Winthrop Community
Health Survey
Winthrop
Environmental Health Facts Subcommittee
(Winthrop Airport
Hazards Committee)
Winthrop Board of
Health
AIR
Brian Dumser, PhD,
CIH
Chair of the
Subcommittee
August 18, 1999
Summary
In many communities located close
to major airports, power generation facilities, or other major industries,
there is a strong perception that pollution generating activities at these
facilities result in a direct negative impact on the health of residents. Statements to this effect have been
repeatedly voiced by representatives of the communities surrounding Logan
airport, but, absent hard data in the existing record, no action has been taken
by responsible authorities to investigate further. Currently, plans are underway for the construction of additional
facilities Logan airport which will markedly increase operational capacity and
the generation of pollutants. While
potent arguments in favor of this expansion are being presented from an
economic standpoint, once again no consideration is being given to the possible
public health impact.
In light of the failure to
address this issue by Massport, or by Federal or State regulatory authorities,
the Winthrop Environmental Health Facts Subcommittee, a voluntary group made up
of residents of the Town of Winthrop Massachusetts, elected to address the
question directly. A strong correlation
is known to exist between exposure to petrochemical exhaust emissions and a
variety of respiratory and cardiovascular diseases (1-10). Logan airport
estimates its daily production of such pollutants at approximately 50,000
pounds per day (11). The Subcommittee undertook a survey to determine whether a
correlation also exists between frequency and severity of respiratory disease
and level of exposure to these pollutants as determined by location in Winthrop
relative to the airport.
The results of this survey demonstrate that a clear increase in
several respiratory diseases and disease symptoms exists between areas of the
Town which are adjacent to the airport, and those more distantly located on
Broad Sound. In fact, for the most
common respiratory diseases, asthma and allergy, disease is twice as common in
the most heavily exposed neighborhood as it is in the least exposed. Finding no other likely explanation for this
effect, the Subcommittee proposes that airport activities, most likely the
generation of airborne pollution from the combustion of gasoline and kerosene,
are indeed negatively affecting the health of the residents of Winthrop.
The implications of these
findings are serious. While the unique
geography and demographics of Winthrop provided a situation where the effects
of airport generated pollution could be studied in isolation from other
pollutant sources, Winthrop is by no means the only community impacted, nor the
community most highly impacted by airport activity-generated emissions. As
sample size determines the sensitivity of the analysis, only the most
frequently occurring respiratory diseases could be adequately tested. Thus, while the case can be made strongly
for asthma and allergenic disease, effects on other less common serious or
life-threatening respiratory and cardiopulmonary conditions which are also
linked to fuel exhaust exposure remain an unexplored possibility. Finally,
while the study convincingly
illustrates the difference in impact due to relative exposure level, it does
not define a level of exposure where impact is minimal or tolerable. In brief, the study demonstrates that serious damage is being done to the
health of the residents of Winthrop at current levels of airport activity, and
this damage correlates with location, a measure of exposure to airport
activity-generated pollution. The
Subcommittee feels it is incumbent on State regulatory authorities responsible
for the public health to further investigate this matter, to further define the
scope and severity of the problem, and initiate processes which will return our
community to the state of health enjoyed by the majority of Massachusetts
citizens.
Introduction
Winthrop is a peninsula which
extends from East Boston south by south east to form the division between Broad
Sound, on its eastern shore, and Boston Harbor on its western shore. A portion of the western shore entirely
encloses, and closely approaches Logan airport. Winthrop is subjected to a variety of disturbances from the
airport, including excessive noise and odors from burned and unburned fuel. Although Logan carries out no air pollution
monitoring in the surrounding communities, their published estimates from
modeling studies indicate approximately 50,000 pounds of airborne pollutants
are released daily, primarily from the combustion of Jet Fuel A. Elsewhere it has been shown that a strong
correlation exists between exposure to such pollutants and a variety of
respiratory and cardiovascular diseases including lung cancer, chronic
obstructive pulmonary disease, asthma and allergic rhinitis (1-10). Individuals residing in communities surrounding
Logan airport show a considerably higher incidence of these diseases compared
to the statewide average (12-14). It
has not been possible to determine whether Logan airport activities contribute
substantially to this health burden however, since the urban location of these
communities presents a complex picture of pollution sources, including
petrochemical pollution from power plants, industries, and heavy road traffic.
Winthrop, by contrast, is a
stable, mature residential community without significant pollution sources
except for the airport. Despite this
fact, asthma incidence in Winthrop closely mirrors that in the mainland
communities which abut the airport, and lung cancer rates for females is 50% higher
than the statewide average (14). Some
neighborhoods in Winthrop are located within a few hundred feet of major
airport runways, while others are located as much as a mile and a half
away. Residents report a marked
difference in perception of chemical odors from the airport in relation to location
in the Town, indicating that different levels of exposure occur within the Town
resulting from distance from the airport and wind direction. In consideration of these facts, this study
was conducted to determine whether any correlation exists between the level of
exposure to air pollutants generated by airport activity and the incidence of
and frequency of symptoms to respiratory disease.
Methods
The Town was divided into 10
neighborhoods, primarily on the basis of natural topography, containing between
1,000 and 2,500 residents each. Two neighborhoods were selected as
likely representing areas of highest
(#1, Court Road, and #2, Cottage Park), and lowest (#5, Winthrop Beach, and #6,
Winthrop Highlands) exposure. A
questionnaire was devised, consisting of 30 questions to obtain information on
the incidence of diagnosed asthma, allergies, chronic bronchitis, chronic
sinusitis, and emphysema, and on the frequency of symptoms experienced. Standard demographic information was also
obtained on gender, age, and the duration of residence in the
neighborhood. A smoking history was
obtained, and information on the frequency of perception of odors caused by
airport-related activities. Responses
to questions on diagnosed disease incidence were yes/no, followed by a question
on time since onset. Responses to
questions on symptom frequency included none and either 4 or 5 frequency
ranges.
Interviews were conducted by
volunteers from the community who were trained in requirements for objective
data collection, chain-of-custody, and anonymity requirements. Interviews were conducted 4 weekday evenings
per week, between the hours of 6:30 and 8:30 PM. Team leaders assigned streets to the interviewers. Every residence in the neighborhood was
approached, one time only, until the entire neighborhood was canvassed. All residences, single and multiple family
dwellings and apartment complexes were sampled, with the exception of
mechanically ventilated buildings. No
commercial establishments were encountered in the zones polled. In this manner,
a random sample of residents was polled which averaged approximately 18% of the
population of the selected neighborhood.
The only exception to this was neighborhood 5, the last area
sampled. Activity was continued in this
area, progressing from north to south, until the desired quota of 500
interviews each in low and high exposure areas was obtained. Each questionnaire was identified only by
neighborhood, and no names or addresses were collected. The questionnaires were collected each
evening and held centrally.
Following data entry, the
database was screened to exclude unsuitable responses. Corrections were made to the database where
possible, for example intelligible but non-numerical responses. Questionnaires with critical data missing or
internally contradictory responses were excluded. Data was also discarded for individuals residing in the
identified zone for less than one year, or who were not in residence for at
least four days per week. All such
changes were recorded. Of the 1000
questionnaires obtained, 838 were admissible, 430 from the high-exposure zone
(Area 1 - 172; Area 2 - 258) and 408
from the low-exposure zone (Area 5 - 197;
Area 6 - 211).
In light of the seriousness of
the effects on human health, and the truncated timetable presented by airport
expansion activities, simplified exploratory statistical analyses were first
carried out by excluding from the data all individuals not smoke-free for the
past five years. Data from high
exposure (areas 1 and 2) and low exposure (areas 5 and 6) zones were pooled,
and symptom frequency compared by chi-squared contingency analysis. The results of this analysis formed the
basis for an earlier report which was presented by the Caucus on Air
Transportation to representatives of the state government July 1, 1999.
While that approach provided a
convincing and statistically significant demonstration of the differential
effect of location on disease incidence, the dataset contains more information
which can be accessed by more sophisticated analyses. To this end, the Subcommittee contracted the services of an
epidemiological analytical firm, John Snow Inc., to further analyze the
data. SAS software was employed to
re-incorporate smokers into the study, correcting for smoking history, age and
sex by means of the Mantel-Haenszel Test.
Additional statistical analyses were performed with Epi Info V6
(15). Further, it was noted that while
low-exposure zones 5 and 6 were essentially equivalent, high exposure zones 1
and 2 showed a differential from one another which was consistent with position
relative to the airport. Contingency
analysis was thus carried out for each of these zones separately, compared to
the joined low-exposure population 5 and 6.
The complete set of statistical analyses, identification and criteria
for data exclusion, complete and amended datasets, and original survey
questionnaires are on file with the Winthrop Board of Health.
Results
Table 1.
Frequency of Odor
Perception
% Response on Scale 0
- 100 (Days/Year)
|
Area
|
0
|
1
|
12
|
25
|
50
|
100
|
Median
|
|
1
|
12.8 %
|
1.2 %
|
4.7 %
|
8.7 %
|
14.5 %
|
58.1 %
|
100 %
|
|
2
|
13.6 %
|
3.9 %
|
8.9 %
|
8.6 %
|
16.7 %
|
48.2 %
|
50 %
|
|
5
|
61.4 %
|
2.5 %
|
1.5 %
|
4.6 %
|
7.1 %
|
15.2 %
|
0 %
|
|
6
|
37.9 %
|
3.3 %
|
9.5 %
|
12.3 %
|
9.0 %
|
28.0 %
|
12 %
|
Table 2.
Relative Risk
High Exposure Area 1
vs Pooled Low Exposure Zone (Areas 5 + 6)
Total Sample
Size - 580
|
Disease
|
Total Cases
|
Relative Risk*
|
p value**
|
|
Allergy
|
202
|
2.18
|
0.001
|
|
Asthma
|
95
|
1.97
|
0.004
|
|
Chronic Sinusitis
|
110
|
1.41
|
0.085
|
|
Chronic Bronchitis
|
45
|
1.25
|
0.5
|
|
Emphysema
|
14
|
1.18
|
0.76
|
Table 3.
Direct evidence of this
differential local concentration was sought in the survey. Frequency of perception of fuel and rubber
odors was sampled in each neighborhood, and the responses converted to an
approximately linear scale from 0 (never) to 100 (two or more times per week). Results (Table 1) were consistent with
spatial location, with mean scores ranging from approximately 30 in zones 5 and
6 to 60 and 69 in zones 2 and 1. Median
scores were 0 (never) in zone 5, 12 (once per month) in zone 6, 50 (once per
week) in zone 2 and 100 (two or more times per week) in zone 1. While it is clear that only direct
monitoring can establish actual and relative concentrations of these
pollutants, sufficient information has been presented here to justify the
classifications of low (areas 5 and 6), moderate (area 2) and high exposure
(area 1).
Disease Incidence.
Ten questions were posed
regarding the presence of each of five respiratory diseases which have been
correlated with exposure to fossil-fuel exhaust , and the date of onset of the
disease. The wording of the questions stressed that the diagnosis had to have
been made by a physician ( “Have you ever been told by a Doctor that you
have...”), and this fact of clinical diagnosis reinforced with an approximate
date of diagnosis. Thus, while the
replies to these questions are self-reported diagnoses, and actual incident
rates derived from them should be viewed with that qualification, they are
presmed to be reasonably truthful and
at least should not be affected by reporting bias between different areas
sampled. Bias on the part of the
interviewer is also controlled in part by the binary response (yes/no)
recorded. It should be further noted
that the initial sampling strategy presented to the interviewers who were also
members of the Subcommittee which defined the study was a sampling of highest
expected and lowest expected exposure zones.
The initial report presented by the committee was analyzed within that
paradigm, and only further analyzed by individual zones following recognition
of real response difference between zones 1 and 2. It is very unlikely that the interviewers regarded these two
contiguous neighborhoods as different in terms of exposure level during the
course of the survey, and the existence of substantial difference in response
indicates an absence of interviewer bias.
Tables 3 and 4 show that a very
clear increase in diagnosed disease exists in the neighborhoods in close
proximity to the airport relative to the more remote locations. Further, while areas 1 and 2 are contiguous,
the epicenter of area 2 is approximately twice the distance from the airport as
that of area 1. Relative risks were
calculated, controlling for possible confounding variables of sex, age and smoking
history. In fact, all four neighborhoods
are demographically very similar, and little effect of these variables was
noted. Estimates of the reliability of
the predicted relative risks, as
indicated by the p values, are influenced both by the magnitude of the
difference and the frequency of the
disease in the population. For the
three most prevalent conditions, allergy, asthma, and chronic sinusitis, the
existence of a clear increase in frequency with position closer to the airport
is striking. Further, the size of the
difference is also impressive. For
allergy and asthma, the most highly exposed population experiences a two-fold
increase in disease incidence compared to the least exposed neighborhoods.
As mentioned above, these
incident rates (Table 4) are a reasonable estimate of the level of diagnosed
disease in the sample group, although they should not be compared to other
studies which are primarily based on hospitalization rate or mortality. The rates presented here are consistent
throughout the population under study, and appropriate for analysis of
spatially-located differences in disease rate among the subgroups of that
population. They do however include
historical cases, and well-controlled or other asymptomatic conditions which
would not appear for example in the Massachusetts Disease Registry. However, they do represent negative impacts
on the health of the community, and to place these figures in a more human
context, predictions on the effects of this differential are presented in Table
4. This estimates that, in areas 1 and
2, contiguous neighborhoods with a combined population of about 3200 people,
there are 220 individuals with asthma, 435 with allergies, and 131 with chronic
sinusitis whose condition is correlated with their location relative to Logan
airport.
Symptom frequency
In contrast to the clear
differences demonstrated for disease incidence, symptom frequency presents a
much more complex picture. Table 6
illustrates symptom frequency for the five diseases sampled in each zone, as
mean values within an approximately linear scale from 0 to 100. Results are highly variable, and overall
scores low due to the high percentage in each group of asymptomatic
respondents. It is probable that the sample size employed is insufficient to
adequately characterize differences in the much smaller symptomatic subset, and
the results should be regarded as inconclusive. The results reinforce rather than contradict data presented on
disease incidence distribution however.
If the responses are recast as binary elements (Table 7. Symptomatic vs Asymptomatic, grouped by
functional pathology) a differential of approximately 50% again emerges between
the pooled high exposure and low exposure zones.
References:
1 Abbey DE,
Ostro BE, Petersen F, Burchette RJ.
Chronic respiratory symptoms associated with estimated long-term ambient
concentrations of fine particulates less than 2.5 microns in aerodynamic
diameter (PM2.5) and other air pollutants.
J Expo Anal Environ Epidemiol 1995 5: (2) 137-159
2 Bhatia R,
Lopipero P, SmithAH Diesel Exhaust
Exposure and Lung Cancer. Epidemiology
1997: 8 : 364
3 Brunekreef
B, Janssen NAH, de Hartog J, Harssema H, Knape M, van Vliet P Air Pollution from Truck Traffic and Lung Function in Children
Living near Motorways. Epidemiology 1997; 8 : 298
4 Dockery DW,
Pope CA III, Xiphing X, Spengler JD, Ware JH, Fay ME, Ferris BG, Speizer
FE. An association between air
pollution and mortality in six US cities.
New England Journal of Medicine, 1993
329: (24) 1753-1760
5 Duhme H,
Weiland SK, Keil U, Kraemer K, Schmid
M, Stender M, Chambless L The Association between Self-Reported
Symptoms of Asthma and Allergic Rhinitis and Self-Reported Traffic Density on
Street of Residence in Adolescents.
Epidemiology 1996;7:578582
6 LoomisD,
Castillejos M, Gold DR, McDonnell W, Borja-Aburto VH Air Pollution and Infant
Mortality in Mexico City. Epidemiology
1999; 10: 118
7 Moolgavkar
SH, Luebeck EG, Anderson EL Air Pollution
and Hospital Admissions for Respiratory Causes in Minneapolis-St. Paul and Birmingham Epidemiology 1997: 8: 364
8 Schwartz
J Air Pollution and Hospital
Admissions for Cardiovascular Disease in
Tucson. Epidemiology 1997; 8 :
371
9 Sheppard L,
Levy D, Norris G, Larson TV, Koenig
JQ Effects of Ambient Air Pollution
on Nonelderly Asthma Hospital Admissions in Seattle, Washington, 1987-1994
Epidemiology 1999; 10: 225
10 Verhoeff
A, Hoek G, Schwartz J, van Wijnen JH Air Pollution and Daily Mortality in Amsterdam Epidemiology 1996; 7: 225 230
11 Logan
Airside Improvements Planning Project Volume IV 1999 EOEA #10458
12 Boston
Neighborhood Health Status Report: The Health of South Boston. Boston Department of Health and Hospitals,
Division of Public Health, Office of Research and Health Statistics. November 1994
13 The Health
of Boston 1998. Boston Public Health
Commission, Office of Research, Health Assessment and Data Systems, Boston
Massachusetts 1998
14 Massachusetts
Community Information Health Profile, Massachusetts Department of Public
Health, Bureau of Health Statistics and Evaluation, Boston Masachusetts.
15 Dean AG,
Dean JA, Coulombier D, Brendel KA, Smith DC, Burton AH, Dicker, RC, Sullivan K,
Fagan, RF, Arner, TG. Epi Info Version
6: a word processing, database and statistics program for public health on
IBM-compatible microcomputers. Centers
for Disease Control and Prevention, Atlanta, Georgia, USA, 1996
16 Beychok
MR. Error Propagation in Air Dispersion
Modleing. Newport Beach CA
Winthrop
Environmental Health Facts Subcommittee
Members of the
Subcommittee Conducting the Survey
Barbara Bishop
Madeline Burke
Eleanor Casey
Greg Curci
John Dowd
Brian Dumser
Arthur Flavin, Sr.
Barbara Corbett
Flavin
Connie Mara
John Marcy
Harvey Maibor
Bob Massa
Kathleen Mccauley
Ellie Olivolo
Judith Silck
Claire Sweeney
Winthrop Air Activist Community Health Survey
With the Winthrop Board of Health
This questionnaire is intended to
establish relevant information regarding the incidence and severity of
respiratory disease in the Town of Winthrop. Make sure that the respondent
understands that nowhere on the questionnaire is there any information that
identifies him or her in any way.
Special Instructions:
However, since in the future we may want to more quickly and efficiently
reassess this information, it is desirable that we establish a means a
communicating with environmentally sensitive individuals (those answering 'yes'
to questions 17,19, or 21). Ask such
individuals if they would be willing to participate further (essentially answer
the same questions again at different times of the year), and if so may we
identify them by address only. If you
obtain their verbal permission, write the full address in your notebook, along
with the number of the question answered in the affirmative.
Enter one answer for each
question on the Survey Response Form (“SRF”).
Complete an SRF for EACH member of a household.
________________________________________________
1. Sex of respondent.
0=Male If the sex of the respondent
is Male, enter a ZERO (0) on the SRF Q1.
1=Female If the respondent is Female,
enter a ONE (1) on the SRF Q1.
2. Age. How old are
you (is the respondent)?
0=0-5 If the respondent is
between 0 and 5 (including 5), enter a ZERO (0) on the SRF Q2.
1=6-12 If the respondent is between
6 and 12 (including 6 and 12), enter a ONE (1) on the SRF Q2.
2=13-20 If the respondent is between
13 and 20 (including 13 and 20), enter a TWO (2) on the SRF Q2.
3=21-40 If the respondent is between
21 and 40 (including 21 and 40), enter a THREE (3) on the SRF Q2.
4=41-60 If the respondent is between
41 and 60 (including 41 and 60), enter a FOUR (4) on the SRF Q2.
5=61
and above If the respondent is 61 or
over, enter FIVE (5) on the SRF Q2.
3. Current location. This
is your (the respondent’s) current residence?
0-9 Enter the grid
number, from the map supplied, of the current location (0 through 9) on SRF Q3.
4. Duration at Current
Location. How long have you
(the respondent) been living at this location?
0=Less
than 1 If response is less than 1
year, enter a ZERO on the SRF Q4.
1-8
= 1-8 If the response is between (and including) 1 thru 8 years, enter the
number (1-8) on the SRF Q4.
9=
=>9 years If the Response is 9
years or more, enter a 9 in the SRF Q4.
5. Previous location. Where did you (the respondent) live
just prior to moving to this location?
0-9 Enter the grid
number, from the map supplied, of the current location (0 through 9) on SRF Q5.
Blank If the Previous Location
is outside Winthrop, leave SRF Q5 blank.
6. Duration at Previous location. How long did you (the respondent)
live at the previous location?
0=Less
than 1 If response is less than 1
year, enter a ZERO on the SRF Q6.
1-8=1-8 If the response is
between (and including) 1 thru 8 years,
enter the number (1-8) on the SRF Q6.
9=
=>9 years If the Response is 9
years or more, enter a 9 in the SRF Q6.
Blank If the Previous Location
is outside Winthrop (Q5 answer is blank), leave SRF Q6 blank.
7. Previous-previous
location. Where did you (the respondent) live two
locations ago?
0-9 Enter the grid
number, from the map supplied, of the Pre/Prev location (0 through 9) on SRF
Q7.
Blank If the Previous-Previous
location is outside Winthrop, leave SRF Q7 blank
8. Duration at Previous-Previous
location. How long did you (the respondent) live at the
previous/previous location?
0=Less
than 1 If response is less than 1
year, enter a ZERO on the SRF Q8.
1-8=1-8 If the response is
between (and including) 1 thru 8 years,
enter the number (1-8) on the SRF Q8.
9=
=>9 years If the Response is 9
years or more, enter a 9 in the SRF Q8.
Blank If the Previous-Previous
Location is outside Winthrop (Q7 answer is blank), leave SRF Q8 blank.
9. Smoking Does the respondent currently smoke cigarettes?
0=Yes If the respondent currently
smokes, enter a ZERO (0) on the SRF Q9.
1=No If the respondent does not
smoke currently, enter a ONE (1) on the SRF Q9.
10. How Much How many packs a day does the respondent smoke?.
0=<
1 If the
respondent smokes less than one pack
per day, enter a ZERO (0) on the SRF Q10.
1=1 If the respondent smokes one pack per day, enter a ONE (1) on
the SRF Q10.
2=1½ If the respondent smokes one and 1/2 packs per day, enter a
TWO (2) on the SRF Q10.
3
= 2 If the
respondent smokes two packs per day,
enter a THREE (3) on the SRF Q10.
4
=>2 If the
respondent smokes more than two packs
per day, enter a FOUR (4) on the SRF Q10.
Blank If the Respondent does not
smoke currently (Q9 = No), leave a blank in SRF Q10.
11. Quit Did the respondent formerly smoke
(and has quit)?
0=Yes If the respondent has quit smoking, enter a ZERO (0) on the
SRF Q11.
1=No If the respondent has NEVER SMOKED, enter a ONE (1) on the SRF
Q11.
12. Smoke-Free How many years since the
respondent quit?
0=<1 If the respondent quit
less than a year ago, enter a ZERO (0) on the SRF Q12.
1-8=1-8 If the respondent quit
between one and eight years ago, enter the number (1-8) on the SRF Q12
9=9
or more If the respondent quit 9
or more years ago, enter a NINE (9) on the SRF Q12.
Blank If the Respondent never
smoked (Q11= No), leave SRF Q12 blank.
The next two questions concern
the amount of time the respondent actually spends in Winthrop.
13. Days/Week Away How many days per week does the
respondent typically spend away from Winthrop, either all the time or during the summer months?
0-7=0-7 If
the respondent spends “X” days per week away from Winthrop, enter the number
(0-7) on SRF Q13.
14. Hours/Day Does the respondent work in the Town of
Winthrop?
0=Yes If the respondent works in
the Town of Winthrop, enter a ZERO (0) on the SRF Q14.
1=No If the respondent does not
work in the Town of Winthrop, enter a ONE (1) on the SRF Q14.
Questions 15 - 24 deal with an
existing condition which has been clinically
diagnosed.
15.
Allergies Have
you ever been told by a Doctor that you have Allergies?
0 - Yes If
the answer is “Yes”, enter a ZERO (0) on the SRF Q15.
1 - No If the answer is “No”, enter
a ONE (1) on the SRF Q15
16.
Allergies History How
long ago were you diagnosed with this condition?
0=<1 Year If
the answer is “Less than one year ago”, enter a ZERO (0) on the SRF Q16.
1=1-5 years If the answer is “Between one and
five years ago”, enter a ONE (1) on the SRF Q16.
2=6-10 years If the answer is “Between six and ten
years ago”, enter a TWO (2) on the SRF Q16.
3 =>10 years If
the answer is “More than ten years ago”, enter a THREE (3) on the SRF Q16.
Blank If the respondent has never been diagnosed with
allergies (Q15=No), leave SRF Q16 blank.
17. Asthma Have
you ever been told by a Doctor that you have Asthma?
0 - Yes If
the answer is “Yes”, enter a ZERO (0) on the SRF Q17. ***Special Instructions***
1 - No If the answer is “No”, enter
a ONE (1) on the SRF Q17.
18.
Asthma History “How
long ago were you diagnosed with this condition?”
0=<1 Year If
the answer is “Less than one year ago”, enter a ZERO (0) on the SRF Q18.
1=1-5 years If the answer is “Between one and
five years ago”, enter a ONE (1) on the SRF Q18.
2=6-10 years If the answer is “Between six and ten
years ago”, enter a TWO (2) on the SRF Q18.
3 =>10 years If
the answer is “More than ten years ago”, enter a THREE (3) on the SRF Q18.
Blank If the respondent has never been diagnosed with
asthma (Q17=No), leave SRF Q18 blank.
19.
Chronic Bronchitis Have you
ever been told by a Doctor that you have Chronic Bronchitis?
0 - Yes If
the answer is “Yes”, enter a ZERO (0) on the SRF Q19. ***Special Instructions***
1 - No If the answer is “No”, enter
a ONE (1) on the SRF Q19
20.
Chronic Bronchitis History “How long ago were you diagnosed
with this condition?”
0=<1 Year If
the answer is “Less than one year ago”, enter a ZERO (0) on the SRF Q20.
1=1-5 years If the answer is “Between one and
five years ago”, enter a ONE (1) on the SRF Q20.
2=6-10 years If the answer is “Between six and ten
years ago”, enter a TWO (2) on the SRF Q20.
3 =>10 years If
the answer is “More than ten years ago”, enter a THREE (3) on the SRF Q20.
Blank If the respondent has never been diagnosed with
chronic bronchitis (Q19=No), leave Q20 blank.
21.
Emphysema Have you ever been
told by a Doctor that you have Emphysema?
0 - Yes If
the answer is “Yes”, enter a ZERO (0) on the SRF Q21. ***Special Instructions***
1 - No If the answer is “No”, enter
a ONE (1) on the SRF Q21.
22.
Emphysema History “How long ago were you diagnosed with
this condition?”
0=<1 Year If
the answer is “Less than one year ago”, enter a ZERO (0) on the SRF Q22.
1=1-5 years If the answer is “Between one and
five years ago”, enter a ONE (1) on the SRF Q22.
2=6-10 years If the answer is “Between six and ten
years ago”, enter a TWO (2) on the SRF Q22.
3 =>10 years If
the answer is “More than ten years ago”, enter a THREE (3) on the SRF Q22.
Blank If the respondent has never been diagnosed with
emphysema (Q21=No), leave Q22 blank.
23.
Sinusitis Have you ever
been told by a Doctor that you have Sinusitis?
0 - Yes If
the answer is “Yes”, enter a ZERO (0) on the SRF Q23.
1 - No If the answer is “No”, enter
a ONE (1) on the SRF Q23.
24.
Sinusitis History “How long ago were you
diagnosed with this condition?”
0=<1 Year If
the answer is “Less than one year ago”, enter a ZERO (0) on the SRF Q24.
1=1-5 years If the answer is “Between one and
five years ago”, enter a ONE (1) on the SRF Q24.
2=6-10 years If the answer is “Between six and ten
years ago”, enter a TWO (2) on the SRF Q24.
3 =>10 years If
the answer is “More than ten years ago”, enter a THREE (3) on the SRF Q24.
Blank If the respondent has never been diagnosed with
sinusitis (Q23=No), leave SRF Q24 blank.
Questions
25 through 30 deal with the frequency
of symptoms to these conditions (How often do you have/use...?)
25.
Inhaler How often do you
use an inhaler?
0=once per month If the response
is “Once per month”, enter a ZERO (0) on SRF Q25.
1=once per week If the
response is “Once a week”, enter a ONE (1) on SRF Q25.
2=2 or more times per week If the response is “Two ormore
times per week”, enter a TWO (2) on SRF Q25.
3=Once a day If the
response is “Once per day”, enter a THREE (3) on SRF Q25.
4=2 or 3 times a day If the response is
“Two or three times a day”, enter a FOUR (4) on SRF Q25.
5=More than 3 times a day If the response is “More than three times a
day”, enter a FIVE (5) on SRF Q25.
Blank = Never If the
response is “Never”, leave SRF Q25 blank.
26.
Asthma Atttack How often do
youexperience an asthma attack?
0=once per month If the response
is “Once per month”, enter a ZERO (0) on SRF Q26.
1=once per week If the
response is “Once a week”, enter a ONE (1) on SRF Q26.
2=2 or more times per week If the response is “Two or more
times per week”, enter a TWO (2) on
Q26.
3=Once a day If the
response is “Once per day”, enter a THREE (3) on SRF Q26.
4=2 or 3 times a day If the response is
“Two or three times a day”, enter a FOUR (4) on SRF Q26.
5=More than 3 times a day If the response is “More than three times a
day”, enter a FIVE (5) on SRF Q26
Blank = Never If the
response is “Never”, leave SRF Q26 blank.
27.
Wheezing How often do you
experience wheezing or shortness of breath?
0=once per month If the response
is “Once per month”, enter a ZERO (0) on SRF Q27.
1=once per week If the
response is “Once a week”, enter a ONE (1) on SRF Q26.
2=2 or more times per week If the response is “Two ormore
times per week”, enter a TWO (2) on SRF Q27.
3=Once a day If the
response is “Once per day”, enter a THREE (3) on SRF Q27.
4=2 or 3 times a day If the response is
“Two or three times a day”, enter a FOUR (4) on SRF Q27.
5=More than 3 times a day If the response is “More than three times a
day”, enter a FIVE (5) on SRF Q27.
Blank = Never If the
response is “Never”, leave SRF Q27 blank.
28.
Bronchitis How often do you experience coughing spells?
0=Once a year If the
response is “Once a year”, enter a ZERO (0) on SRF Q28.
1=Once a month If the
response is ”Once a month”, enter a ONE (1) on SRF Q28.
2=2 or more times per month If the response is “Two or more
time a month”, enter a TWO (2) on SRF
Q28.
3=Once a week If the
response is “Once a week”, enter a THREE (3) on the SRF Q28.
4=More than once a week If the response is “More than
once a week”, enter a FOUR (4) on SRF Q28.
Blank = Never If the
response is “Never”, leave SRF Q28 blank.
29. Sinusitis How often do you experience sinusitis (Runny nose,
tearing eyes, sinus headache)?
0=Once a year If the
response is “Once a year”, enter a ZERO (0) on SRF Q29.
1=Once a month If the
response is ”Once a month”, enter a ONE (1) on SRF Q29.
2=2 or more times per month If the response is “Two or more
time a month”, enter a TWO (2) on SRF
Q29.
3=Once a week If the
response is “Once a week”, enter a THREE (3) on the SRF Q29.
4=More than once a week If the response is “More than
once a week”, enter a FOUR (4) on SRF Q29.
Blank = Never If the
response is “Never”, leave SRF Q29 blank.
30. Odors How
often do you notice exhaust, chemical or fuel odors that you believe to be
airport related?
0=Once a year If the
response is “Once a year”, enter a ZERO (0) on SRF Q30.
1=Once a month If the
response is ”Once a month”, enter a ONE (1) on SRF Q30.
2=2 or more times per month If the response is “Two or more
time a month”, enter a TWO (2) on SRF
Q30.
3=Once a week If the
response is “Once a week”, enter a THREE (3) on the SRF Q30.
4=More than once a week If the response is “More than
once a week”, enter a FOUR (4) on SRF Q30.
Blank = Never If the
response is “Never”, leave SRF Q30 blank.
Note to Surveyor: Don’t forget to sign and date
the Survey Response Form.
Review
answers to Questions 17, 19 and 21. If “Yes”, follow Special Instructions on
Page 1.
