Indoor Air 2015; 25: 157–167 wileyonlinelibrary.com/journal/ina Printed in Singapore. All rights reserved

© 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd INDOOR AIR doi:10.1111/ina.12136

Classroom conditions and CO2 concentrations and teacher health symptom reporting in 10 New York State Schools Abstract This study assessed the relationship between teacher-reported symptoms and classroom carbon dioxide (CO2) concentrations. Previous studies have suggested that poor indoor ventilation can result in higher levels of indoor pollutants, which may affect student and teacher health. Ten schools (9 elementary, 1 combined middle/high school) in eight New York State school districts were visited over a 4-month period in 2010. Carbon dioxide concentrations were measured in classrooms over 48-h, and teachers completed surveys assessing demographic information and self-reported symptoms experienced during the current school year. Data from 64 classrooms (ranging from 1 to 9 per school) were linked with 68 teacher surveys (for four classrooms, two surveys were returned). Overall, approximately 20% of the measured classroom CO2 concentrations were above 1000 parts per million (ppm), ranging from 352 to 1591 ppm. In multivariate analyses, the odds of reporting neuro-physiologic (i.e., headache, fatigue, difficulty concentrating) symptoms among teachers significantly increased (OR = 1.30, 95% CI = 1.02–1.64) for every 100 ppm increase in maximum classroom CO2 concentrations and were non-significantly increased in classrooms with above-median proportions of CO2 concentrations greater than 1000 ppm (OR = 2.26, 95% CI = 0.72–7.12).

N. Muscatiello1, A. McCarthy1, C. Kielb1, W.-H. Hsu1, S.-A. Hwang1,2, S. Lin1,2 1 New York State Department of Health Empire State Plaza, Center for Environmental Health, Albany, NY, USA, 2Department of Epidemiology and Biostatistics, University at Albany School of Public Health, One University Place, Rensselaer, NY, USA

Key words: Teacher; School; Health; Carbon dioxide; Indoor environmental quality; Symptoms.

N. Muscatiello Bureau of Environmental and Occupational Epidemiology, Center for Environmental Health, New York State Department of Health Empire State Plaza, Corning Tower, Rm. 1278, Albany NY 12237, USA Tel.: 518-402-7950 Fax: 518-402-7959 e-mail: [email protected] Received for review 29 July 2013. Accepted for publication 24 May 2014.

Practical Implications

The majority of previous studies that have found associations between ventilation or carbon dioxide (CO2) and health symptoms in schools have focused on children as the target population. This study provides evidence of an association between CO2 and health symptom reporting among teachers, even though the maximum CO2 concentration measured in any of the study classrooms was below 1600 ppm. There was substantial between-classroom, within-school variability in the proportion of CO2 concentrations greater than 1000 ppm, suggesting that classroom-specific (as opposed to school-wide) corrective actions to address sporadic concerns associated with IEQ or ventilation may be a practical first step.

Background

Understanding the health effects associated with school indoor environmental quality (IEQ) is important because of the amount of time spent there by students and staff, and poor IEQ has been cited as the most common environmental hazard in schools (Wakefield, 2002). Carbon dioxide can provide an indication of the adequacy of ventilation to an indoor environment (Satish et al., 2012). School occupants exhale CO2 during respiration. In an indoor environment, CO2 can

build-up above outdoor concentrations if outdoor air is not supplied. Carbon dioxide has been used as a surrogate of exposure to indoor pollutants in studies of occupant reporting of health symptoms (Apte et al., 2000; Simoni et al., 2010). Although ambient outdoor CO2 is generally under 400 ppm, previous studies have frequently measured school concentrations above 1000 ppm, in some cases reaching as high as 4000 ppm (Daisey et al., 2003; Mendell et al., 2013). While these concentrations are still well below those thought to cause direct CO2-related health effects (Godish, 2001), 157

Muscatiello et al. previous studies suggest that poor ventilation can result in higher levels of indoor pollutants (Fox et al., 2003; Godwin and Batterman, 2007; Ramachandran et al., 2005), exposure to which may cause health symptoms. A recent review by Sundell et al. (2011) concluded that associations between ventilation rates and certain health outcomes, including inflammation, respiratory infections, asthma symptoms, and short-term sick leave increases, are biologically plausible. A majority of the research evaluating associations between health and ventilation or CO2 among adults has focused on office environments, and of those studies that have focused on schools the target population has generally been children (Apte et al., 2000; Erdmann and Apte, 2004; Fisk et al., 2009; Simoni et al., 2010). Because of the physiologic differences between children and adults (National Research Council (NRC), 2006), the existing literature related to office environments is relevant to providing background on associations between ventilation or CO2 and health. Fisk et al. (2009) combined results from previous studies of office workers to develop quantitative estimates of the effect of ventilation rate on sick building symptoms which suggest that symptom prevalence may increase by 23% as ventilation rates decrease from 10 to 5 l/s/person and decrease by 29% as ventilation rates increase from 10 to 25 l/s/ person. In a review focusing on studies in schools, Daisey et al. (2003) concluded that inadequate classroom ventilation may result in health symptoms. While many of the studies in the review by Daisey et al. (2003) measured the concentrations of various environmental parameters in schools, fewer investigated links with school occupant health, and only two were referenced in discussions about the relationship between ventilation rates or CO2 and health effects. The school-specific studies reviewed by Sundell et al. (2011) were generally consistent in their findings that poor ventilation may be associated with various health symptom endpoints (Norb€ack and Smedje, 2000; W alinder et al., 1997; W alinder et al., 1998) and higher absenteeism (Shendell et al., 2004b). Simoni et al. (2010), Fraga et al. (2008) and Mi et al. (2006) have also reported associations between student health symptoms and CO2 concentrations. A review of the benefits of green schools by NRC did not identify any studies on the relationship between ventilation and teacher health (NRC, 2006), despite the fact that, according to surveillance data from the National Institute for Occupational Safety and Health and the Centers for Disease Control and Prevention (CDC, 2008), the prevalence of asthma and certain respiratory conditions is among the highest for workers in the educational services sector. Previous studies of teachers have investigated potential risk factors for symptom reporting associated with indoor environmental exposures. W alinder et al. (1997) found an 158

association between nasal mucosa swelling and a school-level air exchange rate, although the study was not designed to link a specific classroom air exchange rate with clinical measures of the teacher in their classroom. Ebbehoj et al. (2005) found positive, and in some cases significant, relationships between female teacher symptoms and estimated classroom mold exposure. Ervasti et al. (2012) found an association between student assessments of the school environment and teacher sick leave. However, previous studies have not directly assessed CO2 as an indicator of IEQ and its effects on teacher health symptoms reporting. Therefore, the aim of this study was to examine the school indoor environment and teacher health by evaluating teacher-reported symptoms in relation to CO2 concentrations and characteristics of the classroom in which they teach. Methods

In the spring of 2010, project staff conducted a field study to assess how school building and classroom conditions may influence teacher health. This was a component of a larger study, funded by the United States Green Building Council, to better understand how school conditions affect occupant health and performance (New York State Department of Health, 2010). The study protocol was approved by the New York State Department of Health Institutional Review Board. Eligible schools were selected from four New York State Board of Cooperative Educational Services regions. Attempts were made to recruit schools with varying building conditions based upon a descriptive analysis of the 2005 New York State School Building Condition Survey (New York State Education Department, 2005), and socioeconomic (SES) status, measured as the percentage of students receiving free lunch (New York State Education Department, 2008). Initially, letters were sent to approximately 40 school administrators requesting their voluntary participation in the study. Subsequently, meetings were held with staff from schools that expressed interest in participating, to provide more information and answer projectrelated questions. Upon confirming a willingness to participate, site visit dates were scheduled. During the site visits, data were collected via teacher and staff surveys, school and classroom assessments, and environmental monitoring of classrooms. Participating schools were provided with a financial incentive to be used by their IEQ team or equivalent, and teachers who completed a survey or volunteered their classroom for assessment were provided with an additional incentive (water bottle and microfiber cloth). Overall, ten schools were visited over a 4-month period in 2010: six in March, one in April, and three in June. Nine of the schools that were visited were elementary schools and one school was a combined middle/high school.

Classroom CO2 and teacher health symptoms Teacher and staff survey

All teachers and staff from each participating school were given the opportunity to complete a self-reported survey of their perceptions of the school environment and work-related health symptoms. The survey collected demographic information about the teachers and their home environment, including gender, age, years at current school, residential proximity to roads with higher traffic volumes (within 300 yds.), pets at home, smoking status, and previous diagnosis of asthma by a doctor. The teacher survey also collected general information for the following: 12 specific symptoms (sinus problems, eye irritation, throat irritation, sneezing, allergy/congestion, cough, wheeze/shortness-of-breath, headache, fatigue, difficulty concentrating, skin irritation, and asthma attacks), classroom cleanliness, visible problems and odors, flooring type, indoor thermal comfort and climate, noise, lighting, and asthma management policies and practices. Teachers were asked to use the current school year as a frame of reference for their responses. In addition, teachers were asked, for each reported symptom, whether the symptom worsened in severity during the school day or week, or went away on weekends or vacations. Work-related symptoms were defined as those which either worsened during the school day or week or improved on weekends or vacation. A reminder e-mail was sent to teachers who did not return a survey after 2 weeks. School and classroom assessment

In up to 10 classrooms per school where teachers volunteered to participate in classroom environmental monitoring, visual observations and assessments were recorded for ventilation-specific variables, including type of ventilation system (unit ventilator vs. centralized), number of filter changes per year, presence of blocked or partially-blocked air supply grilles, and ventilation intake distance from an outdoor diesel source, as well as classroom age. The following classroom sources of potential allergens or irritants were also recorded: visible mold or mold odors, visible moisture or moisture stains, visible dust on hard surfaces, chalkboard, open storage, classroom clutter, soft furniture or toys, carpets, evidence of pests or pest droppings, plants, pets in classroom, air fresheners or fragranceemitting devices, and art supplies in classroom. All classroom assessments were completed when rooms were unoccupied, either before or after the school day. Classroom environmental monitoring

In classrooms that had been assessed by project staff, U12-012 and U12-013 HOBOâ data loggers (Onset Corporation, Bourne, MA, USA) were placed to record classroom temperature, relative humidity and

lighting and were connected to Telaireâ 7001 (Telaire, Goleta, CA, USA) CO2 monitors which recorded point measurements of classroom CO2 concentrations. The HOBOâ data loggers were set to collect measurements every 5 min for 48 h, which always included 2 days that school was in session. The Telaireâ 7001 monitors were calibrated at the beginning of the study with the Telaireâ 2075 calibration kit. Instruments were placed in locations representative of adult breathing zones but out of the reach of children, generally on top of a file cabinet or shelves, and away from supply air. Previous studies indicate that there is high correlation between CO2 concentrations measured in different locations in a classroom and suggest that a single monitoring location can adequately characterize CO2 concentrations (Fox et al., 2003). Once data loggers were in position, teachers were instructed not to move them. In addition, teachers were provided with forms to record classroom occupancy throughout the school day for each of the 2 days of monitoring. Exposure assessment

The primary metrics of exposure were a dichotomous variable categorizing classrooms by CO2 status and a continuous variable representing maximum classroom CO2 concentration recorded over the 2 days of monitoring. Occupancy logs completed by teachers were used with monitoring data to limit the CO2 data set to the subset of measurements logged when students were in the classroom. For the dichotomous metric, the proportion of CO2 measurements which exceeded 1000 ppm was calculated for each classroom. Based on the classroom-specific proportions of CO2 greater than 1000 ppm, the median proportion among all classrooms was identified. The median proportion of CO2 concentrations greater than 1000 ppm (median = 9%) was dichotomized to classroom CO2 status above or below the median. This metric measures the amount of time teachers spent in classrooms with CO2 concentrations above a threshold which has been used in previous studies of health effects potentially related to ventilation problems or increasing levels of indoor pollutants (Kinshella et al., 2001; Simoni et al., 2010). Based upon previous studies, suggesting that poor ventilation results in higher levels of indoor pollutants (Fox et al., 2003; Godwin and Batterman, 2007; Ramachandran et al., 2005), the metric provides an indication of exposure to indoor air pollutants. In addition, the maximum classroom CO2 concentration during the 2 days was used as a metric of the peak concentration of CO2. While neither metric is a true measure of the classroom ventilation rate, they help to differentiate classrooms which may have had a higher proportion of concentrations above 1000 ppm but lower peak concentrations from classrooms which may have had a relatively lower proportion of values above 1000 ppm but higher peak concentrations. 159

Muscatiello et al. Statistical analysis

Analyses were conducted using Statistical Analysis Software, version 9.3 (SAS Institute, Inc., Cary, NC, USA). Classroom environmental monitoring and assessment data, and teacher survey data, were linked by a unique identifying code and summarized descriptively. To limit a potential source of variation in the analysis, this study was limited to traditional classrooms. No portable classrooms were included in the study. The final data set included 64 classrooms from 10 study schools (range 1–9 classrooms per school). Work-related symptoms were aggregated into the following groups: ‘any symptom’, ‘mucosal membrane’ (sneezing, throat irritation, eye irritation, allergy/congestion, sinus problems), ‘lower respiratory’ (cough, wheeze/shortness-of-breath, asthma attacks), ‘neuro-physiologic’ (headache, difficulty concentrating, fatigue), and ‘skin irritation’ (skin irritation), using categorizations similar to those previously used by Erdmann and Apte (2004) and those attributed to Levin (1989) and Apte et al. (2000). None of the classroom sources of potential allergens and irritants were significant in bivariate analysis with classroom CO2 status (see Table S1). To assess the cumulative effect of numerous sources of potential allergen or irritants, individual sources were aggregated by classroom and dichotomized to classrooms above and below the median (median = 6). Spearman’s rank correlation coefficients were calculated to estimate the relationship between day 1, day 2, and both day proportions of CO2 measurements above 1000 ppm, and mean and maximum CO2 concentrations. Fisher’s exact tests were used in bivariate analyses to test the association between symptom group reporting and teacher demographic variables, and between the dichotomous CO2 metric and classroom assessment variables. Marginal models for correlated data in PROC GLIMMIX were used to estimate population-averaged odds ratios and 95% confidence intervals for the association between classroom CO2 and each of the work-related symptom groups. These models are similar to generalized estimating equations available in PROC GENMOD but use likelihood-based approaches rather than the method of moments and also incorporate random effects. Classroom-level covariates were modeled as fixed effects, and schools were modeled as random effects. Methods available in PROC GLIMMIX, proposed by Morel et al. (2003) to better account for potential bias associated with the small number of clusters were applied with an additive sample size correction to the empirical covariance estimator, using the ‘empirical = MBN’ option, to account for clustering within schools. The ‘type = VC’ option was used to model the covariance structure. Covariates included the following classroom assessment-related variables: 160

classroom age, ventilation-related variables (type of ventilation system, number of ventilation filter changes per year, fresh air intake locations near diesel sources), and the dichotomous metric variable for potential sources of allergens or irritants. Workrelated symptom group-specific marginal models also included any teacher demographic variables that were significant in the bivariate analysis. Logistic regression using backward selection methods, with all teacher demographic and classroom assessment-related variables entered in addition to CO2 metrics, was also used to create parsimonious models of the relationship between the classroom CO2 metrics and work-related symptom groups, and assess concordance with the marginal models. In the backward selection analysis, the classroom CO2 metrics were forced into their respective models, and additional variables were retained if the P-value was 0.10 or less. Odds ratios and 95% confidence intervals were calculated for the variables retained in each of the work-related symptom group models. Results

Eighty-seven school spaces (i.e., traditional classrooms, administrative spaces and non-traditional classrooms including offices, libraries, art rooms, and special education rooms) were assessed. Nine administrative spaces and non-traditional classrooms (e.g., offices, libraries, art rooms, and special education rooms) were excluded. Ten classrooms were excluded because either the occupancy log or the survey was not returned. One classroom where environmental monitoring data were logged incorrectly and three traditional classrooms where CO2 was not measured were also excluded. Thus, the data set included 64 classrooms from 10 study schools (range 1–9 per school). These data were linked with 68 teacher surveys (in four classrooms, two teachers or aides returned surveys) to create the final data set. Table 1 shows the proportion of teachers reporting work-related symptoms by demographic characteristic. Skin irritation was only reported by two teachers and was not included in any analyses. Almost 90% of teachers in the study were female, with age distributed fairly evenly above and below age 40. Sixty-three percent of the teachers had been teaching at their current school for less than ten years. Approximately 43% reported living within 300 yards of a road with higher traffic volumes, and 62% had a dog or cat at home. Nearly 21% of the teachers reported having a previous diagnosis of asthma, and only 3% reported smoking. The only bivariate association that was statistically significant was for previous diagnosis of asthma, which was reported significantly more often (P = 0.04) by teachers reporting lower respiratory symptoms,

Classroom CO2 and teacher health symptoms Table 1 Self-reported symptoms among teachers (n = 68) in classrooms with CO2 monitoring, by demographic characteristic, for each symptom groupa

Variable

Totalb [n = 68]

Any symptom (%b) [n = 51]

Mucosal membrane (%b) [n = 38]

Genderc Female 60 45 (75.0) 34 (56.7) Male 7 5 (71.4) 3 (42.9) Agec 10 25 17 (68.0) 11 (44.0) Lives within 300 yards of road with higher traffic volumesc Yes 29 19 (65.5) 14 (48.3) No 36 29 (80.6) 21 (58.3) Pets at home Yes 42 30 (71.4) 24 (57.1) No 26 21 (80.8) 14 (53.9) Previous diagnosis of asthma Yes 14 10 (71.4) 8 (57.1) No 54 41 (75.9) 30 (55.6) Smokes at least once/week Yes 2 1 (50.0) 0 (0.0) No 66 50 (75.8) 38 (57.6)

Lower respiratory (%b) [n = 11]

Neurophysiologic (%b) [n = 33]

9 (15.0) 1 (14.3)

29 (48.3) 4 (57.1)

5 (13.5) 5 (16.7)

16 (53.3) 17 (46.0)

8 (18.6) 3 (12.0)

21 (48.8) 12 (48.0)

3 (10.3) 7 (19.4)

12 (41.4) 19 (52.8)

6 (14.3) 5 (19.2)

20 (47.6) 13 (50.0)

5 (35.7)d 6 (11.1)

7 (50.0) 26 (48.2)

1 (50.0) 10 (15.2)

1 (50.0) 32 (48.5)

a Skin irritation symptom group not shown due to small number with reported condition (n = 2). b Counts may not sum to column total due to missing information; proportions may not sum to 100 due to rounding. c One missing for Gender and Age; three missing for Lives within 300 yards of heavily trafficked road. d Significant Fisher’s exact P-value (P = 0.04).

although lower respiratory symptoms were only reported by 11 teachers. Table 2 shows descriptive statistics for ventilationrelated variables, classroom age, and the classroom allergen/irritant indicator by classroom CO2 status. Approximately 81% of the classrooms were ventilated by classroom-specific fresh air handlers (unit ventilators), with the remaining 19% ventilated by centralized air-handling units that distributed air through ductwork to more than one classroom. In 47% of the classrooms, ventilation filters were changed two times per year, and in 53%, filters were changed three or four times per year. None of the measures were significantly associated with classroom CO2 status. However, there was a marginally significant association between CO2 status and classroom age (P = 0.08) and ventilation filter changes per year (P = 0.08). Newer classrooms and classrooms with two filter changes per year (vs. 3–4 filter changes per year) were more likely to have higher CO2. As shown in Table 3, point CO2 concentrations (5-min averages) measured among all the schools ranged from 352 to 1591 ppm. Approximately 20% of the CO2 measurements recorded in occupied classrooms

Table 2 Bivariate analysis of the association between classroom characteristics and classroom CO2 status Classrooms

Variable

Total [n = 64]

With above-median CO2 (%) [n = 32]

Ventilation-related Type of ventilation system Unit ventilator 52 29 (55.8) Centralized 12 3 (25.0) Ventilation filter changes/year 2x 30 19 (63.3) 39 or 4x 34 13 (38.2) Intake < 50 ft. from diesel sourcea Yes 17 11 (64.7) No 47 21 (44.7) Classroom ≥ 40 years Yes 30 11 (36.7) No 34 21 (61.8) Classroom allergen/irritant indicatorb Yes 35 17 (48.6) No 29 15 (51.7)

With below-median CO2 (%) [n = 32]

Fisher’s exact P-value

23 (44.2) 9 (75.0)

0.11

11 (36.7) 21 (61.8)

0.08

6 (35.3) 26 (55.3)

0.26

19 (63.3) 13 (38.2)

0.08

18 (51.4) 14 (48.3)

1.0

a

Bus, truck, garbage loading/unloading areas. Derived by dichotomizing above and below the median number of potential allergens/irritants among all classrooms (median = 6). b

were above 1000 ppm. The mean CO2 concentrations in classrooms above and below the median were 931 ppm and 706 ppm, respectively, and the mean proportions of CO2 concentrations above 1000 ppm were 38.5% and 1.5%, respectively. Mean classroom CO2 concentrations ranged from 611 ppm in School H to 898 ppm in School B. School I had the minimum and the maximum CO2 concentrations, 352 ppm and 1591 ppm, respectively. School H did not have any recorded concentrations greater than 1000 ppm, although several measurements approached that level. Table 3 Summary of CO2 concentrations and percent of concentrations greater than 1000 ppm for all classrooms, by CO2 status, and by school % classroom CO2 concentrations > 1000 ppm

Classroom CO2 concentrations Classrooms

n

Min

Mean (s.d.)

Med

Max

Min

Mean

Max

All With above-median CO2 With below-median CO2 School A B C D E F G H I J

64 32 32

352 352 363

812 (215) 931 (212) 706 (150)

799 945 708

1591 1591 1139

0 9.6 0

20.0 38.5 1.5

72.5 72.5 8.3

6 6 8 7 8 7 1 5 7 9

435 354 409 404 365 372 381 378 352 404

819 (182) 898 (211) 835 (211) 869 (185) 753 (200) 789 (230) 705 (164) 611 (135) 873 (235) 825 (198)

839 880 836 866 713 740 714 603 910 809

1376 1431 1521 1237 1314 1460 1062 977 1591 1472

0 0 0 0 0 0 – 0 0 0

17.7 27.8 15.7 31.6 15.5 15.3 4 0 39.5 16.4

57.4 55.7 57.2 59.1 53.0 63.9 – 0 72.5 57.4

161

Muscatiello et al.

Fig. 1 Percent of CO2 concentrations > 1000 by classroom

Day 1, day 2, and both day proportions of CO2 measurements above 1000 ppm, along with mean and maximum CO2 concentrations, were highly correlated (Table S2). As indicated in Table 3 and displayed in Figure 1, the proportion of classroom-specific measurements that exceeded 1000 ppm ranged from 0% to nearly 75% (reference line in Figure 1 represents median value of 9.0%). There was substantial betweenclassroom variability within schools. In eight of the ten schools, there was at least one classroom where 0% of the concentrations exceeded 1000 ppm and one classroom where more than 50% of the concentrations were above 1000 ppm. Table 4 shows population-averaged odds ratios for the relationship between work-related symptom groups and classroom CO2 status. Teachers in classrooms with higher CO2 had significantly increased odds of reporting neuro-physiologic symptoms (OR = 2.62, 95% CI = 1.09–6.35) and increased odds of reporting any symptom (OR = 1.74, 95% CI = 0.36–8.52) and mucosal membrane symptoms (OR = 1.80, 95%

Table 4 Bivariate odds ratios from marginal models of teacher-reported, potentially-workrelated symptoms and classroom CO2 status % of teachers reporting by CO2 statusa (n)

Symptom group

% of teachers reporting (n)

In classrooms with abovemedian CO2

In classrooms with belowmedian CO2

Bivariate OR (95% CI)

Any symptom Mucosal membrane Lower respiratory Neuro-physiologic

75.0 (51) 55.9 (38) 16.2 (11) 48.5 (33)

80.0 62.9 14.3 60.0

69.7 48.5 18.2 36.4

1.74 (0.36–8.52) 1.80 (0.44–7.29) 0.75 (0.20–2.78) 2.62 (1.09–6.35)

a

Classrooms with 9% or more of their CO2 measurements greater than 1000 ppm were grouped above median and less than 9% were grouped below median.

162

CI = 0.44–7.29). Lower respiratory symptoms were reported less often, and teachers reporting these symptoms were slightly more likely to be from classrooms with lower CO2 (OR = 0.75, 85% CI = 0.20–2.78). Table 5 shows the population-averaged odds ratios for the relationship between work-related symptom groups and classroom CO2 status, as well as the other covariates included in the model. The only teacher demographic variable controlled for in any of the multivariate models in Table 5a or b was previous diagnosis of asthma in the lower respiratory model, because that was the only association significant in the bivariate analysis. For the marginal models using the dichotomous CO2 metric based upon the median proportion of CO2 concentrations greater than 1000 ppm, the odds of reporting any symptom (OR = 1.54, 95% CI = 0.21–11.62), mucosal membrane symptoms (OR = 1.56, 95% CI = 0.20–11.87), and neuro-physiologic symptoms (OR = 2.26, 95% CI = 0.72–7.12) were non-significantly increased in classrooms with higher CO2. Of the covariates, only classroom age was associated with symptom reporting in any of the models, as teachers in classrooms that were built more than 40 years ago were less likely to report any symptom (OR = 0.14, 90% CI = 0.03–0.59). Table 5b lists the population-averaged odds ratios for the relationship between symptom group reporting and maximum CO2 concentration, controlling for potential confounders. Teachers in classrooms with higher maximum CO2 had significantly increased odds of reporting neuro-physiologic symptoms (OR = 1.30, 95% CI = 1.02–1.64). Supplemental Table S3 displays odds ratios and confidence intervals for the multivariate analysis using logistic regression backward selection methods. None of the teacher demographic variables were selected into the models except for asthma in the lower respiratory symptom model. The odds ratio estimates for the vari-

Classroom CO2 and teacher health symptoms Table 5 Odds ratios and 95% CI for marginal models of the association between health symptoms and the dichotomous CO2 indicator (Part a.) and maximum classroom CO2 concentration (Part b.), controlling for classroom assessment variables and significant teacher demographic variables

Variable

Any symptom OR (95% CI)

Mucosal membrane OR (95% CI)

(a) Dichotomous CO2 indicator (above- or below-median proportion of CO2 concentrations greater than 1000 ppm)a Classroom CO2 above median 1.54 (0.21–11.62) 1.56 (0.20–11.87) Previous diagnosis of asthma – – Classroom age > 40 years 0.14 (0.02–0.89)b 0.32 (0.04–2.61) Univent 0.78 (0.14–4.24) 0.73 (0.12–4.29) Fresh air intake near diesel source 0.58 (0.11–3.06) 0.64 (0.20–2.02) Filter change twice/year 0.32 (0.06–1.83) 1.18 (0.33–4.23) Allergen/irritant indicator above median 1.95 (0.48–7.86) 3.10 (0.82–11.58) (b) Maximum classroom CO2 concentrationa Maximum CO2 concentrationc 1.15 (0.80–1.66) 1.06 (0.71–1.58) Previous diagnosis of asthma – – Classroom age > 40 years 0.12 (0.03–0.71) 0.31 (0.04–2.17) Univent 0.79 (0.13–4.83) 0.80 (0.13–5.01) Fresh air intake near diesel source 0.56 (0.12–2.67) 0.67 (0.20–2.20) Filter change twice/year 0.29 (0.05–1.64) 1.24 (0.34–4.47) Allergen/irritant indicator above median 1.86 (0.46–7.52) 2.88 (0.71–11.65)

Lower respiratory OR (95% CI)

Neuro-physiologic OR (95% CI)

0.48 (0.04–6.22) 5.50 (0.54–55.64) 0.58 (0.03–12.30) 1.38 (0.14–13.51) 0.80 (0.06–11.18) 1.36 (0.17–10.96) 1.76 (0.23–13.64)

2.26 (0.72–7.12) – 0.77 (0.16–3.60) 1.47 (0.39–5.55) 1.55 (0.52–4.65) 0.86 (0.20–3.57) 0.96 (0.26–3.61)

0.98 (0.60–1.60) 5.07 (0.59–43.28) 0.69 (0.05–9.63) 1.30 (0.16–10.79) 0.68 (0.06–7.91) 1.23 (0.17–9.17) 1.91 (0.23–15.87)

1.30 (1.02–1.64) – 0.65 (0.13–3.21) 1.58 (0.41–6.08) 1.47 (0.48–4.51) 0.74 (0.19–3.00) 0.80 (0.21–3.01)

a

Controlling for ventilation-related variables, classroom age, and allergen/irritant indicator; previous diagnosis of asthma only included in lower respiratory model. Bolded values significant at a = 0.05. c Odds ratios are per 100 ppm increase in maximum CO2 concentration. b

ables that were selected into the logistic regression models were similar in direction and, for the most part, similar in magnitude to those in the marginal models. Confidence interval estimates were narrower than those in the marginal models, which may result from not accounting for the effect of classrooms clustered within schools. Discussion

In this study, self-reported symptoms from 68 teachers were more common in classrooms with higher CO2, among the 64 classrooms that were studied. Despite the relatively small sample size and maximum measured CO2 concentrations that were less than what has been reported in some previous studies, the odds of reporting work-related neuro-physiologic symptoms were significantly increased for maximum classroom CO2 concentration, and non-significantly increased for classrooms with above-median proportions of CO2 concentrations greater than 1000 ppm. The odds of reporting any symptoms and mucosal membrane symptoms were also increased, but non-significant, for both of the CO2 metrics. These findings are generally consistent with a recent review which summarized the existing literature on ventilation and CO2 and health and concluded that existing studies have generally found lower ventilation rates to be associated with Sick Building Syndrome (SBS) symptoms, characteristic of the symptoms in our study (Sundell et al., 2011). An earlier review focusing on school IEQ reported that previous studies had found inconsistent relationships between CO2 concentrations and symptoms, but acknowledged that few studies of the school environ-

ment were available (Daisey et al., 2003). This study provides additional insight into the relationship between increased CO2 and health symptom reporting and is one of the first which has linked self-reported teacher survey data with classroom-level (i.e., not school-level) CO2 data. Eight out of the ten schools had at least one classroom where more than 50% of classroom CO2 measurements were greater than 1000 ppm, a common finding in previous studies of school IEQ (Daisey et al., 2003; Mendell et al., 2013; Shendell et al., 2004a,b; Sundell et al., 2011). Maximum classroom CO2 concentrations and the proportion of classroom CO2 concentrations greater than 1000 ppm were highly correlated. At the levels measured in this study, CO2 concentrations were likely not the direct cause of the health effects but may have been associated with increasing concentrations of indoor allergens or irritants, and potentially infectious respiratory agents (Fox et al., 2003; Godwin and Batterman, 2007; Mendell et al., 2013; Ramachandran et al., 2005). There was substantial variation in CO2 concentrations between classrooms within schools, which is perhaps a more relevant finding from a facilities management standpoint. A previous assessment of IEQ in elementary and middle schools by Godwin and Batterman (2007) similarly found wide ranges in CO2 levels among the 64 classrooms they studied, including greater within-school variability than between-school variability. This underscores the importance of treating classrooms as unique environments when performing school ventilation system maintenance and addressing occupant complaints or concerns. Although the total sample is relatively small, the schools that participated 163

Muscatiello et al. were not recruited because of a known ventilation problem or IEQ complaint, which may improve the overall representativeness of the results. Both classroom CO2 metrics were associated with increased, and in the case of maximum CO2 concentrations significantly increased, odds of reporting neurophysiologic symptoms, which included the specific symptoms fatigue, difficulty concentrating, and headache. The population-averaged odds ratio was estimated to increase 2–64% for every 100 ppm increase in the maximum classroom CO2 concentration. Given the range in classroom CO2 concentrations in this study was approximately 600 ppm, the odds ratio for reporting neuro-physiologic symptoms among the classrooms with the highest and lowest maximum CO2 concentrations would be 4.8. Previous studies have reported results which provide evidence of an association between CO2 and neuro-physiologic symptoms. Norb€ ack and Nordstr€ om (2008) conducted a cross-sectional analysis of the health effects of ventilation and temperature in university computer classrooms and concluded that increased CO2 and temperature were associated with reporting of headache and fatigue among college-aged students. They suggested that temperature may be a more important factor based upon attenuated odds ratios after additionally controlling for temperature, relative humidity, and air exchange rate, although a statistically significant association between headache and CO2 remained. In a study of ventilation system types and perceptions of IEQ, Kinshella et al. (2001) found an association between reporting of headaches and the type of system with the highest proportion of CO2 concentrations greater than 1000 ppm, although CO2 was only measured in one classroom per school. A randomized double-blind multiple-crossover trial by Menzies et al. (1993) did not find any association between reporting of systemic symptoms (which included the symptoms comprising the neuro-physiologic group in this study) and changes in ventilation rate. However, as suggested by Sundell et al. (2011), the ventilation levels for the groups compared in that study averaged 30 ft3/min/person and 64 ft3/min/person, so the lack of association may be explained by the high ventilation rates among the entire study group. Other studies have attempted to measure changes in decision-making and task performance at different concentrations of CO2 (Kajtar et al., 2003, as referenced in Sepp€anen and Fisk (2004); Satish et al., 2012). It is possible that symptoms such as headache, fatigue, and difficulty concentrating could influence decision-making performance, although further study would be needed to determine how these symptoms modify the relationship between CO2 and performance-related tasks. The odds of reporting mucosal membrane symptoms (i.e., sneezing, throat irritation, eye irritation, allergy/ congestion, sinus problems) were increased, though 164

not significantly, at increasing maximum CO2 concentrations and among teachers in classrooms above-median CO2. Associations between mucosal membrane symptoms and indoor concentrations of CO2 have also been documented in schools and studies of office environments (Apte et al., 2000; Chao et al., 2003; Daisey et al., 2003; Erdmann and Apte, 2004; W alinder et al., 1997). Although there was no strong evidence that the number of potential sources of classroom allergens or irritants, as qualitatively measured in this study, was related to symptom reporting, the population-averaged odds ratio points estimates were relatively high for teachers reporting mucosal membrane symptoms. In an analysis of the specific sources which may have contributed to the association, the presence of plants in classrooms was a strongest risk factor for reporting mucosal membrane symptoms after controlling for the dichotomous classroom CO2 metric and other potential sources of allergens/irritants (see Table S4). Previous studies have measured lower concentrations of indoor air pollutants and CO2 in rooms with, compared to rooms without, potted plants (Pegas et al., 2012; Tarran et al., 2007; Wolverton et al., 1989; Wood et al., 2006). Evaluating the relationship between the impact of plants in indoor environments and health symptom reporting may provide further insight. Teachers in older classrooms were less likely to report any symptom. Previous studies have found higher levels of VOCs in newer classrooms (Kim et al., 2007; Yang et al., 2009). The NRC (2006) review suggests that classroom age has been used as a surrogate for building condition in past studies of student achievement, but age is not necessarily indicative of classroom condition. Additional study would be needed to determine whether classroom age is a useful indicator for future use or whether the significant finding in this study was due to chance. In our study, a relatively high proportion of teachers reported a previous doctor diagnosis of asthma (~21%) compared to the 10.5% estimated prevalence in the elementary and secondary schools and colleges sector from a 2008 CDC report (CDC, 2008). Asthma was primarily used as a control variable in this analysis. A study by Mi et al. (2006) reported an association between indoor CO2 and current asthma, although classroom CO2 status was not associated with reporting of lower respiratory symptoms in our study. In a study of work-aggravated asthma among educational services industry workers, work-related asthma cases were highest among the ‘teachers and teachers’ aides’ occupational group (Mazurek et al., 2008). One explanation for the discrepancy in asthma prevalence in this study, compared to the surveillance estimates, is that teachers with asthma may have been more interested knowing about the IEQ of their classroom and, therefore, been more willing to voluntarily participate.

Classroom CO2 and teacher health symptoms It is helpful to put the CO2 concentrations measured in this study into context with other studies. Carbon dioxide concentrations and the overall proportion of CO2 concentrations greater than 1000 ppm (20%) were not as high as those reported in other studies. Approximately 12% of the classrooms that were studied had mean CO2 concentrations greater than 1000 ppm, and the maximum CO2 concentration was 1591 ppm. The study by Simoni et al. (2010) found that nearly half of the classrooms had mean CO2 concentrations greater than 1500 ppm. In another study by Fraga et al. (2008), low, medium, and high CO2 exposure was defined as ~1400 ppm, ~1850, and >2100 ppm, respectively. On the other hand, a listing of CO2 mean concentrations and ranges from previous studies in the review by Daisey et al. (2003) displays several which are similar to this study, which may partly explain their conclusion that the studies they reviewed provided suggestive but inconclusive results about the effects of CO2 on health symptoms. Yet even with these smaller differences in the magnitude of ‘exposure’ in this study, the analysis found elevated odds of symptom reporting with increasing maximum CO2 concentrations and in classrooms with above-median proportions of CO2 greater than 1000 ppm. The main strength of this study was the classroomlevel linkage of CO2 concentrations and teacher reporting of symptoms at work. Another strength is that these schools were not selected based upon pre-existing problems, and teachers were not made aware of the ventilation status of their classroom prior to completing the survey. The study was also able to control for several potential confounders related to teacher demographics and the school and home environment. Based upon the qualitative evaluations made during classroom assessments, classrooms were similar in their general condition and did not differ by CO2 status on various indicators of health-related IEQ problems, including dust, moisture, potential sources of chemical irritants, and pest/rodent problems. This suggests that teachers were not differentially exposed to these potential allergens/irritants at different concentrations of CO2. Subsequent to the fieldwork done in this study, data for the 2010 New York State School Building Condition Survey (BCS) were made available (New York State Education Department, 2010). The BCS is, by design, qualitative and only provides a single school-level rating. Nevertheless, where comparable, the relevant school-specific results generally supported findings from the classroom assessments. The main discrepancy was that eight of ten schools were rated as having adequate outdoor air on the BCS, although the validity of that particular item may be limited by its qualitative nature. The main weakness of the study relates to the relatively small sample of classrooms for analysis. However, resource limitations precluded a larger sample.

Selection bias is a concern if the characteristics of teachers who volunteered to participate in the study were systematically different than those of teachers who did not volunteer to participate. However, while that may affect the generalizability of the study, we do not expect that to be differential on classroom CO2 status because teacher volunteers were not aware of their classroom’s CO2 status when they completed the survey. Self-reporting of health effects and some of the potential confounders may also result in measurement bias, although we would not expect that to be differential by classroom CO2 status and result would tend to be attenuated toward the null. Interpreting the covariate models must be done with caution because of the relatively wide confidence intervals in many of the estimates and issues associated with multiple testing. Finally, although we asked teachers to report symptoms occurring during the school year in which the study took place, CO2 concentrations were only measured over 2 days. While analysis of the data indicates that the proportion of CO2 concentrations greater than 1000 ppm were correlated for day 1 and day 2, it is unclear whether these values are representative of classroom CO2 status for the entire year. Conclusions

This study combined surveys, observations, and monitoring data to assess classroom CO2 and teacher reports of health symptoms. Although this study did not directly measure ventilation rates, indoor CO2 concentrations provide an indication of the adequacy of ventilation to the classroom. These results are unique in their assessment and linkage of teacher health symptoms with monitored CO2 concentrations, but support the findings of previous studies that have focused on adults in office settings or students in schools. This study suggests that teachers in classrooms with higher maximum CO2 concentrations, as measured by maximum CO2 concentrations and above-median proportions of CO2 greater than 1000 ppm, are significantly more likely to report neuro-physiologic symptoms (i.e., headache, fatigue, difficulty concentrating), before and after controlling for classroom age, ventilation-related variables, and number of potential sources of classroom allergens and irritants. Our findings also suggest that consideration of lower cost, potentially classroomspecific (as opposed to school-wide) corrective actions to address IEQ concerns associated with ventilation may be a practical first step to handling occupant concerns. Acknowledgements

This work was supported by a grant from the U.S. Green Building Council (USGBC). Its contents are 165

Muscatiello et al. solely the responsibility of the authors and do not necessarily represent the views of USGBC. Supporting Information

Additional Supporting Information may be found in the online version of this article: Table S1. Results of bivariate analysis of the association between presence of potential sources of allergens/ irritants and classroom CO2 status. Table S2. Spearman correlation coefficients for relationship between day 1, day 2, and both days for 64 study classrooms.

Table S3. Odds ratios from backward selection multivariate analysis testing the association between teacher-reported work-related symptom groups and classroom-related covariates excluding teacher demographic variables. Table S4. Odds ratios and 90% CI for association between mucosal membrane symptoms and potential sources of allergen/irritant. Table S5. Comparison of odds ratios and 95% CI from GLIMMIX and GENMOD for the relationship between maximum classroom CO2 and neuro-physiologic symptoms, controlling for covariates.

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