Air pollution and hospital admissions in Sydney, Australia, 1990 to 1994.
OBJECTIVE
This study examined the effects of outdoor air pollutants on daily hospital admissions in Sydney, Australia.


METHODS
A time-series analysis of counts of daily hospital admissions and outdoor air pollutants (1990 to 1994) was performed, by means of Poisson regression that allowed for overdispersion and autocorrelation.


RESULTS
An increase in daily maximum 1-hour concentration of nitrogen dioxide from the 10th to the 90th percentile was associated with an increase of 5.29% (95% confidence interval = 1.07, 9.68) in childhood asthma admissions and 4.60%(-0.17,9.61) in chronic obstructive pulmonary disease (COPD) admissions. A similar increase in daily maximum 1-hour particulate concentration was associated with an increase of 3.01% (-0.38, 6.52) in COPD admissions. An increase from the 10th to the 90th percentile in daily maximum 1-hour nitrogen dioxide, daily maximum 1-hour ozone, and daily mean particulate was associated with an increase in heart disease admissions among those 65 years and older of 6.71% (4.25, 9.23), 2.45% (-0.37, 5.35), and 2.82% (0.90, 4.77), respectively. Heart disease and childhood asthma were primarily associated with nitrogen dioxide; COPD was associated with both nitrogen dioxide and particulates.


CONCLUSIONS
Current levels of air pollution in Sydney are associated with increased hospitalization for respiratory and heart disease.
Morgan
G
G
New South Wales Health Department, Gladesville, Australia. gmorg@doh.health.nsw.gov.au
Corbett
S
S
Wlodarczyk
J
J
D000293:Adolescent; D000328:Adult; D000368:Aged; D000397:Air Pollution / Q000009:adverse effects* / Q000032:analysis*; D001249:Asthma / Q000209:etiology; D002648:Child; D002675:Child, Preschool; D006331:Heart Diseases / Q000209:etiology; D006801:Humans; D007223:Infant; D008173:Lung Diseases, Obstructive / Q000209:etiology; D008875:Middle Aged; D009517:New South Wales; D010343:Patient Admission / Q000706:statistics & numerical data / Q000639:trends*; D016012:Poisson Distribution; D012044:Regression Analysis; D014504:Urban Health