Ambient air pollution and hospitalization for congestive heart failure among elderly people in seven large US cities.
OBJECTIVE
Preexisting data sets were used to investigate the association between hospital admissions for congestive heart failure and air pollutants.


METHODS
Medicare hospital admissions data, ambient air pollution monitoring data, and meteorological data were used to create daily values of hospital admissions for congestive heart failure, maximum hourly temperature, and maximum hourly levels of carbon monoxide, nitrogen dioxide, sulfur dioxide, and ozone. Data were compiled for each of seven cities (Chicago, Detroit, Houston, Los Angeles, Milwaukee, New York, and Philadelphia) for 1986 through 1989. Single-pollutant and multipollutant models with adjustments for temperature, seasonal effects, and weekly cycles were used in conducting negative binomial regression analyses.


RESULTS
Ambient carbon monoxide levels were positively associated with hospital admissions for congestive heart failure in the single-pollutant and multipollutant models for each of the seven cities. The relative risk of hospital admission for congestive heart failure associated with an increase of 10 ppm in carbon monoxide ranged from 1.10 in New York to 1.37 in Los Angeles.


CONCLUSIONS
Hospital admissions for congestive heart failure exhibited a consistent association with daily variations in ambient carbon monoxide. This association was independent of season, temperature, and other major gaseous pollutants.
Morris
R D
RD
Department of Family and Community Medicine, Medical College of Wisconsin, Milwaukee 53226, USA.
Naumova
E N
EN
Munasinghe
R L
RL
D017677:Age Distribution; D000368:Aged; D000393:Air Pollutants / Q000009:adverse effects* / Q000032:analysis; D002248:Carbon Monoxide / Q000009:adverse effects* / Q000032:analysis; D018876:Environmental Illness / Q000453:epidemiology*; D006333:Heart Failure / Q000150:complications* / Q000453:epidemiology*; D006760:Hospitalization / Q000706:statistics & numerical data* / Q000639:trends; D006801:Humans; D016014:Linear Models; D011159:Population Surveillance; D012307:Risk Factors; D014481:United States / Q000453:epidemiology; D014504:Urban Health / Q000706:statistics & numerical data*
D000393:Air Pollutants; D002248:Carbon Monoxide