248 volume 117 | number 2 | February 2009 • Environmental Health Perspectives

Research

The deleterious effects of air pollution 

on human health have been well studied. 

Numerous studies have demonstrated that air 

pollution is associated with respiratory and 

cardiovascular diseases (CVDs) (Health Effects 

Institute 2004; Samet et al. 2000; Spix et al. 

1998). Similarly, influenza also contributes a 

heavy burden of morbidity and mortality from 

respiratory diseases (RDs) and CVDs (Chow 

et al. 2006; Thompson et al. 2003, 2004; 

Wong et al. 2004, 2006). The effects of air pol‐

lutants and influenza viruses on disease patho‐

genesis could potentially interact synergistically 

because both of them affect the respiratory 

system, from the nasal cavity and nasophar‐

ynx to the main airways and alveoli, and also 

through systemic effects on the cardiovascular 

system. The transmission of influenza viruses 

is believed to rely on short-distance disper‐

sion of droplets. However, there is speculation 

that ambient air pollutants, especially particu‐

late matter ≤ 10 μm in aerodynamic diameter 

(PM10), may facilitate the spread of influenza 

viruses by providing condensation nuclei for 

the virus droplets. This is believed to be critical 

to long-range transmission of influenza viruses 

(Hammond et al. 1989).

Laboratory studies have provided some 

evidence to support interaction between 

influenza and air pollution on their adverse 

effects on human health. As early as the 1970s, 

a series of experiments in mice infected by 

influenza viruses showed an increased inci‐

dence of pneumonia after exposure to sulfur 

dioxide (Fairchild et al. 1972). A more recent 

study showed that exposure to diesel exhaust, 

an important source of PM10, could gener‐

ate oxidative stress in human nasal and bron‐

chial epithelial cells and could also enhance 

the attachment of influenza virus to these cells 

(Jaspers et al. 2005). However, the relevance of 

these experimental studies is uncertain in that 

the concentrations of pollutants in animal and 

human laboratory studies were 10–1,000 times 

higher than the average ambient levels observed 

in even relatively highly polluted locations such 

as Hong Kong. Population-based studies are 

needed to assess the effects of human exposure 

in the community.

Despite numerous attempts to study the 

biologic mechanisms behind the interaction 

between air pollutants and influenza viruses, 

to date only the confounding effect of influ‐

enza has been considered in the short-term 

effects of air pollution on human health in 

several multicity projects (Katsouyanni et al. 

2001; Touloumi et al. 2005). In our study 

we evaluated such an interaction from an epi‐

demiologic perspective. This study is part of 

the Public Health and Air Pollution in Asia 

(PAPA) project (Health Effects Institute

2006), which involves four Asian cities and 

aims to provide insight on the short-term 

effects of air pollution on mortality and hos‐

pitalization. In particular, we examined four 

major ambient air pollutants in Hong Kong:

SO2, nitrogen dioxide, ozone, and PM10. 

Specifically, we assessed effect modifica‐

tion of influenza on air-pollution–associated 

hospitalization for RD and its subcategories 

acute respiratory disease (ARD) and chronic 

obstructive pulmonary disease (COPD) and 

on CVD, as well as on air-pollution–associated

mortality of RD, COPD, and CVD.

Materials and Methods

Sources of data. We retrieved daily counts 

of hospitalization from the 14 general hospi‐

tals of the Hospital Authority of Hong Kong 

for the period 1996–2002. We based these 

counts on discharge diagnoses of admission 

records coded according to the International 

Classification of Diseases, 9th Revision (ICD‐9) 

(World Health Organization 1977) and 

10th Revision (ICD-10) (World Health 

Organization 1994). The selected disease 

categories included CVD (ICD-9 codes 

390–459; ICD-10 codes I00–I99) and RD

(ICD-9 codes 460–519; ICD-10 codes J00–

J98), and subcategories of COPD (ICD-9 

codes 490–496; ICD-10 codes J40–J47) and 

ARD (ICD-9 codes 460–466, 480–487; 

ICD-10 codes J00-J05). We divided these 

data into three age groups [all ages com‐

bined, ≥ 65 years of age, and 0–14 years of 

age (for ARD)] and three sex groups (males 

and females and combined). We obtained 

Address correspondence to A.J. Hedley, Department 

of Community Medicine and School of Public 

Health, University of Hong Kong, 5th Floor, 

William MW Mong Block, Faculty of Medicine 

Building, 21 Sassoon Rd., Hong Kong SAR, China. 

Telephone: 852-2819-9282. Fax: 852-2855-9528. 

E-mail: hrmrajh@hkucc.hku.hk

Supplemental Material is available online at http://

www.ehponline.org/members/2008/11605/suppl.pdf

We thank the Hong Kong Environmental 

Protection Department, Census, and Statistics 

Department and Hospital Authority of Hong Kong 

for providing the data. 

This study is part of the Public Health and Air 

Pollution in Asia project, funded by the Health 

Effects Institute in the United States (agreement 

4713-RFIQ03-3/04-9-2). 

The authors declare they have no competing 

financial interests. 

Received 3 April 2008; accepted 3 October 2008.

Modification by Influenza on Health Effects of Air Pollution in Hong Kong

Chit Ming Wong,1 Lin Yang,1 Thuan Quoc Thach,1 Patsy Yuen Kwan Chau,1 King Pan Chan,1 G. Neil Thomas,1

Tai Hing Lam,1 Tze Wai Wong,2 Anthony J. Hedley,1 and J.S. Malik Peiris3

1Department of Community Medicine and School of Public Health, University of Hong Kong, Hong Kong Special Administration 

Region, People’s Republic of China; 2Department of Family and Community Medicine, Chinese University of Hong Kong, Hong Kong 

Special Administration Region, People’s Republic of China; 3Department of Microbiology, University of Hong Kong, Hong Kong Special 

Administration Region, People’s Republic of China

Background: Both influenza viruses and air pollutants have been well documented as major 

hazards to human health, but few epidemiologic studies have assessed effect modification of influenza on health effects of ambient air pollutants.

Objectives: We aimed to assess modifying effects of influenza on health effects of ambient air 

pollutants.

Methods: We applied Poisson regression to daily numbers of hospitalizations and mortality to 

develop core models after adjustment for potential time-varying confounding variables. We assessed 

modification of influenza by adding variables for concentrations of single ambient air pollutants and 

proportions of influenza-positive specimens (influenza intensity) and their cross-product terms.

Results: We found significant effect modification of influenza (p < 0.05) for effects of ozone. When 

influenza intensity is assumed to increase from 0% to 10%, the excess risks per 10-μg/m3 increase in 

concentration of O3 increased 0.24% and 0.40% for hospitalization of respiratory disease in the allages group and ≥ 65 year age group, respectively; 0.46% for hospitalization of acute respiratory disease in the all-ages group; and 0.40% for hospitalization of chronic obstructive pulmonary disease 

in the ≥ 65 group. The estimated increases in the excess risks for mortality of respiratory disease and 

chronic obstructive pulmonary disease in the all-ages group were 0.59% and 1.05%, respectively. 

We found no significant modification of influenza on effects of other pollutants in most disease 

outcomes under study.

Conclusions: Influenza activity could be an effect modifier for the health effects of air pollutants particularly for O3 and should be considered in the studies for short-term effects of air pollutants on health.

Key words: air pollution, cardiorespiratory disease, effect modification, hospitalization, influenza, 

mortality. Environ Health Perspect 117:248–253 (2009). doi:10.1289/ehp.11605 available via 

http://dx.doi.org/ [Online 3 October 2008]
Modification by influenza on air pollution effects

Environmental Health Perspectives • volume 117 | number 2 | February 2009 249

the daily numbers of deaths for the above dis‐

ease categories over the study period from the 

Census and Statistics Department of Hong 

Kong. Because of relatively small numbers of 

daily mortality, we did not perform the ageand sex-stratified analyses when assessing the 

effect modification of influenza on the effects 

of air pollution on mortality of RD, COPD,

and CVD.

Daily mean temperature and relative 

humidity were provided by the Hong Kong 

Observatory (Hong Kong Observatory 2005).

We obtained air pollutant concentrations 

from eight monitoring stations from the Hong 

Kong Environmental Protection Department 

(HKEPD). We derived daily 24-hr mean con‐

centrations of NO2, SO2, and PM10 and 8-hr

(1000–1800 hours) mean concentration of O3

from the HKEPD database. We defined daily 

concentrations as nonmissing if at least 18 of 

24 hourly concentrations of NO2, SO2, and 

PM10, and six of eight hourly concentrations 

of O3 were available. We first centered non‐

missing daily means for each station i [i.e., we 

subtracted individual daily concentrations (Xij) 

by an annual station mean (Xi) for each day j]. 

We then combined the centered data from all 

stations and added them into the annual mean 

of all stations (X) to form X ́ij = (Xij – Xi + X). 

We computed the daily (mean) concentrations 

of individual pollutants for analysis by tak‐

ing the mean of centered X ́ij over all stations 

(Wong et al. 2001).

We obtained weekly numbers of speci‐

mens positive for influenza viruses A and B 

(Flu A+B) or respiratory syncytial virus (RSV) 

and total numbers of specimens tested from 

the Microbiology Laboratory of Queen Mary 

Hospital (Hong Kong). This laboratory rou‐

tinely collects the respiratory specimens from 

the patients with influenza-like symptoms 

(fever > 38°C, with cough and/or sore throat) 

over the Hong Kong Island and conducted the 

immunofluorescent antigen test for Flu A+B. 

We derived the proportions of positive isolates 

of Flu A+B and RSV from the total specimens 

tested, which we then used to assess the effects 

of influenza and to adjust for the potential 

confounding effect of RSV in the model. The 

proportion of positive isolates of Flu A+B, 

which is defined as influenza intensity in this 

study, has been used in assessment of influ‐

enza effects on hospitalization and mortality 

(Wong et al. 2004, 2006). We used the pro‐

portions of specimens positive for influenza 

as a continuous measure for influenza activity 

instead of defining influenza epidemics. This 

allowed us to avoid the bias potentially posed 

by unpredictable seasonality of influenza in 

Hong Kong (Yang et al. 2008). We assumed 

constant activity of influenza virus and RSV 

within a week and interpolated the weekly 

proportions to the daily data, which we set the 

same from Sunday to Saturday.

Data analysis. We used generalized 

additive modeling in this study (Hastie and 

Tibshirani 1990). To control for potential con‐

founding factors due to time-varying covari‐

ates, we first built the core model on the daily 

counts of hospitalization or mortality for each 

disease category, with dummy variables for 

the day of the week and public holidays to 

control for the variation associated with these 

factors. We controlled the weather conditions 

by adding into the core model natural spline 

smoothing functions of daily mean tempera‐

ture and relative humidity, each with three 

degrees of freedom. Additional adjustments in 

the core model included natural spline smooth‐

ing for time trend and seasonality. We chose 

the degrees of freedom for each smoothing 

function according to the observed autocor‐

relations of the residuals using partial autocor‐

relation function (PACF) plots. To reduce the 

autocorrelations that could not be minimized 

through smoothing, we also added autoregres‐

sive terms into the core model. For the core 

models fitted to the mortality data, we consid‐

ered the time-varying confounding factors as 

adequately controlled if the absolute values of 

PACF coefficients were < 0.1 for the first 2 lag 

days and there were no systematic patterns in 

the PACF plots. Because of the large autocor‐

relations within the hospitalization data, we 

added autoregressive terms until all the PACF 

coefficients at the first 30 lag days were < 0.1.

After the core model for each health out‐

come had been established, we entered single 

air pollutant concentrations, influenza inten‐

sity, and the interaction term defined by the 

cross-product between these two variables 

into the core model to obtain the interaction 

model. To adjust for lag effects, we used the 

concentrations of air pollutants averaged over 

the current day and the previous day (lag 

0–1). We added RSV proportions in order to 

control for the potential confounding of RSV 

with influenza. By assuming that the influenza 

intensity of the same day was equal to zero, 

we calculated from the interaction model the 

excess risk (ER) of hospitalization or mortal‐

ity per 10 μg/m3 increase of each air pollut‐

ant as the baseline effect of air pollution. We 

also calculated the ER per 10-μg/m3 increase 

of each air pollutant when we assumed the 

influenza intensity to be its mean level of 

10%, and the change in ER for each air pol‐

lutant associated hospitalization or mortal‐

ity (a measure for the modifying effect of 

influenza) from the interaction model, under 

the assumption that the influenza intensity 

increased from 0% to 10%. We completed 

all the statistical analyses using the statistical 

software package R version 2.5.1 with mgcv 

package version 1.3–25 (R Foundation for 

Statistical Computing, Vienna, Austria). 

Results

During the study period of 1996–2002, influ‐

enza intensity had an average of 10.1% and 

ranged from 0% to 54.6%. The average con‐

centrations of air pollutants were 58.7, 17.8, 

51.6, and 36.9 μg/m3 for NO2, SO2, PM10, 

and O3, respectively (Table 1). Table 1 also 

shows the summary statistics for meteorologic 

data as well as daily mortality and hospitaliza‐

tion outcomes. On average, mortality counts 

of CVD were higher than those of RD, but for 

hospitalization it was the opposite (Table 1).

The baseline effects of the air pollutants 

on mortality, which we calculated under the 

assumption of zero influenza intensity, were 

Table 1. Summary statistics of influenza, air pollution, and meteorologic data.

Percentile

Variables Mean ± SD Minimum 25th 50th 75th Maximum

Temperature (°C) 23.7 ± 4.7 8.9 19.6 24.7 27.8 31.7

Humidity (%) 78 ± 7.8 40.6 74.7 79.8 83.3 92

Influenza (%) 10.1 ± 10.1 0 2.2 7.2 14.5 54.6

Air pollutant (μg/m3) 

NO2 58.7 ± 20 10.1 45.1 56.3 69.6 168

SO2 17.8 ± 12.1 1.8 9.6 14.7 22.1 109.4

PM10 51.6 ± 25.3 13.5 31.8 45.5 66.7 188.5

O3 36.9 ± 23 –8.2a 19.2 31.7 50.8 196.6

Mortality, all ages (no.) 

RD 16.2 ± 5.2 3 12 16 19 34

COPD 5.9 ± 2.9 0 4 6 8 19

CVD 23.8 ± 6.5 6 19 23 28 54

Hospitalization, all ages (no.) 

RD 270.3 ± 56.3 143 230 266 303 586

ARD 104.9 ± 29.8 48 84 99 122 275

COPD 91.5 ± 20 41 77 89 104 176

CVD 203.5 ± 48.5 75 166 202 241 345

Hospitalization (no.) 

RD, ≥ 65 age group 138.5 ± 36.7 57 112 135 160 302

ARD, 0–14 age group 60.1 ± 19.5 22 46 56 72 149

COPD, ≥ 65 age group 59.6 ± 16.7 19 48 58 70 124

CVD, ≥ 65 age group 130.8 ± 30.1 47 108 128 152 222

aValue for O3 concentration is negative because air pollutant concentration data were standardized using the centering 

method. 
Wong et al.

250 volume 117 | number 2 | February 2009 • Environmental Health Perspectives

statistically significant (p < 0.05) for CVD 

associated with NO2 and SO2, and for RD 

associated with NO2 (ER, 1.23%, 1.64%,

and 1.24%, respectively) but were not sig‐

nificant (p > 0.05) for all mortality outcomes 

associated with O3 (Table 2). We found sig‐

nificant modifying effects of influenza for the 

O3 effects on mortality for RD and COPD 

(ER increased 0.59% and 1.05%) but not for 

the other pollutants.

The effects of NO2 on hospitalization at 

the baseline level of influenza were statistically 

significant (p ≤ 0.05) for all the health out‐

comes under study (except for ARD), with ER 

ranging from 0.85% to 1.84%. We found sig‐

nificant (p ≤ 0.05) modifying effects of influ‐

enza for the NO2 effects on hospitalization of 

COPD in the groups ≥ 65 years of age (ER 

increased 0.43%; Table 3).

We found significant (p ≤ 0.001) effects 

of SO2 on hospitalization of CVD at the 

baseline level of influenza (ER, 1.1% and 

1.5% for all-ages and ≥ 65 age groups). We 

found modifying effects of influenza for the 

effect of SO2 on hospitalization to be sig‐

nificant (p ≤ 0.05) only for ARD in all-ages 

group with ER increased 0.86% (Table 3).

For PM10, we found significant effects 

(p ≤ 0.05) at the baseline level of influenza 

for all the health outcomes under study (ER 

ranging from 0.55% to 1.49%). We found 

no significant modifying effects of influenza 

for PM10 on hospitalization in all the disease 

categories under study (Table 4).

We found significant effects of O3 at the 

baseline level of influenza (p ≤ 0.01) for all RD

groups under study (ER ranged from 0.53% 

to 1.39%), but not for CVD disease. Changes 

in ER associated with O3 for hospitalization of 

RD were significant (p ≤ 0.05). ER increased 

0.24% and 0.40% for RD in all-ages and 

≥ 65 age groups, respectively, and increased 

0.46% for ARD in all-ages and 0.40% for 

COPD in ≥ 65 age group when influenza 

intensity increased from 0 to 10% (Table 4).

In analyses stratified by males and females, 

we found significant effect modification of 

influenza (p ≤ 0.05) for the effects of O3

on hospitalization, with increases of 0.38% 

and 0.48% in ER for RD in both males and 

females in the ≥ 65 age groups, respectively; 

and with increase of 0.63% and 0.88% in 

ER for COPD in the females of all-ages and 

≥ 65 groups, respectively. The effect modifica‐

tions of influenza on hospitalization associated 

with O3 tend to be higher and more signif‐

icant for females than for males (Table 5). 

We found no significant effect modification 

of influenza for effects of the other pollut‐

ants on hospitalization in most health out‐

comes under study, except for NO2 with an 

increased ER on COPD in the males in the

≥ 65 group, and for PM10 with decreased 

ER on RD in the males in the all-ages group 

[data not shown; see Supplemental Material, 

Tables 1–3 (http://www.ehponline.org/

members/2008/11605/suppl.pdf)].

Discussion

Previous studies have identified modifying 

effects of climates for the short-term effects 

of air pollutants on mortality; for example, 

the effects of air pollutants were higher in the 

warm season (Katsouyanni et al. 1997), but 

other reports found no noticeable changes 

between seasons (Schwartz 2000) or even 

found larger effects in the cool season (Wong 

et al. 2002). Other effect modifiers have been 

identified as well, such as NO2 concentration,

which markedly modified the effects of PM10

on mortality (Katsouyanni et al. 2001). Our 

study demonstrated effect modification by 

influenza on the effects of single air pollut‐

ants, particularly O3, both on mortality and 

Table 2. Modifying effects of influenza for the four pollutant effects on mortality.

Effect at mean

Modifying effecta Baseline effectb level of influenza intensityc

Pollutant Disease ER 95% CI p-Value ER 95% CI p-Value ER 95% CI p-Value

NO2 RD 0.18 –0.45 to 0.82 NS 1.24 0.27 to 2.22 * 1.42 0.45 to 2.41 **

COPD 1.01 –0.03 to 2.05 NS 0.26 –1.34 to 1.87 NS 1.26 –0.33 to 2.89 NS

CVD 0.15 –0.39 to 0.70 NS 1.23 0.41 to 2.06 ** 1.39 0.56 to 2.22 #

SO2 RD 0.05 –1.12 to 1.23 NS 1.20 –0.38 to 2.81 NS 1.25 –0.35 to 2.88 NS

COPD 0.32 –1.58 to 2.27 NS –0.03 –2.67 to 2.69 NS 0.30 –2.35 to 3.01 NS

CVD –0.45 –1.45 to 0.55 NS 1.64 0.27 to 3.02 * 1.18 –0.20 to 2.57 NS

PM10 RD 0.08 –0.39 to 0.55 NS 0.69 –0.10 to 1.49 NS 0.77 –0.01 to 1.56 NS

COPD 0.50 –0.26 to 1.27 NS –0.05 –1.36 to 1.28 NS 0.45 –0.83 to 1.75 NS

CVD 0.25 –0.15 to 0.65 NS 0.45 –0.23 to 1.13 NS 0.70 0.03 to 1.37 *

O3 RD 0.59 0.04 to 1.14 * –0.16 –1.00 to 0.69 NS 0.42 –0.44 to 1.29 NS

COPD 1.05 0.17 to 1.93 * –0.11 –1.51 to 1.32 NS 0.94 –0.49 to 2.38 NS

CVD 0.04 –0.42 to 0.51 NS 0.58 –0.15 to 1.31 NS 0.62 –0.12 to 1.36 NS

Abbreviations: CI, confidence interval; NS, not significant.

aChange in ER per 10-μg/m3 increase in concentration of air pollutant averaged over the lag 0 and lag 1 days when 

influenza intensity changed from the baseline (0%) to the mean level (10%).

 bER per 10-μg/m3

 increase in concentration 

of air pollutant averaged over the lag 0 and lag 1 days when influenza intensity is assumed equal to 0. cER per 10-μg/m3

increase in concentration of air pollutant averaged over the lag 0 and lag 1 days when intensity is assumed equal to 10% 

(mean level of influenza intensity). *0.01 < p ≤ 0.05; **0.001 < p ≤ 0.01; #p ≤ 0.001.

Table 3. Modifying effects of influenza for NO2 and SO2 effects on hospitalization.

Modifying effecta Baseline effectb Effect at mean level of influenza intensityc

Pollutant Disease Age group (years) ER 95% CI p-Value ER 95% CI p-Value ER 95% CI p-Value

NO2 RD All –0.09 –0.32 to 0.15 NS 0.85 0.51 to 1.18 # 0.76 0.51 to 1.01 #

≥ 65 –0.07 –0.35 to 0.22 NS 1.06 0.64 to 1.48 # 0.99 0.68 to 1.30 #

ARD All 0.33 –0.03 to 0.70 NS 0.55 –0.02 to 1.12 NS 0.88 0.46 to 1.31 #

0–14 –0.18 –0.57 to 0.22 NS 0.44 –0.16 to 1.04 NS 0.26 –0.19 to 0.71 NS

COPD All 0.09 –0.26 to 0.44 NS 1.84 1.32 to 2.35 # 1.93 1.54 to 2.32 #

≥ 65 0.43 0.05 to 0.81 * 1.19 0.62 to 1.76 # 1.62 1.19 to 2.06 #

CVD All 0.04 –0.20 to 0.28 NS 0.98 0.63 to 1.33 # 1.02 0.76 to 1.29 #

≥ 65 –0.03 –0.32 to 0.26 NS 1.30 0.89 to 1.70 # 1.27 0.96 to 1.57 #

SO2 RD All –0.24 –0.65 to 0.16 NS 0.31 –0.23 to 0.86 NS 0.07 –0.30 to 0.44 NS

≥ 65 –0.33 –0.83 to 0.17 NS 0.37 –0.30 to 1.05 NS 0.04 –0.42 to 0.50 NS

ARD All 0.86 0.20 to 1.53 * –0.77 –1.69 to 0.16 NS 0.09 –0.55 to 0.73 NS

0–14 0.53 –0.16 to 1.22 NS –0.60 –1.56 to 0.37 NS –0.07 –0.74 to 0.60 NS

COPD All 0.35 –0.32 to 1.02 NS 0.29 –0.57 to 1.16 NS 0.64 0.04 to 1.25 *

≥ 65 0.41 –0.29 to 1.13 NS 0.17 –0.77 to 1.12 NS 0.58 –0.07 to 1.24 NS

CVD All –0.15 –0.60 to 0.30 NS 1.10 0.52 to 1.69 # 0.95 0.54 to 1.36 #

≥ 65 –0.28 –0.80 to 0.25 NS 1.50 0.83 to 2.17 # 1.22 0.75 to 1.69 #

Abbreviations: CI, confidence interval; NS, not significant.

aChange in ER per 10-μg/m3

 increase in concentration of air pollutant averaged over the lag 0 and lag 1 days when influenza intensity changed from the baseline (0%) to the mean level 

(10%). bER per 10-μg/m3 increase in concentration of air pollutant averaged over the lag 0 and lag 1 days when influenza intensity is assumed equal to 0. cER per 10-μg/m3 increase in 

concentration of air pollutant averaged over the lag 0 and lag 1 days when intensity is assumed equal to 10% (mean level of influenza intensity). *0.01 < p ≤ 0.05; #p ≤ 0.001.
Modification by influenza on air pollution effects

Environmental Health Perspectives • volume 117 | number 2 | February 2009 251

on hospitalization. The difficulty in assess‐

ing the interaction between influenza and air 

pollutants at the population level may occur 

partly because their seasonal peaks do not 

overlap. For example, in Hong Kong NO2

and PM10 are highest in December and 

January, SO2 is highest around August, and 

O3 peaks from September through December 

(data not shown), and influenza tends to 

reach peaks in January–February and May–

July (Wong et al. 2004). Taking advantage of 

long-standing surveillance for air pollutants 

and influenza virus activity, we estimated the 

extent to which influenza modifies the effects 

of air pollutants in this study.

Interestingly, our results suggest that 

positive effect modification of influenza on 

the effects of O3 might be more pronounced 

compared with its modification of the impact 

of the other three pollutants. O3 is a strong 

oxidative agent and also a potent pulmonary 

irritant. For effects of air pollution on mortal‐

ity, we found significant increases in influenza 

intensity only in the effect of O3 on RD and 

COPD; this result did not change the effects 

of the other air pollutants. For effects of air 

pollution on hospitalization, effect modifica‐

tion of influenza on the effects of O3 could 

be detected for ARD, RD, and COPD. 

However, for the other three pollutants, we 

detected such modification only for one of the 

three RD categories (i.e., NO2 for COPD, 

SO2 for ARD, and PM10 for RD). Several 

laboratory-based studies have demonstrated 

the positive interaction between effects of O3

and influenza. In a study using mice, con‐

tinuous exposure of 0.5 ppm (1.0 mg/m3) O3

attenuated acute lung damage during early 

influenza infection but, conversely, exacer‐

bated long-term lung injury (Jakab and 

Bassett 1990). Studies on respiratory viruses 

other than influenza also suggested a possible 

synergistic effect of O3 on respiratory infec‐

tion. For example, exposure to 0.2 ppm (0.4

mg/m3) O3 has been reported to increase the 

efficiency of rhinovirus infection of respiratory 

epithelial cells from 41% to 67%, and this 

effect could be attenuated by the use of anti‐

oxidants (Spannhake et al. 2002). Exposure 

to 0.2 ppm O3 markedly increased adhesion 

of polymorphonuclear leukocytes (PMNs) 

to human tracheal epithelial cells (Tosi et al. 

1994). However, another study in young 

male volunteers showed that intermittent 

exposure to 0.3 ppm O3 after infection by 

rhinovirus did not change adhesion of PMNs

to the nasal epithelium, or levels of interferon 

(Henderson et al. 1988). Interaction between 

influenza and O3 needs more support from 

laboratory studies.

Table 4. Modifying effects of influenza for PM10 and O3 effects on hospitalization.

Age group Modifying effecta Baseline effectb Effect at mean level of influenza intensityc

Pollutant Disease (years) ER 95% CI p-Value ER 95% CI p-Value ER 95% CI p-Value

PM10 RD All –0.16 –0.34 to 0.01 NS 0.78 0.51 to 1.06 # 0.62 0.41 to 0.82 #

≥ 65 –0.15 –0.36 to 0.06 NS 0.98 0.64 to 1.32 # 0.82 0.57 to 1.08 #

ARD All 0.13 –0.14 to 0.40 NS 0.70 0.24 to 1.16 ** 0.83 0.48 to 1.18 #

0–14 –0.11 –0.40 to 0.19 NS 0.55 0.06 to 1.03 * 0.44 0.08 to 0.81 *

COPD All –0.14 –0.40 to 0.12 NS 1.49 1.06 to 1.92 # 1.34 1.02 to 1.67 #

≥ 65 0.09 –0.19 to 0.37 NS 1.02 0.55 to 1.49 # 1.11 0.75 to 1.47 #

CVD All –0.02 –0.20 to 0.16 NS 0.64 0.35 to 0.93 # 0.62 0.40 to 0.84 #

≥ 65 –0.12 –0.33 to 0.09 NS 0.90 0.57 to 1.23 # 0.78 0.53 to 1.03 #

O3 RD All 0.24 0.04 to 0.43 * 0.60 0.32 to 0.88 # 0.84 0.61 to 1.06 #

≥ 65 0.40 0.16 to 0.64 # 0.53 0.17 to 0.89 ** 0.93 0.64 to 1.22 #

ARD All 0.46 0.15 to 0.76 ** 0.84 0.37 to 1.31 # 1.30 0.91 to 1.68 #

0–14 –0.19 –0.51 to 0.13 NS 0.94 0.43 to 1.45 # 0.75 0.34 to 1.16 #

COPD All 0.17 –0.14 to 0.48 NS 1.39 0.93 to 1.85 # 1.56 1.18 to 1.93 #

≥ 65 0.40 0.07 to 0.73 * 0.70 0.19 to 1.20 ** 1.10 0.69 to 1.52 #

CVD All 0.20 –0.02 to 0.41 NS 0.00 –0.29 to 0.30 NS 0.20 –0.05 to 0.45 NS

≥ 65 0.21 –0.03 to 0.46 NS –0.03 –0.37 to 0.31 NS 0.18 –0.11 to 0.47 NS

Abbreviations: CI, confidence interval; NS, not significant.

aChange in ER per 10-μg/m3

 increase in concentration of air pollutant averaged over the lag 0 and lag 1 days when influenza intensity changed from the baseline (0%) to the mean level (10%). bER per 10-μg/m3

 increase in concentration of air pollutant averaged over the lag 0 and lag 1 days when influenza intensity is assumed equal to 0. cER per 10-μg/m3 increase in concentration 

of air pollutant averaged over the lag 0 and lag 1 days when intensity is assumed equal to 10% (mean level of influenza intensity). *0.01 < p ≤ 0.05; **0.001 < p ≤ 0.01; #p ≤ 0.001.

Table 5. The baseline and modifying effects of influenza for effects of O3 on hospitalization by sex.

Age group Modifying effecta Baseline effectb Effect at mean level of influenza intensityc

Disease Sex (years) ER 95% CI p-Value ER 95% CI p-Value ER 95% CI p-Value

RD Male All 0.05 –0.18 to 0.27 NS 0.79 0.46 to 1.13 # 0.84 0.57 to 1.11 #

≥ 65 0.38 0.08 to 0.69 * 0.66 0.20 to 1.11 ** 1.04 0.68 to 1.41 #

Female All 0.22 –0.03 to 0.48 NS 0.65 0.26 to 1.04 ** 0.87 0.56 to 1.19 #

≥ 65 0.48 0.15 to 0.82 ** 0.72 0.20 to 1.25 ** 1.21 0.79 to 1.63 #

ARD Male All 0.01 –0.31 to 0.33 NS 1.03 0.52 to 1.54 # 1.03 0.63 to 1.44 #

0–14 –0.27 –0.67 to 0.14 NS 0.95 0.31 to 1.59 ** 0.68 0.17 to 1.19 **

Female All 0.05 –0.30 to 0.41 NS 0.58 0.01 to 1.15 * 0.63 0.18 to 1.09 **

0–14 –0.19 –0.65 to 0.28 NS 1.23 0.49 to 1.98 ** 1.04 0.45 to 1.64 #

COPD Male All 0.02 –0.32 to 0.36 NS 0.91 0.40 to 1.43 # 0.93 0.51 to 1.35 #

≥ 65 0.25 –0.15 to 0.65 NS 0.71 0.10 to 1.32 * 0.96 0.47 to 1.46 #

Female All 0.63 0.19 to 1.07 ** 1.55 0.87 to 2.23 # 2.19 1.63 to 2.75 #

≥ 65 0.88 0.36 to 1.40 # 1.09 0.27 to 1.91 ** 1.97 1.31 to 2.65 #

CVD Male All 0.21 –0.06 to 0.49 NS –0.10 –0.49 to 0.30 NS 0.11 –0.21 to 0.44 NS

≥ 65 0.30 –0.03 to 0.62 NS –0.05 –0.53 to 0.42 NS 0.24 –0.15 to 0.64 NS

Female All 0.14 –0.13 to 0.41 NS 0.11 –0.28 to 0.50 NS 0.25 –0.07 to 0.58 NS

≥ 65 0.17 –0.14 to 0.47 NS 0.22 –0.23 to 0.66 NS 0.38 0.02 to 0.75 *

Abbreviations: CI, confidence interval; NS, not significant.

aChange in ER per 10-μg/m3

 increase in concentration of air pollutant averaged over the lag 0 and lag 1 days when influenza intensity changed from the baseline (0%) to the mean level (10%). bER per 10-μg/m3

 increase in concentration of air pollutant averaged over the lag 0 and lag 1 days when influenza intensity is assumed equal to 0. cER per 10-μg/m3 increase in concentration 

of air pollutant averaged over the lag 0 and lag 1 days when intensity is assumed equal to 10% (mean level of influenza intensity). *0.01 < p ≤ 0.05; **0.001 < p ≤ 0.01; #p ≤ 0.001.
Wong et al.

252 volume 117 | number 2 | February 2009 • Environmental Health Perspectives

Although PM10 is associated with signifi‐

cant risk of hospitalization for almost all the 

health outcomes under study at both the base‐

line and mean level of influenza intensity, we 

identified significant negative interaction only 

between PM10 and influenza in their effects 

on hospitalization for RD in males in the allages group. Influenza intensity was associated 

with reduction of ER of PM10. This negative 

interaction is in contrast to many previous stud‐

ies, which have demonstrated that exposure 

to PM10 increased the host susceptibility to 

influenza infection by up-regulating immuno‐

regulatory cytokines (Diaz-Sanchez 1997), by 

depressing pulmonary macrophage function 

(Yin et al. 2002) and also by increasing virus 

attachment to respiratory epithelial cells (Jaspers 

et al. 2005). We postulate that the seemingly 

negative interaction between effects of PM10

and influenza on hospitalization observed in 

this study may lie in the linkage of ultraviolet 

radiation (UVR) to PM10. In Hong Kong, 

concentrations of PM10 are negatively corre‐

lated with intensity of UVR in the ambient air 

(r = –0.17, p < 0.001). When the level of PM10

concentration is high, exposure to UVR is low. 

Exposure to erythemal doses of UVR before

influenza infection has been shown to increase 

the influenza-associated mortality in mice in a 

dose-dependent manner, without remarkably 

changing immunity response against influenza 

(Ryan et al. 2000). The adverse health effects 

of PM10 may be partially attenuated by the 

reduced effects due to the associated lowered 

levels of UVR. This attenuation may contrib‐

ute to the observed significant negative interac‐

tion between PM10 and influenza, which we 

found for respiratory hospitalization for males 

[see Supplemental Material, Table 3 (http://

www.ehponline.org/members/2008/11605/

suppl.pdf)], although both PM10 and influ‐

enza infection could independently increase the 

risk of hospitalization. However, the results of 

the laboratory studies describing the effects of 

UVR on immune function remain controver‐

sial and uncertain, and it was suggested that 

severity of respiratory viral infections could be 

related to radiation doses from UVR [reviewed 

by Cannell et al. (2006)]. Future studies may 

provide more insight into the role of UVR in 

interaction between influenza and PM10.

In this study, we found significant posi‐

tive interaction between the effects of influ‐

enza and NO2 on hospitalization for COPD 

in the males in the ≥ 65 age group. Some labo‐

ratory studies described a positive interaction 

between influenza and NO2 (Chauhan et al. 

2003; Frampton et al. 1989; Spannhake et al. 

2002), whereas others did not detect such an 

interaction (Devlin et al. 1999; Frampton et al. 

2002; Goings et al. 1989). We also found that 

the increase in influenza intensity would sig‐

nificantly raise the effects of SO2 on hospitaliza‐

tion for ARD. The damage caused by SO2 to 

the human pulmonary defense system mainly 

involves nonspecific airway reactivity, such as 

lower mucociliary transportation rate, decreased 

alveolar clearance of deposited particles, and 

pulmonary macrophage function (Schlesinger 

1999). People with hypersensitive airways, 

including COPD patients (Cazzola et al. 1991), 

have been shown to be more sensitive to SO2

than are healthy individuals (Schlesinger 1999), 

but we observed the marked positive interac‐

tion between SO2 and influenza only in ARD, 

and not in COPD or CVD.

Interaction between air pollutants and 

influenza could have a competitive or a satu‐

ration effect, in that both need to attach to 

respiratory epithelial cells to cause harm. 

Therefore, if one factor saturates the sites on 

a particular pathway, there may be little room 

for the other to exert any additive effect. Early 

studies in mice showed that exposure to O3

(0.9 ppm for 3 hr) and SO2 (6 ppm for 7 

days) could almost completely or partially 

inhibit influenza virus growth in the nasal cav‐

ity (Andersen et al. 1977; Fairchild 1977). 

Similarly, a high dose of NO2 (1.5 ppm) could 

suppress the replication and release of RSV in 

human bronchial epithelial cells (Becker and 

Soukup 1999). A small reduction in the num‐

ber of pneumonia cases was also observed after 

influenza-infected mice were exposed SO2 at 

a low concentration (of < 10 ppm) (Fairchild 

et al. 1972). Despite the increased awareness 

of the adverse impacts of both air pollution 

and influenza on human health, populationbased studies on the potential synergistic effect 

or even competitive relationship between air 

pollutants and influenza viruses are lacking. 

Laboratory studies are insufficient to demon‐

strate a plausible mechanism for an interaction 

between influenza and air pollution on human 

health, and epidemiologic studies that can give 

support to formulation of plausible hypotheses 

at population level are needed.

The estimated effects of air pollutants at the 

mean level of influenza intensity are consistent 

with our previous studies for the short-term 

effects of air pollutants without adjustment 

for influenza intensity (Wong et al. 2001,

2002). In our study, the modifying effects esti‐

mated from the interaction models, in terms 

of changes in ER per 10-μg/m3 increase in 

concentration of an air pollutant when influ‐

enza intensity increased by 10%, say, for O3

ranged from 0.2% to 0.9%. These are substan‐

tial changes compared with the magnitude of 

air pollution effects of around 1% estimated 

in most studies (Wong et al. 2002, 2004). 

Our results show that the effects of air pollu‐

tion (particularly O3) varied to some extent 

depending on the level of influenza virus in the 

circulation. We also did the analysis without 

adjustment for effect modification of influenza. 

Most estimates for the effects of air pollut‐

ants were significant, with levels lying between 

those in the absence of influenza activity and at 

the mean level of influenza intensity (data not 

shown). Environmental protection and other 

public health agencies should take influenza 

peak seasons into account when they issue air 

pollution and health warnings to the public.

We detected no significant modifying 

effects of influenza on the effects of air pol‐

lutants on mortality, except for O3 effects on 

mortality from RD and COPD. CVD was the 

only disease group of mortality and hospitaliza‐

tion in which we detected no significant inter‐

action between influenza and any air pollutant, 

although influenza and air pollutants have 

been documented to be associated with CVD 

in several epidemiologic studies. Influenza is 

believed to accelerate the coagulation process 

by evoking proinflammatory response, stimu‐

lating prothrombotic cytokines, and increas‐

ing plasma viscosity in human (Madjid et al. 

2004). The biologic impacts of ambient air 

pollutants on progression of CVDs have been 

frequently reported, especially for PM10 and 

O3. Similar to influenza, these air pollutants 

are believed to stimulate systematic inflamma‐

tion and to increase oxidant stress, which may 

subsequently provoke cardiovascular events 

(Brook et al. 2004). However, interaction 

between influenza and ambient air pollutants 

for effects on cardiovascular mortality and hos‐

pitalization does not appear to be of sufficient 

strength to be detected in our model.

A limitation in the interpretation of these 

observations is that it is implausible to reliably 

separate the effects of air pollutants because 

they frequently react with each other; for 

example, NO2 can be photolyzed into nitric 

oxide and oxygen atoms, the latter of which 

combine with molecular oxygen to form O3

(Brook et al. 2004). Future studies for possible 

interaction between influenza and combined 

air pollution may provide more insight into 

the mechanisms by which RDs and CVDs 

associated with exposure to ambient air pol‐

lution are enhanced or weakened by influenza 

infection. A further limitation in interpretation 

of the results relates to multiple comparisons. 

With 24 health outcomes in hospitalization 

(including analyses by sexes) to assess for each 

pollutant, we expect to find about one statisti‐

cally significant interaction result each at a 

5% level. Thus, in the one significant effect 

modification we observed for SO2 or PM10, 

and the two significant effect modifications 

we observed for NO2 only with COPD (in 

males, and males and females combined in the 

≥ 65 age group), we cannot exclude that the 

results may simply be attributable to chance 

for these two pollutants. For O3, we found 

eight statistically significant interactions, and 

two of them are significant at the 0.1% level. 

We believed that the results are unlikely to be 

attributable solely to chance at the 5% level 

even with Bonferroni adjustment. 
Modification by influenza on air pollution effects

Environmental Health Perspectives • volume 117 | number 2 | February 2009 253

In this study, we studied the impact of 

influenza on health effects of air pollution 

at lag 0–1 days. These lag days were recom‐

mended and chosen a priori for presentation 

of the main results in the PAPA studies. 

However, when considering the impact of 

influenza on health effects of air pollutant at 

longer lag days, we observed more statistical 

significant estimates for modifying effects of 

influenza on hospitalization outcomes (data 

not shown). We did not adjust for potential 

changes in mortality counts in year 2001 due 

to a switch of mortality codes from ICD-9 

to ICD-10. Unfortunately, because the data 

were collected through a computerized system 

during the routine medical practice, we were 

unable to do the sensitivity analysis to assess 

the impact of switching codes on our results. 

However, because the changes in mortality 

counts were estimated to be small (Tsang and 

Cheung 2005), and because they affected only 

a short time period in the middle of the study 

period, we believe the impacts of inconsistent 

ICD codes on the results would be minimal.

Conclusions

In this epidemiologic study of interactions 

between air pollution and influenza activity, 

we have shown that influenza modifies the 

effects of air pollution on mortality and hospi‐

talization of RDs. These results support a link 

between air pollution mainly for O3 and influ‐

enza activity in their effects on human health, 

which have been demonstrated in animal stud‐

ies. Further research is needed to clarify what 

conditions produce observable interactions 

between effects of air pollution and influenza 

and to provide the evidence for causality.

Correction

In Table 1, the values for ARD were incor‐

rect in the manuscript originally published 

online. They have been corrected here.

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