Individual-level modifiers of the effects of particulate matter on daily mortality. 2006

Ariana Zeka, and Antonella Zanobetti, and Joel Schwartz
Environmental Health Department, Harvard School of Public Health, 401 Park Drive, Suite 415 West, Boston, MA 02215, USA. azeka@hsph.harvard.edu

Consistent evidence has shown a positive association between particulate matter with an aerodiameter of less than or equal to 10 mum (PM(10)) and daily mortality. Less is known about the modification of this association by factors measured at the individual level. The authors examined this question in a case-crossover study of 20 US cities. Mortality events (1.9 million) were obtained for nonaccidental, respiratory, heart disease, and stroke mortality between 1989 and 2000. PM(10) concentrations were obtained from the US Environmental Protection Agency. The authors examined the modification of the PM(10)-mortality association by sociodemographics, location of death, season, and secondary diagnoses. They found different patterns of PM(10)-mortality associations by gender and age but no differences by race. The level of education was inversely related to the risk of mortality associated with PM(10). PM(10)-related, out-of-hospital deaths were more likely than were in-hospital deaths, as were those occurring during spring/fall versus summer/winter. A secondary diagnosis of diabetes modified the effect of PM(10) for respiratory and stroke mortality. Pneumonia was a positive effect modifier for deaths from all causes and stroke, while secondary stroke modified the effects for all-cause and respiratory deaths. The findings suggest that more attention must be paid to population characteristics to identify greater likelihood of exposures and susceptibility and, as a result, to improve policy making for air pollution standards.

UI MeSH Term Description Entries
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D010316 Particle Size Relating to the size of solids. Particle Sizes,Size, Particle,Sizes, Particle
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D002423 Cause of Death Factors which produce cessation of all vital bodily functions. They can be analyzed from an epidemiologic viewpoint. Causes of Death,Death Cause,Death Causes
D004391 Dust Earth or other matter in fine, dry particles. (Random House Unabridged Dictionary, 2d ed) House Dust,Housedust,Dust, House
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000368 Aged A person 65 years of age or older. For a person older than 79 years, AGED, 80 AND OVER is available. Elderly
D000393 Air Pollutants Any substance in the air which could, if present in high enough concentration, harm humans, animals, vegetation or materials. Substances include GASES; PARTICULATE MATTER; and volatile ORGANIC CHEMICALS. Air Pollutant,Air Pollutants, Environmental,Environmental Air Pollutants,Environmental Pollutants, Air,Air Environmental Pollutants,Pollutant, Air,Pollutants, Air,Pollutants, Air Environmental,Pollutants, Environmental Air

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