Executive Summary

Background and objectives: Locally derived data are needed for the SAR Government and regulatory agencies to support the drafting and implementation of effective legislation for the management and control of the environment. In 1996, the Environmental Protection Department commissioned the Chinese University of Hong Kong to carry out a study on health effects of air pollution and in 1997 the University of Hong Kong to carry out a follow-up validation study. The study performed by the University of Hong Kong identified some irregularities in the way the data were selected, managed and analysed in the previous study. It also obtained effect estimates which were more comparable to the results obtained by the collaborating centres of Air Pollution on Health: a European Approach (APHEA). Finally it pointed to new directions in methodology and in modelling methods adopted by the APHEA Phase Two study which could be used in Hong Kong.

In this study, reported here, the problems of the earlier Hong Kong studies were resolved in that (i) three years of data were used to obtain better models; (ii) non-linearity effects in the pollutant and covariates were modelled using a generalized additive modelling method; and (iii) patterns in the daily variations were explained as far as possible by using more appropriate wave lengths, introducing influenza epidemics in the models and using more recently developed statistical methods to control for autocorrelation in the data.

Health outcomes: Daily counts of hospital admissions with a discharge diagnosis of respiratory disease (ICD9 460-519), chronic obstructive pulmonary disease (COPD) (490-496 excluding 493), asthma (493), cardiac disease (390-429) and ischaemic heart disease (IHD) (410-414), for all ages, as well as hospital deaths due to respiratory (460-519) and cardiovascular (390-459) diseases, for all ages, were used as the 7 major health outcomes. Among them, admissions were sub-categorised as follows: for respiratory disease, into 0-14, 15-64, 65-74 and 75+ age groups; for asthma, into 0-14 and 15-64 age groups; for cardiac disease, into 15-64, 65-74 and 75 age groups and for IHD, into 15-64, 65-74 and 75+ age groups. These categories for all ages and specific age groups formed 19 categories of health outcomes for analysis.

Summary of findings: The effects for each pollutant without adjustment for co-pollutant, on the above-mentioned 19 health outcomes and with adjustment for the most confounding co-pollutant, on the above 7 major health outcomes are summarized in this section.

NO₂: NO₂ was shown to have strong effects on all the 19 health outcomes under study without adjustment for co-pollutants, except on the IHD 15-64 and all ages groups. The effects on the 7 major health outcomes, with adjustment for co-pollutant and autocorrelation, were significant at the 5% level except IHD admissions and cardiovascular hospital deaths for all ages. The effects on asthma admissions and respiratory deaths for all ages were likely to be non-linear. The effects on respiratory, COPD, cardiac and IHD admissions for all ages were higher in the cool than in the warm season.

SO₂: SO₂ did not have an effect on most of the 19 health outcomes under study without adjustment for co-pollutant. With adjustment for co-pollutant and autocorrelation, it had an effect on COPD admissions for all ages (p=0.005). The effect on cardiac admissions for all ages was higher in the cool than in the warm season.

RSP: RSP was associated with most of the 19 health outcomes under study without adjustment for co-pollutant. With adjustment for co-pollutants and autocorrelation, it had an effect on respiratory (p=0.023) and asthma (p=0.045) admissions for all ages and the effects were likely to be non-linear. The effect on cardiac admissions for all ages was higher in the cool than in the warm season.

O₃: O₃ had effects on most of the 19 health outcomes under study without adjustment for co-pollutant. With adjustment for co-pollutant and autocorrelation, it had strong effects on respiratory and asthma admissions for all ages (p=0.000). The effects on COPD, cardiac and IHD admissions for all ages were stronger in the cool than in warm season.

FSP: FSP (PM_2.5) had effects on most of the 19 health outcomes under study without adjustment for co-pollutant. With adjustment for co-pollutant, the effects were not significant for all of the 7 major health outcomes for all ages (p>0.192). But as the pollutant was measured in only one monitoring station and there were missing data problems, the effects need to be further investigated.

Public health implications: The results from this study showed strong short-term effects of air pollutants on hospital admissions and hospital deaths.

In the daily number of hospital admissions for all ages, there was a 4-8% increase due to respiratory disease; 5-15% increase due to chronic obstructive pulmonary disease and 11-22% increase due to asthma. There was also a 3-7% increase in admissions due to a cardiac disease. There was a 3-5% increase due to a cardiovascular disease (ICD9 390-459), which includes cardiac disease as well as cerebrovascular disease and diseases of arteries, arterioles, capillaries, veins and lymphatics. These percentage increases are all expressed as rates per 50 ug/m³ increase in the concentration of air pollutants (NO₂, SO₂, O₃ and RSP).

In the daily number of hospital deaths for all ages, there was a 10% increase due to respiratory disease and 8% increase due to cardiovascular disease for every 50 ug/m³ increase in NO₂. For other pollutants the increases were not significant and they need to be further investigated.

The results suggest that air pollution may show stronger health effects in Hong Kong than those obtained in European cities.

Conclusions: The results from this study show that short-term effects of air pollutants on health are strong. It is both feasible and worthwhile to develop further studies on the health effects of air pollution with a longer series of data, using the methodology adopted by the APHEA protocol. Territory-wide SAR mortality, based on daily mortality counts from the Census and Statistics Department, should be included as one of the main health outcomes to be studied.

1.0 Background and introduction

In 1997, the Department was offered a contract by the Environmental Protection Department (EPD) to study the short-term effects of ambient air pollution on public health using hospital admission data in Hong Kong for the period January 1995 to June 1997¹ and to validate the findings of another similar study on data for the period January 1994 to June 1996.² The results revealed that, similar to other studies overseas, there were significant effects on morbidity and mortality of individual pollutants i.e. nitrogen dioxide (NO₂), sulphur dioxide (SO₂), respirable suspended particulates (RSP) and ozone (O₃). The study performed by the Department modified the way the data were selected, managed and analysed in the previous study and obtained effect estimates which were more comparable to the results obtained by collaborating centres of Air Pollution on Health: a European approach (APHEA). In line with new directions in methodology and in modelling methods adopted by the APHEA-2 protocol,³ our report also pointed out some limitations of both of the Hong Kong studies and indicated what should be done in any future studies.

The limitations in the Hong Kong studies will be further resolved and discussed in this new phase of study. First, with three years of data, a better prediction model will be developed. Second, non-linearity effects in the pollutant(s) or covariates will be modelled using a generalized additive model (in statistical package S-Plus). Third, unexplained patterns in the daily variations will be explained as far as possible by (i) using more appropriate wave lengths for seasonality and terms for time trends, to eliminate as far as possible all unobserved confounding effects; (ii) introducing influenza epidemics in the model to control as much of the observed confounding effects as possible in addition to those due to air temperature and humidity etc; and (iii) using more recently developed statistical methods to control for any auto-correlation and/or extra-Poisson variations in the data.

2.0 Scope and objectives

The following tasks will be completed by the Department of Community Medicine.

1. Single pollutant: A model for each health outcome is fitted with terms to account for all long-term and seasonal patterns and other possible confounding effects. Short-term daily variations are then studied and accounted for by daily variations in SO₂, NO₂, RSP and O₃ individually, based on data from 1 January 1995 to 31 December 1997.

2. Multiple pollutants: From each single pollutant model, the joint effects of each pollutant with other pollutants are studied by putting them in the model. Interactions and multi-collinearity among pollutants are also studied and taken account of, based on the same data as in a) above.

3. Single pollutant PM_2.5: The effect due to PM_2.5 is studied in a similar way as in a) above, but using data from 1 August 1995 to 31 December 1997 when the PM_2.5 concentrations are available from the EPD.

4. Multiple pollutants with PM_2.5: Study b) above but with PM_2.5 instead of RSP. Compare the models with either PM_2.5 or RSP in terms of stability (reliability) in effect estimates.

5. Verification of model: The best model developed from a) to d) above is then used to obtain the predicted daily numbers of admissions for each health outcome. The observed number of admissions in the data 1 January 1998 to 30 June 1998 are compared with the predicted for verification (i.e. predictive validity) of model.

3.0 Materials and methods

4.0 Findings