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«Health and Productivity Gains from Better Indoor Environments and Their Implications for the U.S. Department of Energy William J. Fisk1 Staff ...»

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165

Health and Productivity Gains from Better

Indoor Environments and Their

Implications for the U.S. Department of

Energy

William J. Fisk1

Staff Scientist, Indoor Environment Department, Environmental Energy Technologies

Division, Lawrence Berkeley National Laboratory.

A substantial portion of the U.S. population suffers frequently from

communicable respiratory illnesses, allergy and asthma symptoms, and sick

building syndrome symptoms. We now have increasingly strong evidence that changes in building design, operation, and maintenance can significantly reduce these illnesses. Decreasing the prevalence or severity of these health effects would lead to lower health care costs, reduced sick leave, and shorter periods of illness-impaired work performance, resulting in annual economic benefits for the U.S. in the tens of billions of dollars. Increasing the awareness of these potential health and economic gains, combined with other factors, could help bring about a shift in the way we design, construct, operate, and occupy buildings. The current goal of providing marginally adequate indoor environments could be replaced by the goal of providing indoor environments that maximize the health, satisfaction, and performance of building occupants. Through research and technology transfer, DOE and its contractors are well positioned to help stimulate this shift in practice and, consequently, improve the health and economic well-being of the U.S. population. Additionally, DOE’s energyefficiency interests would be best served by a program that prepares for the potential shift, specifically by identifying and promoting the most energyefficient methods of improving the indoor environment. The associated research and technology transfer topics of particular relevance to DOE are identified and discussed.

________________

1Note that the contents present the views of their authors, not necessarily those of the Department of Energy, RAND, or any other organization with which the authors may be affiliated.

Introduction and Objective Analyses by Fisk and Rosenfeld (1997) provided the first broad review in the U.S.

of the potential to improve both health and productivity through improvements in indoor environments. Subsequent papers (Fisk 2000a, 2000b) have upgraded and updated the analyses. This paper summarizes these prior analyses of the potential improvements in health and associated economic benefits, incorporates a few updates, and discusses the implications for the research and technology transfer programs of the U.S. Department of Energy (DOE). The motivation for this effort is to provide input for strategic planning underway by the DOE.

Unlike our prior analyses, this paper does not consider opportunities to directly enhance work performance, through changes in the indoor environment, without an associated improvement in health. The potential to directly enhance productivity will be addressed at this conference in other papers.

Underlying the analyses presented in this paper are three pathways to healthrelated economic benefits, as illustrated in Figure 1. In all cases, the starting point is a change in building design, operation, and maintenance that improves indoor environmental quality (IEQ) and enhances the health of the building’s occupants.

Economic benefits may result from: (1) reduced health care costs; (2) reduced sick leave; and (3) a reduction in time when health effects diminish the performance of workers while they are at work. The changes in building design, operation, and maintenance undertaken to improve IEQ may increase or decrease building energy use.

Methods The basic approach was to review the relevant literature and analyze the key studies showing linkages between indoor environmental factors and health outcomes. Relevant papers were identified through computer-based literature searches, reviews of conference proceedings, and discussions with researchers.

Communicable respiratory illnesses, allergies and asthma, and sick building syndrome symptoms were identified as the three categories of health effects in the analyses because their prevalences are influenced by IEQ and the affected populations are very large. Published health studies were reviewed to determine the strength of associations between building-related risk factors (e.g., low ventilation rates) and health outcomes. Expertise in building science and engineering provided information on the potential to diminish the risk factors.

With these inputs, plus judgments, the potential reductions in health effects were estimated. The economic costs of these adverse health effects were estimated, primarily by synthesizing and updating the results of previously

–  –  –

published cost estimates. Prior economic estimates were updated to 1996 to account for general inflation, health care inflation, and increases in population (U.S. Department of Commerce 1997). Finally, the potential annual nationwide health and productivity gains were computed by multiplying the population affected and associated costs by the estimated potential percentage reduction in health effects.

Even with the best of the information currently available, there is a high level of uncertainty with these estimates of the health and associated economic gains attainable from improvements in the indoor environment. In general, the largest source of uncertainty is the degree to which health effects could be reduced through practical changes in building design, operation, and maintenance. A range of estimated gains are provided to reflect this source of uncertainty. For sick building syndrome symptoms, the total costs to society are also uncertain;





however, the estimates provided here do not reflect this additional level of uncertainty.

Improvements in the indoor environment depend on changes to building design, operation, maintenance, use, or occupancy. This paper considers whether feasible and practical changes could improve health; however, it does not claim that it will be easy to stimulate the investments or changes in behaviors that are necessary in order to improve IEQ. For example, this paper assumes that it is feasible and practical to restrict indoor tobacco smoking, maintain pets outside of the homes of pet allergic people, improve air filtration systems, prevent low ventilation rates, and reduce water leakage from outdoors to indoors. Realization of the “potential” health and productivity gains identified in this paper will depend on changes in behavior and, in some cases, on financial investments in better building design, operation and maintenance. The expected benefit-to-cost ratios for these measures will often be large because the salaries and benefits of workers typically dominate building energy, maintenance, and lease costs (Woods 1989).

To make this article understandable to a broad audience, the use of potentially unfamiliar statistical terminology has been minimized. For example, as substitutes for the odds ratios or relative risks normally provided in the scientific literature, this article provides estimates of the percentage increases and decreases in outcomes (e.g., health effects) that are expected when buildingrelated risk factors (e.g., mold exposures) are present or absent. Measures of statistical significance are included only within footnotes. The findings reported in this paper would generally be considered to be statistically significant (e.g., the probability that the findings are due to chance or coincidence is generally less than 5%). Appendix 1 of Fisk (2000b) defines the odds ratio, the relative risk, the term “adjusted”, and the means of estimating percentage changes in outcomes from odds ratios or relative risks.

After estimating of potential health and productivity gains, this paper discusses their implication for the US Department of Energy. This discussion is based on the author’s knowledge of the interrelationships among building energy efficiency, IEQ, and health and on his understanding of DOE’s mission and capabilities.

Potential Health and Productivity Gains For each of the three health categories, the subsequent text starts with a review of the evidence for the linkage between indoor environmental conditions and the health outcomes, follows with a discussion of the populations affected and associated costs, and concludes with estimates of the potential health and productivity gains.

Communicable Respiratory Illness

Evidence of Linkage. We first consider communicable respiratory illnesses transmitted between people, such as influenza and common colds. Building characteristics could change the number of aerosols containing virus or bacteria, e.g., droplet nuclei from coughs and sneezes, that are inhaled, increase or diminish the viability of the inhaled virus or bacteria, or modify the susceptibility of occupants to infection. Consequently, the following building characteristics may theoretically affect the prevalences of respiratory illnesses: efficiency or rate of air filtration; rate of ventilation (i.e., supply of outside air per occupant);

amount of air recirculation in ventilation systems, separation between individuals (dependent on occupant density and use of private work spaces); air temperature and humidity (which affect the period of viability of infectious aerosols); and mold levels since molds may increase susceptibility to illness. As discussed in Fisk (2000a), infectious aerosols are thought or known to contribute substantially to transmission of common colds (e.g., rhinovirus infections), influenza, adenovirus infections, measles, and other common respiratory illnesses. Disease transmission due to direct person-to-person contact or to indirect contact via contaminated objects, may be largely unaffected by indoor environmental and building characteristics.

In addition to the theoretical expectations, data are available from several field studies that have examined the association of building characteristics with the prevalence of respiratory illness among building occupants. Two studies were performed in military barracks. A large multi-year investigation by the U.S.

Army (Brundage et al. 1988) determined that clinically-confirmed rates of acute respiratory illness with fever were 50% higher among recruits housed in newer barracks with closed windows, low rates of outside air supply, and extensive air recirculation compared to recruits in older barracks with frequently open windows, more outside air, and less recirculation.2 In another barracks study, Langmuir et al. (1948) compared the rate of respiratory illness with fever among recruits housed in barracks with ultraviolet lights (UV) that irradiated the indoor air near the ceiling (a technology designed to kill infectious bioaerosols) to the rate of respiratory illness among recruits in barracks without UV lights. For the entire study period, the population housed in barracks with UV irradiated air had 23% less respiratory illness.3 Several additional studies from a variety of building types provide relevant information on this topic. Jaakkola et al. (1993), found that office workers with one or more roommates were about 20% more likely to have more than two cases of the common cold during the previous year than office workers with no roommates.4 At an Antarctic station, the incidence of respiratory illness was twice as high in the population housed in smaller (presumably more densely populated) living units (Warshauer et al. 1989). In an older study of New York schools (N.Y. State Commission on Ventilation 1923), there were 70% more ________________

2Adjusted relative risk = 1.51, 95% confidence interval (CI) 1.46 to 1.56.

3No test of statistical significance was performed.

4Adjusted odds ratio = 1.35 (95% CI 1.00 - 1.82).

respiratory illnesses5 and 18% more absences from illness6 in fan-ventilated classrooms compared to window-ventilated classrooms, despite a lower occupant density in the fan-ventilated rooms. Unfortunately, ventilation rates were not measured in the classrooms. Another study investigated symptoms associated with infectious illness among 2598 combat troops stationed in Saudi Arabia during the Gulf War (Richards et al. 1993). The study results suggest that the type of housing (air-conditioned buildings, non-air-conditioned buildings, open warehouses, and tents) influenced the prevalence of symptoms associated with respiratory illness. Housing in air-conditioned buildings (ever versus never housed in an air-conditioned building while in Saudi Arabia) was associated with approximately a 37% greater prevalence of sore throat7 and a 19% greater prevalence of cough.8 Although jails are not representative of other buildings because of severe crowding and residents that are not representative of the general public, disease transmission in jails is an important public health issue and indoorenvironmental factors that influence disease transmission in jails may also be important, but less easily recognized, in other environments. Hoge et al. (1994) studied an epidemic of pneumococcal disease in a Houston jail. There were significantly fewer cases of disease among inmates with 7.4 m2 or more of space9 relative to inmates with less space. The disease attack rate was about 95% higher in the types of jail cells with the highest carbon dioxide concentrations, i.e., the lowest volume of outside air supply per person.10 Drinka et al. (1996) studied an outbreak of influenza in four nursing homes located on a single campus. Influenza, confirmed by analyses of nasopharyngeal and throat swab samples, was isolated in 2% of the residents of Building A versus an average of 13% in the other three buildings 11 (16%, 9%, and 14% in Buildings B, C and D, respectively). After correction for the higher proportion of respiratory illnesses that were not cultured in Building A, an estimated 3% of the residents of Building A had influenza, a rate 76% lower than observed in the other buildings.12 The total number of respiratory illnesses (i.e., influenza plus other respiratory illnesses) per resident was also 50% lower in Building A.

________________

5Difference more than three times probable error.

6Difference greater than probable error.

7Adjusted odds ratio =1.57 (95% CI 1.32-1.88).

8Adjusted odds ratio = 1.33 (95% CI 1.01 - 1.46) 9p=0.03 10Relative risk = 1.95 (95% CI 1.08-3.48).

11p 0.001, Cochran-Mantel-Haenszel statistics 12p 0.001, chi-square Vaccination rates and levels of nursing care did not differ among the buildings.



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