Dr. Daphne Koinis Mitchell discusses the following:
- Effects of Asthma on School Performance: Recent data from Project NAPS
- School-based educational initiatives of the Community Asthma Program of Hasbro Children's Hospital of RI
- Project CASE: Controlling Asthma in Schools Effectively, a multi-level pilot project to enhance asthma control
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Addressing Asthma, Sleep Quality and School Performance
1. Addressing Asthma and School
Performance in Urban Children:
Research, education, and intervention efforts
Thursday, December 12, 2013
9:30 – 10:30 AM EST
This webinar is funded by EPA Grant #XA96161601
2. Please note that these materials are
not to be distributed without
permission.
For more information,
please contact Dr. Daphne Koinis Mitchell
DKoinisMitchell@lifespan.org
3. Research, Education and Intervention
Efforts to Address Asthma and School
Performance in Urban Children
Daphne Koinis Mitchell, Ph.D
Associate Professor (Research)
Director, Community Asthma Program
Hasbro Children’s Hospital
Department of Psychiatry and Human Behavior (Primary)
Department of Pediatrics (Secondary)
Alpert Medical School of Brown University
This work was supported by NICHD; R01 HD057220 (Koinis Mitchell, PI)
RI Department of Health Asthma Control Program
4. Overview
●Effects of Asthma on Urban Children’s School
Performance: Recent Data from Project NAPS
● School-based educational initiatives of the
Community Asthma Program of Hasbro Children’s
Hospital of RI
● Project CASE: Controlling Asthma in Schools
Effectively, a multi-level pilot project to enhance
asthma control
● Future Directions
5. The Asthma Health Disparity
● Asthma morbidity higher and poorer asthma control
in Latino and African-American Children:
● Higher frequency of ER visits and hospitalizations (US DHHS,
2009; Lara et al., 2009; Ortega et al., 2009)
● Less consistent with taking controller medications
(Bauman et al., 2002; Butz et al., 2004; McQuaid et al., 2009; 2012)
6. The Asthma Health Disparity
Disparities are multi-determined
Individual (e.g., genetic, Choudhry et al., 2005; high severity, Esteban et
al., 2009; adherence, McQuaid et al., 2009; 2012; poor perceptual accuracy,
Fritz et al., 2010).
Environmental (e.g., irritants/allergens, Kattan et al., 2005; violencerelated distress, Wright et al., 2004; 2007).
Familial/cultural (e.g., concerns regarding controllers, McQuaid et al.,
2009; alternative treatment approaches, Koinis Mitchell et al., 2009;
discrimination, acculturative stress and neighborhood stress
(Koinis Mitchell et al., 2007, 2009, 2012)
Health care system factors (e.g., public insurance status, lack of
consistent PCP, Jandasek et al., 2010; access to a specialist, Canino et al.,
2012)
7. Pediatric Asthma: The Local Burden
In 2010, approximately 12% of children in RI
were reported to currently have asthma
(higher in urban areas) (RI Dept. of Health, 2012)
In some schools in urban providence, rates
of asthma range from 20-50%
2000 visits for asthma annually in the Hasbro
Emergency Department
8. Urban Children at Increased Risk for
Asthma Morbidity, Missed Sleep,
Poor School Performance
● Increased number of school absences, more missed
sleep, more activity restriction in children with severe
asthma and in urban children (Koinis Mitchell et al; 2007; 2009;
2013)
This group misses more school days (CDC, 2005)
Latino children with asthma are absent more often than whites (Lieu et at . ,
2002)
If not properly treated, can asthma negatively impact
children’s ability to learn when in school? Only self-report,
cross-sectional studies, inconsistent results
9. ASTHMA AND ACADEMIC
PERFORMANCE IN URBAN CHILDREN
Nocturnal
Asthma
and
Performance
in
School
Brown Medical School/Rhode Island Hospital, Providence RI
R01 (R01-1R01HD057220) Eunice Kennedy Shriver, National Institute of Child
Health & Human Development (NICHD)
Daphne Koinis-Mitchell, Ph.D., PI
10. Project NAPS SPECIFIC AIMS
Aim 1: Examine the co-occurrence of asthma status and
academic performance over the school calendar year in a
group of urban, elementary school children
Aim 2: Examine mechanisms that mediate the association
between asthma status and academic performance (e.g.,
sleep quality, allergic rhinitis, and school absences)
Aim 3: Assess contribution of family/cultural risks (e.g.,
perception of severity and levels of fear related to asthma),
and AR symptoms on asthma status and academic
performance.
11. NAPS STUDY DESIGN
Longitudinal, observational study with repeated measures
255 children (age 7-9 years) with asthma and allergic rhinitis
120 children who are free from chronic illnesses and allergies
Recruited from schools and hospital-based clinics
Children are from 4 adjacent urban school districts
Participant in asthma group have persistent level of disease
All children are from African American, Latino, Non Latino White
12. TYPES OF DATA COLLECTED:
MULTIMETHOD APPROACH
Child & Parent Self report
– Asthma, Allergy, Sleep (Daily Diary), Med. Use, Side Effects, Family
Asthma Management, Family/Cultural Risks
Objective Measurements – 1 month, at-home —3 monitoring periods
– Pulmonary function (AM2 handheld spirometer; FEV1/FVC/PEF)
– Sleep Quality (Actiwatch; Sleep efficiency parameters)
– Peak Nasal Inspiratory Flow (In-Check Nasal Flow Meter; PNIF)
Clinical Evaluation
– Physical examination (Confirmation of Asthma/AR Diagnosis
classification of AR/Asthma Severity)
– Pulmonary function testing
– Allergy testing
Academic Data
– Teacher Reports: Academic Functioning during 3 monitoring periods
– School Nurse Reports: Children’s asthma management at school
– Academic Achievement; standardized tests; grades, school absences
13. TIME LINE OF PARTICIPATION
HV/Clinic
Data
Collection
School/PCP/Nurse
Data Collection
Aug 1 – Oct 15
Recruit/Screen
Enrollment (S0)
(HV)
Oct 1 – Nov 31
S1 (Clinic Visit)
Mon Per 1 Begins
For 4 wks after S1
Physician
Query
Monitoring Period 1
Weeks 1 – 4
2 Wks home visit
4 wk home visit
2 wk Teacher Acad
Perf Assessment
Jan 1 – Feb 28
S2 (Home Visit)
Mon Per 2 Begins
Monitoring Period 2
Weeks 1 – 4
2 Wks home visit
2 wk Teacher Acad
Perf Assessment
Apr 1 – May 31
S3 (Home Visit)
Mon Per 3 Begins
Monitoring Period 3
Weeks 1 – 4
2 Wks home visit
2 wk Teacher Acad
Perf Assessment
SNT Packet
June
RA
Collects
End of
School
Year Data
14. ASTHMA MONITOR (AM2)
The Asthma Monitor AM2 measures and saves all relevant
lung function parameters (PEF, FEV1, FVC, MMEF)
19. HYPOTHESIZED ASSOCIATIONS:
Focus on Asthma and Sleep
Allergic Rhinitis
Status
Sleep
Quality
Asthma
Status
Academic
Performance
School
Absence
20. Why Focus on Sleep?
Sleep is important for all children (Wolfson & Carskadon, 1998;
Carskadon et al., 2004)
Children with medical conditions miss more sleep if illness is poorly
controlled (Boergers & Koinis Mitchell, 2010)
NHLBI (1997; 2007) identified sleep as indicator in assessment of
children’s asthma-related adjustment
National Center on Sleep Disorders Research recognized sleep
disturbances as an important factor contributing to racial/ethnic
disparities in health outcomes (NIH, 2007)
Poor sleep quality is an indicator that asthma is in poor control;
relevant for children’s daytime functioning and academic success
21. Mechanistic Pathways Linking
Asthma with Sleep Quality
Asthma symptoms experienced during nighttime hours due
to (Meijer et al., 1995) :
– Dip in cortisol levels at night; increase in inflammatory cytokines/
mediators
– A potential bi-directional relationship with nighttime disturbances
and circadian rhythms (Martin et al., 1998)
– Increased airway resistance at night
– Increased pollen counts during nighttime hours
– Sleep posture facilitates an increase in mucous production
– Increased environmental triggers in urban home settings
– Nonadherence to treatment
(See review: Koinis Mitchell, Esteban, Craig & Klein, JACI, 2012)
Asthma and sleep not assessed in urban children
22. Participant Demographics
To date, 400 urban families enrolled (275 children with asthma, 125 healthy
controls) ; African American (31%), Latino (51%; Dominican or Puerto Rican) and NLW(18%)
backgrounds
Presentation includes data from first 4 years of study; 200 children with asthma
Children between the ages of 7-9 years (Mean=8.4, SD=.9 years)
53% of children are male
67% of families had household incomes below poverty threshold; Ethnic group
differences in the proportion of families at/below poverty: Latinos (81%), African Americans (60%), and non
Latino whites (39%); (X2 = 20.8; p < .001).
Persistent asthma; classified as Mild Persistent (45%), Moderate Persistent (38%)
or Severe (17%). 41% were poorly controlled.
73% (by study clinician) have AR. 72% have persistent symptoms; 47% with
moderate, and 18% with severe intensity. 50% of children with AR were never
diagnosed. 59% receive no treatment or are undertreated
23. Objective Lung Function and
Sleep Quality
Efficiency through actigraphy = number of minutes during the night
coded as sleep
– Example: 600 minutes sleep – 60 minutes awake = 540 (90% sleep
efficiency score)
Multi-level Analyses were nested within child
Examined sleep quality within the Sleep Period
FEV1 was significantly associated with sleep efficiency (F=1.6, p<.001)
Sleep onset latency (F=3.0, p<.001)
Number of night wakings (F=1.4, p<.01)
24. Diary Reported Asthma Symptoms and
Sleep Quality
Analyses were nested within child
Examined sleep quality within the Sleep Period
Self reported asthma symptoms were associated with sleep efficiency
(F=1.9)
Sleep onset latency (F=1.5)
Number of night wakings (F=1.5, all p’s < .001)
25. Asthma Control and Sleep Quality
Children with poorly controlled asthma had lower sleep
efficiency (F=6.4, p=.01), took more time to fall asleep
(F=3.2, p=.05) than children with well controlled asthma
Asthma control associated with sleep duration (F=8.8,
p<.01)
Poor asthma control associated with more variability in # of
wakings across the monitoring period (F=5.3, p=.02).
26. Child Sleep Disturbance (Parent Report)
Total Sleep Disturbance Score
> 80% of sample scored above the clinical cutoff score of
41 (Owens et al., 2000), indicating marked sleep disturbance in
our sample
Total Sleep Disturbance Score significantly associated with
self-reported asthma symptoms: r = .24, p = .03
27. HYPOTHESIZED ASSOCIATIONS:
Focus on Asthma and Academic
Performance
Allergic Rhinitis
Status
Sleep
Quality
Asthma
Status
Academic
Performance
School
Absence
28. Impact of Asthma on School Functioning
Poorer asthma control associated with more school
absences (β = - .43, t= -2.8, p<.01); relationship more
robust for AAs
Children with asthma had a mean of 11 school absences in
the year of their study participation (range = 1 – 52 days)
Control participants had an average of 6 absences (range
= 0 – 34 days)
Across asthma participants, ethnic differences found in
school absences across school year:
Latinos: higher rate of absences (M = 13 days,) relative
to AAs (M=8 days), F (2,127)=3.7, p=.03. NLWs did not
differ from other groups (m=7 days)
29. Impact of Asthma and Sleep on
School Functioning: Teacher ratings of
academic performance
More optimal lung function (FEV1) related to higher quality school
work (F=4.7, β =.19, p=.03) and less careless/hasty school work (F=8.1,
β =-24, p=.00)
Children with poorly controlled asthma had lower quality school work
(F=3.1, β =.18, p=.02) than children with well controlled asthma
Frequency of asthma symptoms by diary report predictive of
careless/hasty schoolwork (β =.13, F=2.9, p=.05)
Associations between asthma and academic performance most robust
within AA subsample. For example, asthma control significantly
predictive of % work completed in AA sample (β =.30, F(1,44)=4.2,
p<.05) but not in other ethnic groups
30. Impact of Asthma and Sleep on
School Functioning: Teacher ratings of
academic performance
Sleep & Academic Functioning
Careless school work associated with poor sleep efficiency (F=8.3, β =
-.23, p<.01), shorter sleep duration (F=5.3, β = -.18, p=.02) and more
night wakings (F=5.5, β =.19, p=.02)
The amount of school work completed positively associated (β =.19,
p=.02) with sleep efficiency
Children who had fewer struggles staying awake in class had on
average, longer sleep duration (F=4.5, β =.17, p=.04)
31. Impact of Asthma and Sleep on
School Functioning: Mediational Analyses
Sleep efficiency significantly mediated the relationship
between asthma control and quality of school work (Sobel
test=1.9)
This result also emerged in the AA subgroup (Sobel test=1.7).
Lung function mediated the association between sleep
duration and school performance (Sobel test = -1.7) in the
full sample and in AAs and NLWs
32. Summary
Nocturnal asthma symptoms affect sleep efficiency in this sample of urban
children; More compromised lung function and poor asthma control
associated with poorer sleep quality
Children who experienced more optimal lung function performed more
effectively in school
Poor sleep quality related to nocturnal asthma affects day-to-day academic
performance
Poorer sleep efficiency, shorter sleep duration, and frequent night wakings
associated with problems with children’s academic learning; ethnic minority
children appear to be more at risk
Future analyses will be conducted with the larger sample
Implications for developing family and school-based interventions to improve
asthma control, sleep quality, and academic performance in urban children
33. PROJECT NAPS
Principal Investigator
Daphne Koinis Mitchell, PhD
Co-Investigators
Julie Boergers, PhD
Gregory Fritz, MD
Robert Klein, MD
Monique LeBourgeois, PhD
Elizabeth McQuaid, PhD
Ronald Seifer, PhD
Jack Nassau, PhD
Maria Theresa Coutinho, PhD
Barbara Jandasek, PhD
Project Director
Sheryl Kopel, MSc
Study Clinicians
Cynthia Esteban, MSN, MPH
Diane Andrade, RN
Julia Estrela, RN
Research Assistants
Christine McCue, BA
Katie Dansereau, BA
Kara Ramos, BA
Brittney Williams, BA
Alvaro Beltran, BA
Kary Vega, BA
Vivian Garcia, BA
Collaborators/Consultants
Robin Everhart, PhD
Amy Wolfson, PhD
Cynthia Garcia-Coll, PhD
34. Programs Addressing –
Asthma at Hasbro
Treatment
The Respiratory
and Immunology
Center
Education
The Community
Asthma Program
Research/Intervention
The Childhood
Asthma
Research
Program
35. Community Asthma Program
Hospital and School-based Classes
“102” Classes (For graduates of “101 classes)
Asthma Support Groups
Asthma Camp
HARP: Home-based Asthma Response Plan
Project CASE – School Program
36. Community Asthma Program Staff
Founded by Bob Klein, M.D
Daphne Koinis Mitchell, PhD, AE-C
Director
Miosotis Alsina
Coordinator
Nico Vehse, M.D.
Medical Consultant, Asthma Camp
Medical Director
Barbara Jandasek, PhD, AE-C
Supervisor of Training
Elizabeth McQuaid, Ph.D.
Previous Director, PI Project HARP
Arelis Valerio, MD, AE-C
Diana Jurado
Carol Shelton, RRT, AE-C
Cathy Kempe, RRT, AE-C
Pastora Medina
Renata Tejada
Nurys Medina de Monsanto
Marguerita Arkins
37. CVS/pharmacy Draw A Breath Program
and School Asthma Partnership
Group-based asthma education for families who have children
with asthma (parent and child class; 85 classes per year)
Based on NHLBI guidelines, updated annually; Tailored to
include relevant barriers
Held at Hasbro and RI Public Schools
Funded through insurance reimbursements and donor support
– no out of pocket cost to families
Taxi service and childcare provided
In past 3 years, services provided to over 2000 families
38. CVS/pharmacy Draw A Breath Program
and School Asthma Partnership
Parent Education (one class, 1 ½ hrs)
– Classes are offered in English and Spanish
– Interpreters arranged as needed
– Standard “101” Class and “102”
Child Education
– “Asthma’s Magic Number”, group asthma
educational curriculum for children ages 6-12
– “Quest for the Code”, CD-ROM class, cosponsored by Child Life
39. Community Asthma Programs:
Additional Initiatives
Asthma Camp
35 inner city children with severe asthma
Latino Asthma Support Group
200 families take part in this group annually
Department of Health Collaborations:
– Project CASE: Asthma School Lunch Program
» Provide School Staff Trainings, In-school workshops
– HARP Program: Home-based Environmental Control
40. Asthma Morbidity: Pre-Assessment
56% of caregivers report their child missed
at least 10 days of school in past year
50% had an oral steroid in past year
46% had an ER visit in past year
41. Asthma Management Barriers
17% have a smoker in the home
31% have a pet in the home
30% have a written asthma action plan
7% have seen an asthma specialist
42. After Participation in Class…
ED visits
Average ED Visits Due
to Asthma
(n=552, 51% response rate )
Pre-class baseline
– 1.28 visits per child
12 month follow-up
– .23 visits per child
583 fewer visits since class
cost savings = $179,738
(*calculated using DHS cost for ED visit due to
asthma in FY 2000-01)
(Depue et al., 2007)
ED visits in last year
2000-01
2001-02
2002-03
2
1.5
1
0.5
0
Baseline
12-mo followup
43. Asthma Outcomes: Results
maintained (2012)
After attending class:
– Parents demonstrate improved asthma
knowledge (t=-16.6; p=.0001)
At 4 month follow-up:
– Asthma control is improved (t=-5.46; p=.001)
– Fewer asthma symptoms (t=-2.1, p<.05)
– Decreased ED visits (p=.001)
44. Future Goals for CAP
Reach more families, particularly through our
school-based classes; classes for specific age
groups (pre-school; High School)
Enhance link with family’s provider (beyond
providing summary letter to pcp?)
Continue evaluation efforts; ED visits from
hospital
Continue to reach “hard to reach” families
(through home-based and school-based
programs; HARP and CASE)
45. Project CASE: Controlling Asthma in
School Effectively
A Collaboration between the RI Department of Health: Asthma
Control Program, and the School Asthma Coalition administered
through the RI DOH; a multi-disciplinary community advocacy group
comprised of community providers and organizations
CAP at Hasbro Children’s Hospital
Mission of Project CASE
To improve asthma outcomes, school functioning and overall health and
well-being of urban children with asthma in the school setting
To provide support and training to school personnel in urban settings
To enhance communication between caregivers of children with asthma
and school nurse teachers who support urban children with asthma
46. CASE: Controlling Asthma in School
Effectively
Components of Project CASE
1) The provision of guidelines-based asthma education to
children with asthma during the school day in
elementary school-settings
a) Focus on schools with highest prevalence of asthma and ED use
(through data provided from the Providence plan)
b) Summary of feedback of each child is presented to the school nurse
teacher following each class
47. CASE: Controlling Asthma in School
Effectively
2) Enhanced linkages between the school nurse teacher and
caregivers; ensuring that each child
a) has an asthma action plan at school filled out by their provider
b) has an asthma rescue inhaler
c) is consistently able to participate in school-based activities
3) The provision of guidelines-based asthma training to
school staff
a) School personnel attend training to learn support students’ needs
b) review asthma policies/procedures for the management of asthma
in school setting
48. CASE: Controlling Asthma in School
Effectively
4) The provision of guidelines-based asthma education to
urban caregivers of children with asthma.
-Asthma education provided to the students’ caregivers
-Classes are administered after school in students’ school setting
5) Environmental Walk-Thru
49. CASE: Controlling Asthma in School
Effectively
We are evaluating the effectiveness of Project CASE
30% of the student body of each elementary school, on average, has
asthma
Of the schools that have participated in the program, SNTs report half
the children with asthma, on average, have rescue inhalers in school.
20% have asthma action plans in school
The majority of children don’t self-carry despite self-carry regulation;
rescue inhalers are kept in SNTs office
We assist in enhancing school staff’s awareness of how to respond to
students’ asthma needs in school
50. CASE: Controlling Asthma in School
Effectively
History, Progress and Future Plans
-4th year of Project CASE (previously Asthma Lunch Program)
-Program began with pilot funding from the DOH
-During first 3 years; 20 during-the day school classes
-This year, targeting 4 schools and implementing evaluation
component
-High attendance rates; children attend classes in school with
the permission of their caregiver
51. CASE: Controlling Asthma in School
Effectively
Long Range Goals:
-Expand CASE to more districts and more schools; expand to
middle schools
-Continue systematic evaluation efforts of the program
-Disseminate program
52. Putting it all together
Many factors contribute to poor asthma management and morbidity in
urban school-aged children
Poor asthma control can affect sleep quality; children’s day to day
functioning in school can be compromised, including their learning
– Many areas to intervene:
» Focus on home (trigger control, medication use, link with caregiver and
SNT)
» Focus on school (availability of action plan, rescue inhaler, awareness of
staff, enhance knowledge and efficacy of students, response to symptoms,
trigger control in school); SNTS need support
» Enhance collaboration with provider, link with specialist, if needed
53. Putting it all together
– Use Community Asthma Educational Programs as Resource
– Environmental assessment programs- family and school-based
– Consider:
» Children are at school majority of the day. Management practices at
home influence child’s sleep and learning (e.g., knowledge of rescue
plan, caregivers daily decisions regarding school attendance)
» Identify children who are groggy/sleepy at school may be in poor
control
» Families’ connection with SNT is important; Child’s asthma
medication should be handy at school and asthma action plan; many
barriers
54. Additional Programs Addressing
Students’ Asthma
Asthma, Physical Activity and Obesity (Koinis Mitchell &
Jelalian, NHLBI)
Peer-Administered Asthma Self-Management in Urban
Middle Schools (Koinis Mitchell & Canino, NICHD)
Asthma and Sleep Intervention for Urban Children (Koinis
Mitchell et al, under review)
56. Questions/Feedback
Thank you for participating!
For further questions on this presentation,
email Daphne Koinis Mitchell
DKoinisMitchell@Lifespan.org
For more information about the
Asthma Regional Council of New England,
visit our website:
http://www.asthmaregionalcouncil.org