Indoor air pollutants: limited-resource households and child care facilities.

Introduction

People living in limited-resource households are exposed disproportionately to indoor air pollutants; their exposure is likely related to housing quality and socioeconomic status (Chi & Laquatra, 1990; Evans & Kantrowitz, 2002; Farr & Dolbeare, 1996). Without regular maintenance, older homes are more likely than newer homes to manifest chipping lead paint, friable asbestos, cracked foundations, and leaking combustion equipment. These conditions contribute to the presence of lead, asbestos, radon, mold, and combustion products as air pollutants, some of which are known asthma triggers. Although environmental and health officials work to raise public awareness about residential indoor air quality, pollutant abatement remains a private responsibility. Systematic approaches to assist limited-resource households assess and address indoor air pollutant risks are missing from policy discussions. The fact that individuals in limited-resource households tend to be renters rather than owners complicates the problem. Who is responsible for abating indoor air pollutants, and from where will resources come to carry out these tasks without affecting the affordability of housing? Although toxic tort litigation has been used as a strategy for compensation in cases involving indoor environmental contamination, this is not a practical solution on a widespread basis.

Roberts and Dickey (1995) cited studies that document the incidence of indoor air pollution and its negative impacts on children, which include lead poisoning, leukemia, and allergies. For physiological and behavioral reasons, children are at higher risk than adults of adverse health effects from environmental toxicants (Goldman, 1995; Staes, Balk, Ford, Passantino, & Torrice, 1994).

Asthma, for example, is a growing concern for children; the Centers for Disease Control and Prevention (CDC) report that the prevalence of asthma among children increased by an average of 4.3 percent per year between 1980 and 1996. Asthma is the cause of 14 million missed school days annually, is the third-ranking cause of hospitalization of children under 15 years of age, and entails an estimated $3.2 billion per year in the United States in costs of treating children under 18 years of age (CDC, 2003a).

Lead poisoning also is a hazard for children. Exposure to lead-contaminated dust and soil in and around older housing places children at risk for developmental delays and behavioral problems. According to CDC (2003b), up to 846,000 children in the United States between one and five years of age have blood lead levels (BLLs) greater than or equal to 10 [micro]g per deciliter ([micro]g/dL). Negative impacts on childhood health are associated with BLLs lower than 10 [micro]g/dL (Canfield et al., 2003). Yet lead poisoning in residential settings is largely preventable (CDC, 2003b).

Efforts are needed to reduce pollutant exposure not only in homes but also in child care settings (Goodman et al., 1994). Community educators, physicians, and parents can play important roles in increasing awareness of and reducing indoor environmental risks. To create better solutions, better understanding of the extent of the risks is first necessary.

Methods

The study reported here involved assessing the levels of radon, asbestos, lead, combustion pollutants, and biological contaminants in homes and child care facilities in rural areas. A two-stage random-sampling procedure was used to obtain a representative sample of households in all non-metropolitan counties in New York State. A cluster analysis was performed on the 24 non-metropolitan counties in the state, as defined by the 1990 census, to determine similar groupings of counties to be used as categories in a stratified sampling design. The groupings were based on six housing characteristics: average number of persons per household, proportion of housing units in multiple-family dwellings, proportion of manufactured homes, proportion of housing units occupied by renters, proportion of housing units built before 1979, and proportion of housing units built from 1980 to 1989. The cluster analysis resulted in six groupings of counties. When one county was randomly selected from each group, the resulting selection comprised Chenango, Columbia, Essex, Franklin, Wyoming, and Hamilton counties.

To arrive at a total sample of approximately 350, weighted random sampling based on population was conducted in each county. The final sample size was n = 328. Telephone surveys with an adult head of the 328 households were conducted to determine demographic and housing characteristics. Each household was offered air quality tests; 132 households consented, and a technician tested these homes during the heating season of 2000-2001. Table 1 gives the household demographic profiles for the sample.

To select child care facilities for the study, the authors obtained a listing of all child care facilities from the Daycare and Child Development Council in each of the six counties. Facilities included family daycare (up to six children cared for in the home of a provider), group family daycare (up to 12 children in a home), and daycare centers (located in a community facility--e.g., a church). From the list of 500 facilities obtained, 150 were randomly selected to receive a letter describing the study and requesting participation; a second letter was later sent to obtain a final sample of 75 facilities.

Of the 75 facilities, 13 were centers (a church, a community building, or a building designed as a child care center); 52 were family daycare homes; and 10 were group family daycare homes. Directors of the 75 facilities completed a telephone survey and were offered indoor air quality tests. Although 57 facilities initially granted such permission, only 24 facilities actually made appointments for site visits once testing began. This unwillingness to participate is understandable given liability concerns. A technician conducted the on-site air quality tests during the heating season of 2000-2001. Of the 24 facilities in which air quality tests were conducted, seven were centers, 14 were family daycare homes, and three were group family daycare homes.

Radon levels were tested with activated carbon canisters in the lowest living area of each home. Carbon monoxide levels were tested with a Bacharach[R] sample draw carbon monoxide analyzer for 10-15 minutes in the central living area of each household; within 5 feet of fuel-burning central heating systems; and, in homes with gas ranges and ovens, at the gas oven vent at oven startup and when the oven reached 350[degrees]F. The technician made visual tests for asbestos and basement mold. Surface-dust sampling, with a gauze pad moistened with distilled water, was used to test for lead on the floor beneath windows.

Radon levels were regressed on income, the presence of mold in the basement, county, and whether a kitchen exhaust fan was ducted to the outdoors. The presence of mold was used as a proxy for general condition of the basement, county as a location indicator, and exhaust fan as a house depressurization indicator. House depressurization has been linked with elevated radon levels (Roberson, Brown, Koomey, & Greenberg, 1998). Test results for radon, lead, and carbon monoxide in households are given in Table 2. Visual identification results for asbestos and mold in households are given in Table 3.

The technician for this study visited 14 of the child care facilities during the heating season to conduct air quality tests that included carbon monoxide tests. Because none of the administrators of the remaining seven facilities agreed to activate heating systems during the warmer months when they were visited, heating system-related carbon monoxide tests were not conducted at those facilities. In addition, 15 facilities had electric cook stoves, so only nine oven-related carbon monoxide tests were conducted. For the total of 17 heating system-related carbon monoxide levels that were measured, no levels over the maximum exposure level were detected, not even in one facility in which a disconnected flue pipe for a liquefied petroleum gas-fired water heater was discovered. Carbon monoxide levels for the eight gas ovens ranged from 60 to 480 ppm at the startup spike (mean = 327.12; SD = 280.92). Levels at oven temperature ranged from 6 to 33 ppm (mean = 13.12; SD = 11.41).

Testing for radon, lead, asbestos, and mold in the child care facilities followed the same procedures used for the homes.

Results

Results from the radon regression show a significant and negative relationship between household income and radon. This negative relationship is likely due to lower-quality housing among lower-income groups and housing deficiencies that create radon pathways, such as foundation cracks and dirt basement floors.

Regressions with carbon monoxide and lead levels, with independent variables related to age and condition of the house, did not show this relationship. This may be due to the small number of homes (seven) with lead in floor dust above the U.S. Environmental Protection Agency's (U.S. EPA's) maximum allowable level of 40 [micro]g/[ft.sup.2]. However, there was a significant and negative correlation between income and carbon monoxide levels at oven temperature (350[degrees]F) (r = -.402; p = .01), which is probably related to insufficient exhaust in the kitchen or poorly maintained appliances. All told, 60 percent of the homes in the sample had no sufficient exhaust in the kitchen: 26 percent had no exhaust fan or operable window in the kitchen; 4 percent had fans that did not work, and 30 percent had recirculating fans. Lower-income households also are more likely to have older cooking appliances that have not been maintained.

Table 4 indicates that unsafe levels of lead and radon were observed in the child care facilities. Particularly disturbing are the lead levels detected, which were seven times higher than U.S. EPA's maximum exposure level. Table 5 shows that asbestos was present in 27 percent of the facilities. Friability was not analyzed because of university concerns over liability. Therefore, the authors cannot make any conclusions about hazard level. Mold was observed in one-third of the facilities. One of these was a recently constructed facility with a wet crawlspace that was littered with debris.

Discussion

The finding of a significant and negative relationship between income and radon exposure in this sample is similar to the finding by Chi and Laquatra (1990). It does not mean that low household income increases radon levels in a home, but that low-income households tend to live in lower-quality housing than do higher-income households. In areas prone to high radon levels, those lower-quality units are likely to have more radon pathways into the home. In a study of indoor air quality in 23 low-income homes, Tsongas (1995) reported that one-third of the homes had ovens that caused carbon monoxide levels exceeding 9 ppm in the cooking area. Tsongas also reported on several other studies that examined oven-produced carbon monoxide levels in homes. One recommendation from that research was the need to stress the importance of using exhaust fans while cooking to reduce carbon monoxide. This recommendation is not always practical, however, as 60 percent of the homes in the current study did not have operable kitchen exhaust fans. The significant and negative correlation between oven-produced carbon monoxide and income warrants further study.

Although the two-stage random-sampling procedure used in this study produced a representative sample of all non-metropolitan counties in New York State, the small sample size warrants a cautious interpretation of results. The significant relationships observed between lower-income households and certain indoor air pollutants have, however, been reported by other researchers and should be investigated in a larger follow-up study.

In the child care facilities, the high levels of radon and lead and the presence of mold are cause for serious concern. The highest lead level (240 [micro]g/[ft.sup.2]) and highest radon level (6.9 picocuries per liter [pCi/L]) were observed in two different centers. Basement mold was observed in one center and five homes. Asbestos was visually identified in three centers and three homes, but its presence alone does not indicate a health hazard. For asbestos to pose a health hazard, it must be friable and airborne. Although analyses to determine the extent of asbestos hazards were not conducted as part of this research, it is worth noting that to prevent hazards from occurring, the asbestos would require ongoing observation and maintenance. Whether such maintenance occurs and whether children are experiencing environmental-pollutant exposures in both their homes and their child care facilities are subjects worthy of further investigation.

Conclusions and Implications

The results reported in this paper contribute to the growing discussion about indoor air quality in lower-income households and child care facilities. Health officials and policy makers agree that indoor air pollutants pose serious health risks, and they expend considerable resources to raise public awareness of these risks. The fact that pollutant mitigation in privately owned homes remains a personal responsibility, however, creates a policy dilemma. Rural areas of New York State have been characterized for years as being in a state of economic decline, which has negative impacts on household income and housing quality (Ziebarth, Prochaska-Cue, & Shrewsbury, 1997). Low-income households have few if any resources for pollutant abatement. A companion study currently under way at Cornell University is examining the effectiveness of teaching residents of low-income households strategies to minimize their risks of exposure to indoor air pollutants.

Indoor air quality in child care facilities should be an important concern of facility owners and parents. A three-pronged approach may be necessary to broaden public awareness. First, at the policy level, indoor air quality standards could become part of facility license granting and license renewals. Local health departments could administer these requirements when they review other safety measures. Second, facility owners and directors could be educated about these issues and thereby stay ahead of the policy curve. Initiatives to improve or expand child care facilities could include improving indoor air quality. Design criteria for renovations also might include attention to reducing exposure to chemicals in flooring or furnishings and ensuring adequate air flow (Staes et al., 1994).

Third, parents could be educated about the issues so that they can inquire about indoor air quality before enrolling their children in child care facilities. Physicians and other health care providers could provide information to parents on environmental risks during routine immunizations (Koch, 1994).

Should public resources, such as low-interest loans or grants, be made available to low-income households and child care facilities for indoor air-pollutant mitigation? To evaluate this question, the overall cost of indoor air pollution to society needs to be examined. Lead poisoning in children leads to lowered intelligence levels and behavioral problems (Canfield et al., 2003). Mold is a trigger for allergies and asthma, both of which lead to school and work absences, productivity losses, and increased health costs (Fisk, 2000). Exposures to asbestos, carbon monoxide, and radon can lead to preventable deaths (American Lung Association, U.S. Consumer Product Safety Commission, & U.S. EPA, 1996, 1997; U.S. EPA, 1993).

An analysis of the benefits and costs to society of improving indoor air quality in Low-income homes and child care facilities would be useful to provide guidance to policy makers about this issue. Future research could assess health care costs and the reduced productivity of affected children as students and future workers as well as the cost of facility renovation or replacement.

TABLE 1 Demographic Characteristics of the Households in the Sample

Characteristic    Minimum       Maximum       Mean          Standard
                                                            Deviation

Age of household  22            86            53.61             14.25
  head
Education level   Grade school  Postgraduate  Technical or      --
                                              vocational
                                              school
Household income  <$5,000       >$50,000      $23,900       $9,750.05
Number of         0             3             0.58               0.91
  children

TABLE 2 Test Results for Households

Pollutant      Maximum        Minimum        Maximum          Mean
               Exposure       Observed       Observed
               Level*

Radon            4 pCi/L      0.03 pCi/L        19.70 pCi/L     1.64
Lead            40 [micro]g/  0.04[micro]g/    660 [micro]g/   16.92
                  [ft.sup.2]    [ft.sup.2]        [ft.sup.2]
CO, central      9 ppm        0 ppm             14 ppm          0.70
  heating
CO, oven       100 ppm        0 ppm          1,544 ppm        185.75
  start-up
  spike
CO, at oven     25 ppm        0 ppm            213 ppm         18.04
  temperature
CO, living/      9 ppm        0 ppm             14 ppm          0.39
  family
  room

Pollutant      Standard   N
               Deviation

Radon            2.75     114
Lead            71.11     130
CO, central      2.36      96
  heating
CO, oven       341.83     126
  start-up
  spike
CO, at oven     32.2       46
  temperature
CO, living/      1.64     127
  family
  room

*Maximum exposure levels are from the following sources:
** radon--U.S. EPA,
** lead--U.S. EPA,
** CO in living space--U.S. EPA, and
** CO oven startup spike and CO at oven temperature--Tsongas (1995).

TABLE 3 Visual Identification Results for Households

Pollutant      Affirmative    Negative     N

Asbestos           20           107       127
Basement mold      11           102       113

TABLE 4 Test Results for Child Care Facilities

Pollutant    Minimum          Maximum      Mean   Standard Deviation  N

Radon      0.30 pCi/L        6.90 pCi/L    1.62          1.87         13
Lead       0.63 [micro]g/  240 [micro]g/  18.12         49.15         24
             [ft.sup.2]      [ft.sup.2]

TABLE 5 Visual Identification Results for Child Care Facilities

Pollutant      Affirmative    Negative     N

Asbestos            6            16        22
Basement mold       6            12        18

Acknowledgements: The authors are grateful for the assistance provided by Heidi Tinnes and Susan Lang in the preparation of this paper. Yasimin Miller, Director of the Survey Research Institute at Cornell University, assisted with the survey portion of this project. This work was supported by the U.S. Department of Agriculture's Cooperative State Research, Education and Extension Service, under Hatch project NYC-327403.

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J. Laquatra, Ph.D.

L.E. Maxwell, Ph.D.

M.Pierce, M.S.

Corresponding Author: Joseph Laquatra, Hazel E. Reed Human Ecology Extension Professor in Family Policy, Department of Design and Environmental Analysis, Cornell University, E-208 Martha Van Rensselaer Hall, Ithaca, NY 14853-4401. E-mail: [e-mail].