exposure to home and school environmental triggers and asthma morbidity in chicago inner-city...

ORIGINAL ARTICLE LOWER AIRWAYS

Exposure to home and school environmental triggers andasthma morbidity in Chicago inner-city childrenElizabeth Banda1, Victoria Persky1, Gay Chisum2, Maureen Damitz2, Rhonda Williams2 & Mary Turyk1

1Division of Epidemiology and Biostatistics, University of Illinois at Chicago School of Public Health, Chicago, IL, USA; 2Respiratory Health

Association of Metropolitan Chicago, Chicago, IL, USA

To cite this article: Banda E, Persky V, Chisum G, Damitz M, Williams R, Turyk M. Exposure to home and school environmental triggers and asthma morbidity in

Chicago inner-city children. Pediatr Allergy Immunol 2013: 24: 734–741.

Keywords

asthma emergency department visit; asthma

hospitalization; asthma morbidity; indoor

asthma triggers; inner-city children; asthma

age groups

Correspondence

Elizabeth Banda, University of Illinois at

Chicago School of Public Health, 1603

W. Taylor, M/C 923, Chicago, IL 60612, USA

Tel.: 312-355-3974

Fax: 312-996-0064

E-mail: [email protected]

Accepted for publication 6 October 2013

DOI:10.1111/pai.12162

Abstract

Background: In children, asthma hospitalization rates are highest among those aged

0–4 yr, indicating more acute and/or severe asthma exacerbations in younger children.

We investigated the relationship between indoor exposures and three asthma

morbidity measures in children of different age groups (0–4, 5–11, and 12 yr of age

or older). Identifying the factors leading to asthma morbidity in specific subgroups

may lead to a better understanding of the disease and contribute to the development of

effective interventions tailored to subgroups.

Methods: Children between 0 and 18 yr of age with asthma were enrolled in an asthma

intervention program. At enrollment, hospitalizations, emergency room visits (ED),

asthma night symptoms, and exposure to conditions in the child’s home and school/

daycare related to indoor allergens were collected using standardized questionnaires.

Associations of exposure with the three asthma outcomes were estimated using logistic

regression, stratified by age group.

Results: Of 246 children enrolled, the youngest age group had more hospitalizations in

the past year, more ED visits in the past year, and more night awakenings in the past

month due to asthma than the oldest two age groups (p = 0.02; p < 0.0001; and

p = 0.01, respectively). Overall, more associations of exposures to home triggers were

found with hospitalization in children aged 0–11 yr, while classroom triggers were more

likely to be associated with hospitalizations among the oldest two groups, 5–18 yr of age.Conclusions: Examining the relationship of specific environmental exposures with

asthma exacerbations and hospitalizations across age group and in different indoor

environments warrants further study.

Asthma, the most common chronic disease in children in the

USA, affects 7.1 million children aged 0–17 yr, approximately

one-third of all asthmatics in the USA (1). Differences in

asthma prevalence and morbidity exist among population

subgroups, which are often explained by variation in social,

economic and environmental factors. In children, asthma

hospitalization rates are highest in the age group 0–4 yr (2)

indicating more severe asthma exacerbations among younger

children.

While causes for asthma exacerbations and hospitalizations

are well documented, variations in risk across age group are

less understood. Studies have identified viral infections as

major triggers of asthma exacerbations and hospitalizations in

children and adults (3–5). Similarly, a large body of evidence

suggests that exposure to indoor pollutants (such as second

hand smoke) and indoor allergens (such as dust mite, cat, dog,

mouse, cockroach, and molds) play an important role in the

exacerbation of asthma (6, 7) in children (8–10) and adults (11).

Relationships in some studies are stronger in children with

specific allergies to the exposures (9, 10). Other studies that do

not include allergy testing have found associations with

dampness (12), cockroach allergen (8), and wall integrity

(11). Identifying factors leading to asthma morbidity in specific

subgroups is important, as it may lead to a better understand-

ing of the disease, its risk factors, and the development of

effective interventions tailored to subgroups, which may

subsequently result in better asthma outcomes.

Intervention studies have shown improved asthma control

with modification of the home environment. Some have

demonstrated that advice by physicians (13) as well as case-

management by trained social workers (14) and research

assistants focused on modification of the home environment

(15) can reduce asthma symptoms in children. Other studies

showed improved measures of control with intensive home visit

734 Pediatric Allergy and Immunology 24 (2013) 734–741 ª 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd

Pediatric Allergy and Immunology

intervention by community health workers (16) and with

integrating home visits by community educators with clinic-

based education (17, 18), public housing education (19), home

remediation (20), school screening (21), and community-based

healthcare providers (22, 23).

Few of the above-mentioned studies were able to delineate

effects of specific indoor exposures and those that were able

to examine specific exposures did not yield consistent results

(8, 10–12, 24). A home-based intervention by community

educators in a predominantly African American low-income

Chicago neighborhood with detailed visual assessments

provides a unique opportunity to examine associations of

specific indoor home and school environmental exposures with

measures of asthma morbidity across age groups.

Methods

Study population

The data for this analysis come from a cohort of 246 children

from 158 families enrolled in an asthma intervention project

aimed at improving asthma control in children residing in the

Englewood and West Englewood communities on the South-

side of Chicago. In 2005, the asthma hospitalization rate was

44/10,000 for children aged 2–17 yr living in Englewood, and

21/10,000 for children aged 2–17 yr living in the rest of

Chicago (personal communication, Rich Forshee, Illinois

Department of Public Health). Data collected from an addi-

tional 87 children from 59 families from one of the community

health educators (CHEs) were deemed unreliable and excluded.

Another group of 54 children from 36 families was not

included because they did not complete a home assessment.

Children enrolled were referred to the program from a variety

of sources, predominantly healthcare providers and school

screenings. Enrollment into the program occurred between

January 2006 and November 2008. All children were 0–18 yr of

age with a physician’s diagnosis of asthma as reported by the

caregiver. Evaluation of this program was approved by the

University of Illinois at Chicago Office for the Protection of

Research Subjects. The present study is a cross-sectional

analysis of exposures and level of asthma morbidity at baseline.

Data collection

Data used in our analysis were collected by two CHEs working

for the Respiratory Health Association of Metropolitan

Chicago: one a registered nurse, the second with a bachelor

of science degree. At enrollment, caregivers were surveyed by

the CHE regarding their child’s asthma symptoms, healthcare

utilization, asthma history and daycare/school triggers.

Approximately one month later, the CHE performed a home

assessment that consisted of surveying participants regarding

their home environment and performing a home walkthrough

recording the presence of asthma triggers and home conditions.

Exposures were evaluated using a modified version of the

Coover tool, a home assessment form developed by an asthma

nurse and used for inspection of the home environment in two

previous asthma studies (25, 26). CHEs were trained on how to

complete the home assessment and shadowed by a field

supervisor during their first home inspections to ensure that

assessments were completed correctly.

Three parentally reported asthma morbidity measures were

selected for analysis: any hospitalization in the last 12 months,

any emergency department (ED) visit in the last 12 months and

>2 night awakenings in the past month due to asthma

symptoms. Asthma-related environmental home conditions

and parentally-reported classroom triggers were selected for

analysis. Environmental factors known to be common asthma

triggers (based on the literature) and additional factors

suspected to contribute to asthma exacerbations were deter-

mined by self-report and visual inspection including smoke in

the home, dampness, mold, holes in the walls, cockroaches,

rodents, furry/feathered pets, plants, wall-to-wall carpeting

anywhere in the home, wall-to-wall carpeting in the child’s

sleeping area, clutter in the child’s sleeping area, dusty/dirty

surfaces, peeling wallpaper/flaking paint, >2 people per bed-

room, furry pets in the bedroom, renting home, and eating in

the bedroom. Classroom triggers included plants/aquariums

and carpet. A number of other classroom triggers (pets, mold/

mildew, roaches, water damage, rodents, smokers, presence of

wood stove or fireplace) were evaluated but not selected for

further analysis because they were reported infrequently. For

children ≤4 not in daycare (20/58), classroom trigger exposures

were counted as zero. Three variables were created from the

individual environmental factors: sum of home triggers, sum of

child’s bedroom triggers and none vs. any classroom triggers

(see Table 2 for details). Because previously published findings

report varying asthma hospitalization rates among pediatric

age groups in the USA, children were stratified into three age

groups: 0–4 yr of age, 5–11 yr of age, and 12 yr of age and

older (2).

Statistical methods

Univariate associations of symptoms and triggers across age

were assessed by chi-square tests. We used multivariable

logistic regression models with a random intercept to account

for clustering of children within families (SAS PROC GEN-

MOD) to study associations between individual environmental

factors and the three dichotomous asthma morbidity measures

at baseline. We examined hospitalizations, ED visits and night

awakenings by age group controlling for sex, with additional

control for seasonality in night awakenings. Seasons were

defined as fall (September–October), winter (November–March), spring (April–May), and summer (June–August). All

analyses of children age 0-4 yr were adjusted for daycare

attendance. All analyses were performed using SAS 9.2

manufactured by SAS Institute Inc., Cary, North Carolina,

USA.

Results

Of the 246 children enrolled in the program, 24% were aged

0–4, 48% were 5–11 and 28% were ≥12 yr old; 16% had been

hospitalized in the past year, 46% visited an ED in the past

year and 37% awakened at night >2 times in the past month

Pediatric Allergy and Immunology 24 (2013) 734–741 ª 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd 735

Banda et al. Indoor triggers and asthma morbidity

due to asthma symptoms (Table 1). Significant differences were

found in asthma characteristics across age groups, with

decreasing frequency of number of children hospitalized,

visiting the ED, and awakening at night as age increased.

There were no statistically significant differences in asthma

management characteristics across groups other than caregiv-

ers’ ability to manage their children’s asthma based on CHE’s

assessment (Table 1). Caregivers with children ≥12 yr of age

tended to be the most capable of managing their child’s asthma

and those with children aged 0–4 yr the least capable. Having

more than one child with asthma did not significantly affect

caregiver’s ability to manage their children’s asthma (not

shown). Contrary to a USA sample of children with asthma

(27), a high percent of children were on medication: 90% on

reliever medication and 44% on controller medication.

With respect to environmental characteristics (Table 2), the

most common environmental exposures were living in a home

with holes in the walls or floors, mold, wall-to-wall carpeting,

clutter in the bedroom, dust/dirty surfaces, and >2 people per

bedroom. Classroom triggers more often reported were plants/

aquariums (10%) and carpet (14%). Among participants, 24%

were exposed to at least one school trigger (Table 2).

Analysis by age group

Exposure to some individual home environmental triggers

differed statistically across age group. Overall, children aged

0–4 yr tended to have lower levels of exposure than older age

groups (Table 2). Differences in exposure to classroom triggers

were not found.

In all children, hospitalizations were associated with holes in

the wall, the sum of home triggers, and plants/aquariums and

carpet in the classroom (Table 3). More significant associations

were apparent in the younger two age groups, compared with

those ≥12 yr old, although specific triggers differed across age

group. In the youngest age group, exposure to dampness,

mold, holes in the wall, cockroaches, rodents, number of home

exposures, and plants/aquarium in the classroom were signif-

icantly associated with hospitalization. For children aged 5–11,carpet in the bedroom, >2 people in the bedroom, plants/

aquariums and carpet in the classroom were positively asso-

ciated, while plants and sum of bedroom triggers were inversely

associated, with hospitalizations. For those ≥12 yr old, holes in

the wall, plants/aquarium in the classroom, and carpet in the

classroom were positively associated with hospitalizations.

Far fewer significant associations were seen with ED visits

than with hospitalizations, with most of the associations

occurring among the older two age groups and only carpet in

the classroom being associated with ED visits among all

children (Table 4). ED visits were significantly associated with

> 2 people per bedroom, carpet in the classroom, and plants in

the home (last variable inversely associated) in children aged

5–11 and with sum of home triggers in children ≥12 yr old.

Among all children, night symptoms were significantly

associated with holes in the walls, cockroaches, ≥1 classroom

condition, and carpet in the classroom (Table 5). Across age

group, night symptoms were significantly inversely associated

with dampness in the home and positively associated with ≥1classroom trigger and carpet in the classroom in children aged

5–11 yr, while inversely associated with carpet in the house and

positively associated with plants/aquariums in the classroom in

children age ≥12 yr.

Discussion

Overall, this study finds more associations of exposures to

home triggers with hospitalization in younger children aged

0–11 yr than those aged12–18 yr.These findingsmaybepartially

Table 1 Asthma characteristics by age group (n = 246)

All ages (n = 246) Ages 0–4 (n = 58) Ages 5–11 (n = 118) Ages ≥12 (n = 70)Chi-square

p-value% Reported % Reported % Reported % Reported

Asthma characteristics

Hospitalized in the past year 16 28 13 11 0.02

Emergency room visit

in the past year

46 71 43 29 <0.0001

Night awakenings 37 49 39 24 0.01

Asthma management

On reliever medication 90 95 91 87 0.31

On controller medication 44 45 47 39 0.49

Never miss medication* 35 44 33 30

Sometimes miss medication* 50 44 55 44 0.44

Often miss medication* 16 12 13 26

Reliever + control vs.

Reliever only†

48 48 50 42 0.55

Ability to manage asthma‡ 62 48 62 74 0.01

*Percentages based on 107 children on controller medication.

†Based on a sample size of 221 children on medication.

‡Based on the CHE’s evaluation using the Asthma Ability Form.

Values in bold are statistically significant, p< .05.


Indoor triggers and asthma morbidity Banda et al.

explained by their potentially spending a greater proportion of

time at home. In a recent study of USA children, those of

preschool age were shown to spend less time outdoors

than previous generations (28). Associations with dampness,

Table 2 Environmental characteristics by age group (n = 246)

Environmental factors

All ages (n = 246) Ages 0–4 (n = 58) Ages 5–11 (n = 118) Ages ≥12 (n = 70)Chi-square

p-value% Exposed % Exposed % Exposed % Exposed

Home triggers*

Smoke 39 38 42 34 0.54

Dampness‡ 31 26 31 36 0.49

Mold 49 41 46 61 0.05

Holes§ 40 40 39 42 0.92

Cockroaches 20 21 20 17 0.84

Rodents 30 22 31 36 0.26

Furry pets 30 22 32 31 0.37

Plants 26 16 34 21 0.02

Carpet anywhere in home 51 59 52 44 0.27

Carpet in bedroom 40 47 39 37 0.52

Clutter in bedroom 69 64 66 77 0.19

Dusty/dirty surfaces 61 72 56 61 0.11

Peeling wallpaper/flaking paint¶ 31 17 38 31 0.02

>2 people per bedroom 44 51 41 43 0.48

Pet sleeps in bedroom 7 9 5 9 0.56

Rents 53 66 50 49 0.10

Eating in bedroom 29 33 28 30 0.73

Sum of home triggers**

0–3 31 36 31 26

4–5 31 40 25 36 0.07

>6 38 24 44 39

Sum of bedroom triggers††

0 11 16 10 10

1 24 16 30 20

2 24 26 24 23 0.38

3 21 21 15 31

≥4 20 22 21 16

Classroom triggers‡‡

Pets 3 3 4 0 0.30†

Plants/aquariums 10 7 14 6 0.13

Mold/mildew 3 0 4 1 0.17†

Roaches 2 0 3 3 0.43†

Carpet 14 16 17 7 0.19

Water damage 2 0 4 1 0.28†

Rodents 6 2 7 9 0.23†

Smokers 4 3 4 4 0.94†

Sum of school triggers dichotomized§§

0 76 79 70 84 0.08

≥1 24 21 30 16

*Percentages based on sample sizes of 241–246.

†Indicates 33% or 50% of cells have count <5; chi-square may not be valid test.

‡Dampness: signs of leaks in ceilings or walls and/or signs of water leaks in the bathroom, kitchen or any other room with water.

§Holes: Holes in the walls or floors and/or space between the wall and baseboard.

¶Also includes falling plaster anywhere in the home.

**Sum of home triggers: smoke, holes, dampness, mold, carpeting anywhere in the home, plants, furry pets, cockroaches, rodents, clutter in

the bedroom, and peeling wallpaper/flaking paint.

††Sum of bedroom triggers: clutter, food eaten in child’s bedroom area, live plants, wall-to-wall carpet, dusty/dirty surfaces, peeling wallpaper/

flaking paint, and holes.

‡‡Based on a sample size of 237.

§§Sum of school triggers: pets, plants/aquariums, mold/mildew, roaches, carpet, water damage, rodents, and smokers.

Values in bold are statistically significant, p< .05.



cockroaches, and rodents are consistent with findings from

previous studies (8–10, 12). In age-stratified analyses,more home

triggers were found to be associated with asthma hospitalization

in the youngest two age groups, whereas classroom triggers were

associated in the older two age groups indicating the importance

of targeting areas or spaces highly used by children when

performing environmental interventions. This is supported by

previous studies demonstrating reductions in levels of cockroach

allergen and dust mite allergens in the bedroom as being

significantly correlatedwith a decrease in asthmamorbidity (15).

When associations of individual environmental factors with

other morbidity measures (ED visits and night symptoms) were

examined, fewer factors appeared to be significant. The lack of

association between environmental factors and ED visits is not

surprising as ED visits are not necessarily indicative of asthma

severity for our population. Our study population makes high

use of the ED as demonstrated by the number of children

visiting the emergency room in the past year (46%); frequently,

at baseline the ED was used as the regular care office for the

child’s asthma.

A new finding in our study was the association between

individual classroom triggers and hospitalizations, ED visits

and night symptoms, predominantly in children aged 5 yr and

older. Only two factors were analyzed individually (plants

and/or aquarium and carpet) because they were more

prevalent (roughly 10% of children were exposed to each of

Table 3 Associations of indoor environmental triggers with asthma hospitalizations in the past year by age group* (n = 246)


All ages (n = 246) Ages 0–4† (n = 58) Ages 5–11 (n = 118) Ages ≥12 (n = 70)

OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)

Home triggers‡

Smoke 0.58 (0.21, 1.59) 1.36 (0.39, 4.80) 0.39 (0.08, 1.81) 0.21 (0.02, 1.86)

Dampness 1.07 (0.44, 2.60) 5.35 (1.27, 22.46) 0.32 (0.07, 1.50) 1.11 (0.18, 6.91)

Mold 2.36 (0.95, 5.85) 4.14 (1.19, 14.45) 2.62 (0.72, 9.58) 2.06 (0.32, 13.41)

Holes 3.02 (1.20, 7.56) 3.60 (1.06,12.21) 1.63 (0.41, 6.55) 12.43 (1.35, 114.24)

Cockroaches 1.10 (0.44, 2.73) 5.92 (1.34, 26.20) 0.56 (0.11, 2.87) NE§

Rodents 2.25 (0.77, 6.53) 7.39 (1.68, 32.58) 1.50 (0.33, 6.87) 3.50 (0.58, 21.10)

Furry pets 0.89 (0.37, 2.15) 1.32 (0.31, 5.51) 0.69 (0.18, 2.70) 1.35 (0.23, 7.88)

Plants 0.59 (0.23, 1.51) 3.24 (0.62, 16.86) 0.12 (0.01, 0.98) 1.26 (0.20, 8.09)

Carpet anywhere in home 0.54 (0.22, 1.36) 0.78 (0.23, 2.63) 0.30 (0.08, 1.10) 0.38 (0.06, 2.33)

Carpet in bedroom 2.21 (0.88, 5.54) 0.81 (0.24, 2.66) 10.95 (1.43, 84.00) 4.80 (0.47, 49.27)

Clutter in bedroom 1.64 (0.62, 4.32) 6.83 (0.93, 49.96) 1.05 (0.28, 4.00) 0.87 (0.13, 5.89)

Dusty/dirty surfaces 1.27 (0.33, 4.87) 3.79 (0.68, 21.15) 0.90 (0.22, 3.64) 0.57 (0.08, 3.94)

Peeling wallpaper/flaking paint 1.58 (0.46, 5.45) 1.29 (0.27, 6.13) 2.10 (0.51, 8.55) 2.94 (0.40, 21.59)

>2 people per bedroom 2.21 (0.87, 5.64) 1.11 (0.32, 3.82) 7.48 (1.87, 29.91) 0.77 (0.08, 7.50)

Pet sleeps in bedroom 1.60 (0.51, 5.03) 5.00 (0.66, 37.93) 1.27 (0.12, 13.10) NE§

Rents 1.13 (0.44, 2.87) 0.43 (0.11, 1.66) 1.56 (0.43, 5.63) 1.07 (0.16, 7.08)

Eating in bedroom 1.84 (0.73, 4.66) 2.79 (0.84, 9.27) 0.94 (0.25, 3.52) 2.62 (0.38, 17.94)

Sum of home triggers

0–3 Reference Reference Reference Reference

4–5 5.75 (1.71, 19.32) 11.01 (1.06, 114.00) 3.15 (0.67, 14.88) NE§

≥6 2.16 (0.77, 6.07) 52.42 (3.74, 735.62) 0.51 (0.11, 2.29) NE§

p for trend 0.23 0.001 0.25 0.98

Sum of bedroom triggers

0 Reference Reference Reference Reference

1 1.07 (0.17, 6.67) 2.01 (0.12, 34.51) 0.32 (0.05, 2.15) NE§

2 0.51 (0.14, 1.90) 1.79 (0.13, 23.79) 0.15 (0.02, 0.94) NE§

3 1.06 (0.30, 3.78) 3.75 (0.29, 48.32) 0.38 (0.07, 2.06) NE§

≥4 0.77 (0.20, 2.98) 6.98 (0.58, 83.51) 0.08 (0.01, 0.69) NE§

p for trend 0.79 0.07 0.08 0.39

Classroom triggers¶

≥1 vs. 0 triggers 2.07 (0.57, 7.47) 1.70 (0.35, 8.28) 2.19 (0.54, 8.91) 4.87 (0.49, 48.65)

Plants/aquariums 7.05 (1.49, 33.40) 19.06 (1.56, 232.31) 5.71 (1.05, 30.90) 48.39 (2.57, 910.50)

Carpet 4.69 (1.41, 15.66) 3.43 (0.60, 19.61) 4.27 (1.21, 15.00) 21.67 (1.62, 289.16)

*Odds ratios adjusted for sex and clustering of children in families.

†Adjusted for daycare.

‡Based on sample sizes of 241–246.

§Could not be estimated.

¶Based on sample size of 237.

Values in bold are statistically significant.



these factors). Having one or more trigger in the classroom

increased the likelihood of children aged 5–11 yr to experience

disturbed sleep. Having plants and/or aquariums in the

classroom increased the likelihood of children in all age

groups to be hospitalized and children ≥12 yr old to have

disturbed sleep. Carpeting in the classroom was also associ-

ated with all three asthma outcomes among children aged

5–11 and with hospitalizations among those ≥12 yr of age.

These findings suggest that environmental asthma interven-

tions should not only focus in the home, but also in schools,

which have been identified as a major source of allergen

exposure that could possibly contribute to disease exacerba-

tion and where children spend a large amount of time (24).

Recent scientific literature includes few studies evaluating the

relationship between asthma outcomes and indoor allergen

exposures in schools and daycare environments (29). More

research in this area is needed.

Our findings have several limitations. First, the design of this

investigation was cross-sectional. Thus, no temporal relation-

ship between indoor exposures and asthma could be estab-

lished. Second, outcomes were determined by parental report

rather than through symptom diaries or by review of medical

records. Bias in reporting of night awakenings may differ by

age group, as parents may be more aware of sleep disturbances

Table 4 Associations of indoor environmental triggers with ED visits in the past year by age group* (n = 246)




Home triggers‡

Smoke 0.89 (0.50, 1.62) 0.82 (0.26, 2.59) 1.11 (0.50, 2.42) 0.44 (0.15, 1.30)

Dampness 0.99 (0.52, 1.87) 3.80 (0.67, 21.72) 0.68 (0.29, 1.57) 1.41 (0.46, 4.28)

Mold 0.92 (0.51, 1.67) 1.01 (0.29, 3.54) 0.79 (0.36, 1.74) 2.51 (0.80, 7.90)

Holes 0.95 (0.50, 1.77) 0.44 (0.12, 1.58) 0.88 (0.39, 1.99) 2.13 (0.70, 6.49)

Cockroaches 1.27 (0.63, 2.55) 0.79 (0.20, 3.17) 2.14 (0.87, 5.30) 0.44 (0.09, 2.08)

Rodents 0.91 (0.45, 1.84) 0.57 (0.15, 2.17) 1.13 (0.48, 2.65) 1.30 (0.39, 4.33)

Furry pets 0.88 (0.48, 1.64) 0.93 (0.22, 3.98) 0.87 (0.38, 1.95) 1.22 (0.39, 3.82)

Plants 0.59 (0.32, 1.08) 1.62 (0.27, 9.70) 0.29 (0.12, 0.67) 1.98 (0.67, 5.85)







Pet sleeps in bedroom 0.78 (0.25, 2.46) 0.59 (0.09, 4.07) 1.17 (0.17, 8.29) 0.44 (0.04, 4.49)

Rents 1.07 (0.60, 1.92) 0.25 (0.05, 1.20) 1.38 (0.65, 2.93) 0.83 (0.26, 2.60)




4–5 1.94 (0.92, 4.10) 1.42 (0.34, 5.97) 1.26 (0.46, 3.48) 19.06 (2.17, 167.13)

≥6 0.84 (0.44, 1.61) 1.26 (0.29, 5.56) 0.69 (0.29, 1.61) 4.94 (0.57, 43.18)

p for trend 0.51 0.72 0.35 0.31



1 0.81 (0.26, 2.47) 0.22 (0.02, 2.10) 0.57 (0.15, 2.12) NE§

2 0.83 (0.32, 2.18) 0.55 (0.07, 4.13) 0.72 (0.20, 2.51) NE§

3 0.77 (0.29, 2.07) 0.54 (0.06, 4.53) 0.41 (0.09, 1.84) NE§

4 0.82 (0.27, 2.43) 3.41 (0.28, 41.77) 0.27 (0.07, 1.04) NE§

p for trend 0.78 0.17 0.06 NE

Classroom triggers¶

≥1 vs. 0 triggers 1.43 (0.65, 3.14) 1.33 (0.31, 5.72) 1.65 (0.69, 3.94) 1.03 (0.12, 9.02)


Carpet 3.82 (1.49, 9.78) 4.26 (0.43, 42.73) 3.41 (1.19, 9.75) 4.81 (0.39, 58.59)

*Odds ratios adjusted for sex and clustering of children in families.



§Could not be estimated.

¶Based on a sample size of 237.




in younger children and children were not always present at

interviews. Parental underreporting of their children’s asthma

symptoms and asthma triggers has been documented (30). The

presence of classroom triggers was also not confirmed. Use of

multiple school rooms and probably different exposures among

rooms in children ≥12 yr of age could not be accounted for,

decreasing the precision of our exposure estimates. Third, other

etiologic factors of asthma that could be confounders were not

assessed including history of viral infection (although correct-

ing for seasonality might have partially controlled for the

effects of viral infection on night symptoms) and atopic

allergies. Fourth, our small sample size yielded estimates with

wide confidence intervals underscoring the importance of

future studies with larger sample sizes.

Examining the age–specific relationships of environmental

exposures with asthma exacerbations and hospitalizations

warrants further study. Despite these limitations, our findings

highlight the importance of assessing exposure to classroom, as

well as home environmental triggers. If confirmed by other

studies, differences seen among age groups could support

specific intervention strategies aimed at decreasing asthma

morbidity in high-risk populations.

Acknowledgments

We would like to acknowledge the Englewood and West

Englewood communities for their participation, and the many

community andmedical partners thatmade this project possible.

Table 5 Associations of indoor environmental triggers with >2 asthma night awakenings in the past month by age group* (n = 246)




Home triggers‡

Smoke 1.49 (0.76, 2.95) 0.92 (0.29, 2.90) 2.13 (0.84, 5.42) 1.03 (0.30, 3.53)

Dampness 0.50 (0.25, 1.03) 2.49 (0.65, 9.51) 0.27 (0.10, 0.75) 0.51 (0.13, 1.92)

Mold 0.68 (0.34, 1.37) 1.00 (0.31, 3.21) 0.67 (0.29, 1.56) 0.77 (0.19, 3.16)

Holes 2.29 (1.18, 4.44) 3.17 (0.95, 10.52) 2.35 (0.97, 5.67) 3.22 (0.92 11.32)

Cockroaches 2.32 (1.15, 4.68) 4.00 (0.83, 19.25) 1.99 (0.73, 5.37) 2.31 (0.68, 7.83)

Rodents 1.18 (0.54, 2.61) 0.56 (0.12, 2.56) 2.27 (0.87, 5.89) 1.04 (0.24, 4.47)

Furry pets 1.45 (0.73, 2.90) 2.26 (0.55, 9.26) 1.58 (0.64, 3.90) 0.98 (0.31, 3.08)

Plants 1.02 (0.52, 2.02) 0.68 (0.14, 3.33) 1.11 (0.46, 2.64) 0.99 (0.25, 3.92)







Pet sleeps in bedroom 0.96 (0.25, 3.68) 0.63 (0.08, 5.04) 2.05 (0.35, 11.92) 0.42 (0.04, 4.28)

Rents 1.21 (0.64, 2.29) 0.96 (0.28, 3.27) 1.58 (0.69, 3.61) 0.78 (0.21, 2.83)




4–5 2.13 (0.92, 4.91) 2.12 (0.63, 7.12) 1.65 (0.52, 5.28) 4.67 (0.71, 30.88)

≥6 1.34 (0.64, 2.78) 2.14 (0.46, 9.94) 1.42 (0.55, 3.63) 1.31 (0.18, 9.57)

p for trend 0.50 0.27 0.50 0.87



1 1.45 (0.51, 4.13) 4.13 (0.49, 34.99) 0.76 (0.19, 3.01) 3.03 (0.19, 47.59)

2 1.14 (0.45, 2.90) 3.62 (0.66, 19.83) 0.55 (0.14, 2.17) 1.07 (0.08, 14.79)

3 1.18 (0.47, 2.97) 2.46 (0.43, 14.17) 1.47 (0.34, 6.35) 1.06 (0.10, 10.76)

≥4 0.58 (0.18, 1.81) 0.92 (0.16, 5.46) 0.25 (0.04, 1.50) 1.80 (0.14, 23.26)

p for trend 0.21 0.57 0.20 0.76

Classroom triggers§

≥1 vs. 0 triggers 2.40 (1.06, 5.43) 1.05 (0.31, 3.59) 3.08 (1.13, 8.44) 4.39 (0.74, 25.97)


Carpet 3.36 (1.22, 9.24) 1.33 (0.32, 5.54) 3.65 (1.20, 11.13) 11.12 (0.58, 212.00)

*Odds ratios adjusted for sex, season, and clustering of children in families.



§Based on a sample size of 235 children.




Funding

Funding for this project included grants from the Merck

Childhood Asthma Network, Inc. (MCAN) funded by the

MerckCompanyFoundation and theLloydA.FryFoundation.

Conflict of Interest

No conflict of interest declared.

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