khan AA, Cerniglia CE. 1994. Detection of Pseudomonas aeruginosa from clinical and environmental samples by amplification of the exotoxin A gene using PCR. Applied Environmental Microbiology 60:3739–3745. [PMC free article: PMC201881] [PubMed: 7986047]
  • Kilpeläinen M, Terho EO, Helenius H, Koskenvuo M. 2001. Home dampness, current allergic diseases, and respiratory infections among young adults. Thorax 56(6):462–467. [PMC free article: PMC1746066] [PubMed: 11359962]
  • Koskinen OM, Husman TM, Meklin TM, Nevalainen AI. 1999. The relationship between moisture or mould observations in houses and the state of health of their occupants. European Respiratory Journal 14(6):1363–1367. [PubMed: 10624768]
  • Lange JL, Thorne PS, Lynch NL. 1997. Application of flow cytometry and fluorescent in situ hybridization for assessment of exposures to airborne bacteria. Applied Environmental Microbiology 63:1557–1563. [PMC free article: PMC168448] [PubMed: 9097451]
  • Lee SC, Chang M, Chan KY. 1999. Indoor and outdoor air quality investigation at six residential buildings in Hong Kong. Environment International 25(4):489–496.
  • Li CS, Hsu CW, Tai ML. 1997. Indoor pollution and sick building syndrome symptoms among workers in day-care centers. Archives of Environmental Health 52(3):200–207. [PubMed: 9169630]
  • Loan R, Siebers R, Fitzharris P, Crane J. 2003. House dust-mite allergen and cat allergen variability within carpeted living room floors in domestic dwellings. Indoor Air 13(3): 232–236. [PubMed: 12950585]
  • Macher JM. 2001. a. Review of methods to collect settled dust and isolate culturable microorganisms. Indoor Air 11(2):99–110. [PubMed: 11394016]
  • Macher JM. 2001. b. Evaluation of a procedure to isolate culturable microorganisms from carpet dust. Indoor Air 11(2):134–140. [PubMed: 11394012]
  • Macher JM, Huang FY, Flores M. 1991. A two-year study of microbiological indoor air quality in a new apartment. Archives of Environmental Health 46(1):25–29. [PubMed: 1992929]
  • Macneil L, Kauri T, Robertson W. 1995. Molecular techniques and their potential application in monitoring the microbiological quality of indoor air. Canadian Journal of Microbiology 41(8):657–665. [PubMed: 7553450]
  • Michel O, Ginanni R, Duchateau J, Vertongen F, Le Bon B, Sergysels R. 1991. Domestic endotoxin exposure and clinical severity of asthma. Clinical and Experimental Allergy 21:441–448. [PubMed: 1913267]
  • Michel O, Kips J, Duchateau J, Vertongen F, Robert L, Collet H, Pauwels R, Sergysels R. 1996. Severity of asthma is related to endotoxin in house dust. American Journal of Respiratory and Critical Care Medicine 154:1641–1646. [PubMed: 8970348]
  • Miller JD, Young JC. 1997. The use of ergosterol to measure exposure to fungal propagules in indoor air. American Industrial Hygiene Association Journal 58:39–43. [PubMed: 9018836]
  • Milton DK, Alwis KU, Fisette L, Muilenberg M. 2001. Enzyme linked immunosorbent assay specific for (1→6) branched, (1→3)-β-D-glucan detection in environmental samples. Applied and Environmental Microbiology 67(12):5420–5424. [PMC free article: PMC93324] [PubMed: 11722887]
  • Miraglia M, Brera C, Colatosti M. 1996. Application of biomarkers to assessment of risk to human health from exposure to mycotoxins. Microchemical Journal 54(4):472–477. [PubMed: 8979962]
  • Mohamed N, Ng'ang'a L, Odhiambo J, Nyamwaya J, Menzies R. 1995. Home environment and asthma in Kenyan schoolchildren: a case-control study. Thorax 50(1):74–78. [PMC free article: PMC473715] [PubMed: 7886654]
  • Nafstad P, Øie L, Mehl R, Gaarder P, Lodrup-Carlsen K, Botten G, Magnus P, Jaakkola J. 1998. Residential dampness problems and symptoms and signs of bronchial obstruction in young Norwegian children. American Journal of Respiratory and Critical Care Medicine 157:410–414. [PubMed: 9476851]
  • Nevalainen A. 1989. Bacterial aerosols in indoor air. (doctoral dissertation). Publications of the National Public Health Institute A3/1989, Kuopio, Finland.
  • Nevalainen A, Pasanen A-L, Niininen M, Reponen T, Kalliokoski P. 1991. The indoor air quality in Finnish homes with mold problems. Environment International 17:299–302.
  • NRC (National Research Council). 1991. Human Exposure Assessment for Airborne Pollutants. Washington, DC: National Academy Press.
  • Özkaynak H, Xue J, Spengler J, Wallace L, Pellizzari E, Jenkins P. 1996. Personal exposure to airborne particles and metals: results from the Particle TEAM Study in Riverside, California. Journal of Exposure Analysis and Environmental Epidemiology 6(1):57–78. [PubMed: 8777374]
  • Parat S, Perdrix A, Fricker-Hidalgo H, Saude I. 1997. Multivariate analysis comparing microbial air content of an air-conditioned building and a naturally ventilated building over one year. Atmospheric Environment 31:441–449.
  • Park JH, Spiegelman DL, Burge HA, Gold DR, Chew GL, Milton DK. 2000. Longitudinal study of dust and airborne endotoxin in the home. Environmental Health Perspectives 108:1023–1028. [PMC free article: PMC1240157] [PubMed: 11102291]
  • Park JH, Gold DR, Spiegelman DL, Burge HA, Milton DK. 2001. House dust endotoxin and wheeze in the first year of life. American Journal of Respiratory and Critical Care Medicine 163(2):322–328. [PubMed: 11179100]
  • Pastuszka JS, Paw UKT, Lis DO, Wlazło A, Ulfig K. 2000. Bacterial and fungal aerosol in indoor environment in Upper Silesia, Poland. Atmospheric Environment 34(22):3833–3842.
  • Pena J, Ricke SC, Shermer CL, Gibbs T, Pillai SD. 1999. A gene amplification-hybridization sensor based methodology to rapidly screen aerosol samples for specific bacterial gene sequences. Journal of Environmental Science and Health Part A—Toxic/Hazardous Substances & Environmental Engineering 34(3):529–556.
  • Pirhonen I, Nevalainen A, Husman T, Pekkanen J. 1996. Home dampness, moulds and their influence on respiratory infections and symptoms in adults in Finland. European Respiratory Journal 9(12):2618–2622. [PubMed: 8980978]
  • Platt SD, Martin CJ, Hunt SM, Lewis CW. 1989. Damp housing, mould growth, and symptomatic health state. British Medical Journal 298(6689):1673–1678. [PMC free article: PMC1836778] [PubMed: 2503174]
  • Platts-Mills TAE, Chapman MD. 1987. Dust mites: immunology, allergic disease, and environmental control. Journal of Allergy and Clinical Immunology 80:755–775. [PubMed: 3320157]
  • Platts-Mills TAE, de Weck AL. 1989. Dust mite allergens and asthma—a worldwide problem. Journal of Allergy and Clinical Immunology 83:416–427. [PubMed: 2645343]
  • Price JA, Pollock I, Little SA, Longbottom JL, Warner JO. 1990. Measurement of airborne mite antigen in homes of asthmatic children. Lancet 336:895–897. [PubMed: 1976929]
  • Reynolds S, Thorne P, Donham K, Croteau EA, Kelly KM, Lewis D, Whitmer M, Heederik D, Douwes J, Connaughton I, Koch S, Malmberg P, Larsson BM, Milton DK. 2002. Interlaboratory comparison of endotoxin assays using agricultural dusts. American Industrial Hygiene Association Journal 63:430–438. [PubMed: 12486776]
  • Rizzo MC, Naspitz CK, Fernandez-Caldas E, Lockey RF, Mimica I, Sole D. 1997. Endotoxin exposure and symptoms in asthmatic children. Pediatric Allergy and Immunology 8(3): 121–126. [PubMed: 9532251]
  • Roponen M, Kiviranta H, Seuri M, Tukiainen H, Myllykangas-Luosujärvi R, Hirvonen MR. 2001. Inflammatory mediators in nasal lavage, induced sputum and serum of employees with rheumatic and respiratory disorders. European Respiratory Journal 18:542–548. [PubMed: 11589353]
  • Roponen M, Toivola M, Alm S, Nevalainen A, Jussila J, Hirvonen MR. 2003. Inflammatory and cytotoxic potential in the airborne particle material assessed by nasal lavage and cell exposure methods. Inhalation Toxicology 15(1):23–38. [PubMed: 12476358]
  • Ross MA, Curtis L, Scheff PA, Hryhorczuk DO, Ramakrishnan V, Wadden RA, Persky VW. 2000. Association of asthma symptoms and severity with indoor bioaerosols. Allergy 55:705–711. [PubMed: 10955695]
  • Rylander R. 1999. Indoor air-related effects and airborne (1→3)-β-D-glucan. Environmental Health Perspectives 107(Supplement 3):501–503. [PMC free article: PMC1566228] [PubMed: 10346999]
  • Rylander R, Persson K, Goto H, Yuasa K, Tanaka S. 1992. Airborne β,1-3-glucan may be related to symptoms in sick buildings. Indoor Environment 1:263–267.
  • Sabbioni G, Wild CP. 1991. Identification of an aflatoxin G1-serum albumin adduct and its relevance to the measurement of human exposure to aflatoxins. Carcinogenesis 12(1): 97–103. [PubMed: 1899057]
  • Sexton K, Ryan PB. 1988. Assessment of Human Exposure to Air Pollution: Methods, Measurements, and Models. In: Air Pollution, the Automobile, and Public Health. AY Watson, editor; , RR Bates, editor; , D Kennedy, editor. , Eds. Sponsored by the Health Effects Institute, Cambridge, MA. Washington, DC: National Academy Press. [PubMed: 25032292]
  • Sonesson A, Larsson L, Fox A, Westerdahl G, Odham G. 1988. Determination of environmental levels of peptidoglycan and lipopolysaccharide using gas chromatography-mass spectrometry utilizing bacterial amino acids and hydroxy fatty acids as biomarkers. Journal of Chromatography 431(1):1–15. [PubMed: 3235520]
  • Sonesson A, Larsson L, Schütz A, Hagmar L, Hallberg T. 1990. Comparison of the Limulus Amebocyte Lysate Test and gas chromatography-mass spectrometry for measuring lipopolysaccharides (endotoxins) in airborne dust from poultry-processing industries. Applied Environmental Microbiology 56:1271–1278. [PMC free article: PMC184394] [PubMed: 2187411]
  • Strachan DP, Carey I. 1995. Home environment and severe asthma in adolescence: a population based case-control study. British Medical Journal 311:1053–1060. [PMC free article: PMC2551362] [PubMed: 7580660]
  • Strachan DP, Flannigan B, McCabe EM, McGarry F. 1990. Quantification of airborne moulds in the homes of children with and without wheeze. Thorax 45(5):382–387. [PMC free article: PMC462482] [PubMed: 2382244]
  • Szponar B, Larsson L. 2000. Determination of microbial colonisation in water-damaged buildings using chemical marker analysis by gas chromatography-mass spectrometry. Indoor Air 10:13–18. [PubMed: 10842456]
  • Szponar B, Larsson L. 2001. Use of mass spectrometry for characterising microbial communities in bioaerosols. Annals of Agricultural and Environmental Medicine 8(2):111–117. [PubMed: 11748866]
  • Tariq S, Matthews SM, Stevens M, Hakim EA. 1996. Sensitization to Alternaria and Cladosporium by the age of 4 years. Clinical and Experimental Allergy 26:794–798. [PubMed: 8842553]
  • Taskinen TM, Laitinen S, Nevalainen A, Vepsäläinen A, Meklin T, Reiman M, Korppi M, Husman T. 2002. Immunoglobulin G antibodies to moulds in school-children from moisture problem schools. Allergy 57:9–16. [PubMed: 11991303]
  • Thatcher TL, Layton DW. 1995. Deposition, resuspension, and penetration of particles within a residence. Atmospheric Environment 29(13):1487–1497.
  • Thatcher, TL, McKone TE, Fisk WJ, Sohn MD, Delp WW, Riley WJ, Sextro RG. 2001. Factors affecting the concentration of outdoor particles indoors (COPI): Identification of data needs and existing data. LBNL-49321. Berkeley, CA: Lawrence Berkeley National Laboratory Report.
  • Thorne PS, Lange JL, Bloebaum PD, Kullman GJ. 1994. Bioaerosol sampling in field studies: can samples be express mailed? American Industrial Hygiene Association Journal 55: 1072–1079. [PubMed: 7992798]
  • Thorne PS, Reynolds SJ, Milton DK, Bloebaum PD, Zhang X, Whitten P, Burmeister LF. 1997. Field evaluation of endotoxin air sampling assay methods. American Industrial Hygiene Association Journal 58:792–799. [PubMed: 9373925]
  • Van Emon JM, Reed AW, Yike I, Vesper SJ. 2003. Measurement of Stachylysin™ in serum to quantify human exposures to the indoor mold Stachybotrys chartarum . Journal of Occupational and Environmental Medicine 45(6):582–591. [PubMed: 12802211]
  • Verhoeff AP, van Reenen-Hoekstra ES, Samson RA, van Strien RT, Brunekreef B, van Wijnen JH. 1994. Fungal propagules in house dust. I. Comparison of analytic methods and their value as estimators of potential exposure. Allergy 49:533–539. [PubMed: 7825720]
  • Verhoeff AP, van Strien RT, van Wijnen JH, Brunekreef B. 1995. Damp housing and childhood respiratory symptoms: the role of sensitization to dust mites and molds. American Journal of Epidemiology 141:103–110. [PubMed: 7817966]
  • Waegemaekers M, van Wageningen N, Brunekreef B, Boleij JS. 1989. Respiratory symptoms in damp homes. A pilot study. Allergy 44(3):192–198. [PubMed: 2712255]
  • Wever-Hess J, Kouwenberg JM, Duiverman EJ, Hermans J, Wever AM. 2000. Risk factors for exacerbations and hospital admissions in asthma of early childhood. Pediatric Pulmonology 29(4):250–256. [PubMed: 10738011]
  • Willeke K, Lin X, Grinshpun SA. 1998. Improved aerosol collection by combined impaction and centrifugal motion. Aerosol Science and Technology 29(5):439–456.
  • Williamson IJ, Martin C, McGill G, Monie RDH, Fennery AG. 1997. Damp housing and asthma: a case-control study. Thorax 52(3):229–234. [PMC free article: PMC1758502] [PubMed: 9093337]
  • Wood RA, Eggleston PA, Lind P, Ingemann L, Schwartz B, Graveson S, Terry D, Wheeler B, Adkinson NF Jr. 1988. Antigenic analysis of household dust samples. The American Review of Respiratory Disease 137(2):358–363. [PubMed: 3341627]
  • Yang CY, Tien YC, Hsieh HJ, Kao WY, Lin MC. 1998. Indoor environmental risk factors and childhood asthma: a case-control study in a subtropical area. Pediatric Pulmonology 26(2):120–124. [PubMed: 9727763]
  • Zock JP, Jarvis D, Luczynska C, Sunyer J, Burney P. 2002. Housing characteristics, reported mold exposure, and asthma in the European Community Respiratory Health Survey. Journal of Allergy and Clinical Immunology 110(2):285–292. [PubMed: 12170270]



This section is derived from Clearing the Air (IOM, 2000), pages 51–54.


Deposition on surfaces will cause 5-µm-aerodynamic-diameter particles to be removed from indoor air at a rate equivalent to 1.5–5 air changes per hour of ventilation (Thatcher et al., 2001). For a 10-µm particle, removal by deposition may be as high as the equivalent of 10 air changes per hour of ventilation. Thus, in most buildings, deposition on surfaces is the largest removal process for particles of 5–10 µm.


This section is derived from Clearing the Air (IOM, 2000), pages 55–56.


Sampling strategies or diagnostic tools to assess whether a building has dampness or mold problems or to assess potential sources of exposure are discussed separately in Chapters 2 and 6.


Addressed in greater detail in Clearing the Air (IOM, 2000), page 54, from which this discussion is derived.


Endotoxin unit is a standardized unit of biologic activity, measured with the LAL test and calibrated to the U.S. Pharmacopoeia reference endotoxin; it is equal to the international unit of activity used by the World Health Organization.

Copyright 2004 by the National Academy of Sciences. All rights reserved.
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