Abstract and Introduction
Abstract
Objective: The goal of this study was to estimate the associations between outdoor air pollution and cardiovascular hospital admissions for the elderly.
Design: Associations were assessed using the case-crossover method for seven cities: Auckland and Christchurch, New Zealand ; and Brisbane, Canberra, Melbourne, Perth, and Sydney Australia. Results were combined across cities using a random-effects meta-analysis and stratified for two adult age groups: 15-64 years and ≥ 65 years of age (elderly) . Pollutants considered were nitrogen dioxide, carbon monoxide, daily measures of particulate matter (PM) and ozone. Where multiple pollutant associations were found, a matched case-control analysis was used to identify the most consistent association.
Results: In the elderly, all pollutants except O3 were significantly associated with five categories of cardiovascular disease admissions. No associations were found for arrhythmia and stroke. For a 0.9-ppm increase in CO, there were significant increases in elderly hospital admissions for total cardiovascular disease (2.2%) , all cardiac disease (2.8%) , cardiac failure (6.0%) , ischemic heart disease (2.3%) , and myocardial infarction (2.9%) . There was some heterogeneity between cities, possibly due to differences in humidity and the percentage of elderly people. In matched analyses, CO had the most consistent association.
Conclusions: The results suggest that air pollution arising from common emission sources for CO, NO2, and PM (e.g., motor vehicle exhausts) has significant associations with adult cardiovascular hospital admissions, especially in the elderly, at air pollution concentrations below normal health guidelines.
Relevance to clinical and professional practice: Elderly populations in Australia need to be protected from air pollution arising from outdoor sources to reduce cardiovascular disease.
Introduction
There have been several studies on the short-term effects of air pollution on hospital admissions (Burnett et al. 1997a, 1997b; Le Tertre et al. 2002; Pope 2000; Samet et al. 2000), but most have examined single cities. Such single-city studies have been criticized for being applicable only to the city under study and for using different modeling approaches. These comments have led to multicity meta-analyses where the results are pooledfor example, the National Morbidity, Mortality, and Air Pollution Study (NMMAPS) conducted on behalf of the Health Effects Institute in the United States and the APHEA (Air Pollution and Health: A European Approach) studies in Europe. NMMAPS examined the associations between daily hospital counts for cardiovascular admissions in the elderly and air pollutants in 14 cities in different regions of the United States (Dominici et al. 2002b; Samet et al. 2000). The APHEA studies have taken place in two stages, and the latest (APHEA2) comprised eight European cities in the investigation of associations of air pollution on daily cardiovascular admissions (Le Tertre et al. 2002). Multicity studies have also been conducted in Canada (Burnett et al. 1997a, 1997b).
Despite these studies, the strength of the association between outdoor air pollution and health effects is still unclear because of the complexity of the time-series modeling. In addition, when multiple pollutants have been examined, the independent effects of each pollutant are usually addressed in multipollutant models, but these are sensitive to the modeling assumptions. If the association with one pollutant is nonlinear or varies by season, then a two-pollutant model assuming a linear relationship with each pollutant might not give the independent effect of the second pollutant. Therefore, the case-crossover design (Maclure 1991), which is less sensitive to model assumptions, is more appropriate. This method investigates the effects of acute exposures and can also examine both multiple exposures and interactions between exposures. It has been applied to the analysis of the acute effects of environmental exposures, especially air pollution (Sunyer et al. 2000). The method matches case days to nearby control days and hence controls for covariates that change slowly over time (e.g., age, smoking behavior, and usual diet). Such matching also controls for seasonal variation and time trends in the health event (Bateson and Schwartz 2001).
In this study we aimed to find associations between outdoor air pollutant and cardiovascular disease (as measured by counts of hospital admissions) in cities in Australia and New Zealand. The study used two age groups, ≥ 65 years of age (elderly) and 15-64 years of age, although the focus here is on the elderly. The study also examined differences in the associations between cities.