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Are peak expiratory flow Are peak expiratory flow rates of asthmatics impaired rates of asthmatics impaired by levels of SOby levels of SO22 in the EPA in the EPA
'safe' zone?'safe' zone?The project was reviewed and approved by the University of Medicine and Dentistry of New Jersey’s Institutional Review Board for human subject research at Robert Wood Johnson Medical School & New Jersey Medical School.
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April 13, 2005April 13, 2005Presented to thePresented to the
NJ CLEAN AIR COUNCILNJ CLEAN AIR COUNCILApril 13, 2005 PUBLIC HEARINGApril 13, 2005 PUBLIC HEARING
onon"Air Pollution - Effects on Public "Air Pollution - Effects on Public Health, Health Care Costs andHealth, Health Care Costs and
Health Insurance Costs"Health Insurance Costs"
by Stanley H. Weiss, MDby Stanley H. Weiss, MD
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The full study report is currently draft and is The full study report is currently draft and is undergoing review by the New Jersey undergoing review by the New Jersey Department of Environmental ProtectionDepartment of Environmental Protection(DEP) Division of Science Research & (DEP) Division of Science Research & Technology (DSR) Bureau of Environmental Technology (DSR) Bureau of Environmental Health Science and Environmental Assessment. Health Science and Environmental Assessment. A final report will be provided to the A final report will be provided to the DEP following receipt and responses to any DEP following receipt and responses to any comments. comments.
The report has already been reviewed by DSM.The report has already been reviewed by DSM.
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AUTHORSAUTHORSStanley H. Weiss, MD 1,2,3 Azadeh Tasslimi, BA 1 Amy Davidow, PhD 1
Kathy Belby, RN 1Shahnaz Alimokhtari, MS 4
Clifford P. Weisel, PhD 2,3,4
(1) Department of Preventive Medicine and Community Health, UMDNJ – New Jersey Medical School, 30 Bergen St, Suite ADMC 1614, Newark, NJ 07107, 973-972-4623 [email protected]
(2) UMDNJ School of Public Health(3) Co-Principal Investigators (4) Environmental and Occupational Health Sciences Institute,
UMDNJ – EOHSI/RWJMS, 170 Frelinghuysen Rd, EOHSI 3-314, Piscataway, NJ 08855.
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PURPOSEPURPOSE Determine if changes in Determine if changes in
peak flow expiratory flow rate (PEFR) peak flow expiratory flow rate (PEFR) among among
asthmatic school children asthmatic school children were related to were related to
air pollution from air pollution from sulfur dioxide (SOsulfur dioxide (SO22).).
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SETTINGSETTING
3 3 RuralRural communities in communities in Warren County, NJ (Northwestern NJ)Warren County, NJ (Northwestern NJ)
1. Belvidere 1. Belvidere
2. White Township 2. White Township
3.3. Harmony TownshipHarmony Township
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WARREN COUNTY, NJ
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School SurveysSchool SurveysFall 2002Fall 2002
A survey of asthma symptoms was conducted of all students with A survey of asthma symptoms was conducted of all students with the cooperation of the public schools in the community. In the cooperation of the public schools in the community. In conjunction with review with the school nurses and related f/u, conjunction with review with the school nurses and related f/u, these data were used to determine the actual pediatric and these data were used to determine the actual pediatric and adolescent asthma rates by age, gender and other parameters.adolescent asthma rates by age, gender and other parameters.
Hierarchical estimates of prevalence for Hierarchical estimates of prevalence for the 1641 students (K-12) werethe 1641 students (K-12) were::
““Physician-diagnosed, Current Asthma”Physician-diagnosed, Current Asthma” 11%11%““Undiagnosed Current Respiratory Symptoms,Undiagnosed Current Respiratory Symptoms, that can be consistent with asthma”that can be consistent with asthma” 11%-18%11%-18%““Physician-diagnosed Asthma, Physician-diagnosed Asthma, no current symptoms”no current symptoms” 7%-11%7%-11%““No Evidence of Asthma” No Evidence of Asthma” 57%-71%57%-71%
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PROSPECTIVE STUDY FEBRUARY – JUNE 2003
ELIGIBILITY for ENROLLMENT:
All ‘Physician-Diagnosed’ Asthmatic students enrolled in the public school systems of Belvidere, White Township and Harmony Townships and in grades 5 through 12, who had asthma symptoms during the prior year or had prescription medicine for asthma
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WEB-BASED QUESTIONNAIREWEB-BASED QUESTIONNAIREGOAL: Capture All Relevant Information & Minimize # Of
Questions Asked In Order To Maximize Participation & Compliance Rate
COMPONENTS (SYMPTOMS AND POTENTIAL MODIFIERS):1. General Health, 2. Prevalence & Severity Symptoms Related to Asthma & Resp Problems, 3. Measurement of Peak Expiratory Flow Rate4. Medication Use,5. Encounters w/ Potential Triggers of Asthma (i.e. smoke, animal fur, etc)
DESIGNED WITH PULL-DOWN MENUS SO THAT IT COULD BE COMPLETED ON A DAILY BASIS AND TAKE LESS THAN 10 MINUTES
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AIR-MONITORING SITESAIR-MONITORING SITESAIR POLLUTION LEVELS were collected AIR POLLUTION LEVELS were collected continuouslycontinuously at at 3 MONITORING STATIONS3 MONITORING STATIONS::
SULFUR DIOXIDE (SOSULFUR DIOXIDE (SO22) ) Emitted by Coal-powered plants in the areaEmitted by Coal-powered plants in the areaKnown respiratory irritantKnown respiratory irritant
PARTICULATE MATTER BELOW 2.5 microns (PMPARTICULATE MATTER BELOW 2.5 microns (PM2.52.5))Emitted by combustion processes & formed in atmosphereEmitted by combustion processes & formed in atmosphereSuggested to be linked to cardiovascular & respiratory ailmentsSuggested to be linked to cardiovascular & respiratory ailments
OTHER AIR POLLUTANTS OTHER AIR POLLUTANTS (Volatile Organic Compounds - VOCs) (Volatile Organic Compounds - VOCs)
Data collected periodically on Data collected periodically on 7070 VOCs, but limited number of measurements VOCs, but limited number of measurements
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STUDY PARTICIPANTS:
51% (64/125) of asthmatic students (physician-diagnosed), grades 5-12, were eligible and then gave informed consent to participate
*Higher participation rate in the elementary and middle school than in the high school.
RECRUITMENT INTO STUDY ON ROLLING BASIS:•Start - January 30, 2003•Last student accepted into the study - May 6, 2003
All students were asked to continue to enter data until June 19, 2003. Thus, the potential number of days of data entry varied from 45 to 141 days.
PROSPECTIVE STUDY
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TOTAL # OF STUDENT-DAYS TOTAL # OF STUDENT-DAYS ON WHICHON WHICHSYMPTOMS, MEDICATIONS, SYMPTOMS, MEDICATIONS, AND PEFRAND PEFR ENTERED ENTERED= = 4,7774,777
TOTAL # OF STUDENT-DAYS TOTAL # OF STUDENT-DAYS ON WHICHON WHICHW/ SYMPTOMS & MEDICATIONS, W/ SYMPTOMS & MEDICATIONS, BUT NO PEFRBUT NO PEFR ENTERED ENTERED = = 824 824
TOTAL NUMBER OF TOTAL NUMBER OF STUDENT-DAYS ON WHICH SYMPTOMS & STUDENT-DAYS ON WHICH SYMPTOMS & MEDICATIONS WERE ENTERED MEDICATIONS WERE ENTERED BY PARTICIPANTSBY PARTICIPANTS == 5,6015,601
DATA COLLECTED
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Data ExclusionsData Exclusions• 3 subjects were dropped from analysis who had completed the web-based survey on less than 14 days.
• Data Monitoring during the course of the study suggested that 1 subject had unreliable data; he was contacted during the course of the study and he could not resolve critical inconsistencies. • Inconsistencies noted for other students were all satisfactorily resolved.
This left 60 subjects for analysis.
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STATISTICAL ANALYSISSTATISTICAL ANALYSISOne monitoring site was at Belvidere HS.One monitoring site was at Belvidere HS.Initial statistical analysis was performed using Initial statistical analysis was performed using Belvidere residents only, since SO2 was directly Belvidere residents only, since SO2 was directly measured in their town.measured in their town.
Examined PEFRExamined PEFR– Objective measure of respiratory functionObjective measure of respiratory function– Continuous values, which offers analytic advantagesContinuous values, which offers analytic advantages
Examined medication useExamined medication use– ongoing/prophylactic/in response to problemongoing/prophylactic/in response to problem
Developed mixed modelDeveloped mixed model
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MIXED MODEL•How much the change in peak flow rate is related to other changes (pollution, temperature, and other factors)
•Controls for each individual subject**This is an advantage because PEFR varies with a number of physiological variables, in particular, height, weight, age, & gender (1-6)
Outcome = Natural Logarithm (ln) of PEFRMethod = Mixed Model with a Random (Subject-level) Effect
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MIXED MODELVariables included in Stepwise Assessments:
•Daily and daytime (6am-8pm) - maximum and mean: hourly & 5-minute SO2 •mean SO2 (linear & non-linear terms) •same day, 1- and 2-day lagged SO2•peak and mean same-day, and mean lagged, PM2.5•Above data are from each of the 3 monitoring stations•mean daytime (7am-6pm) temperature•age, gender•same-day medication use (controller)•pollen (trees, grass, weeds, mold)
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Best Fit for ModelBest Fit for Model
• PEAK 5-MINUTE DAYTIME (6AM-8PM) SO2 from Belvidere
• MEAN PRIOR DAY SO2 from Belvidere
• DAYTIME TEMPERATURE (7AM-6PM)
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Same effect of SOSame effect of SO22 seen for White Township students; seen for White Township students; – Consistent with the Belvidere monitoring station being Consistent with the Belvidere monitoring station being
between a major source of SO2 & White Twp between a major source of SO2 & White Twp
No statistical association for students in Harmony No statistical association for students in Harmony TownshipTownship– Harmony in a different direction from the Belvidere Harmony in a different direction from the Belvidere
monitormonitor– other monitoring site also not appropriate for exposure other monitoring site also not appropriate for exposure
characterization for Harmony residentscharacterization for Harmony residents
Harmony Twp residents who attend Belvidere HS Harmony Twp residents who attend Belvidere HS were included in modelwere included in model
Model applied to White & Harmony Model applied to White & Harmony using Belvidere HS SOusing Belvidere HS SO22 Data Data
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FULL MODEL RESULTSDESCRIPTION OF STUDY PARTICIPANTS
HARMONY TWP HS STUDENTS - 4WHITE TWP STUDENTS - 16BELVIDERE STUDENTS - 27
TOTAL IN FULL MODEL ANALYSIS - 47
FEMALES - 28 (60%): MALES - 19 (40%)
Age Mean - 13 yrs Range - 9-19 yrs Median - 13 yrs
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SOSO22 values in Belvidere: Ranged up to - values in Belvidere: Ranged up to -
21 21 ppb for Daily ppb for Daily MeanMean SO SO22
On 16 (On 16 (1111%) of 141 days, %) of 141 days, the daily mean SO2 was the daily mean SO2 was >> 10 ppbppb
331331 ppb for 5-minute Daytime ppb for 5-minute Daytime PeakPeak SO SO22
On 14 (10%) of 141 days, the peak 5-minute SO2 was > 100 ppb
The effect on Peak flow on reaching these 2 levels of SO2 are displayed on the next slide…
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Coefficient Coefficient P-P-ValueValue
% % Reduction Reduction in PEFRin PEFR
5-minute 5-minute Daytime Daytime (6am-8pm)(6am-8pm)
Maximum Maximum SO2 SO2 -0.06932-0.06932 0.00710.0071 -0.69%-0.69%
For a 100 ppb For a 100 ppb increase in SO2increase in SO2
Prior Day Prior Day Mean SO2 Mean SO2 -1.1434-1.1434 0.00040.0004 -1.1%-1.1%
For a 10 ppb For a 10 ppb increase in SO2increase in SO2
Results of Final PROC Mixed Model With All 47 Subjects
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The total variability among the peak flow rates was The total variability among the peak flow rates was not the same for all students; the study’s statistician not the same for all students; the study’s statistician examined the contribution of each of the 47 students examined the contribution of each of the 47 students to the modelto the modelThe statistical association between SOThe statistical association between SO22 levels and levels and peak flow rates appeared to vary with individualspeak flow rates appeared to vary with individuals– 2 students appear highly sensitive2 students appear highly sensitive to SO to SO22
– 3333 students appear to be somewhat sensitive to SO students appear to be somewhat sensitive to SO22
– 1212 students appear not to be sensitive to SO students appear not to be sensitive to SO22
Analyses were conducted to determine which subjects contributed particularly to
the observed associations
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Coefficient Coefficient P-P-ValueValue
% Reduction % Reduction in PEFRin PEFR
Very Sensitive Very Sensitive Subjects (n=2)Subjects (n=2)
SO2 5-minute SO2 5-minute Daytime Max Daytime Max -0.3174-0.3174 <0.0001<0.0001 -3.1%-3.1%
For a 100 ppb For a 100 ppb increase in SO2increase in SO2
SO2 Prior Day Mean SO2 Prior Day Mean -5.9878-5.9878 <0.0001<0.0001 -5.8% -5.8% For a 10 ppb For a 10 ppb increase in SO2increase in SO2
Somewhat Somewhat Sensitive Sensitive Subjects (n=33)Subjects (n=33)
SO2 5-minute SO2 5-minute Daytime MaxDaytime Max -0.07286-0.07286 0.03260.0326 -0.73% -0.73%
For a 100 ppb For a 100 ppb increase in SO2increase in SO2
SO2 Prior Day Mean SO2 Prior Day Mean -8.7320-8.7320 0.04040.0404 -0.87% -0.87% For a 10 ppb For a 10 ppb increase in SO2increase in SO2
Post-hoc sub-group Multivariate analyses
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Student A – Bivariate Display of DataBelvidere resident, grade 7, male
5-minute Daytime SO2 Max vs. ln of Peak FlowUnivariate Analysis
y = -0.1358x + 6.4426R2 = 0.0067
atSO2=0, ln(pf)=6.443
SO2=0.100ppm, ln(pf)=6.429-1.4% in peak flow
5.6
5.8
6
6.2
6.4
6.6
6.8
0 0.1 0.2 0.3 0.4SO2 5-min daytime max (ppm)
ln of P
F
Subject ALinear (Subject A)
Prior Day SO2 Mean vs. ln of Peak FlowUnivariate Analysis
y = -7.7717x + 6.4699R2 = 0.165
at SO2=0, ln(pf)=6.470at SO2=0.01ppm, ln(pf)=6.392
-7.5% in peak flow
5.6
5.8
6
6.2
6.4
6.6
6.8
0 0.005 0.01 0.015 0.02 0.025Prior Day SO2 Mean (ppm)
ln of P
F
Subject ALinear (Subject A)
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Student B – Bivariate Display of DataWhite Twp resident, grade 5, male
5-minute Daytime SO2 Max vs. ln of Peak FlowUnivariate Analysis
y = -0.1866x + 5.8107R2 = 0.0102
at SO2=0, ln(pf)=5.811at SO2=0.100ppm, ln(pf)=5.792
-1.9% in peak flow
5
5.1
5.2
5.3
5.4
5.5
5.6
5.7
5.8
5.9
6
0 0.1 0.2 0.3 0.4SO2 5-Minute Daytime Max (ppm)
ln of P
F
Subject BLinear (Subject B)
Prior Day SO2 Mean vs. ln of Peak FlowUnivariate Analysis
y = -10.379x + 5.8396R2 = 0.2174
at SO2=0, ln(pf)=5.840at SO2=0.01ppm, ln(pf)=5.736
-9.9% in peak flow
5
5.1
5.2
5.3
5.4
5.5
5.6
5.7
5.8
5.9
6
0 0.005 0.01 0.015 0.02 0.025Prior Day SO2 Mean (ppm)
ln of P
F
Subject BLinear (Subject B)
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Association betweenAssociation between Mean Prior-DayMean Prior-Day SOSO22 and PEFR and PEFR
This model predicts overall for the 47 students, that for a 10 parts per billion (ppb) increase in prior-day mean SO2 there is an average decrement in PEFR of 1.1%.
For the 2 most sensitive students, this effect was roughly 6 times greater (-5.8%), and this magnitude of effect could be of clinical significance.
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This model predicts overall for the 47 students, that for a 100 ppb increase in peak same-day SO2 there is an average decrement in PEFR of 0.69%
For the 2 most Sensitive Students, this effect was nearly triple (-3.1%).
Association between Max Same-Day SO2 & PEFR
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CURRENT FEDERAL GUIDELINESCURRENT FEDERAL GUIDELINESSOSO22 Air Quality Standards Air Quality Standards
A guideline has been proposed by the US Environmental Protection Agency (EPA), based on the conclusion that in some localized situations, 5-minute SO2 concentrations above 1600 µg/m3 might pose a health threat to sensitive individuals. [Draft Guideline Document for Ambient Monitoring of 5-Minute SO2 Concentrations, EPA, Office of Air Quality Planning and Standards, Research Triangle Park, NC, July 20, 2000; see also http://airqap.com/monitoring/Benchmarks%20for%20SO2%20&%20PM25.htm ].
This corresponds to an average over the five minutes of 615 ppb.
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CURRENT FEDERAL GUIDELINESCURRENT FEDERAL GUIDELINESSOSO22 Air Quality Standards Air Quality Standards
Most air pollution monitors measure the amount of pollution in the air on almost a continuous basis.
Current guidelines assume that higher levels of pollution can be tolerated without effect for short periods of time.
Thus, the National Ambient Air Quality Standards have an averaging time as well as a concentration associated with them. Typically, the longer the averaging time is, the lower is the level of the standard.
The averaging times utilized in development of standards represent simplifications of a more complicated statistic. Refer to 40 CFR Part 50 (in the Code of Federal Regulations) for guidance on how the standard are required to be computed for regulatory purposes.
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SUMMARYSUMMARY We observed significant effects on peak flow rate at
levels well below the federal 24 hour standard (mean daily value) for SO2 of 140ppb, which had been set to deal with short term effects in the overall population.
Some asthmatics appear to be especially sensitive to SO2. Relatively low levels of SO2 had a magnitude of effect on respiratory function that raise clinical concern.
Our data suggest that even more transient exposure, to levels far below this guideline, may pose a health threat to sensitive individuals.
Further analyses to examine asthma symptoms are in progress.
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LIMITATIONSLIMITATIONSThe grouping of which students were most The grouping of which students were most sensitive to SO2 was determined through data sensitive to SO2 was determined through data analysis, not analysis, not a priori.a priori.
Thus, further follow-up may be useful to Thus, further follow-up may be useful to prospectively assess whether the same students prospectively assess whether the same students remain sensitive. However, if medication remain sensitive. However, if medication regimens change, this might affect sensitivity. regimens change, this might affect sensitivity. Modeling to incorporate medication changes Modeling to incorporate medication changes may be useful, but will be complicated.may be useful, but will be complicated.
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LIMITATIONSLIMITATIONS
• The statistical association does not rule out that the effect is due to an unmeasured factor that correlates with both SO2 and peak flow.
• The study was conducted in a single region, and thus cannot be assumed to necessarily generalize to other communities.
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RECOMMENDATIONSRECOMMENDATIONS Given that some persons may be
especially sensitive to SO2, the definition of what constitutes a “safe level” may need to be revised.
Some asthmatics may need to be especially cognizant of SO2 pollution in their region and may need to attempt to modify their exposure when levels are high.
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AcknowledgementsSupported in part by grants from Roche Vitamin (DSM) Inc through the SEP Mechanism of NJ Department of Environmental Protection - see also http://dsmcap.com/ Students & their families who took time to make the entries
Special thanks are due to Beecher Zollinger, MD and the school nurses Jill Broscius, RN, Lynn Serniuk, RN, Lois Hampshire, RN, and Donna Golda, RN.
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ReferencesReferences (1) Knudson RJ, Slatin RC, Lebowitz MD, Burrows B. The maximal expiratory flow-
volume curve. Normal standards, variability, and effects of age. Am Rev Resp Dis 1976; 113:587-600.
(2) Quackenboss JJ, Lebowitz MD, Krzyzanowski M. The normal range of diurnal changes in peak expiratory flow rates. Am Rev Resp Dis 1991; 143:323-330.
(3) Krzyzanowski M, Quackenboss JJ, Lebowitz MD. Peak expiratory flow rates and symptoms to ambient ozone. Arch Environ Health 1992; 47(2):107-115.
(4) Chiang ST, Han TS. Peak flow rate in relation to age, sex, and anthropometric measurements. Acta Paediatr Scand 1965; 54:439-445.
(5) Hegewald MJ, Capo RO, Jensen RL. Intraindividual peak flow variability. Chest 1995; 107(1):156-161.
(6) Polgar G, Promadhat V. Standard Values: Peak expiratory flow rates and normal values. Pulmonary function testing in children: Techniques and standards. Philadelphia: W.B.Saunders Company, 1971. Pages: 188-194.
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Related Presentations from this StudyRelated Presentations from this Study 1. Tasslimi A, Weisel CP, Belby K, Morales L, Lee N, Weiss SH. Apparent prevalence of
adolescent asthma: impacts of asthma definition and sources of information. The 8th Annual Public Health Symposium, held at Rutgers University, Piscataway, NJ, April 7, 2003.
2. Diamond AC, Weisel CP, Lee N, Weiss SH. Design and implementation of an Internet-based questionnaire for daily ascertainment of asthma status in a prospective study. The 8th Annual Public Health Symposium, Rutgers University, Piscataway, NJ, April 7, 2003.
3. Diamond AC, Weisel CP, Lee N, Weiss SH. Design, implementation and monitoring of Internet-based prospective data collection in an epidemiologic study of asthma and the environment. Research Symposium on Genomics, Proteomics, Pharmacogenomics and Bioinformatics. Robert Wood Johnson Medical School, Piscataway, NJ, May 9, 2003.
4. Weiss SH, Tasslimi A, Lee N, Alimokhtari S, Morales L, Hom HL, Weisel CP. Understanding the prevalence of asthma in a community: Impacts of study design and definition. The 131st Annual Meeting (November 15-19, 2003) of the American Public Health Association, San Francisco, Session 4262.0 [Tues, Nov 18, 2003], Abstract #60074.
5. Weisel CP, Weiss SH, Tasslimi A, Diamond A, Alimokhtari S. Use of a web-based questionnaire to collect exposure and symptom data in asthmatic adolescents [abstract].
In: Abstract Book - 14th Annual Conference of the International Society of Exposure Analysis; 2004 Oct 17-21; Philadelphia, PA. Platform W2C Exposure and Health Interface; Abstract number W2C-03; p 290.
6. Weiss SH, Tasslimi A, Davidow AL, Weisel CP. Are peak expiratory flow rates of asthmatics impaired by levels of SO2 in the EPA 'safe' zone? The 132nd Annual Meeting (November 2004) of the American Public Health Association, Washington DC, Session 3118.0: Monday, November 8, 2004 (oral).
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Supplemental SlidesSupplemental Slides
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ADVANTAGES IN ADVANTAGES IN USING A WEB-BASED USING A WEB-BASED
QUESTIONNAIREQUESTIONNAIRE
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POTENTIAL ADVANTAGESPOTENTIAL ADVANTAGESPAPER VERSIONPAPER VERSION
Administration of Administration of daily daily questionnaires can questionnaires can be time and labor be time and labor intensive, paper intensive, paper needs periodic needs periodic retrievalretrieval
WEB BASEDWEB BASED
Web based system Web based system accessed by accessed by participate at participate at his/her his/her convenience, entry convenience, entry often faster, contact often faster, contact with staff minimizedwith staff minimized
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PAPER VERSIONPAPER VERSION
Compliance, Compliance, particularly for particularly for children/adolescents, children/adolescents, is often low for daily is often low for daily questionnairesquestionnaires
Compliance rate Compliance rate unknown until unknown until attempting to retrieve attempting to retrieve datadata
WEB BASEDWEB BASED
Children/adolescents Children/adolescents are on computers are on computers daily so smaller daily so smaller intrusion in their intrusion in their lives lives
Compliance checked Compliance checked in real timein real time
POTENTIAL ADVANTAGESPOTENTIAL ADVANTAGES
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PAPER VERSIONPAPER VERSION
Paper questionnaires Paper questionnaires require subsequent require subsequent entry with associated entry with associated transcription errorstranscription errors
WEB BASEDWEB BASED
Data is directly added Data is directly added to data base, minimal to data base, minimal errorserrorsChecks can be made to Checks can be made to restrict to valid entriesrestrict to valid entriesData can be reviewed Data can be reviewed quickly so participants quickly so participants can be contacted for can be contacted for questionsquestions
POTENTIAL ADVANTAGESPOTENTIAL ADVANTAGES
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SURVEY INSTRUMENTSURVEY INSTRUMENTSection 1 (28 questions)Section 1 (28 questions)
Details on symptoms, triggers, location and peak Details on symptoms, triggers, location and peak flow rateflow rate Each includes time of day & duration Each includes time of day & duration
Section 2Section 2Details on medication takenDetails on medication takenAmount and time of dayAmount and time of day
Picklist and check box entriesPicklist and check box entriesEntry for current and previous two days permittedEntry for current and previous two days permittedStop & restart after each major section possibleStop & restart after each major section possible
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The home page contains a login, relevant links, important announcements, and information.
These are changed periodically.
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SYMPTOM SECTIONSYMPTOM SECTIONTracking of individual health and asthma Tracking of individual health and asthma related symptoms along with when problems related symptoms along with when problems occurredoccurredExposure to asthma triggers (smoke, Exposure to asthma triggers (smoke, allergens, animal, etc)allergens, animal, etc)What microenvironments visitedWhat microenvironments visitedPeak flow rates (up to 4 values)Peak flow rates (up to 4 values)Summary verification provided before savingSummary verification provided before savingInternal checks for general and specific Internal checks for general and specific symptomssymptoms
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2005 April 132005 April 13 4747
MEDICAL USE SECTIONMEDICAL USE SECTIONComprehensive medication tracking Comprehensive medication tracking includes time of intake and dosageincludes time of intake and dosage A user’s medications are chosen from a A user’s medications are chosen from a medication database medication database (contains over 200 medications, both (contains over 200 medications, both prescription and over the counter, prescription and over the counter, characterize by type).characterize by type).Checks for medicine combinations and Checks for medicine combinations and dosage that are not medically advisabledosage that are not medically advisable
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CONCLUSIONSCONCLUSIONS
Web Based Questionnaires are Web Based Questionnaires are feasible for daily entry from feasible for daily entry from adolescent and children (grades 4 – adolescent and children (grades 4 – 12) – data from 64 students over 2 – 4 12) – data from 64 students over 2 – 4 months obtainedmonths obtained
Real time monitoring can help Real time monitoring can help improve compliance and qualityimprove compliance and qualityWhen combined with telephone/ When combined with telephone/
e-mail reminders and incentivese-mail reminders and incentives
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CONCLUSIONSCONCLUSIONS(continued)(continued)
Data entry errors are greatly reducedData entry errors are greatly reduced
Entry can be more rapid than paper – Entry can be more rapid than paper – (only 5 – 10 minutes per day required)(only 5 – 10 minutes per day required)
Has potential for use in large Has potential for use in large epidemiological studies for population epidemiological studies for population who typically access computerwho typically access computer
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PILOT STUDYPILOT STUDY10 students, grades 5-12, with physician-diagnosed asthma, were enrolled in a Pilot Study to:
1) Verify that web site functioned correctly
2) Verify accuracy of Data Collection
3) Elicit feedback from students to improve Site for ease of entry
4) Field-tested Baseline Questionnaire that ascertained the general health of the subjects and their medication; medication data were used to individualize the web questionnaire for each subject.
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Confirmation of Validity of Confirmation of Validity of Survey ResponsesSurvey Responses
All data were first reviewed to verify that no inconsistencies existed in the input that might have resulted from either inadvertent or intentional errors.
Each subject’s responses were plotted chronologically to examine trends in the data and for individual data points that differed from the previous and next days data.
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Least Sensitive SubjectsLeast Sensitive Subjects ((n=12n=12))
CoefficientCoefficient P-valueP-value
SO2 5-minute Daytime Maximum SO2 5-minute Daytime Maximum 0.0063070.006307 NSNS
SO2 Prior Day Mean SO2 Prior Day Mean -0.00048-0.00048 NSNS
Post-hoc Sub-group Multivariate Analyses of the “Least Sensitive Subjects”
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MIXED MODELAccounts for different number of repeat measurements made on each individual
Implements random effects in a statistical model framework & permits modeling the covariance structure of the data• It can compute efficient estimates of fixed effects and valid errors estimates within the Generalized Linear Modeling (GLM) procedure. • It is important to model the covariance structure for repeated measures data because measurements taken close in time are often highly correlated. • A log transformation of the peak flow rate was done so that the dependent variable of the GLM was close to normally distributed.
