American Journal of Epidemiology
ª The Author 2009. Published by the Johns Hopkins Bloomberg School of Public Health.
All rights reserved. For permissions, please e-mail: [email protected].
Vol. 169, No. 10
DOI: 10.1093/aje/kwp032
Advance Access publication April 2, 2009
Original Contribution
Are the Short-term Effects of Air Pollution Restricted to Cardiorespiratory
Diseases?
Sophie Larrieu, Agnès Lefranc, Gaëlle Gault, Edouard Chatignoux, Franck Couvy,
Bernard Jouves, and Laurent Filleul
Initially submitted July 18, 2008; accepted for publication January 26, 2009.
Short-term effects of air pollution on common morbidity are largely unknown. The authors explored links between
daily levels of air pollution (nitrogen dioxide, ozone, and particulate matter less than 10 lm in diameter (PM10)) and
medical home visits made for diverse reasons in Bordeaux, France, during 2000–2006. Daily numbers of visits
were obtained from a network of general practitioners. The excess relative risk (ERR) of a visit for each indicator
associated with increased pollutant levels was estimated by fitting a Poisson regression model, controlling for wellknown confounding factors and temporal trends. Positive and significant associations were found between air
pollution and most health indicators. A 10-lg/m3 increase in PM10 levels was associated with increases in visits for
upper and lower respiratory diseases (ERRs were 1.5% (95% confidence interval (CI): 0.3, 2.7) and 2.5% (95% CI:
0.5, 4.4), respectively), headache and asthenia (ERR ¼ 3.5%, 95% CI: 1.3, 5.9), and skin rash and conjunctivitis
(ERR ¼ 3.2%, 95% CI: 0.2, 6.8). Significant associations were also found between nitrogen dioxide and ozone
and several health indicators. Distributed-lag models showed no harvesting effect, and some effects persisted up
to 15 days after exposure increased. These results suggest that considering only the most severe effects of air
pollution leads to underestimation of its impact on public health.
air pollution; asthenia; conjunctivitis; exanthema; headache; primary health care; respiratory tract diseases
Abbreviations: CI, confidence interval; ERPURS, Evaluation des Risques de la Pollution Urbaine sur la Santé; ERR, excess
relative risk; PM10, particulate matter less than 10 lm in diameter.
The health effects of air pollution have been subject to
intense epidemiologic and experimental study during the
past 2 decades. It is now well-documented that day-to-day
variations in air pollutant levels are associated with cardiorespiratory morbidity and mortality (1), and several biologic
hypotheses have been proposed to explain air pollutant effects, mainly involving acute pulmonary inflammation and
oxidative stress (2). These effects have been widely studied
for particulate air pollution, but there is also substantial
evidence concerning gaseous pollutants such as ozone and
nitrogen dioxide. The exposure-risk relations observed are
usually described as linear without any threshold (3, 4), or
results suggest that the threshold above which no effect
would be observed is far below the concentrations observed
in urban areas (5). Furthermore, the severity of these effects
is widely variable, and they can affect more or fewer people;
indeed, short-term effects of air pollution are often represented as a pyramid, with the mildest but not uncommon
effects at the bottom and the least common but more severe
effects at the top (Figure 1).
Most epidemiologic studies conducted to date have focused on severe events such as mortality, hospitalizations,
and emergency room visits. On the other hand, more common effects have been less well described, mainly because
of the unavailability of reliable indicators of primary-care
setting, symptoms, or medication use. A few studies showed
a significant association between air pollutant levels and
general practitioner home visits in Paris, France (6),
Correspondence to Dr. Sophie Larrieu, French Institute of Public Health Surveillance (InVS), Cire Aquitaine, Espace Rodesse, 103 bis rue
Belleville, BP952, 33063 Bordeaux Cedex, France (e-mail: [email protected]).
1201
Am J Epidemiol 2009;169:1201–1208
1202 Larrieu et al.
other neighboring cities where urbanization and background
air pollutant levels could be considered homogeneous, representing a total population of approximately 600,000
inhabitants.
Estimates of pollution exposure
Figure 1. Pyramidal representation of the hypothesized short-term
effects of air pollution on health.
London, United Kingdom (7–9), and Hong Kong, China
(10), but those studies focused on respiratory diseases; other
symptoms have rarely been investigated.
In Bordeaux, a mid-sized metropolitan area in southwestern France, a network of 60 general practitioners has been
collecting data on the practitioners’ activities for many years,
allowing us to link their activity with air pollutant levels
measured over the Bordeaux area. Therefore, our aim in this
study was to explore the links between daily levels of air
pollution indicators (nitrogen dioxide, ozone, and particulate matter less than 10 lm in diameter (PM10)) and daily
numbers of medical home visits made for nonsevere reasons, some of which are known to be associated with air
pollution (respiratory diseases) and others of which have
a less well described association with air pollution (headache, asthenia, conjunctivitis, and skin rash) in this area.
MATERIALS AND METHODS
Study population and period
This study was conducted during the period 2000–2006 in
the area of Bordeaux, France. It included Bordeaux and 21
The local air quality monitoring network, AIRAQ (http://
www.airaq.asso.fr/), provided data on daily levels of ambient air pollutants measured within the study area: nitrogen
dioxide, PM10, and ozone. We used measurements from the
4 background monitoring stations available in the study
area, because they are not influenced by occasional sources
of pollution, since they are located some distance away from
major roads and industries.
For each air pollutant, we calculated correlation coefficients for correlations between the different stations in order
to ensure that they all measured the same type of pollution
(r > 0.60); the daily level of each air pollution indicator was
then computed as the arithmetic mean of the daily levels
recorded by the stations (for PM10 and nitrogen dioxide) or
the arithmetic mean of the daily maximum of 8-hour moving averages (for ozone).
Health outcomes
SOS Médecins is the primary emergency and health-care
network in France, providing home medical visits by general practitioners in response to private house calls 24 hours
a day, 7 days a week. In the urban area of Bordeaux, SOS
Médecins comprises 60 general practitioners who make
more than 400 visits per day, operating in an area of approximately 800,000 inhabitants. Characteristics concerning
each visit are logged into a local database; all symptoms
and/or complaints reported by the patients are coded and
recorded according to the International Classification of
Primary Care, Second Edition (11), as well as the final diagnosis. From this database, we extracted daily numbers of
visits made to people living in the study area for the following reasons: upper and lower respiratory diseases, asthma,
asthenia, headache, conjunctivitis, and skin rash (Table 1).
In order to evaluate any bias in the analysis, we also extracted and modeled daily numbers of visits made for lumbago, which is unrelated to air pollution a priori, according
to the same method.
Table 1. Health Indicators and Corresponding ICPC-2 Codes Used in a Study of Air Pollutant Effects, Bordeaux, France, 2000–2006
Health Indicator
Corresponding Syndrome(s) and/or Symptom(s)
ICPC-2 Code(s)
Upper respiratory diseases
Tonsillitis, sinusitis, rhinitis, nasopharyngitis, pharyngitis, laryngitis, tracheitis
R75, R76, R77, R83, R97
Lower respiratory diseases
Bronchitis, bronchiolitis, chronic obstructive pulmonary disease, cough
R78, R79, R95, R05
Asthma
Asthma
R96
Asthenia
Asthenia
A04
Headache
Headache
N01, N89
Conjunctivitis
Conjunctivitis
F70, F71
Skin rash
Dermatitis, eczema, urticaria, skin rash
S07, S87, S98
Abbreviation: ICPC-2, International Classification of Primary Care, Second Edition (11).
Am J Epidemiol 2009;169:1201–1208
Short-term Effects of Air Pollution
Potentially confounding factors
Data on the following potentially confounding factors
were collected: ambient temperature measured at the
Bordeaux meteorologic station, obtained from the national
meteorologic institute (Météo-France); periods of influenza
epidemics, obtained from the SOS Médecins database (according to a local influenza epidemic threshold that usually
allows monitoring of the disease in the area); pollen counts
measured at the Bordeaux pollen monitoring station, obtained from the French surveillance system for pollen counts
(Réseau National de Surveillance Aérobiologique); and dates
of holidays, obtained from the French Ministry of Education.
LogðEðYt ÞÞ ¼ a þ bX þ
15
X
1203
cðsÞZts ;
s¼0
with c being constrained to follow a cubic polynomial function. As in the generalized additive Poisson regression models, the number of degrees of freedom was chosen to
minimize residual autocorrelation.
This model could not be used for ozone, because the term
for interaction between ozone and season led to many
breaks in the pollutant series.
RESULTS
Statistical analysis
Daily numbers of medical home visits were analyzed with
time-series methods, using generalized additive Poisson regression models allowing for overdispersion (12). Each air
pollution indicator was included in the model as a linear
term, and different lags were tested: pollutant levels on
the current day and up to 3 days before (lags of 0, 1, 2,
and 3 days) and mean levels during the current day and
the previous 1, 2, or 3 days (lags of 0–1, 0–2, and 0–3
days). The lag that minimized Akaike’s Information Criterion (13) was retained. Adjustments were made for possible
confounders—including long-term trends, seasonality, days
of the week, holidays, minimum temperature on the current
day and maximum temperature on the previous day, and influenza epidemics—following the methods of the APHEA-2
[Air Pollution And Health: A European Approach] Study
(14). Long-term trends and seasonality were modeled using
penalized cubic regression splines. The degree of smoothing
of the spline function was chosen to remove seasonal and
long-term temporal trends by minimizing the autocorrelation in the residuals. Dummy variables for days of the week
and holidays were included as other independent variables.
Temperature and influenza epidemics were modeled using
natural splines with 3 degrees of freedom for each. The lack
of residual autocorrelation was checked through the partial
autocorrelation, and the Bartlett test was used to check that
white noise was obtained.
A term for interaction between ozone and season was
introduced into the regression models to specifically assess
the effect of ozone during the warmer months (April–
September).
All results are presented as the excess relative risk (ERR)
of a medical home visit (expressed as a percentage) associated with a 10-lg/m3 increase in air pollution indicator
level. To determine whether there were any effects in subgroups of the population, we also performed analyses on
specific age groups, when the number of events was large
enough, notably to estimate specific ERRs for frail populations such as children under age 15 years (15) and people
aged 65 years or more (16).
Since the health effects of air pollution may persist for
several days after exposure or, on the contrary, potential
morbidity displacement may exist (17), we also used
distributed-lag models to better describe pollutant effects
that were delayed by up to 15 days, as follows:
Am J Epidemiol 2009;169:1201–1208
The study area comprised 22 cities and more than
600,000 inhabitants, of whom 15.5% were less than 15 years
of age and 15.7% were aged 65 years or older. Descriptive
results for daily air pollutant levels and health indicators are
shown in Table 2.
Bordeaux is a moderately polluted area, with annual
mean levels of nitrogen dioxide and PM10 that are largely
below the current French annual guidelines (40 lg/m3) (18),
but PM10 levels are slightly above the 2005 World Health
Organization guidelines (20 lg/m3) (19). Daily maximum
levels of 8-hour moving averages of ozone overtook the
threshold for health protection (120 lg/m3) during less than
5% of the study period.
During the 7-year study period, a total of 895,710 medical
home visits were made by SOS Médecins Bordeaux, corresponding to a daily mean of 350 visits. Visits for respiratory
diseases represented approximately 20% of the activity of
the general practitioners. Since the numbers of visits for the
4 other indicators were quite low, we grouped together the
indicators asthenia and headache, which correspond to
a general health impairment without another diagnosed disease, and conjunctivitis and skin rash, which can be related
to irritation and atopy.
As Figure 2 shows, the general practitioners’ activity
showed important day-of-the-week and seasonal variations.
The daily number of visits increased on weekends and during the winter.
We constructed specific models for each health indicator
and each air pollution indicator. The mean of the lag 0–3
days led to the best model for all indicators except headache/asthenia, for which a lag of 0 was considered for every
air pollution indicator. Table 3 presents the ERR of a medical
home visit associated with a 10-lg/m3 increase in air pollutant levels for each health indicator.
The risk of a visit for upper respiratory diseases was
significantly increased by 1.5% (95% confidence interval
(CI): 0.3, 2.7) during the 3 days following a 10-lg/m3 increase in PM10 levels; a similar but nonsignificant trend was
also observed for an increase in nitrogen dioxide levels.
Similarly, the risks of consulting a general practitioner for
lower respiratory diseases increased by 2.6% (95% CI: 0.2,
4.9) and 2.5% (95% CI: 0.5, 4.4) following 10-lg/m3 increases in nitrogen dioxide and PM10 levels, respectively.
Asthma was not associated with any of the indicators considered, and no trend was found, nor was an association
1204 Larrieu et al.
Table 2. Daily Air Pollutant Levels and Daily Numbers of General Practitioners’ Visits Made for
Different Health Indicators, Bordeaux, France, 2000–2006
Air Pollution or
Health Indicator
Mean Minimum
5th
50th
95th
Maximum
Percentile Percentile Percentile
Pollutant Level, lg/m3
Nitrogen dioxide
21.9
3.8
8.0
20.3
41.3
80.3
Ozone
Ozone in spring and summera
69.3
2.7
32.5
68.2
111.8
142.7
84.8
37.5
48.7
81.5
117.1
PM10
142.7
21.1
5.0
10.3
18.8
38.5
88.2
No. of Visits
Upper respiratory diseases
57.6
8
25
56
96
149
Lower respiratory diseases
16.4
0
4
14
38
77
Asthma
3.5
0
0
3
8
19
Asthenia
2.2
0
0
2
5
11
18
Headache
4.1
0
1
4
8
Conjunctivitis
0.6
0
0
0
2
8
Skin rash
3.5
0
0
3
8
15
Lumbago (control)
5.7
0
2
5
11
20
Abbreviation: PM10, particulate matter less than 10 lm in diameter.
April 1–September 30.
a
found between visits made for respiratory diseases and
ozone.
The daily number of visits made for headache or asthenia
was significantly associated with the 3 air pollution indicators
considered; same-day ERRs were 2.8% (95% CI: 0.4, 5.3),
3.5% (95% CI: 1.3, 5.9), and 1.7% (95% CI: 0.2, 3.3) for
10-lg/m3 increases in nitrogen dioxide, PM10, and ozone levels, respectively. The risk of a visit for skin rash or conjunctivitis was also increased during the 3 days following increases
in PM10 (ERR ¼ 3.2%, 95% CI: 0.2, 6.8 (close to significance)) and ozone (ERR ¼ 3.0%, 95% CI: 0.4, 5.7) levels.
700
600
500
400
300
200
Daily No. of Visits
800
700
600
500
400
300
200
100
July 1, 2006
July 1, 2005
January 1, 2006
January 1, 2005
July 1, 2004
January 1, 2004
July 1, 2003
January 1, 2003
July 1, 2002
January 1, 2002
July 1, 2001
July 1, 2000
January 1, 2001
January 1, 2000
0
Figure 2. Seasonal (main graph) and daily (inset) numbers of medical home visits (gray line) made to persons in the Bordeaux metropolitan area and 7-day moving averages (black line), Bordeaux,
France, 2000–2006.
Lastly, the daily number of visits made for lumbago,
which we chose as the control outcome in order to evaluate
any bias in the analyses, was not associated with any of the
pollutant indicators considered.
Results from complementary analyses of specific age
groups are illustrated in Figure 3. Although the confidence
intervals overlapped, central estimates of ERR were much
higher in the elderly for respiratory diseases (upper and
lower), regardless of the type of pollutant, suggesting
a higher effect in this subgroup. This difference was particularly important for upper respiratory diseases, with ERRs
of 12.3% (95% CI: 4.9, 19.7) and 8.3% (95% CI: 2.0, 14.7)
being associated with 10-lg/m3 increases in nitrogen dioxide and PM10 levels, respectively, in this subgroup. In the
other age groups, effects were close to each other.
For asthma, in addition to the whole population, no association was observed in children.
When distributed-lag models were used, no harvesting
effect was observed, regardless of which health indicator
was considered. Figure 4 compares the results from initial
models and from distributed-lag models, in which up to
15 days of lag time between the exposure and health effects
were considered. Taking into account lags over 15 days did
not lead to larger associations between PM10 and numbers
of home visits, whatever the diagnosis considered, whereas
estimates for nitrogen dioxide were much higher when the
effects of lags of up to 15 days on upper respiratory diseases
(global ERR ¼ 5.7%, 95% CI: 2.7, 8.8) and lower respiratory diseases (global ERR ¼ 9.4%, 95% CI: 4.7, 14.3) were
considered. It is also noteworthy that there was a much
higher effect of nitrogen dioxide on visits for skin rash
and conjunctivitis when delayed effects were considered,
even though the excess risk was not significant because of
a large confidence interval.
Am J Epidemiol 2009;169:1201–1208
Short-term Effects of Air Pollution
1205
Table 3. Excess Relative Risk (%) of a Medical Home Visit Associated With a 10-lg/m3
Increase in Air Pollutant Levels, Bordeaux, France, 2000–2006
Nitrogen Dioxide
ERR
Ozone
PM10
Diagnosis
95% CI
ERR
95% CI
ERR
95% CI
1.7, 0.5
a
Upper respiratory diseases
0.8
0.7, 2.3
1.5
0.3, 2.7
0.6
Lower respiratory diseasesa
2.6
0.2, 4.9
2.5
0.5, 4.4
0.4
2.5, 1.7
Asthmaa
1.1
3.0, 5.2
0.5
3.1, 4.1
0.8
3.9, 2.3
Headache or astheniab
2.8
0.4, 5.3
3.5
1.3, 5.9
1.7
0.2, 3.3
Skin rash or conjunctivitisa
0.3
3.3, 4.2
3.2
0.2, 6.8
3.0
0.4, 5.7
0.3
3.4, 2.9
0.5
2.3, 3.5
0.5
1.6, 2.6
a
Lumbago (control)
Abbreviations: CI, confidence interval; ERR, excess relative risk; PM10, particulate matter less
than 10 lm in diameter.
a
Lag of 0–3 days.
b
Lag of 0 days.
The persistence of nitrogen dioxide effects over 15 days is
illustrated in Figure 5, which represents the ERR of a visit
for upper respiratory diseases estimated for each lag up to
14 days through distributed-lag models. This ERR started to
decrease progressively about 10 days after exposure and was
significant up to a lag of 11 days.
DISCUSSION
This study is one of the few to have investigated shortterm relations between air pollution and morbidity through
diagnoses made by general practitioners. It underlines that
the health effects of air pollution are not restricted to the
cardiorespiratory system but can also increase the risks of
other conditions that have rarely been described as being
associated with air pollution, such as headache, asthenia,
conjunctivitis, and skin rash.
The main strength of this study was the availability of
reliable health data reflecting the activity of general practitioners in the general population, which is usually hard to
monitor. Indeed, anyone in need of a medical visit can call
<15 years
15–44 years
45–64 years
≥65 years
Excess Relative Risk, %
20
15
10
5
0
–5
–10
NO2
PM10
O3
Upper Respiratory Diseases
NO2
PM10
O3
Lower Respiratory Diseases
Figure 3. Excess relative risk (%) of a medical home visit for upper
and lower respiratory diseases associated with a 10-lg/m3 increase in
air pollutants, Bordeaux, France, 2000–2006. NO2, nitrogen dioxide;
O3, ozone; PM10, particulate matter less than 10 lm in diameter. Bars,
95% confidence interval.
Am J Epidemiol 2009;169:1201–1208
SOS Médecins, which therefore makes visits in the general
population by definition. The medical diagnoses are recorded by the physicians themselves after every visit, using
standardized codes for each disease. This is not the case for
similar organizations in France, which have only been collecting information on the complaints, symptoms, and infections reported by the patients. That is the reason for the
main limitation of this study: It was a unicentric study because of the lack of similar available data from other cities
covering the past several years. The population served by
SOS Médecins might have changed during the study period,
which was quite long, and it might also have changed according to season, since the study area has a high level of
tourism. However, the adjustment for season and long-term
trends allowed us to take into account those variations, as
well as variations in the general practitioners’ activity. Concerning exposure, all of the monitoring stations were selected in accordance with local experts who considered
them representative of the background exposure within the
study area. Although levels measured by these stations do
not accurately reflect individual levels of exposure, published research has shown that their day-to-day variations
are well correlated with variations in individual exposure
(20).
Our results for respiratory diseases are globally in agreement with those of the few studies that have investigated
relations between air pollution and general practitioner activity, and are supported by biologic hypotheses. Indeed,
almost all of the studies that investigated the association
between PM10 and general practitioners’ visits for upper
(6, 9, 10) and/or lower (6, 21) respiratory diseases observed
such a relation; the exception was 1 study focusing on children, for which the study period was very short (22). Concerning nitrogen dioxide, most of the studies found an
association between this indicator and consultations for
respiratory diseases (10, 21–23); this was not found in the
latest period of a study based on visits made by SOS
Médecins in the Greater Paris area (6). The associations
between PM10 and nitrogen dioxide, on the one hand, and
respiratory diseases, on the other hand, were higher in the
elderly. It is probable that air pollution exacerbates preexisting conditions that are more likely to affect elderly
1206 Larrieu et al.
15
0–3 Days Effect
Excess Relative Risk, %
15-Day Cumulative Effect
10
5
0
–5
URD
LRD Headache, Skin Rash,
Asthenia Conjunctivitis
NO2
URD
LRD Headache, Skin Rash,
Asthenia Conjunctivitis
PM10
Figure 4. Comparison of excess relative risks (%) of a medical home visit obtained using a lag time of 0–3 days with excess relative risks obtained
using distributed-lag models (15-day cumulative effect), Bordeaux, France, 2000–2006. LRD, lower respiratory diseases; NO2, nitrogen dioxide;
PM10, particulate matter less than 10 lm in diameter; URD, upper respiratory diseases. Bars, 95% confidence interval.
people. Furthermore, aging is characterized by a decrease in
antioxidant defenses, and the elderly may constitute a group
at high risk of suffering from oxidation phenomena induced
by air pollution (24). Like other investigators (6, 21), we did
not find any association between respiratory diseases and
ozone, although this pollutant is well-known for its oxidative properties and was significantly associated with respiratory medical visits in London and Hong Kong (8, 10).
The most innovative results of this study concern the
association between air pollution and conjunctivitis and skin
rash, in relation to a potential atopic etiology of these 2
diseases, as well as the association between air pollution
and headache and asthenia, which reflects general health
impairment without a clearly diagnosed disease. To our
knowledge, no experimental study has shown such an association, because these symptoms cannot be objectively measured and therefore are diagnosed on a declarative basis.
Excess Relative Risk, %
2
1
0
–1
0
1
2
3
4
5
6
7
8
9
10 11 12 13 14
Lag, days
Figure 5. Excess relative risk (%) of a medical home visit for upper
respiratory diseases associated with a 10-lg/m3 increase in nitrogen
dioxide levels, by lag time, Bordeaux, France, 2000–2006. Bars, 95%
confidence interval.
However, a link between air pollution and physicians’ visits
for headache was observed in the Evaluation des Risques de
la Pollution Urbaine sur la Santé (ERPURS) program (23),
with ERRs slightly lower than but in the same range as those
in the current study. Szyszkowicz (25) also found a link
between several air pollutant indicators and emergency visits for headache in Montreal, Canada; several lag times were
tested, and the highest ERRs associated with pollutant level
increases were observed for the same day, just as in the
present study, and were within the same range. Thus, air
pollutants could have a very short-term effect on unspecific
syndromes like asthenia and/or headache—conditions
which are not very severe but can be painful and affect many
people.
Conjunctivitis and skin rash were also significantly associated with PM10 and ozone levels, confirming the potential
link between air pollution and allergic diseases other than
respiratory diseases. Indeed, exposure to air pollutants is
able to trigger an immunoglobulin E response and to induce
oxidative protein damage in the stratum corneum, leading to
the disruption of barrier function and exacerbation of atopic
dermatitis (26). In the ERPURS program (22), eye conditions were found to be exclusively related to ozone levels;
the concordance of results from both our study and the
ERPURS study strongly favors an association between eye
diseases and ozone, which could be explained by its wellknown irritant and oxidant properties. Ocular inflammation
and dryness were also shown to be related to high concentrations of atmospheric pollutants in patients suffering from
eye discomfort syndrome (27). Lastly, 2 other studies comparing prevalences of atopic eczema (28) or atopic dermatitis and allergic rhinoconjunctivitis (29) showed that
prevalences were higher in the most polluted areas. Our
results are therefore in accordance with those of the few
published studies available, which all suggest the existence of
a link between air pollutant exposure and dermatitis and/or
Am J Epidemiol 2009;169:1201–1208
Short-term Effects of Air Pollution
eye diseases. Furthermore, results found for more commonly studied indicators are totally in accordance with
results from the literature, which also favors a robustness
of our analyses with regard to these innovative health
indicators.
Also favoring the robustness of our results is the lack of
any significant relation between air pollution and visits
made for lumbago, the outcome chosen as the control health
indicator, since it is not related a priori to air pollution.
In addition, we used distributed-lag models which have
been recently used in environmental epidemiology in order
to quantify the so-called ‘‘mortality displacement effect’’
(17). In our study, distributed-lag models produced effect
estimates similar to or higher than those of models using
3-day moving averages, suggesting that 1) the effect of air
pollution is not simply advanced by a few days, since no
obvious harvesting effect is observed, and 2) effects associated with increases in nitrogen dioxide levels persist for
2 weeks after exposure for both upper and lower respiratory
diseases. The fact that the use of distributed-lag models led
to higher effect estimates for nitrogen dioxide and several
health indicators (respiratory diseases, conjunctivitis, and
skin rash) but not for other pollution and health indicators
suggests that different pollutants can have more or less delayed effects. However, it is difficult to know whether these
different types of effects are really linked to the pollutant
itself or whether the pollutant acts as a surrogate for other
exposures.
The lack of association between air pollution and asthma
can be considered surprising in the context of results existing in the literature (30–32). However, studies using data on
general practitioner activity are more controversial: In the
London study, visits for asthma were associated with several
air pollution indicators (7); in the ERPURS program in
Paris, this was also the case during the 1991–1995 period
(23), but such an association was no longer observed during
2000–2003 (6). Thus, the lack of association could be explained, on the one hand, by the lower number of daily
events in comparison with the previous period (representing
only 1% of all visits) and, on the other hand, by the fact that
asthma treatment has changed, and the context of crisis that
motivates general practitioners’ visits might have been consequently modified. Indeed, asthma patients often treat
themselves if a crisis occurs and might go directly to the
emergency room (without calling a general practitioner) if
the crisis cannot be controlled using their usual medication.
In conclusion, we found evidence of an association between air pollutant levels and daily numbers of general
practitioners’ visits for various syndromes. This study
proves the relevance of such data for epidemiologic research
in the field of environmental health. Furthermore, the results
of this study will sensitize doctors to the importance of
giving as precise a diagnosis as possible, and this will probably help to further increase data quality; better precision in
diagnosis will allow us to obtain more specific data on
health indicators in the future. The links observed with conjunctivitis, skin rash, headache, and asthenia are very innovative, since few studies have shown relations with them
because of the lack of suitable data. They strongly suggest
that cardiorespiratory diseases are not the only conditions
Am J Epidemiol 2009;169:1201–1208
1207
that can be induced or exacerbated by air pollution and show
that focusing on very severe events leads to underestimation
of air pollution effects. In terms of public health, this study
suggests that a large number of medical visits are attributable to air pollution in Bordeaux, where current levels of air
pollutants are globally close to European air quality guidelines for health protection. This is one more convincing
argument for promoting all measures aimed at reducing
pollutant emissions, on both the individual and collective
levels, even in moderately polluted areas.
ACKNOWLEDGMENTS
Author affiliations: French Institute of Public Health
Surveillance, Bordeaux, France (Sophie Larrieu, Gaëlle
Gault, Laurent Filleul); French Institute of Public Health
Surveillance, Saint Maurice, France (Agnès Lefranc); SOS
Médecins, Bordeaux, France (Franck Couvy, Bernard
Jouves); and Regional Observatory of Health Ile-de-France,
Paris, France (Edouard Chatignoux).
The authors thank SOS Médecins Bordeaux and AIRAQ
for their collaboration in providing data and their very useful participation.
Conflict of interest: none declared.
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