Asthma activity contributes to poorer academic outcomes across a range of indicators, and urban minority children with asthma, particularly Latino children, may be at heightened risk for poorer academic performance. School management guidelines for asthma need to be consistently implemented and tailored for school staff, caregivers, and students with asthma to address challenges of managing asthma within the urban school setting.

Analyses revealed that children with asthma experienced a higher number of school absences when compared with healthy controls. Greater disparities in academic outcomes emerged when examining ethnic differences within the groups of children with and without asthma. Poor academic outcomes were observed in Latino children with asthma. Furthermore, a strong correspondence of poor asthma outcomes and decrements in academic performance were seen in the full sample, and these associations emerged across ethnic groups.

Two hundred sixteen black/African American (33%), Latino (46%), and non-Latino white (21%) urban children, ages 7 to 9 years completed a clinic- and home-based protocol that assessed asthma and allergy status, objective measurements of lung function, and academic functioning.

Examine 1) academic performance across a range of indicators in a group of urban children with asthma and urban children without chronic illness and ethnic differences in these associations, and 2) associations between asthma and academic performance in the group of urban children with asthma and ethnic differences in these associations.

Urban minority children experience high levels of asthma morbidity. Poor school performance can be an indicator that asthma is in poor control. Little attention has been paid to examining real-time links between asthma and academic performance, particularly in high-risk groups.

In this report, we compare academic performance of a carefully evaluated group of urban children with asthma with that of their urban counterparts without asthma, and we examine ethnic differences in these associations. Based on previous results showing associations between poorer asthma control and poorer sleep quality and shorter sleep duration,as well as increased absences in urban children with asthma,we expect those in our study to experience poorer academic performance across indicators compared with their healthy peers. Given the cumulative impact that uncontrolled asthma and urban stressors can have on morbidity and daily functioning,we expect urban minority children with asthma to have the poorest academic outcomes relative to minority children without asthma. Within those with asthma, we also examine the association between asthma status (as measured by asthma control, lung function, and daily report of asthma symptoms) and academic performance measured across a 4-week monitoring period, as well as ethnic differences in these associations. We expect that poorer asthma will be associated with decrements in academic performance, and that these associations will be moderated by ethnicity. Specifically, we expect the association between poorer asthma and academic performance will be more profound in the ethnic minority children, given that it has been shown that morbidityand exposure to urban stressors are found to be greater in this group.

Another way in which asthma can affect academic performance is through its impact on sleep. Nocturnal asthma can affect children's sleep quality and duration,which can interfere with attention in school and impact the quality of school work. Moreover, urban minority children with asthma are exposed to increased environmental triggersand are found to have poorer adherence to asthma daily controller medications than their non-Latino white counterparts.These risks can increase symptoms at home and in school, which may impact learning. To date, the extent to which asthma affects urban children's academic performance across multiple academic indicators (eg, absences, grades) is not well documented.

Urban minority children are at increased risk for asthma morbidity.Factors related to urban living, such as exposure to urban stressors violence, neighborhood stress,environmental irritants and allergens,poorer medication adherence,and cultural factors related to ethnic background (eg, acculturative stress, discrimination)place this group at greater risk for poorer asthma control and morbidity. When asthma is poorly controlled, children are at greater risk for decrements in other areas of functioning, such as academic performance. Children with asthma are more prone to school absences than their healthy peers,and urban minority children with asthma are at even greater risk.In some urban areas, children with asthma miss an average of up to 2 weeks more of school than those without asthma.Missing school can disrupt learning and school-based social activities. Furthermore, frequency of absences is an important indicator of asthma morbidity in childrenand has been used as a proxy for academic performance in studies including children with asthma.Thus, school absences disrupt learning continuity, putting children with poorly controlled asthma or those with persistent/severe asthma at further risk for poorer academic performance.

The Wide Range Achievement Test-Third Edition (WRAT-4)was used to evaluate academic accomplishment in reading and arithmetic and is normed for children ages 5 to 11 years. Psychometric properties have been reported.

Each participant's primary classroom teacher reported on the participant's academic performance during 2 weeks within the monitoring period in which the child's asthma was assessed. The scale included 3 items, with Likert-type response options assessing: work quality, percentage of work completed, and carelessness with school work. Acceptable reliability has been demonstrated in prior research (Cronbach's alpha = .86)and in the current sample (Cronbach's alpha = .87). Single-item total correlations ranged from .42% of schoolwork completed (a similarly low value was found in previous work)to .74 (quality of school work).

School absences and grades were collected from children's final grade reports for the school year of study participation. Because grades can be reported in different metrics in various school systems, they were converted to numeric percentiles (eg, if “4.5” was the top of the scale in 1 school district, and “O+” was at the top in another district, both were assigned a value of 100%).

Families completed a daily diary twice daily to document the child's breathing problems during the day and evening, using standard procedures.Diary-reported symptoms were summarized across the monitoring period by computing a proportion of monitored days during which breathing problems were noted.

Children's lung function was assessed twice daily at home, in the morning and evening, during the monitoring period, using a hand-held computerized spirometer (AM2+; ERT; Yorba Linda, CA). At the beginning of each session, a research assistant oriented both the parent and child to the proper use of the device and how to perform a forced, sustained, expiration.Participants were instructed to complete 3 “blows” each morning and evening before taking any asthma or allergy medications. The best of 3 blows (ie, the highest FEV% predicted value) was retained for the trial. Details concerning data cleaning and reduction procedures have been published,including normative values used for FEVbased on children's age.

At the end of the monitoring period, families completed the Childhood Asthma Control Test,a well-validated questionnaire of asthma-related impairment validated for children aged 4 to 11 years. Using standardized scoring procedures,a dichotomous variable was computed using a total cutoff score of 19; those below were classified as having poor asthma control, and those above as having well-controlled asthma.

During the study clinic visit, the study clinician documented children's current asthma and allergy medications. Caregivers reported how often their child missed doses of daily controller medications, on a scale from 1 (misses doses all of the time) to 5 (never misses doses).Seventy-eight percent of caregivers reported their children were using daily asthma controller medications; 73% reported inhaled corticosteroid use. Eighteen percent reported that their children were using first-generation antihistamines for AR symptoms. The average self-reported asthma medication adherence was 3.6 (standard deviation [SD] = 1.3; range, 1-5), suggesting that most participants were moderately adherent to their prescribed medications, although given this is a self-report assessment it is likely an overestimation of children's medication adherence.

Allergic rhinitis was evaluated given its co-morbidity with allergic asthma by (1) evidence on physical examination, (2) type and frequency of parent report of AR symptoms in the past month, including an assessement of AR Control; and (3) allergy skin prick testing (Greer Laboratories, NC) to perennial and seasonal allergens. Allergic rhinitis severity was classified according to clinical practice guidelines.

Comparison of the effects of fluticasone propionate aqueous nasal spray and loratadine on daytime alertness and performance in children with seasonal allergic rhinitis.

Comparison of the effects of fluticasone propionate aqueous nasal spray and loratadine on daytime alertness and performance in children with seasonal allergic rhinitis.

The clinic study visit consisted of a medical history and physical examination, allergy skin prick testing, and pulmonary function testing. Confirmation of asthma diagnosis and severity classification were made by a study clinician using standard NHLBI EPR-3 guidelines.Lung function measurements (forced expiratory volume in 1 second [FEV], forced vital capacity [FVC], etc.) were evaluated using the Koko incentive spirometer (nSpireHealth, Longmont, CO) before and after short-acting beta agonist administration.Children's height and weight were measured, from which body mass index was computed using normative data.

Child participants' primary care providers and asthma/allergy specialists (when applicable) completed a checklist detailing the date of child's last office visit, asthma or AR diagnosis, suspected allergy triggers, significant medical history, and current asthma and rhinitis treatment. This information was used to evaluate the child's asthma and allergy status.

Assessments were administered verbally in English or Spanish by research staff fluent in both languages and according to caregivers' preference (24% of caregivers preferred to have the interview conducted in Spanish). Standardized procedures were used for the translation of instruments.All measures to children were implemented in English. Participants received monetary compensation for completed sessions. Study approval was obtained from the local Institutional Review Board.

The assessment of academic indicators occurred concurrently with asthma monitoring. After enrollment, each child's teacher was asked to complete a 2-week short-term academic performance assessment that dovetailed with the last 2 weeks of the monitoring period. After the clinic visit, families visited our laboratory, and the child's academic achievement was assessed. Grades and school absences were received from each child's school for the entire academic year the child participated in the study.

Data herein were collected during the fall/winter of each of the 4 Nocturnal Asthma and Performance in School study years. Demographic information and information regarding asthma and medication use were collected at the initial study visit. The second visit occurred at our hospital-based asthma and allergy clinic, during which study clinicians evaluated and confirmed children's asthma diagnosis and persistent severity status as well as allergy status, and confirmed asthma medication use. Given that the larger study also included a focus on allergic rhinitis, the clinical evaluation included an assessment of allergic rhinitis. Immediately after this clinic visit, children and their caregiver participated in a 4-week home-based monitoring period, during which the child used a portable device twice daily to assess lung function. Participants also completed a daily diary containing information relevant for assessment of self-reported asthma symptoms. Standardized procedures were used to orient and train families on the use of the home-based spirometer during the first visit and the subsequent clinic visit (see below). Midway through the monitoring period, study staff returned to the home to download and review electronic lung function data and to collect information on asthma and allergic rhinitis (AR) control. Staff implemented standard procedures to encourage protocol adherence.

Participants were recruited from the 4 largest urban school districts in an urban Northeast US city, and from hospital-based ambulatory pediatric clinics. Study eligibility criteria for the asthma participants required that the child was between 7 and 9 years old, the child's legal guardian was willing to participate, and self-identified as Latino (Dominican or Puerto Rican), black/African American, or non-Latino white (NLW); the child attend an urban public school in 1 of the 4 targeted school districts that are identified as being high-risk for asthma prevalence and asthma-related health care utilization; and that the child had physician-diagnosed asthma or caregiver-reported asthma symptoms in the previous 12 months. Additionally, at screening, each child was initially evaluated for persistent asthma either by caregiver report of a current prescription for an asthma controller medication or report of recurrent daytime or nighttime symptoms, activity limitation, rescue medication use, or 2 or more oral steroid bursts in the prior 12 months.Inclusion criteria for the healthy control group were similar to those described for the asthma participants, except for the need to meet the asthma-related criteria. Exclusion criteria for both groups included moderate to severe cognitive impairment as indicated by school placement; use of a stimulant medication for attention deficit hyperactivity disorder; another pulmonary or chronic health condition; or a diagnosed sleep disorder that would confound examination of primary hypotheses. We did not exclude sleep-disordered breathing, because this condition is highly co-morbid with asthma, and we are ultimately interested in designing “real-world” interventions for these children.

Data were collected within a larger 5-year study, Project Nocturnal Asthma and Performance in School, that assessed the co-occurrence of asthma, allergic rhinitis, sleep quality, and academic functioning in urban children and healthy controls across 1 academic year.

Among NLW children, there were borderline associations between better lung function (FEV) and better quality of work (t = 2.15, P = .04). Furthermore, more daily reported symptoms were significantly associated with worse quality of work (t = −2.63, P = .01), worse WRAT math scores (t = −2.22, P = .03), and more school absences (t = 2.57, P = .01). Finally, better asthma control was associated with better quality of work (b = 2.33, P = .03) ( Table 5 ).

Among black children, more daily reported symptoms were associated with more school absences (t = 2.50, P = .01). Finally, better asthma control was associated higher WRAT math scores (t = 2.52, P = .01) and fewer school absences (t = −2.96, P = .01).

Finally, significant associations were found between asthma and academic indicators, stratified by ethnicity ( Table 5 ). Among Latinos, better lung function was associated with less careless schoolwork (t = 2.38, P = .02), as well as higher WRAT math (t = 2.73, P = .01) and reading scores (t = 2.98, P = .003). Furthermore, higher FEV variability was associated with worse WRAT math (t = −2.20, P = .02), and reading scores (t = −2.19, P = .03).

Estimates are unstandardized regression coefficients from models comparing each predictor (column) with each outcome (row) adjusting for asthma severity within each ethnicity group.

Adjusted associations between asthma and academic indicators among children with asthma appear in Table 4 (across ethnicity) and Table 5 (separately by ethnicity). Among children with asthma, better lung function (higher FEV% predicted) was associated with teacher reports of better quality school work (t = 2.31, P = .02) and less careless work (t = 2.39, P = .02). Less FEVvariability was associated with better WRAT math scores (t = −2.25, P = .03). More daily reported asthma symptoms were borderline associated with teacher reports of lower percentage of work completed (t = −2.04, P = .04), and significantly associated with more absences (t = 2.59, P = .01). Finally, better asthma control was significantly associated with higher quality of work (t = 2.35, P = .02) and fewer absences (t = −2.51, P = .01) and borderline associated with more work completed (t = 2.02, P = .04) and higher WRAT math scores (t = 2.03, P = .04). All effect estimates appear in Table 4

A similar analysis explored between-ethnic differences in academic indicators among healthy controls ( Table 3 ). Latinos had lower WRAT math scores compared with NLWs (t = −2.53, P = .01). In addition, black children had borderline lower quality of work scores as reported by teachers compared with NLWs (t = −2.09, P = .04). Models suggest no differences between Latino and black participants.

Estimates are unstandardized regression coefficients (standard errors). Negative effects denote cases in which mean academic outcome in Asthma group was lower than mean outcomes in control. Models controlled for asthma severity.

a Estimates are unstandardized regression coefficients (standard errors). Negative effects denote cases in which mean academic outcome in Asthma group was lower than mean outcomes in control. Models controlled for asthma severity.

Regression-based approaches for testing between-group differences (asthma vs control) on academic indicators appear in Table 2 (aggregated over ethnicity). Regression coefficients (b) are presented and refer to unstandardized coefficients or, equivalently, adjusted mean differences between groups. Models suggest significant between-group differences in total school absences, such that children with asthma had a greater number of school absences compared with healthy controls (t = 2.18, P = .03) and indicated a nearly 3-day difference between groups ( Table 2 ). No significant differences were seen between asthma and control groups with respect to other academic indicators.

Bivariate correlation analysis suggested correlations between asthma severity and asthma control (rho = −0.25, P < .001) and FEV 1 % predicted (rho = −0.17, P = .02). Furthermore, asthma severity was negatively associated with quality of school work (rho = −0.17, P = .01). Thus, all subsequent models of asthma and academic outcomes controlled for asthma severity.

Participants (n = 395; 130 healthy control children and 265 children with asthma) were 8.30 years old on average (SD = 0.86), more than half were male (53%) and reported living at or below the poverty threshold (67%). A full description of the sample appears in Table 1

Following Rothman,we recognize the risk in adjusting for multiple comparisons, which may increase type II error rates at the expense of type I errors. However, to be conservative, we used Benjamini-Hochberg correction for multiple comparisons (this resulted in an adjusted significance level of .04). Even with our approach, most results summarized maintained their significance or were borderline significant (we have indicated when this was the case). All analyses were completed using SAS 9.3; unadjusted significance was α = .05 a priori for testing the primary hypotheses.

Next, the associations between asthma and academic outcomes were examined using a series of generalized linear models, in which each academic outcome was regressed on each asthma outcome, controlling for confounders. Models were run only among the subsample with asthma. Finally, we explored whether the asthma-academic associations differed by ethnicity, using a series of subgroup analyses.

We tested the association between group status (Asthma vs Control) and each academic outcome, using a series of generalized linear models. Models controlled for potential confounders that were identified in preliminary analyses. Generalized linear models use a likelihood-based approach to estimation and thus make use of all available data without directly imputing missing outcomes. We compared our results with those of completers-only. Because results did not significantly differ, we present the full model (all enrollees). Finally, ethnic differences in academic outcome were examined separately by group (asthma, control), using a similar modeling approach (generalized linear models). Because our hypotheses regarding the associations between asthma and academic outcomes pertained to individual effects of asthma and different elements of academic function (eg, school work, attendance), we chose to model each academic outcome separately instead of creating a composite score. The latter would not allow for identifying the effects of asthma on specific components of academic success.

Demographic, asthma, and academic outcomes were summarized for the aggregated sample and compared between groups (children with asthma vs healthy controls), using analysis of variance (continuous variables) and χtests (categorical variables). Outcome variables (academic outcomes) were assessed for normality. Bivariate correlations were used to identify potential confounders. Spearman rank order correlations were used to test for associations between demographic variables hypothesized a priori as potential confounders (age, sex, poverty level, sleep-disordered breathing, and asthma severity) and asthma and academic outcomes. A variable was considered a confounder if it was associated with both the predictor (asthma variables) and outcome (academic variables) at a conservative P < .10 level, and was controlled for in subsequent analyses.

Discussion

In a carefully evaluated sample of urban children with persistent asthma, this study examined associations among a range of asthma and academic indicators. The current study is an in-depth investigation of the extent to which asthma may impact urban children's academic performance through both objective and subjective measurements. A demographically matched control group of children with no asthma allows for examination of academic indictors between the 2 groups, and the extent to which asthma status may challenge optimal academic performance. Ethnic differences in outcomes between children with and without asthma were also examined to inform future tailored interventions that can be implemented in medical or academic settings.

3 Koinis-Mitchell D.

Kopel S.J.

Boergers J.

et al. Good sleep health in urban children with asthma: a risk and resilience approach. 11 Basch C.E. Asthma and the achievement gap among urban minority youth. , 12 Reynolds K.C.

Boergers J.

Kopel S.J.

Koinis-Mitchell D. Multiple comorbid conditions, sleep quality and duration, and academic performance in urban children with asthma. 42 Koinis-Mitchell D.

McQuaid E.

Fritz G.

et al. Culturally and contextually tailored asthma self-management for urban, Latino middle school students: the Rhode Island-Puerto Rico ASMAS program. 43 National Asthma Education and Prevention Program

Expert Panel Report 3: Guidelines for the Diagnosis and Management of Asthma. 43 National Asthma Education and Prevention Program

Expert Panel Report 3: Guidelines for the Diagnosis and Management of Asthma. 7 Koinis-Mitchell D.

McQuaid E.L.

Seifer R.

et al. Multiple urban and asthma-related risks and their association with asthma morbidity in children. 43 National Asthma Education and Prevention Program

Expert Panel Report 3: Guidelines for the Diagnosis and Management of Asthma. Regarding differences in academic outcomes by asthma status in our sample, as expected, the number of school absences across the academic year of participation in the study was higher in children with asthma than in their no-asthma peers. When children are symptomatic, caregivers may elect to keep them at home, in case urgent care or visits to the health care provider are warranted. Nocturnal asthma has also been related to poorer sleep quality.When children miss sleep because of asthma, caregivers also may elect to keep the child home.We have shown that caregivers' fear of their child's asthma symptoms may contribute to decisions to keep the child home from school.Strategies to reduce absences may include identifying children with asthma who miss school more often, so that the school nurse or child's primary teacher can encourage the family to see the child's primary care provider.Educating caregivers on the risk for absences related to poor asthma control can be useful to promote consistent learning in this group. Educational strategies for caregivers can include a review of when best to communicate with the school nurse regarding the child's asthma status (eg, in the morning), how to communicate (eg, by phone) and what information to share (eg, symptom frequency, history of urgent care visits, treatment plan).Low levels of medication adherence, increased environmental exposures, and urban stress present additional challenges to optimal preventative asthma management behaviors in this group.Still, given that guidelines for optimal management of asthma in schoolare challenging to implement consistently in urban schools, reviewing strategies to reduce absenteeism with caregivers, school nurses, and school staff through asthma management educational training is clearly needed.

More pronounced differences in academic outcomes were found by ethnicity within the asthma and healthy control groups, the most robust being within the asthma group. For example, Latinos and black children with asthma had poorer academic outcomes than their NLW counterparts, with Latino children having the poorest outcomes across a range of indicators.

44 Koinis-Mitchell D.

McQuaid E.L.

Kopel S.J.

et al. Cultural-related, contextual, and asthma-specific risks associated with asthma morbidity in urban children. 45 Koinis-Mitchell D.

Kopel S.J.

Esteban C.

et al. Asthma status and physical activity in urban children. 23 Fritz G.K.

McQuaid E.L.

Kopel S.J.

et al. Ethnic differences in perception of lung function: a factor in pediatric asthma disparities?. 46 McQuaid E.L.

Kopel S.J.

Klein R.B.

Fritz G.K. Medication adherence in pediatric asthma: reasoning, responsibility, and behavior. 47 McQuaid E.L.

Vasquez J.

Canino G.

et al. Beliefs and barriers to medication use in parents of Latino children with asthma. Results suggest that asthma status can exacerbate ethnicity-based disparities in academic outcomes in urban minority children with asthma. Latino children with asthma appear to have the highest risk for poor academic performance. Our prior work has shown that urban Latino children with asthma face urban stressors and unique cultural-related stressors (eg, acculturative stress,higher levels of fear of asthma,poorer symptom perception,lower medication adherence,and greater concerns regarding medicationsthat may put them at risk for poor academic performance. Future work should identify contributing factors to poor school performance among specific groups of children with asthma, because these stressors and poor sleep may be areas to target in future interventions.

Our results also suggest that asthma may impact children's academic performance. For example, better lung function was related to better quality school work and less careless work by teacher report. Furthermore, the more lung function varied for children across the monitoring period, the poorer their WRAT math scores were. More frequent symptom reports by children and caregivers were related to less work completed and more school absences. Finally, better asthma appeared to be important for a number of academic indicators, including higher levels of teacher-reported quality of school work and a higher percentage of work completed, higher WRAT math scores, and fewer absences. These results suggest the important role of asthma management for children's academic performance. Although each asthma indicator was related to several academic outcomes, asthma control was associated with the most academic outcomes. Asthma control, a marker of morbidity, can be useful to identify children who may be at risk for problems with school performance.

More associations between asthma indicators and a range of academic outcomes were observed in the Latino group of children, followed by the NLW group of children. Latino children's lung function variables were related to their achievement scores and teacher-reported impressions of the quality of their work. A range of asthma indicators (lung function, control, symptom reports) related to several academic indicators in the NLW group of children. In the black group of children, only symptom reports were related to more absences and less work completed, by teacher report. Overall, not a single academic indicator seemed to be affected by poorer asthma status more often in the overall asthma sample or in the specific ethnic groups. However, children's grades were not associated with asthma activity in the group of children with asthma, whereas teacher-reported academic indicators, school absences, and achievement scores were each associated with more asthma activity.

22 Esteban C.A.

Everhart R.S.

Kopel S.J.

Klein R.B.

Koinis-Mitchell D. Allergic sensitization and objective measures of sleep in urban school-aged children with asthma. 12 Reynolds K.C.

Boergers J.

Kopel S.J.

Koinis-Mitchell D. Multiple comorbid conditions, sleep quality and duration, and academic performance in urban children with asthma. Several limitations of the current study should be noted. We examined academic performance and asthma through objective approaches (eg, lung function via AM2+); however, the design did not capture potential bidirectional relationships in real time. This cross-sectional design may pose limitations for inferring directional or causal associations. We used means across monitoring periods for variables collected daily, such as the asthma variables. Furthermore, academic variables were collected at the end of the semester rather than during the specific time of an asthma event and included both objective and subjective measures of academic function. Likewise, other health or behavioral agents, such as sleep quality, as well as other psychosocial factors (eg, family functioning, caregiver stress) may have impacted academic or asthma variables. Furthermore, allergic rhinitis is highly co-morbid in urban children with asthma and may impact sleep quality,which also can affect academic outcomes.In addition, seasonality, infectious triggers, and allergy status can contribute to AR and asthma symptoms and academic functioning and should be considered in future research with urban children. Further, exposure to environmental triggers in the home, school, and neighborhood environment can exacerbate symptoms, and possibly contribute to academic outcomes. Future research should assess the mediating role of specific behavioral, environmental, and health processes on asthma and academic functioning in larger samples of urban children.