DOI: 10.1542/peds.2008-2525 2009;124;218Pediatrics

Emma Forbes-Jones and Jill S. HaltermanMaria Fagnano, Edwin van Wijngaarden, Heidi V. Connolly, Margaret A. Carno,

Sleep-Disordered Breathing and Behaviors of Inner-City Children With Asthma  

  http://pediatrics.aappublications.org/content/124/1/218.full.html

located on the World Wide Web at: The online version of this article, along with updated information and services, is

 

of Pediatrics. All rights reserved. Print ISSN: 0031-4005. Online ISSN: 1098-4275.Boulevard, Elk Grove Village, Illinois, 60007. Copyright © 2009 by the American Academy published, and trademarked by the American Academy of Pediatrics, 141 Northwest Pointpublication, it has been published continuously since 1948. PEDIATRICS is owned, PEDIATRICS is the official journal of the American Academy of Pediatrics. A monthly

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Sleep-Disordered Breathing and Behaviors of Inner-City Children With Asthma

WHAT’S KNOWN ON THIS SUBJECT: Asthma is one of the leadingcauses of childhood illness. Studies have linked asthmasymptoms with both childhood behavior problems and troubled

sleep. There is growing, but limited, evidence that children with SDBmay have worse behavior.

WHAT THIS STUDY ADDS: We found that poor sleep wasindependently associated with behavior problems in a largeproportion of urban children with asthma. Systematic screening

for poor sleep in this high-risk population might help to identifychildren who would benefit from further intervention.

abstractOBJECTIVE: To explore the relationship between sleep-disorderedbreathing (SDB) and behavioral problems among inner-city childrenwith asthma.

METHODS: We examined data for 194 children (aged 4–10 years) whowere enrolled in a school-based asthma intervention program (re-sponse rate: 72%). SDB was assessed by using the Sleep-RelatedBreathing Disorder Questionnaire that contains 3 subscales: snoring,sleepiness, and attention/hyperactivity. For the current study, wemod-ified the Sleep-Related Breathing Disorder Questionnaire by removingthe 6 attention/hyperactivity items. A sleep score of�0.33 was consid-ered indicative of SDB. To assess behavior, caregivers completed theBehavior Problem Index (BPI), which includes 8 behavioral subdo-mains. We conducted bivariate analyses andmultiple linear regressionto determine the association of SDB with BPI scores.

RESULTS: Themajority of children (meanage: 8.2 years)weremale (56%),black (66%), and insured by Medicaid (73%). Overall, 33% of the childrenexperienced SDB. In bivariate analyses, childrenwith SDB had significantlyhigher (worse) behavior scores compared with children without SDB ontotal BPI (13.7 vs 8.8) and the subdomains externalizing (9.4 vs 6.3), inter-nalizing (4.4 vs 2.5), anxious/depressed (2.4 vs 1.3), headstrong (3.2 vs 2.1),antisocial (2.3 vs 1.7), hyperactive (3.0 vs 1.8), peer conflict (0.74 vs 0.43),and immature (2.0 vs 1.5). In multiple regression models adjusting forseveral important covariates, SDB remained significantly associated withtotal BPI scores and externalizing, internalizing, anxious/depressed, head-strong, and hyperactive behaviors. Results were consistent across SDBsubscales (snoring, sleepiness).

CONCLUSIONS: We found that poor sleep was independently associ-ated with behavior problems in a large proportion of urban childrenwith asthma. Systematic screening for SDB in this high-risk populationmight help to identify children who would benefit from additional in-tervention. Pediatrics 2009;124:218–225

CONTRIBUTORS: Maria Fagnano, MPH,a Edwin van Wijngaarden,PhD,b Heidi V. Connolly, MD,c Margaret A. Carno, PhD,c EmmaForbes-Jones, PhD,d and Jill S. Halterman, MD, MPHa

aDepartment of Pediatrics, bCommunity and PreventiveMedicine, cSchool of Nursing and dDepartment of Psychiatry,University of Rochester School of Medicine and Dentistry,Rochester, New York

KEY WORDSchildhood asthma, inner-city, behavior, sleep-disorderedbreathing

ABBREVIATIONSBPI—Behavior Problem IndexOSA—obstructive sleep apneaSDB—sleep-disordered breathingSRBD—sleep-related breathing disorder

www.pediatrics.org/cgi/doi/10.1542/peds.2008-2525

doi:10.1542/peds.2008-2525

Accepted for publication Nov 7, 2008

Address correspondence to Maria Fagnano, MPH, University ofRochester School of Medicine, Strong Memorial Hospital, 601Elmwood Ave, Box 777, Rochester, NY 14642. E-mail:maria�fagnano@urmc.rochester.edu

PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275).

Copyright © 2009 by the American Academy of Pediatrics

FINANCIAL DISCLOSURE: The authors have indicated they haveno financial relationships relevant to this article to disclose.

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Asthma is one of the leading causes ofchildhood illness,1–3 affecting nearly 9million children in the United States.4

The public health burden of childhoodasthma is extensive including highrates of hospitalizations2,5–7 and emer-gency department visits,3,5,8,9 absentee-ism from school and work,5,10 and im-paired quality of life.11,12 Furthermore,children from poor and African Ameri-can backgrounds suffer dispropor-tionately from asthma.8,13,14

Several studies have linked asthmasymptoms and childhood behaviorproblems, such as hyperactivity andinattention.15–17 For example, a meta-analysis of 26 studies found that chil-dren with persistent asthma symp-toms had higher levels of behavioralproblems compared with healthy chil-dren.16 Troubled behavior among chil-drenwith asthmamay be compoundedby sleep-disordered breathing (SDB),which encompasses a continuum ofsleep-related disturbances rangingfromprimary snoring to overt obstruc-tive sleep apnea (OSA). SDB is becom-ing increasingly recognized in chil-dren, with prevalence estimatesranging from 0.7% to 3% for the moresevere OSA18–21 to as high as 7% to 25%for the milder form of SDB, primarysnoring.19,22–25 SDB in childhood mayalso be associated with persistentwheezing or asthma.20,26,27

There has been growing evidence thatchildren with SDB have higher rates ofbehavioral problems compared withchildren without SDB,24,25,28,29 and im-provement in SDB may alleviate behav-ioral problems in children.30,31 How-ever, limitations in the publishedliterature preclude us from drawing acausal link between sleep and behav-ior,32 and additional studies areneeded to help develop a more com-plete understanding of this relation-ship. Research in high-risk popula-tions may be particularly useful,because one would expect associa-

tions may be stronger in more suscep-tible groups of individuals.

We are not aware of studies that havespecifically explored the relationshipbetween SDB and behavior in a com-munity sample of nonreferred urbanchildrenwith asthma. It is important toassess the relationship between SDBand behavior among this sample, asthis is a high-risk group of children forboth sleep and behavior problemswhomay particularly benefit from appro-priate interventions. In this study, weexplored the association between SDBand troubled behaviors in a sample ofurban children with asthma. We hy-pothesized that children with parent-reported poor sleep would have worsebehaviors.

METHODS

Setting and Participants

This study used data collected from anongoing school-based asthma inter-vention program.33 This randomized,controlled trial was designed to evalu-ate the impact of school nurse–admin-istered maintenance asthma medica-tions and an environmental tobaccosmoke-reduction program for inner-city children in Rochester, New York.Our analysis included a communitysample of 226 children, aged 3 to 10years, enrolled in the program (overallresponse rate: 72%).

For enrollment, we identified childrenthrough school health forms, and ascreening form was administered bytelephone with the child’s primary care-giver to determine eligibility for theintervention. Children with physician-diagnosed asthma and persistentsymptoms in the past year based onnational guidelines34 were eligible.Written informed consent was ob-tained from all primary caregiversand assent was obtained from chil-dren �7 years of age before enroll-ment in this study.

From August 2006 to November 2006,each participating family received anextensive home visit to collect baselinedata, including demographic informa-tion, asthma symptom severity, medi-cations, health care utilization, childbehaviors, and caregiver factors. Fam-ilies received a follow-up telephonecall each month to discuss the child’sasthma symptoms and health care uti-lization. At the end of the school year(approximately June 2007), we con-ducted an extensive final follow-uptelephone call. We assessed symp-toms, child behavior, sleep problems,and additional information during thisfinal interview. We also collected a sa-liva sample for cotinine measurementand measured the child’s height andweight at the end of the school year.

For the current analysis, we excluded16 childrenwithout final follow-up data(7 withdrawn, 8 lost to follow-up, 1 in-complete data) and 2 children �4years of age, because the behaviorscale used here is not validated for thisage group. We also excluded 14 chil-dren with an autism diagnosis (includ-ing autism, Asperger syndrome, andpervasive developmental disorder).Our final analytic sample included 194children. The University of Rochester’sinstitutional review board approvedthe study protocol.

Assessment of Behavior

We assessed childhood behavior usingthe previously validated BehaviorProblem Index (BPI).35 The BPI was cre-ated by Peterson and Zill by usingmany of the same questions as Achen-bach’s Childhood Behavior Checklist.36

This 32-item survey is used to assessbehaviors during the previous 3months for children 4 to 17 years ofage; 28 items are included in the sur-vey for children �12 years of age.Caregivers are asked to respond tostatements of behavior by reportingwhether each behavior is “not true,”

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“sometimes true,” or “often true” oftheir child. All positive responses(sometimes true and often true) arescored as a 1 and summed to create atotal behavior score (range: 0–28). Ascore of �14 indicates significant be-havior problems.37 The BPI can also bedivided into several subscales: exter-nalizing (18 items), internalizing (10items), anxious/depressed (5 items),antisocial (6 items), hyperactive (5items), headstrong (5 items), peerconflict (3 items), and immature (4items). Examples of statements in-cluded in the BPI include, “Has troublegetting along with others,” “Demandsa lot of attention,” and “Is too fearful oranxious.”

Assessment of SDB

We assessed sleep problems by usingthe 22-item Sleep-Related BreathingDisorder (SRBD) scale.38,39 The SRBDscale is a validated subscale of thePediatric Sleep Questionnaire38 andcontains questions about snoring,sleepiness, apnea, attention, and hy-peractivity. Parents respond to ques-tions about sleep-related behaviors byresponding, “yes” � 1, “no” � 0, or“don’t know”� missing. The mean re-sponse from nonmissing items cre-ates a score between 0 and 1. A sleepscore of �0.33 has been effective inidentifying pediatric SDB by using poly-somnygraphy as the gold-standard as-sessment.38,39 Use of the SRBD scale inthe current study was permitted by itscreator, Ronald D. Chervin, MD, MS(personal written communication,2007).

The SRBD scale contains 3 subscales:snoring, sleepiness, and attention/hy-peractivity. Because we evaluated therelationship between SDB and behav-iors, including hyperactivity, we modi-fied the SRBD scale to exclude the6 attention/hyperactivity questions.These items include statements aboutdifficulty organizing tasks, fidgeting,

and interrupting conversations. Analy-sis of the SRBD scale without the 6 at-tention/hyperactivity questions is con-sistent with previous work of DrChervin.40

Assessment of Covariates

We examined child, caregiver, and en-vironmental covariates for this analy-sis. Child factors in this study con-sisted of standard demographicvariables for each child, including gen-der, race (white/black/other), ethnic-ity (Hispanic/not Hispanic), and child’sage. We also included Medicaid insur-ance (yes/no), prematurity (yes/no),BMI (age- and gender-adjusted zscore), and current asthma severity(intermittent/persistent) as othervariables that may be related to sleepand behavior. We assessed asthma se-verity during the final follow-up inter-view by asking parents to report thenumber of days in the previous 14 daystheir child had daytime asthma symp-toms and the number of days withnighttime asthma symptoms. Childrenwith�5 days of daytime symptoms or�2 nights with asthma symptoms dur-ing the past 2 weeks were consideredto have persistent asthma symptomsbased on national guidelines.34

Caregiver factors included the caregiv-er’s age (�30/�30 years), caregiver’seducation (less than high school/morethan high school), parent depression,parent stress, and parent quality of life.

We evaluated parent depression usingthe Kessler Psychological Distressscale.41 The Kessler Psychological Dis-tress scale is a 10-item scale used toassess symptoms of depression andanxiety. We asked caregivers how fre-quently they experienced each item(eg, nervous, depressed) in the past 4weeks (“none of the time” [score� 1]to “all of the time” [score � 5]). Wesummed scores from all items andhigher scores indicate a higher risk ofdepression, anxiety, or both (range:

10–50). We then divided scores into 4categories (well, mild, moderate, andsevere psychological distress) basedon previously validated domains.42

We measured parent stress by usingquestions from the competence sub-scale of the Parenting Stress Indexwith permission from the publisher(Psychological Assessment Resources,Inc, Lutz, FL).43 We included 5 items on a5-point scale and summed scores for atotal parent stress score (range:5–25). Higher scores indicate in-creased parental stress.

Caregivers also rated their quality oflife by using the Pediatric AsthmaCaregivers Quality of Life Question-naire by Juniper et al.12 Parents an-swered 13 questions about how theirchild’s asthma may have interferedwith normal daily activity over the pastweek. The questions on the PediatricAsthma Caregivers Quality of Life Ques-tionnaire are rated on a 7-point Likertscale with 1 being “all of the time” and7 being “none of the time.” Responseswere averaged for a mean quality-of-life score (range: 1–7).

Environmental tobacco smoke expo-sure was measured by both parentreport and the child’s level of salivarycotinine. Cotinine, a metabolite of nic-otine, is used as a biomarker for manyintervention studies for young chil-dren with asthma.44,45 We collected sa-liva samples from each child duringthe time of the final follow-up assess-ment by using standard collectiontechniques. All samples were mea-sured with a standard enzyme-linkedimmunosorbent assay and reported innanograms per milliliter (ng/mL).

Analysis

Analysis was performed by using SPSS15.0 (SPSS Inc, Chicago, IL). We con-ducted Student’s t tests to comparemean BPI scores for children with(sleep score � 0.33) and without(sleep score� 0.33) SDB. Multiple lin-

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ear regression analyses were con-ducted to determine if children withSDB have more behavior problems. Ini-tial covariates included in the regres-sion analysis included demographicvariables, covariates that were sig-nificant in the bivariate analysis, andkey exposure variables (caregiversmokes, salivary cotinine, asthma se-verity, preventive asthma medication,and treatment group). We performedbackward stepwise regression to in-clude covariates with selection crite-ria of P� .20 for entry and P� .15 toremain in the model. These analyseswere repeated for the behavioral sub-scales of the BPI. A 2-sided � value of�.05 for the primary hypothesis wasconsidered statistically significant.With our sample size, we estimatedthat we could detect a 3-point differ-ence in total BPI scores between chil-dren with and without SDB, with 80%power and an � value of .05.

RESULTS

Overall, the majority of children weremale (56%), black (66%), and insuredby Medicaid (73%). Some childrenwere born prematurely (11%), and theaverage age of the children was 8.2years. Twenty-six percent of childrenhad persistent asthma symptoms dur-ing the previous 2 weeks, and mostchildren were prescribed a preventiveasthma medication (86%). One third ofparents had less than a high schooleducation, and 41% of children livedwith at least 1 smoker in the home(Table 1).

In this sample, children’s sleep scoresranged from 0 to 0.88 with a meanscore of 0.27 (SD: 0.20). Overall, 33% ofthe children had a sleep score of�0.33, indicating SDB. Children withSDB were more likely to be female,have a parent with less than a highschool education, have nighttimeasthma symptoms, and have a higher

BMI (Table 1). In addition, the parentsof children with SDB were significantlymore stressed, depressed, and had alower quality of life. There were no dif-ferences in age, race, ethnicity, insur-ance status, exposure to tobaccosmoke, prematurity, asthma severity,use of preventive asthma medication,or treatment group between childrenwith and without SDB.

Table 2 shows the scores on the totalBPI and the behavior subscales. Over-all, 32% of children had a total BPIscore of �14, indicating a significantbehavioral concern that may warrantprofessional intervention. Comparedwith children with no sleep difficulties,children with SDB scored significantlyhigher on the total BPI (13.84 vs 8.9; P� .001) and on each of the behaviorsubscales (all P� .05).

The results of multiple linear regres-sion analyses are shown in Table 3 us-ing the sleep score as a dichotomousvariable (SDB/no SDB). The initial modelfor each regression contained the fol-lowing covariates: child’s age, race, eth-

nicity, gender, parent education, BMI zscore, parent smoking status, cotininelevel, parent depression, parent stress,parent quality of life, asthma severity,nighttime asthma symptoms, use ofpreventive asthma medication, andtreatment group. Using the backwardstepwise regression, many of these co-variates did not remain in the finalmodels, which are indicated in Table 3.Overall, SDB remained significantly asso-ciated with total BPI score, and external-izing, internalizing, anxious/depressed,headstrong, and hyperactive behaviorswhen controlling for pertinent covari-ates (Table 3).

Because nighttime symptoms ofasthma could be confused with SDBsymptoms, particularly for items onthe sleepiness subscale, we repeatedthe analyses by using scores on thesleep subscales (snoring and sleepi-ness) separately. In each of these anal-yses we found similar significant asso-ciations shown between higher sleepscores and worse behaviors (resultsnot shown).

TABLE 1 Population Demographics and Covariates by SDB

Overall(N� 194)

No SDB(N� 130)

SDB(N� 64)

P

Child gender, male, n (%) 109 (56) 80 (62) 29 (45) .045Child age, ya 8.17 (1.88) 8.14 (1.9) 8.22 (1.85) .771Race, n (%)White 17 (9) 12 (9) 5 (8) .337Black 129 (66) 90 (69) 39 (61)Other 48 (25) 28 (22) 20 (31)Hispanic, n (%) 51 (26) 34 (26) 17 (27) �.999Medicaid insurance, n (%) 141 (73) 93 (72) 48 (75) .732Parent age� 30, n (%) 64 (33) 46 (36) 18 (28) .331Parent education� high school, n (%) 64 (33) 36 (28) 28 (44) .034�1 smoker in the home, n (%) 79 (41) 49 (38) 30 (47) .277Caregiver smokes, n (%) 57 (29) 33 (25) 24 (38) .095Child born premature, n (%) 21 (11) 13 (10) 8 (13) .623Persistent asthma, n (%) 51 (26) 30 (23) 21 (33) .169Nights with asthma symptoms (over 2 wk)a 1.29 (2.8) 0.95 (2.3) 1.97 (3.4) .016Parent depression, mild-severe, n (%) 60 (31) 34 (26) 26 (41) .048Parent stress, points (%)a,b 9.46 (3.62) 8.97 (3.5) 10.47 (3.6) .006Parent quality of life, points (%)a,c 6.41 (.73) 6.52 (.59) 6.18 (.92) .002Child’s BMI z scorea 0.80 (1.8) 0.61 (2) 1.19 (1.12) .040Salivary cotinine, ng/mLa 2.21 (1.9) 2.29 (1.9) 2.04 (1.8) .412Preventive asthma medication, n (%) 167 (86) 113 (87) 54 (84) .662Treatment group, n (%) 92 (47) 66 (72) 26 (41) .222a Values shown are mean (SD).b The range for Parent Stress score is 5–25 points.c The range for Parent Quality of Life score is a mean of 1–7 points.

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DISCUSSION

We examined the association betweenSDB and childhood behavior problemsamong a group of inner-city childrenwith asthma. We found that one thirdof urban children with asthma may besuffering from SDB. This is consider-ably higher than the current estimatesof SDB in children, and suggests thatroutine screening for SDB might beparticularly important for childrenwith asthma. Similarly, we found that

32% of these children have behavioralsymptoms severe enough to warrantadditional evaluation. It is clear fromthese findings that urban childrenwithasthma are at risk for both SDB andpoor behavior.

Children with asthma and SDB hadworse behavior compared with chil-dren without sleep difficulties. Chil-dren with SDB scored nearly 5 pointshigher on the total BPI compared withchildren without SDB. This means thatchildren with SDB exhibited, on aver-age, 5 more problem behaviors thanchildren without sleep difficulties.These findingswere particularly prom-inent in the externalizing domains, in-cluding hyperactivity and headstrongbehaviors, and remained even whencontrolling for important variablesthat can influence children’s sleep, be-havior, and parent’s report of sleepand behavior.

Previous research has also demon-strated a relationship between sleepdisturbances and externalizing behav-ior problems. For example, a recentlypublished study of children with a clin-ical diagnosis of SDB compared chil-dren’s scores on the SRBD scale (ex-cluding the 6 attention/hyperactivityquestions) with their behaviors beforeand after adenotonsillectomy.30 Theauthors reported a strong associationbetween children’s sleep scores andinattention, oppositional behaviors,and an attention-deficit/hyperactivity

disorder index before surgery, withsome suggestion of improvement aftersurgery. Another study found similarresults among a large population-based sample of children, wheresymptoms of SDB were present in 25%of children,25 and these children weremore likely to exhibit problem behav-iors such as hyperactivity, inattention,and aggressive behaviors.

A strength of our study was that wewere able to account for many possi-ble confounding variables in our anal-yses, which is noteworthy, because theetiology of poor childhood sleep iscomplex. For example, black children,children who are overweight or obese,and children who were born prema-turely have been found to be at an in-creased risk for SDB.20,46,47 Further-more, mental distress of parents hasalso been associated with poor childsleep.48,49 Similarly, behavior problemsare more prevalent among poor andurban populations.50 Social and envi-ronmental stressors such as socioeco-nomic status, familial issues, and envi-ronment can influence both asthmaand behavioral outcomes.16

Our study is unique in that it explored therelationship between sleep and beha-vior among a nonreferred, community-based sample of children by using pre-viously validated surveys. Much of theliterature assessing sleep and behav-ior has included children from clinicalpractices for sleep assessment, behav-ioral assessment, or adenotonsillec-tomy.32 Our study observed the asso-ciation between sleep and behavioramong a group of nonreferred, urbanchildren with asthma, a population thatcould potentially benefit substantiallyfrom assessment and intervention.

Lastly, the BPI and SDB surveys used inour study are brief and could be usedin a clinical setting to help identify chil-dren with poor sleep or troubled be-havior. Several studies have used the

TABLE 2 Overall and Subscales of BPI Scores According to SDB Status

Overall(N� 194)

No SDB(N� 130)

SDB(N� 64)

P

Total BPI scorea 10.53 (7.3) 8.9 (7.3) 13.84 (6.3) �.001Externalizinga 7.4 (5.1) 6.38 (5.1) 9.47 (4.3) �.001Internalizinga 3.13 (2.7) 2.52 (2.6) 4.38 (2.6) �.001Anxious/depresseda 1.68 (1.6) 1.3 (1.5) 2.45 (1.5) �.001Headstronga 2.51 (1.7) 2.2 (1.7) 3.22 (1.5) �.001Antisociala 1.96 (1.8) 1.75 (1.7) 2.4 (1.7) .013Hyperactivea 2.2 (1.8) 1.79 (1.7) 3.03 (1.65) �.001Peer conflicta 0.54 (0.9) 0.43 (0.8) 0.765 (0.94) .011Immaturea 1.64 (1.3) 1.48 (1.3) 1.97 (1.25) .014BPI score�14, n (%) 62 (32) 31 (24) 31 (48) .001a Values shown are mean (SD); a high score indicates a greater problem with behavior.

TABLE 3 Linear Regression Models:Dichotomous Sleep Score PredictingBehavior Problems

Dependent Variables � SE R2 P

Total BPIa,b,cd,e,f,g .313 .130 .294 .017Externalizingb,c,d,e,h,i,j .318 .126 .275 .013Internalizingc,d,e,i,j .303 .108 .337 .006Anxious/depresseda,c,d,e,h,j,k .249 .087 .374 .005Headstronga,c,e,h,i,l .275 .097 .225 .005Antisociala,c,e,h .074 .101 .200 .462Hyperactiveb,c,d,e,f,j,m,n .288 .098 .356 .004Peer conflictd,g,h,i,l,m .065 .071 .237 .367Immaturea,b,c,d,e,h,o .104 .089 .191 .245

The following covariates were included in the backwardstepwise regression analyses. The covariates that re-mained in the final model are indicated next to each of thedependent variables.a Race,b ethnicity,c primary caregiver smokes,d parent depression,e parent stress,f asthma severity,g preventive asthma medication,h salivary cotinine level,i nighttime asthma symptoms,j treatment group,k gender,l parent education,m BMI z score,n parent quality of life, ando child age.

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BPI as a parent-report measure to as-sess behavioral problems in chil-dren.15,51,52 In addition, the use of theSRBD scale in research as a way toidentify children with SDB is increas-ingly common.30,39,53

Limitations

There were some limitations to thisstudy. This was a cross-sectional studyand, therefore, we cannot establish adirectional relationship between SDBand behavior problems in this sampleof children. In addition, behavior prob-lems were assessed by caregiver onlyand were not confirmed with physi-cians, teachers, or with subsequentassessments. Similarly, SDB was notconfirmed with polysomnography, thecurrent standard for diagnosis of SDB.However, recent studies have found astrong correlation between a sleepscore of�0.33 and a diagnosis of SDBby using polysomnography.30,39 In addi-tion, we did not have information re-garding previous surgeries includingtonsillectomy or adenoidectomy.

All families were recruited from an in-ner-city community, and many of these

families experience stressful lives thatmay contribute to parents’ report ofboth sleep and behavior problems.Fortunately, we were able to controlfor several factors including parentdepression, stress, and quality of lifein our multiple regression analysis. Inaddition, this study used data at theend of a 7 to 9 month asthma interven-tion program, and although we wereable to control for the influence of theintervention in our models, we realizethat caregivers may respond differ-ently to questions depending on theirviews of the intervention.

Lastly, it is possible that parents mayconfuse some symptoms of SDB withnighttime asthma symptoms. For ex-ample, symptoms such as “strugglingto breathe” or “intermittent breath-ing” at night could be interpreted aseither asthma symptoms or SDB. How-ever, symptoms of snoring are lesslikely to be confused with symptoms ofasthma, and when we repeated ouranalysis using the individual subscales(snoring and sleepiness) we foundsimilar, consistent relationships be-tween SDB and behavior.

Implications

Childhood sleep disorders are oftenoverlooked in the clinical setting, andthis study identifies a group of chil-dren who may be at particularly highrisk. In 2002, the American Academy ofPediatrics recommended that physi-cians screen all children for snoring todetermine risk of OSA.54 This recom-mendation underscores the impor-tance of sleep disorders and chil-dren’s health. The findings of this studysuggest that clinicians should be par-ticularly diligent about screening allchildren with asthma for SDB, and con-sider sleep disorders as a possiblerisk factor for behavior problems. Ad-ditional investigation is needed to de-termine if treatment of sleep disor-ders would help to decrease behaviorproblems in this population.

ACKNOWLEDGMENTS

This study was funded by NationalHeart, Lung, and Blood Institute grantR01-HL079954 and the Halcyon HillFoundation.

We thank Kelly Conn, MPH, for assis-tance with the manuscript.

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DOI: 10.1542/peds.2008-2525 2009;124;218Pediatrics

Emma Forbes-Jones and Jill S. HaltermanMaria Fagnano, Edwin van Wijngaarden, Heidi V. Connolly, Margaret A. Carno,

Sleep-Disordered Breathing and Behaviors of Inner-City Children With Asthma  

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