### 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 CVD s (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 (PM 10 

### ), 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 PM 10 

### , 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 : SO 2 

### , nitrogen dioxide, ozone, and PM 10 

### . 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 –2 002. We based these counts on discharge diagnoses of admission records coded according to the International Classification of Disease s, 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 Peiris 3

1 Department of Community Medicine and School of Public Health, University of Hong Kong, Hong Kong Special Administration Region, People’s Republic of China; 2 Department of Family and Community Medicine, Chinese University of Hong Kong, Hong Kong Special Administration Region, People’s Republic of China; 3 Department of Microbiology, University of Hong Kong, Hong Kong Special Administration Region, People’s Republic of China



### B ackground 

### : 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 influ

enza on health effects of ambient air pollutants.

O b jectives 

### : We aimed to assess modifying effects of influenza on health effects of ambient air pollutants.

M ethods 

### : 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.

R

esults 

### : 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/m 3 

### increase in concentration of O 3 

### 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 dis

ease 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.

C onclusions 

### : Influenza activity could be an effect modifier for the health effects of air pollutants par

ticularly for O 3 

### and should be considered in the studies for short-term effects of air pollutants on health.

K

ey 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 age

and 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 NO 2 

### , SO 2 

### , and PM 10 

### and 8

- hr (1000–1800 hours ) mean concentration of O 3 

### from the HKEPD database. We defined daily

concentrations as non missing if at least 18 of 24 hourly concentrations of NO 2 

### , SO 2 

### , and

PM 10 

### , and six of eight hourly concentrations of O 3 

### were available. We first centered non

‐ missing daily means for each station i [i.e., we subtracted individual daily concentrations ( X

ij 

### ) by an annual station mean ( X

i 

### ) 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



### = ( X

ij 

### – X i 

### + 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 auto regressive 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 inter action 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/m 3 

### increase of each air pollut

‐ ant as the baseline effect of air pollution. We also calculated the ER per 10

- μg/m 3 

### 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/m 3 

### for NO 2 

### , SO 2 

### , PM 10 

### , and O 3 

### , 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/m 3 )

NO 2 58.7 ± 20 10.1 45.1 56.3 69.6 168 SO 2 17.8 ± 12.1 1.8 9.6 14.7 22.1 109.4
PM 10 51.6 ± 25.3 13.5 31.8 45.5 66.7 188.5 O 3 36.9 ± 23 –8.2 a 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

a V alu e for O 3 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 NO 2 

### and SO 2 

### , and for RD associated with NO 2 

### (ER

, 1.23%, 1.64%

, and 1.24%, respectively) but were not sig

‐ nificant ( p > 0.05) for all mortality outcomes associated with O 3 

### ( Table 2 ). We found sig

‐ nificant modifying effects of influenza for the
O 3 

### effects on mortality for RD and COPD (ER increased 0.59% and 1.05%) but not for the other pollutants. The effects of NO 2 

### 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 NO 2 

### 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 SO 2 

### 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 SO 2 

### on hospitalization to be sig

‐ nificant ( p ≤ 0.05) only for ARD in all

- ages group with ER increased 0.86% (Table 3).

For PM 10 

### , 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 PM 10 

### on hospitalization in all the disease categories under study (Table 4). We found significant effects of O 3 

### 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 O 3 

### 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 O 3 

### on hospitalization, with increase s 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 O 3 

### 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 NO 2 

### with an increased ER on COPD in the males in the

≥ 65 group, and for PM 10 

### with decreased ER on RD in the males in the all

- ages group [ data not shown ; see Supplemental Material, Table s 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 NO 2 

### concentration

, which markedly modified the effects of PM 10 

### on mortality (Katsouyanni et al. 2001). Our study demonstrated effect modification by influenza on the effects of single air pollut

‐ ants, particularly O 3 

### , both on mortality and **Table 2**

**.** Modifying effects of influenza for the four pollutant effects on mortality

. Effect at mean Modifying effect a Baseline effect b level of influenza intensity c
Pollutant Disease ER 95% CI p -Value ER 95% CI p -Value ER 95% CI p -Value

NO 2 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 #

SO 2 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

PM 10 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 *

O 3 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.

a Change in ER per 10

- μg/m 3 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%)

. b ER per 10

- μg/m 3 increase in concentration of air pollutant averaged over the lag 0 and lag 1 days when influenza intensity is assumed equal to 0

. c ER per 10

- μg/m 3 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 NO 2 and SO 2 effects on hospitalization

. Modifying effect a Baseline effect b Effect at mean level of influenza intensity c
Pollutant Disease Age group (years) ER 95% CI p -Value ER 95% CI p -Value ER 95% CI p -Value

NO 2 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 #

SO 2 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.

a Change in ER per 10

- μg/m 3 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%)

. b ER per 10

- μg/m 3 increase in concentration of air pollutant averaged over the lag 0 and lag 1 days when influenza intensity is assumed equal to 0

. c ER per 10

- μg/m 3 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 NO 2 

### and PM 10 

### are highest in December and January, SO 2 

### is highest around August, and
O 3 

### 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 O 3 

### might be more pronounced compared with its modification of the impact of the other three pollutants. O 3 

### is a strong oxidative agent and also a potent pulmonary irritant. For effects of air pollution on mortal

‐ ity, we found significant increase s in influenza intensity only in the effect of O 3 

### 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 O 3 

### 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.

, NO 2 

### for COPD,
SO 2 

### for ARD

, and PM 10 

### for RD). Several laboratory

- based studies have demonstrated the positive interaction between effects of O 3 

### and influenza. In a study using mice, con

‐ tinuous exposure of 0.5 ppm (1.0 mg/m 3 

### ) O 3 

### 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 O 3 

### on respiratory infec

‐ tion. For example, exposure to 0.2 ppm (0.4 mg/m 3 

### ) O 3 

### 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 O 3 

### markedly increased adhesion of polymorphonuclear leukocytes (PMN s ) to human tracheal epithelial cells (Tosi et al. 1994). However

, another study in young male volunteers showed that intermittent exposure to 0.3 ppm O 3 

### after infection by rhinovirus did not change adhesion of PMN s to the nasal epithelium, or levels of interferon (Henderson et al. 1988). Interaction between influenza and O 3 

### needs more support from laboratory studies.

**Table 4.** Modifying effects of influenza for PM 10 and O 3 effects on hospitalization

. Age group Modifying effect a Baseline effect b Effect at mean level of influenza intensity c
Pollutant Disease (years) ER 95% CI p -Value ER 95% CI p -Value ER 95% CI p -Value

PM 10 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 #

O 3 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.

a Change in ER per 10

- μg/m 3 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%)

. b ER per 10

- μg/m 3 increase in concentration of air pollutant averaged over the lag 0 and lag 1 days when influenza intensity is assumed equal to 0

. c ER per 10

- μg/m 3 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 intensit y)

. *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 O 3 on hospitalization by sex

. Age group Modifying effect a Baseline effect b Effect at mean level of influenza intensity c
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.

a Change in ER per 10

- μg/m 3 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%)

. b ER per 10

- μg/m 3 increase in concentration of air pollutant averaged over the lag 0 and lag 1 days when influenza intensity is assumed equal to 0

. c ER per 10

- μg/m 3 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 intensit y)

. *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 PM 10 

### 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 PM 10 

### and influenza in their effects on hospitalization for RD in males in the all

ages group. Influenza intensity was associated with reduction of ER of PM 10 

### . This negative interaction is in contrast to many previous stud

‐ ies, which have demonstrated that exposure

to PM 10 

### 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 effect s of PM 10 

### and influenza on hospitalization observed in this study may lie in the linkage of ultra violet radiation (UVR) to PM 10 

### . In Hong Kong, concentrations of PM 10 

### are negatively corre

‐ lated with intensity of UVR in the ambient air ( r

=
– 0.17, p < 0.001). When the level of PM 10 

### 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 PM 10 

### 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 PM 10 

### 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 PM 10 

### 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 PM 10 

### . In this study, we found significant posi

‐ tive interaction between the effects of influ

‐ enza and NO 2 

### on hospitalization for COPD in the males in the ≥ 65 age group. Some labo

‐ ratory studies described a positive interaction between influenza and NO 2 

### (Chauhan et al. 2003; Frampton et al. 1989; Spannhake et al. 2002), whereas other s 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 SO 2 

### on hospitaliza

‐ tion for ARD. The damage caused by SO 2 

### to the human pulmonary defense system mainly involves non specific 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 SO 2 

### than are healthy individuals (Schlesinger 1999), but we observed the marked positive interac

‐ tion between SO 2 

### 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 O 3 

### (0.9 ppm for 3 hr ) and SO 2 

### (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 NO 2 

### (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 SO 2 

### 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, population

based 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/m 3 

### increase in concentration of an air pollutant when influ

‐ enza intensity increased by 10%, say

, for O 3 

### 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 O 3 

### ) 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 detect ed no significant modifying effects of influenza on the effects of air pol

‐ lutants on mortality, except for O 3 

### 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 CVD s have been frequently reported, especially for PM 10 

### and
O 3 

### . 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, NO 2 

### can be photolyzed into nitric oxide and oxygen atoms, the latter of which combine with molecular oxygen to form O 3 

### (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 CVD s 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 SO 2 

### or PM 10 

### , and the two significant effect modifications we observed for NO 2 

### 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 O 3 

### , 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 RD s. These results support a link between air pollution mainly for O 3 

### 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.

C orrection



### 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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