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Outdoor air pollution and uncontrolled asthma in the
San Joaquin Valley, California
Ying-Ying Meng,
1
Rudolph P Rull,
2,3
Michelle Wilhelm,
4
Christina Lombardi,
1
John Balmes,
5,6
Beate Ritz
4
ABSTRACT
Background The San Joaquin Valley (SJV) in California
ranks among the worst in the USA in terms of air quality,
and its residents report some of the highest rates of
asthma symptoms and asthma-related emergency
department (ED) visits and hospitalisations in California.
Using California Health Interview Survey data, the
authors examined associations between air pollution and
asthma morbidity in this region.
Methods Eligible subjects were SJV residents (2001
California Health Interview Survey) who reported
physician-diagnosed asthma (n¼1502, 14.6%). The
authors considered two outcomes indicative of
uncontrolled asthma: (1) daily or weekly asthma
symptoms and (2) asthma-related ED visits or
hospitalisation in the past year. Based on residential zip
code, subjects were assigned annual average
concentrations of ozone, PM
10
and PM
2.5
for the 1-year
period prior to the interview date from their closest
government air monitoring station within an 8 km
(5 miles) radius.
Results Adjusting for age, gender, race/ethnicity,
poverty level and insurance status, the authors observed
increased odds of experiencing daily or weekly asthma
symptoms for ozone, PM
10
and PM
2.5
(OR
ozone
1.23, 95%
CI 0.94 to 1.60 per 10 ppb; OR
PM10
1.29, 95% CI 1.05 to
1.57 per 10
m
g/m
3
; and OR
PM2.5
1.82; 95% CI 1.11 to
2.98 per 10
m
g/m
3
). The authors also observed increased
odds of asthma-related ED visits or hospitalisations for
ozone (OR 1.49, 95% CI 1.05 to 2.11 per 10 ppb) and
a 29% increase in odds for PM
10
(OR 1.29, 95% CI 0.99 to
1.69 per 10
m
g/m
3
).
Conclusions Overall, these findings suggest that
individuals with asthma living in areas of the SJV with
high ozone and particulate pollution levels are more likely
to have frequent asthma symptoms and asthma-related
ED visits and hospitalisations.
The San Joaquin Valley (SJV) in California is
a region with some of the worst air quality in the
USA, with levels of particulate matter (PM) and
ozone (O
3
) exceeding state and federal air quality
standards. The SJV, which covers Fresno, Kern, San
Joaquin, Stanislaus, Tulare, Merced, Kings, and
Madera Counties, is home to over 3.5 million Cali-
fornians. For 109 days in 2001, the SJV exceeded the
federal 8 h O
3
standard (0.08 ppm at the time),
reaching a maximum 8 h O
3
level of 0.120 ppm.
1
The SJV also exceeded the 24 h federal standard for
particulate matter less than 10
m
m in aerodynamic
diameter (PM
10
), (150
m
g/m
3
) during 12 days in
2001.
12
Furthermore, in 2000, the SJV recorded the
highest 24 h maximum and annual average
concentrations of particulate matter less than
2.5
m
m in aerodynamic diameter (PM
2.5
), in the
state, reaching values nearly twice the federal
standards (65
m
g/m
3
at the time and 15
m
g/m
3
,
respectively).
2
With few exceptions, the SJV is
characterised by flat terrain, with most of its area
lying below 400 feet in elevation and surrounded by
mountains which trap pollutants in the valley.
3
SJV residents suffer from asthma at high rates.
According to 2001 California Health Interview Survey
(CHIS), Fresno was among the top California counties
in terms of asthma symptom prevalence (13.4%).
Merced, Fresno, San Joaquin and Tulare Counties all
had rates of asthma-related emergency department
(ED) visits or hospitalisations higher than the mean
rate for all California counties.
4
However, due to a lack
of asthma surveillance in California, it is not known
whether higher asthma symptom prevalence and
hospitalisation rates in the SJV are related to high
exposures to air pollutants including PM and O
3
or
other factors such as a relatively high percentage of the
population with poor access to healthcare and low
socio-economic status. As part of the new national
environmental public health tracking (EPHT) initia-
tive led by the Centers for Disease Control and
Prevention,
5
we linked asthma data from CHIS with
air pollution data from ambient monitors to examine
associations between air pollution and uncontrolled
asthma in SJV residents while controlling for some
well-known asthma risk factors.
METHODS
Study population
Subjects eligible for this study were individuals
with a self-reported physician diagnosis of asthma
who resided in the SJV region and for whom the
CHIS collected health data between November
2000 and September 2001. This restriction to indi-
viduals with asthma diagnoses minimises the
possibility of misclassification of outcome due to
other respiratory diseases. CHIS is a biennial
random-digit dial telephone survey of California
adults, adolescents and children, and in 2001 was
conducted in 55 428 California households. The
weighted extended interview completion rate for
adults was 64%, and the weighted adult screener
completion rate was 59%. The interviews were
conducted in English, Spanish or one of four Asian
languages to obtain information on demographic
characteristics, health-related behaviours, health
status and conditions, access to healthcare and
insurance coverage. Respondents were also asked to
report their residential zip code. Detailed descrip-
tions of CHIS 2001 sampling and survey methods
are available elsewhere.
6
1
UCLA Center for Health Policy
Research, Los Angeles,
California, USA
2
Northern
California Cancer Center,
Berkeley, California, USA
3
Department of Health Research
and Policy, Stanford University
School of Medicine, Stanford,
California, USA
4
Department of
Epidemiology and Center for
Occupational and Environmental
Health, School of Public Health,
University of California, Los
Angeles, California, USA
5
Department of Medicine,
University of California, San
Francisco, California, USA
6
Division of Environmental
Health Sciences, School of
Public Health, University of
California, Berkeley, California,
USA
Correspondence to
Dr Ying-Ying Meng, 10960
Wilshire Blvd, Suite 1550, Los
Angeles, CA 90024, USA;
yymeng@ucla.edu
Accepted 2 May 2009
142 J Epidemiol Community Health 2010;64:142e147. doi:10.1136/jech.2009.083576
Research report
Interviews were completed for 10 307 individuals residing in
the SJV study area. For the following analyses, we selected 1502
(14.6% of interviewed) respondents who reported ever having
been diagnosed by a physician as having asthma. The actual
study population varied for each model depending on the avail-
ability of covariate data and pollutant measurements. The
University of California, Los Angeles Institutional Review Board
approved this study as being exempt from review.
Exposure assessment
We restricted our study population to individuals residing within
zip codes in relatively close proximity (5 miles x8 km) to a
California Air Resources Board or local air-quality management
district monitoring station. Using US Census Block (2000)
population densities, we located the population-weighted
centroid of each zip code in which one or more respondents
resided and assigned each of these centroids to the nearest
monitoring station measuring a specific pollutant within an
8 km radius. The distance from each population-weighted zip
code centroid to each air-monitoring station was assessed using
ArcView GIS software (Version 3.3; ESRI, Redlands, California).
For each of five pollutants (CO, NO
2
,O
3
,PM
10
and PM
2.5
), we
selected the nearest station within 8 km with available data for
a given pollutant. Consequently, for some zip codes, measure-
ments of specific pollutants may have been taken at different
stations. Sensitivity analyses were performed using 3-, 6-, 8- and
16 km distances for linking residential zip code centroids to
monitors. The 8 km range was selected to ensure a radius large
enough to balance the need for a sufficient sample size against
a potential increase in exposure misclassification with increasing
residential distances from monitoring stations.
7
Annual average concentrations of the five pollutants were
estimated for each subject within the 8 km radius using data
collected at the assigned stations for the 1-year period prior to the
interview date. These averages were based on hourly measure-
ments for the gaseous pollutants (CO, NO
2
and O
3
); and 24 h
average measurements for PM
10
and PM
2.5
(with most stations
recording measurements every 6 and 3 days for these pollutants,
respectively). In the SJV, 11, 18, 21, 15 and 11 stations provided
CO, NO
2
,O
3
,PM
10
and PM
2.5
measurements, respectively.
Statistical methods
We employed logistic regression to evaluate associations
between our air pollution metrics and asthma morbidity.
Specifically, we examined differences in our exposure metrics
for: (1) respondents with asthma reporting daily or weekly
symptoms (participants were asked in a single question to report
frequency of asthma symptoms, such as coughing, wheezing,
shortness of breath, chest tightness and phlegm production) in
the previous year versus those reporting less-than-weekly
symptoms; and (2) respondents with asthma reporting at least
one asthma-related ED visit or hospitalisation in the previous
year versus those not reporting such healthcare utilisation.
Regression analyses incorporated sampling weights to take
unequal probabilities of selection into the CHIS sample into
account. In addition to evaluating the pollutants (CO, NO
2
,O
3
,
PM
10
,PM
2.5
) as continuous measures, we also looked at quartiles
of their distribution in the study population. Exposure at levels
below the 25th percentile was used as the referent category for
each pollutant. Pollutant associations were evaluated in single-
and multipollutant crude and adjusted models.
We evaluated changes in point and 95% CI estimates
when including the potentially confounding risk factorsdage,
race/ethnicity, poverty level, gender, insurance status, delays in
care for asthma, cigarette smoking (adults only) and employ-
ment (adults only)din our models (table 1). Poverty level was
used as an aggregated indicator of socio-economic status, while
insurance status served as an indicator of access to care. Delays
in care for asthma, cigarette smoking and employment were
not included in the final models because they did not change
the air-pollution-effect estimates by more than 10%. Conse-
quently, the final adjusted models presented here include age,
gender, race/ethnicity, poverty level and health insurance
status.
RESULTS
Overall, 25.7% of respondents with asthma in the SJV reported
experiencing daily or weekly symptoms in the past 12 months
Table 1 Weighted prevalence of frequent symptoms or emergency
department visits/hospitalisations by demographic characteristics among
2001 California Health Interview Survey respondents with reported
asthma diagnoses, San Joaquin Valley, California
Daily/weekly
symptoms*
Emergency
department visits/
hospitalisation
No
Prevalence
(%)yNo
Prevalence
(%)y
All respondents with asthma 1487 25.7 1502 9.2
Age
1e17 487 16.3 493 17.3
18e34 250 19.4 251 5.9
35e64 574 29.5 578 9.0
65+ 176 38.8 180 5.4
Gender
Male 578 21.5 582 12.1
Female 909 24.4 920 10.2
Race/ethnicity
Latino 308 23.6 310 17.9
Asian/others 133 18.0 134 10.3
AfricaneAmerican 96 23.7 97 11.5
White 950 23.4 961 8.3
Household federal poverty levelz
<100% 271 24.3 272 11.9
100e299% 667 22.4 675 12.7
300%+ 549 23.3 555 8.4
Insurance status
Currently uninsured 133 27.4 135 6.9
Uninsured anytime past 12 months 73 21.9 74 17.6
Insured all past 12 months 1281 22.6 1293 11.0
Delay in care for asthmax
Yes 115 54.8 115 28.2
No 1357 20.2 1371 9.8
Current smoking{
Currently smoking 206 35.1 207 6.7
Quit smoking 294 29.1 297 10.1
Never smoked 500 22.2 504 6.4
Employment{
Employed 574 19.8 577 5.1
Unemployed 415 38.4 421 10.9
*Participants were asked in a single question to report the frequency of asthma symptoms,
such as coughing, wheezing, shortness of breath, chest tightness and phlegm production.
yPercentages are weighted to take unequal probabilities of selection into the California
Health Interview Survey sample into account.
zPercentages were defined using the 2001 federal poverty guidelines ($9044 for one person,
$11 559 for a family of two; incomes at 300%+ FPL federal poverty level were three times
these amounts).
xIndividuals who reported delaying or foregoing any medical care they felt they needed
(such as seeing a doctor, a specialist, or other health professional) for asthma were assigned
a value of 1 for one ‘delay in care for asthma’.
{Measured in respondents ages 18+.
J Epidemiol Community Health 2010;64:142e147. doi:10.1136/jech.2009.083576 143
Research report
(table 1). The prevalence of daily or weekly symptoms increased
with age, with older people (65 years and older) being most likely
to report having frequent symptoms. Those reporting being
currently uninsured were more likely to report daily or weekly
symptoms than those who were insured. In line with this,
respondents who experienced delays in care for their asthma
were also much more likely to report daily/weekly symptoms
than those who never experienced delays in care. Adults who
were unemployed, currently smoking or previous smokers were
also more likely to report daily or weekly symptoms.
We observed an overall prevalence of 9.2% for asthma-related
ED visits or hospitalisations in the past year among SJV
respondents who reported a previous diagnosis of asthma, with
the highest prevalence in children (#17 years of age) (17.3%).
Latino, Asian/Other and AfricaneAmerican respondents
reported a higher prevalence of ED visits or hospitalisations than
Caucasians, with the rate for Latinos being approximately double
that of Caucasians. The prevalence of ED visits or hospital-
isations was also higher in lower-income groups. Respondents
who reported delays in care for their asthma were almost three
times more likely to have visited the ED or to have been hospi-
talised than those who did not report delays in care. Adults who
reported that they previously smoked and those who were
currently unemployed were also more likely to visit the ED or be
hospitalised for their asthma.
Interquartile ranges and correlation coefficients for respon-
dents’annual average pollutant measures are shown in table 2.
The annual average O
3
was positively correlated with both PM
10
and PM
2.5
, and negatively correlated with NO
2
and CO in the
SJV during our study period.
Overall, we did not observe any associations between annual
average concentrations of NO
2
or CO and the outcomes of
interest. Thus, we limit our discussion of results to O
3
,PM
10
and
PM
2.5
. Crude and adjusted effect estimates (ORs and 95% CIs)
for each pollutant, as continuous and categorical measures from
single pollutant models, are shown in table 3. ORs based on
multipollutant models for O
3
combined with PM
10
or PM
2.5
did
not differ substantially from single-pollutant estimates (results
not shown).
Based on the adjusted models, we observed a 23% increase in
the odds of daily or weekly symptoms per 10 ppb increase in
annual average O
3
(OR 1.23, 95% CI 0.94 to 1.60), a 29% increase
per 10
m
g/m
3
increase in annual average PM
10
(OR 1.29, 95% CI
1.05 to 1.57) and an 82% increase per 10
m
g/m
3
increase in PM
2.5
(OR 1.82; 95% CI 1.11 to 2.98). Based on quartiles of annual
averages of the pollutants, we observed positive exposure-
response trends for PM
10
and PM
2.5
.
We observed a 49% increase in prevalence of asthma-related
ED visits or hospitalisations per 10 ppb increase in annual
average O
3
(OR 1.49, 95% CI 1.05 to 2.11) and a 29% increase in
odds per 10
m
g/m
3
in PM
10
(OR 1.29, 95% CI 0.99 to 1.69) after
adjusting for age, gender, race/ethnicity, poverty and insurance
status. Although annual average PM
2.5
exposures above the level
of the reference group ($25th percentile, 17.9
m
g/m
3
) appeared to
double the risk for hospitalisations or ED visits, the CIs around
these estimates were quite wide, perhaps due to the smaller
sample size available for this outcome.
Age-stratified results are shown in table 4. Among children,
there was a 63% increase in ED visits and hospitalisations per
10 ppb increase in O
3
(OR 1.63, 95% CI 0.95 to 2.81). No asso-
ciations between daily or weekly symptoms and exposure to O
3
,
PM
10
and PM
2.5
were observed for children. In contrast, the odds
of daily or weekly symptoms were increased for all three
pollutants among adults, with a 40% increase in this outcome per
10 ppb increase in O
3
(OR 1.40, 95% CI 1.02 to 1.91), a 43%
increase per 10
m
g/m
3
PM
10
(OR 1.43, 95% CI 1.13 to 1.82) and
an almost threefold increase in the odds of frequent symptoms
per 10
m
g/m
3
change in PM
2.5
(OR 2.96, 95% CI 1.60 to 5.50).
The odds of adult ED visits for asthma increased 30e60% per
10 ppb or
m
g/m
3
increase in O
3
and PM, respectively, but 95% CIs
for all estimates included null values.
DISCUSSION
Few studies have examined associations between outdoor air
pollution and uncontrolled asthma in the SJV, an area with some
of the highest pollutant levels in the USA. Our results indicate
that both O
3
and PM in the SJV have adverse health
effects on individuals with asthma. We observed associations
between annual average concentrations of O
3
,PM
10
or PM
2.5
and
frequent asthma symptoms or asthma-related ED visits and
hospitalisations while adjusting for insurance status, poverty
level, race/ethnicity, gender and age.
Comparison with previous studies
Our results agree with existing evidence that O
3
can impact
asthma morbidity.
8 9
Studies have linked short-term O
3
exposures
with increased asthma-related hospitalisations and ED visits
among children.
10e12
Fewer studies have looked at the effect of O
3
on adults with asthma, but several have shown an association
with increased asthma exacerbations and ED visits.
13 14
Our results agree with previous studies linking PM
10
with
asthma symptoms in adults.
15
Using 5-day averages and
controlling for aeroallergens, one study showed an association
with increased ED visits and both PM
10
and PM
2.5
in individuals
with asthma.
16
Our study population represents mainly urban
residents (including suburban) in SJV (94e97% urban depending
on pollutant) because we restricted our study population to
respondents residing in zip codes where the population centroid
fell within 5 miles (x8 km) of a monitoring station. Since urban
areas in SJV are moderately sized and sur rounded by agricultural
lands, sources of ambient particles differ from other metropolitan
areas. The sources of PM
10
in Fresno and Bakersfield are, in
descending order, dust from roads and agricultural activities,
Table 2 Annual average pollutant concentration range and correlation matrix for respondents within 5 miles (x8 km) of a monitoring station
Median
(interquartile
range, 25e75%)
Correlation matrix (no of respondents)
O
3
(ppb) PM
10
(
m
g/m
3
)PM
2.5
(
m
g/m
3
)NO
2
(ppb) CO (ppm)
O
3
(ppb) 30.3 (27.1 to 34.0) 1 (759)
PM
10
(
m
g/m
3
) 42.7 (31.7 to 44.3) 0.50 (724) 1 (774)
PM
2.5
(
m
g/m
3
) 21.4 (17.9 to 23.5) 0.52 (591) 0.89 (617) 1 (617)
NO
2
(ppb) 19.0 (16.0 to 21.4) e0.53 (675) e0.31 (643) e0.06 (510) 1 (675)
CO (ppm) 0.56 (0.53 to 0.65) e0.12 (562) 0.46 (538) 0.48 (505) 0.01 (562) 1 (562)
CO, carbon monoxide; NO
2
, nitrogen dioxide; O
3
, ozone; PM
10
, particulate matter less than 10
m
m in aerodynamic diameter; PM
2.5
, particulate matter less than 2.5
m
m in aerodynamic diameter.
144 J Epidemiol Community Health 2010;64:142e147. doi:10.1136/jech.2009.083576
Research report
secondary ammonium nitrate formed from mobile and stationary
combustion sources, wood burning and secondary ammonium
sulfate, while the major sources of PM
2.5
are ammonium nitrate,
organic and elemental carbon from combustion, and ammonium
sulfate.
17
Limited studies have been carried out on the health
effects of this unique mix of particles. An experimental study
showed that concentrated ambient fine and ultrafine particles
from Fresno air, a mainly urban area (including suburbs),
consisting primarily of ammonium nitrate, organic and elemental
carbon, and metals, caused inflammatory changes in the airway
lining fluid of healthy adult rats.
18
Another ongoing study in the
SJV, the Fresno Asthmatic Children’s Environment Study aims to
determine the short- and long-term health effects of PM and to
identify which components are responsible for the exacerbation of
symptoms in children with asthma in Fresno, California. Some of
their preliminary data suggest that traffic may be an important
contributor to decreased lung function in children with asthma.
19
If the traffic-related fraction of PM
2.5
is the most important
contributor to asthma symptoms in some of our study population
in SJV, there is likely exposure misclassification in our estimates,
since ambient monitoring data from stations deliberately sited
away from major roadways do not adequately represent expo-
sures to some traffic-related pollutants (eg, ultrafine particles).
20 21
This misclassification may also explain why we did not observe
any effect for NO
2
, an indicator for traffic-related pollution, in our
analysis.
Age-specific effects
Our analyses stratified by age (1e17 years vs 18+ years) suggest
that exposures to O
3
and PM
10
are associated with ED visits and
hospitalisation in children and adults with asthma, though
associations seem stronger for children, and association estimates
are imprecise due to small sample sizes for ED visits and hospi-
talisations. On the other hand, associations for daily or weekly
symptoms were only observed for adults in our study. For chil-
dren, the absence of associations for daily or weekly symptoms
may be in part due to outcome misclassification, since symptoms
were parent-reported for the 12 months prior to the interview for
Table 3 Association (OR (95% CI)) between annual average air pollution concentrations and asthma outcomes for California Health Interview Survey
2001 respondents residing in the San Joaquin Valley, California (all ages)
Daily/weekly symptoms* Emergency department visits/hospitalisation
Crude AdjustedyCrude Adjustedy
Ozone (193 yes, 559 no) (78 yes, 681 no)
Continuous (per 10 ppb) 1.13 (0.88 1.46) 1.23 (0.94 to 1.60) 1.47 (1.05 to 2.07) 1.49 (1.05 to 2.11)
Quartile
<27.0 1.00 1.00 1.00 1.00
27.1 to 30.2 1.68 (1.01 to 2.79) 1.54 (0.91 to 2.61) 2.44 (1.18 to 5.07) 2.35 (1.12 to 4.95)
30.3 to 33.9 1.97 (1.19 to 3.26) 2.18 (1.30 to 3.68) 1.75 (0.81 to 3.79) 1.80 (0.82 to 3.95)
34.0+ 1.44 (0.86 to 2.42) 1.62 (0.95 to 2.61) 2.63 (1.27 to 5.43) 2.65 (1.26 to 5.57)
PM
10
(198 yes, 569 no) (79 yes, 695 no)
Continuous (per 10
m
g/m
3
) 1.31 (1.08 to 1.60) 1.29 (1.05 to 1.57) 1.32 (1.01 to 1.73) 1.29 (0.99 to 1.69)
Quartile
<31.71 1.00 1.00 1.00 1.00
31.72 to 42.66 1.68 (0.99 to 2.85) 1.73 (1.00 to 2.98) 1.78 (0.87 to 3.67) 2.00 (0.95 to 4.20)
42.67 to 44.33 1.96 (1.17 to 3.30) 1.89 (1.11 to 3.22) 1.42 (0.67 to 3.01) 1.45 (0.67 to 3.11)
44.34+ 2.64 (1.60 to 4.37) 2.51 (1.49 to 4.21) 2.17 (1.08 to 4.36) 2.03 (1.00 to 4.13)
PM
2.5
(152 yes, 459 no) (58 yes, 559 no)
Continuous (per 10
m
g/m
3
) 1.86 (1.15 to 2.99) 1.82 (1.11 to 2.98) 1.42 (0.74 to 2.71) 1.47 (0.76 to 2.84)
Quartile
<17.89 1.00 1.00 1.00 1.00
17.90 to 21.39 1.39 (0.76 to 2.51) 1.53 (0.83 to 2.84) 2.03 (0.85 to 4.86) 2.15 (0.87 to 5.29)
21.40 to 23.49 2.03 (1.14 to 3.60) 1.82 (1.01 to 3.29) 2.53 (1.08 to 5.95) 2.33 (0.97 to 5.58)
23.50+ 2.39 (1.36 to 4.20) 2.46 (1.38 to 4.41) 2.23 (0.94 to 5.31) 2.30 (0.95 to 5.56)
*Participants were asked in a single question to report the frequency of asthma symptoms, such as coughing, wheezing, shortness of breath, chest tightness, and phlegm production.
yAdjusted for age, gender, race/ethnicity, poverty and insurance status.
O
3
, ozone; PM
2.5
, particulate matter less than 2.5
m
m in aerodynamic diameter; PM
10
, particulate matter less than 10
m
m in aerodynamic diameter.
Table 4 Association (OR (95% CI)) between annual average air pollution concentrations and asthma outcomes for California Health Interview Survey
2001 respondents residing in the San Joaquin Valley, California by age group*
Children (ages 1e17) Adults (ages 18+)
Daily/weekly
symptomsy
Emergency
department/
hospitalisation
Daily/weekly
symptomsy
Emergency
department/
hospitalisation
Ozone (32 yes, 215 no) (29 yes, 221 no) (161 yes, 344 no) (49 yes, 460 no)
Continuous (per 10 ppb) 0.76 (0.42 to 1.38) 1.63 (0.95 to 2.81) 1.40 (1.02 to 1.91) 1.43 (0.87 to 2.34)
PM
10
(36 yes, 222 no) (31 yes, 230 no) (162 yes, 347 no) (48 yes, 465 no)
Continuous (per 10
m
g/m
3
) 0.90 (0.60 to 1.37) 1.31 (0.89 to 1.93) 1.43 (1.13 to 1.82) 1.29 (0.87 to 1.92)
PM
2.5
(25 yes, 173 no) (21 yes, 179 no) (127 yes, 286 no) (37 yes, 380 no)
Continuous (per 10
m
g/m
3
) 0.64 (0.27 to 1.50) 1.48 (0.62 to 3.50) 2.96 (1.60 to 5.50) 1.58 (0.56 to 4.43)
*Adjusted for gender, race/ethnicity, poverty and insurance status.
yParticipants were asked in a single question to report the frequency of asthma symptoms, such as coughing, wheezing, shortness of breath, chest tightness and phlegm production
O
3
, ozone; PM
2.5
, particulate matter less than 2.5
m
m in aerodynamic diameter; PM
10
, particulate matter less than 10
m
m in aerodynamic diameter.
J Epidemiol Community Health 2010;64:142e147. doi:10.1136/jech.2009.083576 145
Research report
children younger than 12 years old.
22
For adults, ED visits and
hospitalisations may be less common because they are more
likely to self-treat for an attack at home with medication, while
worried parents may be more likely to take their children to the
ED at the first sign of an attack.
23
EPHT
The goal of EPHT is to develop a tracking system that integrates
data about environmental exposures with data about diseases
that are possibly linked to the environment.
5
The results of this
study enhance our confidence in using survey data, such as
the CHIS, linked with air-quality monitoring data for EPHT
at the regional level. Our findings also suggest a few lessons
about the use of population-based surveillance data for EPHT.
First, it is very important to ensure a sufficient sample size at
the geographic resolution of interest, for example air basin or
county, to detect regional variations in associations between
environmental exposures and health effects. Second, zip code
information for the study population can be used to examine
associations between health effects and air pollutants, especially
those relatively homogeneously distributed within communities
(eg, O
3
). Third, since many chronic diseases have multiple causes
and are influenced by many factors, it is important to control for
confounding factors related to socio-economic status, access to
healthcare and health risk behaviours. In this regard, CHIS has
advantages over many administrative data sources such as vital
statistics, hospital discharge data or claims data which do not
have information on these confounders.
7
The use of CHIS 2001 data for EPHT does have some limi-
tations. We did not have any information on duration of resi-
dence in the same house and neighbourhood for the study
population to evaluate whether exposures preceded the outcome
events, though subsequent CHIS will have the information. We
also did not have any information on how much time respon-
dents spent at or near their home, so some misclassification
would result for respondents who worked, went to school or
otherwise spent a considerable amount of time in areas away
from home that are characterised by different air pollution
levels. In addition, the growing popularity of cell phones is
a concern for landline-telephone surveys. According to the 2001
Current Population Survey data for the year 2001, only 2.2% of
California households and only 5.2% of households below the
poverty level did not have a telephone line. SJV has one of the
highest poverty levels in the state (CHIS 2001). If poor people,
who are more likely to be exposed to higher levels of air pollu-
tion and also more likely to suffer from uncontrolled asthma, are
less likely to be sampled, the associations we report here for air
pollution are probably underestimates.
Study outcomes and a prior asthma diagnosis were self-
reported by respondents and not verified by objective measures.
Because clinical measurements of airway responsiveness appear
to reflect the activity and severity of asthma at the time of
measurement only, it is generally acceptable to collect data on
long-term prevalence of symptoms and exacerbations by ques-
tionnaires.
24
However, due to variations in physician practices
and a lack of access to care, especially in uninsured and low-
income populations, underdiagnosis of asthma may be
a concern.
25 26
In addition, we recognise that the outcome of ED
visits or hospitalisations is problematic, given that some of the
CHIS respondents may have visited the ED for asthma care that
was not emergent. Such visits are likely motivated by asthma
symptoms, and thus relate to asthma care needs. Finally, while
including only CHIS respondents with currently active asthma
would have been desirable for the study of associations between
air pollutants and control of asthma, only information on ever
diagnosis of asthma was available from the CHIS 2001 survey.
The inclusion of respondents with inactive asthma, therefore,
may have led to an underestimation of the strength of
pollutanteasthma outcome associations.
CONCLUSIONS
In summary, we observed that both O
3
and particulate matter
are associated with frequent asthma symptoms and asthma-
related ED visits or hospitalisations in the SJV of California. The
results of this study also enhance our confidence in using Cali-
fornia Health Interview Survey data linked with air monitoring
data to track the impact of air pollution or policy changes
designed to decrease air pollution in specific regions of California.
Further study is needed to determine how changes in the
contributions of various sources of pollution will affect the
health of residents, particularly in vulnerable subpopulations.
Acknowledgements The authors thank H Yu and others, for statistical and
programming support, and S Nathan and M Kuruvilla, for research assistance.
Funding This study was supported by the Centers for Disease Control and Prevention
as part of the University of California, Berkeley Center of Environmental Public Health
Tracking Center.
Competing interests None.
Ethics approval Ethics approval was provided by the University of California, Los
Angeles Institutional Review Board.
Provenance and peer review Not commissioned; externally peer reviewed.
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