Sleep Breath (2008) 12:381–392
DOI 10.1007/s11325-008-0174-x
ORIGINAL ARTICLE
Obstructive sleep apnea and history of asthma
in snoring children
Maya Ramagopal & Steven M. Scharf &
Darryl W. Roberts & Carol J. Blaisdell
Received: 10 September 2007 / Revised: 4 February 2008 / Accepted: 6 February 2008 / Published online: 18 April 2008
# The Author(s) 2008
Abstract Asthma has been identified as a possible risk
factor for Obstructive Sleep Apnea (OSA) in children. It is
not known whether parent-reported asthma increases the
likelihood of the diagnosis of OSA in snoring children. We
hypothesized that snoring children with asthma are more
likely to have OSA than snoring children without asthma.
This study is a 1-year retrospective review of polysomnogram and questionnaire data collected on 236 patients
referred to the University of Maryland Pediatric Sleep
laboratory for evaluation of snoring. Of the 236 patients,
58% (137/236) were boys, and 79% (173/219 reporting
race) were African-American (AA). The age at referral was
7.2±3.7 years (mean±S.D.). Mean body mass index (BMI)
M. Ramagopal
Division of Pulmonary Medicine and Cystic Fibrosis Center,
Department of Pediatrics, University of Medicine & Dentistry
of New Jersey-Robert Wood Johnson Medical School,
New Brunswick, NJ, USA
S. M. Scharf
Sleep Disorders Center, Division of Pulmonology
and Critical Care, University of Maryland School of Medicine,
Baltimore, MD, USA
D. W. Roberts
Department of Organizational Systems and Adult Health,
University of Maryland School of Nursing,
Baltimore, MD, USA
C. J. Blaisdell
Division of Pediatric Pulmonology and Allergy,
University of Maryland School of Medicine,
Baltimore, MD, USA
M. Ramagopal (*)
Division of Pulmonary Medicine and Cystic Fibrosis Center,
89 French Street,
New Brunswick, NJ 08901, USA
e-mail:
[email protected]
percentile was 73.4±32.3%, with 43.2% (54/125) >95th
percentile. A history of asthma was reported by 31.4% (74/
236); no subject was symptomatic on the night of the study.
We found no increased risk for polysomnographically diagnosed OSA for asthmatics. To the contrary, by logistic regression analysis, a parent/guardian report of asthma decreased
the odds of having OSA by 34% (p=0.027), controlling for
individual and socioeconomic factors and assessment results.
Polysomnographic (PSG) differences between asthmatic and
non-asthmatic children were found in only the arousal index
(11.0 vs.9.3±6.5/h, p=0.099) and total sleep time (337.1±
64.3 vs. 347±65.2 min, p=0.1) In a referral-based group of
predominantly AA inner-city snoring children, asymptomatic
asthma decreased the likelihood of OSA.
Keywords African-American . Snoring . OSA . Asthma .
Polysomnogram
Introduction
Obstructive sleep apnea (OSA) refers to the occurrence of
repetitive episodes of complete or partial upper airway
obstruction during sleep, and affects 1–3% of children in
the US [1].OSA and primary snoring (PS) can be
considered on a continuum, from infrequent partial sleeprelated upper airway obstruction without significant hypoxemia or hypercarbia (PS) to apnea with hypoxemia and
carbon dioxide retention [2]. Sleep disturbances as a
consequence of nocturnal asthma have been reported in
children [3], but there is only a small body of literature
describing polysomnographic (PSG) features in asthma.
Respiratory illnesses such as asthma, which affects 7.5–
10% of American children, and atopy are reported to be risk
factors for the development of OSA [4–6].
382
While OSA and asthma are considered separate diagnoses, some have suggested that they may in fact be associated.
The pathophysiology of these disorders likely overlap, given
that both are affected by inflammation, neural input, and
anatomic factors such as obesity [5]. Nocturnal asthma may
cause sleep disruption and/or poor quality sleep; unstable
asthma treated with oral corticosteroids may increase the risk
of OSA [7]. Snoring and noisy breathing are the hallmarks of
OSA in children and are also recognized as common
complaints of children with asthma [8]. These symptoms
are common reasons for referral for PSG evaluation.
The primary aim of this study is to determine whether
there is an association between OSA and asthma in
pediatric patients referred for PSG for nocturnal snoring.
We hypothesized that asthma, as reported on a medical
history questionnaire obtained on the night of study would
increase the likelihood of OSA. In addition, we expected to
find differences in sleep architecture and physiological
parameters between asthmatic and non-asthmatic snorers.
Materials and methods
Study sample
Data were obtained from a 1-year (July 2003 to June 2004)
retrospective review of clinical charts and overnight PSG
results of patients referred to the pediatric sleep laboratory
at the University of Maryland for evaluation of obstructive
sleep apnea with a chief complaint of snoring. The
Institutional Review Board at the University of Maryland
approved this study and granted an “exempt protocol”
status for the chart review.
Charts and PSG results on 236 patients between the ages
of 2 and 15 years were reviewed. Current symptom and
history data were obtained from a questionnaire that was
completed by the adult caregiver accompanying the child
on the night of the study. The questionnaire included patient
demographics, the patient’s past medical history (including
asthma), medication use, sleep, and daytime behaviors.
Asthma case definition was determined by an answer of
“yes” asthma (item 1), as a listed diagnosis (item 2), or
asthma related medication use (item 3, General Medical
Information—Appendix) as previously used in Baltimore
children [9]. Medical insurance information was available
from hospital intake data. We did not directly collect data
on household income or other indices of socioeconomic
status. As reported by other authors, we used median
household incomes from the zip code of the patients’
residence using US government census information for the
year 2000 as an indirect estimation of socioeconomic status
[10, 11]. In addition, we coded zip codes falling within the
Baltimore Metropolitan Statistical Area as urban.
Sleep Breath (2008) 12:381–392
Only children aged 2 to 15 years, referred to the sleep
laboratory for diagnostic studies for the chief complaint of
snoring, were included in this study. Even though our
laboratory studies patients up to 21 years of age, we chose
the age group of 2–15 for analysis to maintain consistency
in the application of pediatric criteria for the diagnosis of
OSA. Those referred for oxygen, continuous or bilevel
positive airway pressure titration, or evaluation of parasomnias were excluded from the analysis. The pediatric
sleep laboratory at the University of Maryland serves
largely an inner-city population.
Standard overnight monitoring was accomplished with the
Alice 4 diagnostic system (Respironics, Murrysville, PA,
USA). The patient slept in a quiet darkened room up to 7 h
with a parent or guardian present. The montage included EEG
leads O1A2, O2A1, C1A2, C2A1, LOC, ROC, submentalis
EMG, EKG, measurements of airflow (oronasal thermistor)
and end tidal CO2 (ETCO2), chest and abdominal impedance
using strain gauges, and oxyhemoglobin saturation using a
Nellcor pulse oximeter. Respiratory events were described
as: 1) obstructive apneas, with cessations of airflow with
continued thoracic and/or abdominal respiratory effort lasting
two respiratory cycles in duration; or 2) hypopneas, with
reductions of airflow >50% associated with ≥4% fall in
oxygen saturation or post-event arousal [12]. The severity of
OSA was defined by the apnea–hypopnea index (AHI;
number of obstructive apneas and hypopneas per hour of
sleep). The arousal index included respiratory and nonrespiratory arousals per hour of sleep. Baseline and nadir
oxyhemoglobin saturation, baseline and peak ETCO2 in
addition to sleep stage were recorded. No patient was acutely
ill on the night of the study. Polysomnographic scoring was
performed in 30-s epochs according to the Rechtshaffen–
Kales criteria [13] by the same technician and reviewed by
one of two pulmonologists.
When the height and weight were obtained at the time of
the overnight PSG, we were able to calculate the body mass
index (BMI) based on the Center for Disease Control
nutrition and activity website and is expressed in kg/m2
[14]. BMI percentile was calculated to represent 5th–95th
percentile as “normal” and >95th as “overweight” [15].
OSA is defined as an obstructive AHI of five or more
events per hour and/or an obstructive apnea index of one or
more events per hour [16, 17]. For the purposes of this
paper, OSA was defined as AHI>2.
Analysis
Data were analyzed using Stata/SE for Windows (StataCorp.
2005. Stata Statistical Software: Release 9.2. College
Station, TX, USA: StataCorp LP). Data were compiled and
where appropriate, expressed as mean±SD when data were
normally distributed (as identified using the Stata command
Sleep Breath (2008) 12:381–392
“sktest” [18], group differences between the means were
assessed using the two sample t test. However, when data
were non-normally distributed, differences between group
medians were compared using the Mann–Whitney U test,
and are so indicated. In addition, some data were prepared
using dichotomous valuations, in which cases chi-square
testing was used. Logistic regression was performed to
ascertain predictors of OSA controlling for known risk
factors such as age, gender, BMI, ethnicity, medical
insurance status, and median income for zip code. Differences in OSA prevalences were compared using chi-square.
We are unaware of published consensus guidelines for OSA
severity in children; therefore, the AHI severity levels used
were our best clinical judgment. For some analyses, where
indicated, we analyzed data using different definitions of
“positive” for OSA: an AHI of >2, or >5 as there is no
agreement among clinicians which threshold to use.
Due to the preliminary and clinical nature of the study, in
which a type II or beta error is less troublesome and can
generate further hypotheses and research questions, we relaxed our assumptions of significance to reject the null hypothesis at the 10% level. In future investigations on this
population, the knowledge generated from this preliminary
study will permit us to recruit larger samples, therefore permitting us to use more rigorous assumptions of significance.
Results
Clinical characteristics
The average age of the cohort was 7.18±3.74 years (mean±
SD), with most of the children <11 years old (n=190 or
80.5%). There were more boys (n=137 or 58%) than girls.
Ethnicity data was available on 219 subjects, with the
majority being African-American (n=173 or 79%), followed
by Caucasians (n=39 or 17.8%). Hispanics and Asians were
minimally represented (2.3% and 0.9%, respectively). This
reflects the socio-demographic profile of Baltimore City in
which 20% of the population is between 5 and 17 years and
90% of these children are African-American [19]. The
median household income estimated from zip codes and
census data was $36, 661±$15,669. Most of the children in
this study were on medical assistance (n=171, 72.5%),
showing that they came from households in the lowerincome brackets.
Because height was not consistently measured on all
subjects on the night of the PSG, BMI was calculated on 124
subjects only. The mean BMI was 22.4±8.27 kg/m2, and the
mean BMI percentile was 74.3±31.7. Most of the children
(71/125 or 56.8%) had BMI calculated at <95th percentile.
The remaining 54 children were overweight. Weight was
available on 207 subjects; the mean was 79.6±55.2 kg.
383
Asthma was reported by 74 (31.4%) of the caregivers.
Table 1 shows the comparison of asthmatic and nonasthmatic subjects with respect to gender, race, AHI, BMI
percentile, median household income by zip code, and
insurance status. There were no significant differences in
any demographic variable between asthmatics and nonasthmatics. Of the 41 subjects with asthma on whom we
could calculate BMI, 20 were obese.
Whether OSA was defined as an AHI >2 or >5 there
were no significant differences in OSA prevalence for
asthmatics compared to non-asthmatics in bivariate analyses. PSG findings with an AHI<2 was diagnosed in 139/
236 (58.9%) of all subjects (Table 2). The levels of severity
that were analyzed were AHI <2, 2≤5, 5–10, and >10.)
OSA, described as AHI ≥2 was diagnosed in 97/236
(41.1%) of all snorers referred for a PSG. AHI 2–4.9 was
identified in 36 (15.3%), and AHI>5 was seen in 61
subjects. While we hypothesized that asthma would
increase the severity of OSA, the distribution of OSA
severity was not significantly different between asthmatics
and non-asthmatics in the bivariate analyses (data not
shown, p=0.622). Please refer to Table 3 for a listing and
description of all variables used for analysis.
However, in logistic regressions that included several
PSG results as further independent variables and controlled
for individual factors and socioeconomic factors (Table 4), we
found that reported asthma significantly decreased the odds
of OSA (OR [odds ratio] 0.399, 0.160–0.994, p=0.040).
In bivariate analysis, African-American children were
significantly more likely to have OSA (chi-square 13.05,
p<0.0001), but were no more likely to have asthma (chisquare 0.097, p=0.76). Because this sample is primarily
African-American, it was possible that this finding is
artifactual (data not shown). We explored the relationship
between race and OSA further in the aforementioned
Table 1 Clinical characteristics of asthmatics and non-asthmatics
Variable
Asthma
(N=74)
N (column %)
Non-asthma
(N=162)
Boys, N (%)
African-American, N (%)
BMI >95th percentile
Weight for age >95th
percentile
Private Insurance
43
53
20
25
(58.1%)
(71.6%)
(27.0%)
(33.8%)
94 (58.0%)
120 (74.1%)
34 (21.0%)
48 (29.6%)
20 (27.0%)
x ± SD
7.5±3.6
6.9±14.9
76.9±31.6
37,889±16,635
45 (27.8%)
Age (years±SD)
AHI (mean±SD)
BMI percentile (±SD)
Estimated median
household income ($)
All NS
7.0±3.8
4.2±6.4
71.7±32.6
36,154±15,416
384
Sleep Breath (2008) 12:381–392
Table 2 Distribution of OSA severity and asthma
Table 4 Predictors of OSA
AHI
Asthma
Non-asthma
Total
OSA
Odds
ratio
P>|Z|
95% CI
<2
2–4.9
>5
Total
N (column %)
44 (59.5%)
9 (12.1%)
21 (28.4%)
74
95 (58.6%)
27 (16.7%)
40 (24.7%)
162
139 (58.9%)
36 (15.3%)
61 (25.9%)
236
Asthma reported by
parent/guardian*
Baseline ETCO2 (torr)
Peak ETCO2 (torr)
Baseline SaO2%**
Nadir SaO2%**
T90 (minutes)
boy
African- American**
ages 6–10
ages 11–15
weight for age <95%ile
Private insurance
Living in urban area
Median income for
zip code*
0.3993
0.048
0.1604
0.9939
0.8825
1.1525
1.3170
0.9145
1.1436
1.3534
2.8500
0.8803
1.2031
0.6877
0.3688
1.0000
0.3993
0.266
0.112
0.095
0.063
0.230
0.460
0.056
0.786
0.742
0.474
0.203
0.275
0.048
0.7081
0.9674
0.9530
0.8321
0.9184
0.6068
0.9717
0.3510
0.4004
0.2469
0.0794
0.9999
0.1604
1.0999
1.3732
1.8199
1.0050
1.4240
3.0187
8.3588
2.2079
3.6148
1.9152
1.7134
1.0000
0.9939
P=0.622
logistic regression. In this regression, we found that
African-American children have 2.85 times higher odds of
OSA. (Table 4, p=0.056).. Likewise, children on medical
assistance were at increased odds of OSA compared to
those with private insurance in the bivariate analysis (chisquare 4.68, p=0.031), but that finding was not supported
in the logistic regression. The AHI was lower in the
African-American group, but the difference was not
significant 3.3 vs.5.7 obstructive events/hour, p=0.14). In
bivariate analysis, African-Americans were significantly
more likely to have an AHI>5 (chi-square 5.40, p=0.02) or
to have an AHI>2 (chi-square 20.06, p<0.0001).
Sleep disruption can be a manifestation of nocturnal
asthma. We investigated parameters of sleep fragmentation
for children with and without asthma by polysomnography.
Table 3 Variable identification and range
Variable name
Value
range
Independent/dependent variables
OSA
Asthma
PSG results
Baseline ETCO2 (torr)
Peak ETCO2 (torr)
Baseline SaO2%
Nadir SaO2%
T90 (minutes)
Individual factors
Boy
African- American
Age group
Weight between 5th
& 95th percentile
Socioeconomic factors
Private insurance
Living in urban area
Median income for
zip code
0–1
0–1
23–52
35–71
88–100
31–97
0–205
Level
Dichotomous
Dichotomous
Continuous
Continuous
Continuous
Continuous
Continuous
Logistic regression: Log likelihood=−79.7200404; number of obs =
156 (decreased observations are due to missing data); LR chi2 (15)=
48.44; Prob >chi2 =0.0000; pseudo R2 =0.2330
*Significant at p≤0.05
**Significant at p≤0.10
Total sleep time was significantly decreased in asthmatics at
333±64 min vs. 347±65 min for non-asthmatics (Mann–
Whitney U, z=1.656, p=0.10). Asthmatics had an increased
arousal index (11.3±7.4) compared to non-asthmatics (9.3±
6.4, p=0.099), with no difference in slow wave sleep as a
percentage of total sleep time (SWS/TST%), rapid eye
movement as a percentage of total sleep time (REM/TST
%), sleep efficiency (time asleep as a percentage of total
sleep time), or physiological measurements such as baseline
and nadir oxyhemoglobin saturation (SaO2%), exhaled
carbon dioxide (ETCO2), or time spent with oxyhemoglobin saturations <90% (T90).
Discussion
0–1
0–1
1–4
0–1
0–1
0–1
6,148–03,879
Dichotomous
Dichotomous
Categorical
(1=1–5 yrs, 2=
6–10 yrs,
3=11–14 yrs,
4≥15 yrs)
Dichotomous
Dichotomous
Dichotomous
Continuous
The main finding in this study is that a history of asthma
reported by a snoring child’s guardian decreases the
likelihood of OSA, but is associated with mild sleep
disturbance. This finding actually was opposite to what
we originally postulated. Surprisingly, there was no major
difference between asthmatics and non-asthmatics in
parameters that would suggest poor sleep. In the ensuing
discussion, we review these findings in light of the
currently available literature.
Snoring and noisy breathing are recognized as common
symptoms in pediatric patients with asthma [8]. In this
regard, several theories have been proposed to explain why
Sleep Breath (2008) 12:381–392
upper airway abnormalities might constitute a risk for
asthma or vice versa. OSA and asthma share risk factors
such as allergic rhinitis, gastroesophageal reflux, and
obesity [20, 21]. In addition, similar cytokine, chemokine,
and histologic changes are seen in both OSA and asthma
[22]. Abnormalities of the nasopharynx and lower airways
may co-exist due to similar airway responses to inflammatory or atopic stimuli [20]. Sleep deprivation, chronic upper
airway edema, and inflammation associated with OSA may
further exacerbate nocturnal asthma symptoms [22, 23].
The “one airway” hypothesis suggests that upper airway
inflammation and intermittent hypoxia from obstruction
may influence the expression and severity of disease of the
lower respiratory tract [24]. CPAP treatment of OSA
improves asthma control in adults, particularly nocturnal
attacks [25] and bronchial hyperresponsiveness [26].
Tonsillectomy and/or adenoidectomy (T&A), rather than
CPAP, is the first line of treatment in pediatric OSA and is
curative in 75–100% of the cases [5]. It is not known if
treatment of OSA changes the course of asthma in pediatric
populations.
In spite of the above rationale, self-reported asthma was
actually inversely correlated with the likelihood of OSA
although not with severity. We speculate that this surprising
finding is due to a referral bias. It is likely that parents of a
child diagnosed with asthma are more vigilant regarding
nighttime symptoms and/or are referred more often due to
increased interactions with medical professionals. Since
asthma symptoms are often worse at night, noisy breathing
may have been mistaken for snoring, prompting a referral
for a sleep study. In other words, self-reported asthma
predicted a lower likelihood of having OSA. We do not
have a biologically plausible explanation for this. We
speculate that our unexpected finding is a result of parents
and caregivers of asthmatic children being more vigilant to
nocturnal symptoms. Since both asthma and OSA can have
overlapping nocturnal symptoms, there may be some
reporting bias on the part of parents, who might choose to
“over” report the presence of asthma in children who snore.
We did not perform objective assessments of airways
obstruction or bronchial hyperreactivity in this retrospective
analysis. Finally, we did not evaluate atopy in this cohort,
which could predispose to both asthma and OSA. However,
to determine if there is a positive relationship between
asthma and OSA, a population-based study would need to
be performed.
Thirty-three percent of children in this study had
guardian-reported asthma, which is three times the national
prevalence rate of 10% [9, 28] and statewide asthma
prevalence of 10.6% [29]. This rate is also higher than the
20% asthma prevalence rate in some inner-city Baltimore
schools for children from the same catchment area [9]. Data
were obtained from a clinical questionnaire that was not
385
validated at the time of this study. However, the majority of
the clinical questions were similar to that used in the BASS
questionnaire, which is a 50-item validated questionnaire
for OSA screening in children [27]. Asthma “yes” as a
listed diagnosis on school emergency forms, albuterol or
inhaled steroid was a method used in a previous study for
case definition of asthma in Baltimore children [9].
Body mass index percentiles of participants in this study
revealed that more than 40% were obese with a BMI >95th
percentile, which may have influenced the high prevalence
of asthma in this snoring cohort. The Cleveland Children’s
Sleep and Health Study found that there was a 1.89-fold
increased risk of wheeze, but not asthma in 8- to 11-yearold inner city children with sleep disordered breathing
(snoring with or without OSA) [15] and that sleep
disordered breathing might explain in part the relationship
between obesity and asthma.
Asthma and OSA have common risk factors such as
African-American ethnicity, obesity, atopy, and poor socioeconomic status [8, 20, 30, 31]. Consistent with the
literature [5, 6, 21, 32] we found that African-American
children were 3.13 times more likely to have OSA and 4.9
times more likely to have asthma than other children. There
was also an increased risk of OSA in children on medical
assistance compared to those with private insurance. Low
SES, severe neighborhood disadvantage, and neighborhood
distress are proposed risk factors for childhood OSA [33].
This may reflect increased exposure to environmental
triggers of airways inflammation as the housing stock of
Baltimore’s inner city is burdened with cockroach and
mouse allergen [34], which contribute to symptoms of
allergic rhinitis and asthma. We did not find, however, a
difference in OSA severity between African-American and
Caucasian children referred for PSG. This may be because
African Americans were overrepresented in our cohort.
While others have reported that asthma increases the
prevalence of snoring [8, 31], it has not been previously
reported whether or not a history of asthma increases the
risk or severity OSA in children. Chi-square analysis
showed that a diagnosis of asthma did not increase the
severity of AHI (p=0.549). Indeed, by logistic regression
analysis, a self-report of asthma decreased the odds of
having OSA (AHI>2) by 40%, controlling for individual
and socioeconomic factors.
There are few data on the polysomnographic findings in
subjects with asthma. Initial reports over three decades ago
by Kales et al.[35] suggest that children with asthma have a
decrease in stage 4 sleep, total sleep time, and frequent
awakenings when compared to normal controls. Some
authors [36] have demonstrated a greater fall in nocturnal
saturation in subjects with stable asthma when compared to
healthy individuals [36, 37]. In our study, asthmatic snorers
had worse sleep quality as judged by indices of sleep
386
fragmentation than non-asthmatic snorers. This was demonstrated by a slightly higher arousal index, and lower TST.
Despite the small increase in arousal index in those with
asthma, we are unclear of the clinical relevance of this finding. We do acknowledge the difficulty in scoring of arousals;
however, consistency was maintained by having the same
technician read all the studies. Increased sleep fragmentation
in asthma could also be due to the use of asthma medications
such as albuterol, theophylline, and corticosteroids. None of
our patients was using these medications the night of the
study. While our patients were asymptomatic per parent and
technician observation, it is possible that subclinical airways
obstruction could have led to greater sleep fragmentation. We
did not measure airflow by spirometry during the night to
determine if this was the case.
It is unclear if snoring per se alters sleep architecture. In
a study of 14 adults, eight “heavy” snorers and six “light”
snorers, Hoffstein et al. [38] reported that there was no
change in TST, SWS, and REM time between the two
groups, but found that snoring intensity did affect sleep
efficiency. In another study, the same authors reported that
in a group of adult symptomatic snorers and asymptomatic
non-snorers, arousals were respiratory in origin in the
snorers, but were EEG arousals in non-snorers. The total
arousal indexes in both groups, however, were similar [39].
A major limitation of this study was the lack of an
objective diagnosis of asthma as well as the fact that there
were no data in the questionnaire about the frequency of
and severity of the most recent asthma exacerbation. This
was a referral-based and not a population-based study,
which may explain the high prevalence of reported asthma.
Sleep Breath (2008) 12:381–392
A parent report of asthma is the standard for the Behavioral
Risk Factor Survey [40], which is a national survey
instrument that has been validated. Further study of a
cohort of asthmatic children when symptoms are well
controlled compared to those with poorly controlled asthma
would elucidate further the relationship between pediatric
asthma and risk of obstructive sleep apnea.
In conclusion, predominantly African-American innercity children, referred to the sleep laboratory for an
evaluation of snoring, have a high prevalence of selfreported asthma. The odds of OSA were lower in those with
prior history of asthma. OSA severity did not change with
or without a history of asthma. A higher arousal index in
the asymptomatic stable asthmatics suggests a mechanism
other than overt nocturnal symptoms of asthma responsible
for sleep fragmentation. Objective testing using methacholine or exercise challenges and the use of validated asthma
questionnaires to confirm prior vs. current history of asthma
will be useful to study the association between asthma and
OSA more thoroughly.
Acknowledgments The authors would like to thank Adrien Flahault,
Jeffrey Kleinberg, and Kinyemi Bunting for their assistance in
establishing the database at the Pediatric Sleep Disorders Center at the
University of Maryland.
Open Access This article is distributed under the terms of the
Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any
medium, provided the original author(s) and source are credited.
Sleep Breath (2008) 12:381–392
387
Appendix
DATE: ____________
PEDIATRIC SLEEP DISORDERS CENTER
NIGHT SLEEP STUDY QUESTIONNAIRE
CHILD’S NAME _______________________________________ DATE OF BIRTH _________
HOME ADDRESS ___________________________________________________________
CITY _________________________ STATE ________
TELEPHONE ___________________________
ZIP CODE _______________
WORK __________________________
CELL _______________________________
CURRENT PEDIATRICIAN ________________________________________________
TELEPHONE ______________________________
FAX _________________________
NAME OF PERSON FILLING OUT THIS FORM _____________________________________
RELATIONSHIP TO CHILD _________________________________
CLOSEST FRIEND/RELATIVE NOT LIVING WITH YOU ____________________________
ADDRESS ________________________________________________________________
CITY __________________________ STATE _______
ZIP CODE ______________
TELEPHONE ______________________________
RELATIONSHIP TO CHILD _________________________________________________
HOW MUCH DID YOUR CHILD WEIGH AT BIRTH _________________________
WAS YOU CHILD BORN AT 9 MONTHS (40 WEEKS)?
No
IF BEFORE, HOW ANY WEEKS? ______________________
IF AFTER, HOW MANY WEEKS? ______________________
Yes
388
Sleep Breath (2008) 12:381–392
FAMILY INFORMATION
1. Do you have other children? If so what are their names, how old are they?
NAME
DATE OF BIRTH
__________________________________________
_________________
__________________________________________
_________________
__________________________________________
_________________
__________________________________________
_________________
2. Do your other children have problems with sleep?
No
Yes
If so, what? _________________________________________________________________
___________________________________________________________________________
3. Does either parent have sleep apnea as diagnosed by a doctor?
No
Yes
4. Does a grandparent have apnea as diagnosed by a doctor?
No
Yes
5. Does either parent snore?
No
Yes
6 Does either parent smoke?
No
Yes
BRIEF MEDICAL HISTORY
1. Has this child ever had surgery on tonsils, adenoids, or palate?
(circle all that apply)
No
Yes
If so, what was the date of surgery? _____________________________
If so, where was the surgery performed and who was the doctor?
(Place) ____________________________________________________________
(Doctor) ___________________________________________________________
GENERAL MEDICAL INFORMATION
1. Does this child have asthma?
No
Yes
2. Does this child have any medical problems? If so, please list below:
a. _________________________________
d. _______________________________
b. _________________________________
e. _______________________________
c. _________________________________
f. ________________________________
Sleep Breath (2008) 12:381–392
389
3. List any medications your child is presently taking (including non-prescription)
a. _________________________________
d.
b. _________________________________
e.
c. _________________________________
f.
4. Is your child on oxygen?
None
Continuous
Night only
Feeding only
If so, what are the settings? ________________________________
If so, which equipment company do you use?
SLEEP HABITS
1. Does your child have excessive movements during sleep?
usually still
normal movements
somewhat restless
extremely restless
2. Does your child have excessive nightmares?
never
rarely
more than once/week
most nights
1 to 4 times/month
3.Does your child walk during sleep?
never
rarely
more than once/week
most nights
1 to 4 times/month
4. Does your child talk during sleep?
never
rarely
more than once/week
most nights
1 to 4 times/month
5. Does your child wake during night, i.e. for a drink, bathroom?
never
rarely
more than once/week
most nights
1 to 4 times/month
6. If your child is over 5 years old, does he/she wet the bed?
never
rarely
more than once/week
most nights
1 to 4 times/month
7. Does your child have heavy sweating during sleep?
never
rarely
more than once/week
most nights
1 to 4 times/month
390
Sleep Breath (2008) 12:381–392
8. Does your child’s lips or skin turn blue during sleep?
No
Yes
9. Do you ever see or hear your child stop breathing during sleep?
No
Yes
10. Do you ever see your child struggling to breathe during sleep?
No
Yes
11. Do you ever shake your child to make him/her breathe?
never
rarely
more than once/week
most nights
1 to 4 times/month
12. Do you ever watch your child sleeping at night, afraid about his/her breathing?
13. Does the child sleep with you in the same bed?
No
Yes
No
Yes
14. How often does your child snore?
never
rarely
more than once/week
most nights
1 to 4 times/month
15. How loud is your child’s snoring?
mild to quiet
medium to moderately loud
loud
extremely loud
16. Does your child toss and turn in his/her sleep?
17. Does your child have allergies?
No
No
Yes
Yes
(If so, what kind):
18. Does your child have ear infections?
never
rarely
2 to 5 times/year
6 or more times/year
19. How often does your child have a sore throat?
never
rarely
2 to 5 times/year
6 or more times/year
20. Is your child hard to awaken in morning?
No
Yes
21. Does your child have morning headaches?
No
Yes
22. Does your child have bad breath?
No
Yes
23. Is child a daytime mouth breather?
never
sometimes
usually
24. Does your child have a runny nose?
only with a cold
usually runny
Sleep Breath (2008) 12:381–392
391
constantly, every day
sometimes between colds
25. Is child sleepy during the day?
usually
sometimes
never
No
26. Is your child overweight?
Yes
How much weight has your child gained in the past year? __________________
27. Describe your child’s social interactions:
withdrawn
typical or average for age
outgoing
28. Overall, what grades does your child receive in school? _______________
No
29. Has there been a recent decline in school performance?
Yes
30 How would you describe your child’s appetite at present?
poor
typical/average
excessive
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