Grantee Research Project Results
Final Report: Bioaerosols, Health, and Productivity in a Large Office Building
EPA Grant Number: R824797Title: Bioaerosols, Health, and Productivity in a Large Office Building
Investigators:
Institution: Harvard University
EPA Project Officer: Chung, Serena
Project Period: October 1, 1995 through September 30, 1998
Project Amount: $439,035
RFA: Indoor Air Quality in Large Office Buildings (1995) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Air
Objective:
Building-related illnesses are of increasingly common concern. However, the causes and cures remain obscure. This project was designed to longitudinally evaluate the role of environmental factors on reported symptoms and measured working efficiency in a group of office workers.
Although a single large building was to be the focus, difficulties in obtaining access forced the use of working spaces in five different buildings. This slowed the project and increased the difficulties involved in gathering data, but expanded the range of environmental conditions available for study.
Overall we collected continuous data on CO2, RH, and temperature from 28 sites in 5 buildings over a period of 18 months. We collected environmental samples (air samples for fungi and bacteria, dust samples for estimation of 'dustiness', culture of fungi and bacteria, and assay of allergens) on a total of 17 occasions from these sites. We also recruited 180 individuals, and recovered 729 six-week questionnaires, and 4103 weekly questionnaires. Measures of working efficiency were collected from 171 individuals, with an average of about 2 tests/person/week, and a total of 2176 tests overall.
Methods evaluations revealed that Andersen conversions were not necessary for the data set, and that MEA and DG-18 culture media produced very similar results so that the resulting data could be combined.
Using Principal Component Analysis (PCA), airborne fungal recoveries grouped into four factors which explained 53% of the variance. Airborne fungal concentrations varied seasonally with the highest median value in August and the lowest in January. Total airborne fungal concentrations were negatively correlated with CO2 and positively related to relative humidity. PCA factors 1 and 2 were negatively correlated with CO2 and positively correlated with RH
Similar studies for dustborne fungi. These populations clustered into three factors using PCA. Concentrations of dust fungi were related to temperature and CO2 levels. Cat and dust mite allergens were consistently present in dust in all buildings.
Analysis of this large data set is continuing, with current emphasis on relationships between weekly and daily symptom reporting and environmental variables. The data are the subject of two doctoral theses, and have stimulated creation of a bioaerosols analysis working group at the School.
Summary/Accomplishments (Outputs/Outcomes):
Overview of the problem
Office buildings are increasingly the focus of complaints related to air quality. Because air quality is rarely studied in well-maintained, non-complaint buildings, there are no reference guidelines on which to base recommendations for remedial actions when complaints do occur. These data are especially lacking for airborne biological agents such as bacteria and fungi, so that the presence of any of these common organisms is often interpreted as constituting a problem.
In addition to the lack of data on exposures in non-complaint buildings, it is not clear how air quality is related to perception, comfort, and productivity in the office environment. Thus, decisions on whether or not to attempt to improve air quality are often based solely on the expense related to the improvement rather than the overall equation balancing remediation expense against potentially more costly losses in productivity.
Goals of these studies
The Large Building Study is designed to extend the protocol developed for the EPA-BASE studies by more intensively studying a single building over time, with expansion of the assessments for biological agents, and by adding a component designed to evaluate the effects of air quality parameters on worker productivity. To accomplish this overall goal:
- We have established baseline levels and patterns of variability for important indoor air quality measures over time in non-complaint office buildings. These measures include temperature, relative humidity, carbon dioxide levels, ventilation rates, and water activity in materials. We have collected sequential samples from each building over 18 months for analysis of dust and airborne fungi and bacteria, dustborne arthropod and animal allergens, and dust and airborne endotoxin.
- We have used brief questionnaires administered bimonthly over 12 months to monitor comfort, air quality perception, and symptoms known to be related to specific air contaminants in a group of workers in each building. We used a computer test developed by NASA to measure productivity in these same workers.
- We will compare symptom prevalence and proficiency on the computer test with environmental measurement data taking repeated measures and co-variation into account.
- We will these results to similar data collected during the EPA BASE studies in a large cross-section of office buildings.
Problems with building selection
The protocol, as originally written, involved the use of a large building owned by a Boston-based investment company employing more that 1500 people in the building. The advantages of this building were:
- the large numbers of people working in more or less open office spaces, and all doing similar jobs;
- the fact that the company monitors productivity by monitoring telephone usage;
- the fact that upper management of the company understood the value of the study and agreed (in writing) to collaborate with our group.
After the study was funded, the company management introduced our protocol to their attorneys who strongly vetoed any involvement by the company. It spite of considerable efforts we were unable to obtain access to the building. We then explored other large commercial buildings. Unfortunately, the attorneys uniformly considered the study to present a legal risk, and we were unsuccessful.
Instead, we approached non-profit institutions in the Boston area and were able to obtain permission to use 4 University office buildings and a downtown office building partially occupied by a State agency. Implications of the use of these multiple buildings are the following:
Numbers of participants: There was no single building with enough employees in units where supervisors were willing to cooperate to allow us to use a single building. We have thus been forced to use sites in a total of four different buildings to obtain the necessary number of participants.
Ventilation systems: Each building has its own ventilation system. This forced us to do the ventilation assessments ourselves, because we had only arranged for our outside contractor to do a single building. We do have consulting access to the same company (that does many of the BASE studies), and have followed their protocols exactly but used our own personnel.
Number of employees available/sampling site: The maximum number of employees available at any single sampling site in the chosen buildings is 10. This means that we have had to increase the number of sampling sites, the number of samples collected, and therefore the cost of the sampling protocol.
Productivity: Neither the University or the State agency maintains productivity records on office personnel. Fortunately, through our contacts in NASA, we have been able to gain access to a set of computer tests that are used to assess the response of shuttle astronauts to their environment. We are using two tests. The first uses pattern recognition (recognizing whether or not a letter or number is in an appropriate orientation); the second tests short term memory. The set of tests has been evaluated by the US Air Force in 5000 office workers, and this control data base is available for these studies. We feel that the use of this test is an improvement to the project. The test will eventually be commercially available, and could be used widely in future studies. It also is likely to more generally and more accurately measure the effects of changes in air quality than the productivity measures used by investment companies.
Because of the unavailability of the original commercial building, we have had delays in recruiting, have had to significantly increase the number of sampling sites, and have had to instigate an external measure of working efficiency. These changes all have been costly, and we have had to make changes in our original protocol to reduce costs.
- We have eliminated Burkard spore trap sampling following collection of pilot data that indicated that this sampler is insufficiently sensitive for use in our relatively clean buildings.
- We are archiving dust samples for future analysis of ergosterol and endotoxin.
- We have reduced the frequency of integrated sampling to once each six weeks (from monthly).
- We are performing working efficiency measures on only 3/4 of total participants.
- On the other hand, we have added a weekly questionnaire that addresses relatively short-term changes in symptoms (See attachments). Even with these economies, we have collected important and reliable data with respect to the longitudinal effects of building conditions (especially with respect to bioaerosols) on perception, symptoms, and working efficiency of occupants.
Approaches for completion of the study
Because of our initial difficulties in recruitment, we were not able to complete this study during the grant period. However, we are continuing (and will continue) to bring the studies to completion. To facilitate this effort, we have involved two doctoral students in the project. Both have participated in sample/data collection, and are using the studies as the basis of their doctoral theses. We have divided the work into two large sections to facilitate this approach.
- Jasmine Chao is using the data from the University buildings, and is focusing on the physical environmental parameters and bacteria and fungi as well as the questionnaire and working efficiency data from all the buildings.
- Jenny Lee is analyzing all of the allergen data, and is focusing on the physical environmental parameters from the State agency and will do the EPA/BASE comparisons.
Both of these students are required to prepare at least 3 publishable manuscripts to satisfy their thesis requirements. As these students prepare each paper for publication, copies of the final manuscripts will be submitted to the EPA.
Final study design
Buildings
We have used spaces within five different buildings for these studies.
University buildings
The four University buildings used are in busy urban areas. Buildings 1, 2, and 3 are 14, 4, and 10 stories respectively, forming an inter-connected campus building complex. Four different air-handling units controlled the 7 administrative offices selected from these three buildings. All four are constant air volume systems. Fourteen sampling sites were selected from Building 4, a 10-story office building on a different campus. The building is supplied by 2 air handling units and 380 fan coil units. Temperature sensors are installed in almost every room, and are monitored by the computer system in the building manager's office.
State office building
The State office building is situated in downtown Boston surrounded by numerous historical buildings. The building itself is a newly renovated modern high-rise (48 floors) air-conditioned building. The collaborating agency is located on the first 8 floors with its own entrance. The remaining 40 floors are residential condominiums with a separate entrance.
Sampling site and participant selection
Meetings were held to acquaint employees and union representatives with the study. All attendees were given information regarding the study and consent forms. In addition, walkthroughs were conducted and groups of people in especially suitable locations (5-10 people in open areas) were encouraged to review our literature and to participate. Based on consent forms received, a number of sites in each building were chosen. These are summarized in Table 1.
Table 1. Initial site and participant recruitment
Building | # Sites | # Participants |
University buildings | 20 | 105 |
State office building | 8 | 75 |
Totals | 28 | 180 |
Environmental samples
Sampling | Analysis | Frequency | |
CO2 | Direct reading | Continuous | |
Temp. | Direct reading | Continuous | |
RH | Wet/dry bulb temp. | Wet/dry bulb calculation | Continuous |
Aw | RH, Surface temp | Calculation | 6-week events* |
Dust Fungi | Vacuum samples, floor and chairs | Culture: DG18, MEA | 6-week events* |
Dust Bacteria | Vacuum samples, floor and chairs | Culture: R2A | 6-week events* |
Air Fungi | N-6 Andersen | Culture: DG18, MEA | 6-week events* |
Air Bacteria | N-6 Andersen | Culture: R2A | 6-week events* |
Allergens | Vacuum samples Floor and chair dust |
Immunoassay | 6-week events* |
Surface dust | Adhesive film contact | Densitometry | 6-week events |
*Each event: 1 week, 2 days/week, 2 sample sets/day/site=4 sample sets/site/event
Human studies
Confidentiality
The human studies protocol was assessed by our IRB and approved. Briefly, each participant was given a code number known only to the investigator collecting data who maintains a code key. The code investigator for each building collected base and 6-week questionnaires. Weekly questionnaires were deposited in a locked box for collection by the code investigator. Working efficiency tests are performed and data stored only by code in the computer.
Table 3. Questionnaire types
Base | EPA base questionnaire |
6-week | Base questionnaire minus questions on parameters not likely to change (e.g., sex) |
Weekly | Symptoms experienced over the past week |
Working efficiency tests
A standardized computer test, Nova Scan A (NTI, Inc., Dayton OH) was used to evaluate work performance. Nova Scan A was designed to test higher cognitive functions that might be applicable to jobs that involve high degrees of information processing. This test consists of three specific tasks: spatial visualization, continuous memory and attention monitoring. The first test uses pattern recognition (recognizing whether or not a letter or number is in an appropriate orientation); the second tests short term memory. The two tests are taken together, with each screen presenting one test or the other randomly. After about 20 repetitions to establish an individual baseline for each worker, the test is used to assess excursions from the baseline by assessing scores (% correct answers) and the time it takes to do the test.
Schedule for data collection
Table 4. Summary of the Sampling week schedule
Time | Monday | Tuesday | Thursday |
AM | Distribute BASE or 6-week questionnaire | Collect airborne fungi and bacteria | Collect airborne fungi and bacteria |
PM | Collect airborne fungi and bacteria | Collect airborne fungi and bacteria | |
After hours | Dust sampling in chairs and floors Measure water activity Surface dust sampling |
Data collected
Environmental measures
Table 5: 6-Week site and measurement summary University buildings
Event | 1st | 2nd | 3rd | 4th | 5th | 6th | 7th | 8th | 9th | 10th |
1997 | 1998 | |||||||||
Date | 5/5 | 6/23 | 8/4 | 9/15 | 10/27 | 12/8 | 1/19 | 3/2 | 4/13 | 5/25 |
# of Sites | 20 | 20 | 20 | 20 | 21 | 19 | 15 | 14 | 15 | 15 |
Air organisms | 20 | 20 | 20 | 20 | 21 | 19 | 15 | 14 | 15 | 15 |
Dust (floors) | 20 | 20 | 20 | 20 | 21 | 19 | 15 | 14 | 15 | 15 |
Dust (Chairs) | 20 | 20 | 20 | 20 | 21 | 19 | 15 | 14 | 15 | 15 |
Water Activity? | 20 | 20 | 19 | 20 | 21 | 19 | 15 | 14 | 15 | 15 |
Surface Dust? | NA | NA | 18 | 18 | 19 | 17 | 9 | 12 | 13 | 15 |
? Water Activity is the amount of water available in a substrate for microorganisms' growth.
Table 6: 6-Week site and measurement summary: State Office Building
Event | 1st | 2nd | 3rd | 4th | 5th | 6th | 7th |
1998 | 1999 | ||||||
Date | 4/27 | 6/8 | 7/20 | 8/24 | 10/5 | 11/30 | 1/11 |
# Sites | 8 | 8 | 8 | 8 | 7 | 7 | 7 |
Air organisms | 8 | 8 | 8 | 8 | 7 | 7 | 7 |
Dust (floors) | 8 | 8 | 8 | 8 | 7 | 7 | 7 |
Water Activity | 8 | 8 | 8 | 8 | 7 | 7 | 7 |
Surface dust | 8 | 8 | 8 | 8 | 7 | 7 | 7 |
All air and dust samples have been weighed and cultured for fungi and bacteria, and assayed for dust mite and cat allergens
Human studies
Table 7: Enrolled subjects and loss over time by building: University buildings
Event | 1st | 2nd | 3rd | 4th | 5th | 6th | 7th | 8th | 9th | 10th | Totals |
1997 | 1998 | ||||||||||
Date | 5/5 | 6/23 | 8/4 | 9/15 | 10/27 | 12/8 | 1/19 | 3/2 | 4/13 | 5/25 | |
# of Sites | 20 | 20 | 20 | 20 | 21 | 19 | 15 | 14 | 15 | 15 | |
6-Week Quest. | 82 | 70 | 56 | 51 | 56 | 51 | 45 | 41 | 40 | 38 | 530 |
Weekly Quest. | 347 | 329 | 301 | 300 | 319 | 264 | 272 | 239 | - | - | (2371) |
Computer Tests | 226 | 244 | 189 | 177 | 181 | 120 | 172 | 154 | - | - | (1463) |
Table 8: Enrolled subjects and loss over time: State office building
Event | 1st | 2nd | 3rd | 4th | 5th | 6th | 7th |
Date | 4/27/98 | 6/8/98 | 7/20/98 | 8/24/98 | 10/5/98 | 11/30/98 | 1/11/99 |
# of Sites | 8 | 8 | 8 | 8 | 7 | 7 | 7 |
6-Week Quest. | 62 | 37 | 37 | 30 | 21 | 23 | 21 |
Weekly Quest. | 301 | 211 | 190 | 166 | 134 | 118 | 138 |
Computer Tests | 81 | 63 | 58 | 53 | 68 | 56 | 41 |
Table 9: Questionnaire and computer tests: overall totals
University | State agency | Totals | |
6-wk questionnaires | 498 | 231 | 729 |
Weekly questionnaires | 2845 | 1258 | 4103 |
Computer tests | 1756 | 420 | 2176 |
Table 10: Weekly participation rates: University buildings
(initial: 105) | Weekly Questionnaires | Computer tests | |||
Event | # recruits remaining | # | #/person | # | #/person |
1 | 98 | 442 | 4.51 | 250 | 2.55 |
2 | 100 | 393 | 3.93 | 255 | 2.55 |
3 | 99 | 308 | 3.11 | 232 | 2.34 |
4 | 97 | 301 | 3.10 | 197 | 2.03 |
5 | 101 | 313 | 3.10 | 175 | 1.73 |
6 | 92 | 314 | 3.41 | 150 | 1.63 |
7 | 71 | 272 | 3.83 | 179 | 2.52 |
8 | 68 | 242 | 3.56 | 160 | 2.35 |
9 | 79 | 260 | 3.31 | 158 | 2.01 |
Table 11: Weekly participation rates: State Agency
Initial:75 | Weekly Questionnaires | Computer tests | |||
Event | # recruits remaining | # | #/person | # | #/person |
1(6w) | 71 | 301 | 4.24 | 81 | 1.14 |
2(6w) | 66 | 211 | 3.2 | 63 | .95 |
3(5w) | 62 | 190 | 3.06 | 58 | .94 |
4(6w) | 60 | 166 | 2.77 | 53 | .88 |
5(8w) | 46 | 134 | 2.91 | 68 | 1.48 |
6(6w) | 43 | 118 | 2.74 | 56 | 1.3 |
7 | 40 | 138 | 3.45 | 41 | 1.03 |
Status of data entry
All data entry and checking is complete for the University building data. All data is being maintained as PC, mainframe, and portable disc files. Status of data on the State office building is as follows:
- Allergen data have been entered into the database.
- Questionnaire data have been entered into the database.
- Computer test data were downloaded and entered into the database.
- Environmental data on carbon dioxide, temperature and relative humidity were downloaded and entered into the database.
Additional data collection to be done
Analysis of environmental samples
Samples have not been analyzed for endotoxin or ergosterol
Data, entry, development of final data sets
- Environmental data on water activity were calculated but have not yet been entered.
- Environmental data on fungi and bacteria have not yet been entered.
Results
Ms. Chao and Ms. Lee are currently preparing the following manuscripts to satisfy their thesis requirements.
Environmental measurements
Manuscript 1: Longitudinal studies of airborne fungi in office buildings
Positive hole conversions (comparisons of Andersen data with and without conversions).
Characterizing fungal populations
Summary Statistics
Distributions over time
Fungal concentration modeling (GAM models)
Draft conclusions
- Positive hole conversions for Andersen data were not necessary in this data set.
- MEA recovered slightly more total fungi, and more fungal taxa than DG-18. However, the differences were too small to be important, and data from the two culture media were combined for further analysis.
- Overall, airborne fungal concentrations (CFU/m3 of air) for 10 sampling events were:
- Mean: 42, SD 70
- Median: 22
- Min/Max: 1/618
- Four principal component factors were found explaining 53% of the variance
- Airborne fungal concentrations varied seasonally with the highest median value in August and the lowest in January.
- Distributions over time for PCA factors 1 and 2 differed.
- Total airborne fungal concentrations were negatively correlated with CO2 and positively related to relative humidity.
- PCA factors 1 and 2 were negatively correlated with CO2 and positively correlated with RH
Manuscript 2: Longitudinal studies of dustborne fungi in office buildings Plate loading and dilution effects
Characterizing populations
Summary statistics
Fungal concentration modeling
Environmental factors predicting fungal concentrations in floor and chair dust
Total fungi floor | PCA factor 1 floor | PCA factor 2 floor | |
Time | Yes | Yes | Yes |
CO2 | Yes | Yes | Yes |
Temperature | Yes | Yes | No |
Water activity | No | No | Yes |
Grams of dust in chairs | No | No | No |
Total fungi chairs | PCA factor 1 chairs | PCA factor 2 chairs | |
Time | Yes | Yes | Yes |
CO2 | No | No | No |
Temperature | No | No | No |
Water activity | No | No | No |
Grams of dust in floor cover | Yes | Yes | Yes |
Manuscript 3: Dust as a source for airborne fungi in office buildings
Air-dust relationships for total fungi
Correlations between PCA factors for air and dust
Air dust relationships for individual taxa
Effects of environmental factors on air dust relationships
Manuscript 4: Factors controlling allergen prevalence in office buildings (This is the first paper proposed for Ms. Lee's thesis).
Summary statistics
Modeling of allergen concentrations
Human studies
These data are currently being analyzed. Proposed manuscript outlines are presented below. Because of the early stage of these analyses, these are provisional and are likely to change.
Manuscript 5: Environmental predictors for monthly symptom reporting in office workers
Distributions of Demographic Data
Symptom Prevalence over Time
Symptom groupings
Modeling symptom prevalence
Generalized estimating equations (GEE) and generalized linear mixed models (GLIMMIX) are used to correlate symptom presence (a binomial distribution) with psychosocial factors and environmental measurements. The autocorrelations resulting from repeated self-reported symptoms are accounted for by GEE/GLIMMIX modeling. Appropriate models are constructed for each symptom group.
Manuscript 6. Environmental predictors for daily symptom reporting in office workers
Distributions of Demographic Data
Symptom Prevalence over Time
Distributions of Daily Environmental Variables
Effects of Psychosocial Factors and Environmental Exposures on Daily Health Symptoms
GEE and GLMMIX are used to explore the correlations between daily symptoms and environmental and psychosocial factors. Models are obtained for each symptom group.
Manuscript 7. Environmental factors predicting working efficiencies for occupants of large office buildings
Distributions of Demographic Data
Distributions of Number of Computer Tests over Time
Correlations between Working Efficiencies and Environmental Exposures
Generalized additive models (GAM) in S-Plus are employed to model correlations between computer test scores and environmental variables. Serial correlation (autocorrelation) resulting from repeated measurements for same subject will be examined using partial autocorrelation functions in S-Plus and will be accounted for by including fixed subject effect in the models.
Manuscript 8: Allergens, symptoms, and working efficiency in office buildings
Manuscript 9: Relationships between cross-sectional and longitudinal data for large office buildings (Ms. Lee)
Outlines being formulated by Ms. Lee
Journal Articles on this Report : 3 Displayed | Download in RIS Format
Other project views: | All 3 publications | 3 publications in selected types | All 3 journal articles |
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Type | Citation | ||
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Chao HJ, Schwartz J, Milton DK, Burge HA. Populations and determinants of airborne fungi in large office buildings. Environmental Health Perspectives 2002;110(8):777-782. |
R824797 (Final) |
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Chao HJ, Milton DK, Schwartz J, Burge HA. Dustborne fungi in large office buildings. Mycopathologia 2002;154(2):93-106. |
R824797 (Final) |
Exit |
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Chao HJ, Schwartz J, Milton DK, Burge HA. The work environment and workers' health in four large office buildings. Environmental Health Perspectives 2003;111(9):1242-1248. |
R824797 (Final) |
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Supplemental Keywords:
Scientific Discipline, Health, Air, Geographic Area, air toxics, Health Risk Assessment, State, Risk Assessments, Biochemistry, indoor air, Atmospheric Sciences, Biology, EPA Region, building related illness, hvac, particulates, exposure and effects, buildings, ambient air, MA, workplace, human exposure, inhalation, sick building syndrome, bioaerosols, Massachusetts, indoor air quality, Region 1, longitudinal variationProgress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.