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Reanalysis of the Harvard Six Cities Study, part II: sensitivity analysis.

Following the validation and replication of the Harvard Six Cities Study (Krewski et al., this issue), we conducted a wide range of sensitivity analyses to explore the observed associations between long-term exposure to fine particle or sulfate air pollution and mortality. We examined the impact of alternative risk models on estimates of risk, taking into account covariates not included in the original analyses. These risk models provided a basis for identifying covariates that may confound or modify the association between fine particle or sulfate air pollution and mortality, and for identifying sensitive population subgroups. The possibility of confounding due to occupational exposures was also investigated. Residence histories were coded for the study subjects and were used to examine temporal patterns of exposure and risk. Our sensitivity analyses showed the mortality risk estimates for fine particle and sulfate air pollution to be highly robust against alternative risk models of the Cox proportional hazards family, including models with additional covariates from the original questionnaires not included in the original published analyses. There was limited evidence of departures from the proportional hazards assumption. Flexible exposure-response models provided some evidence of departures from linearity at both low and high sulfate concentrations. Incorporating information on changes over time in cigarette smoking and body mass index had little effect on the association between fine particles and mortality. There was limited evidence of variation in risk with attained age, gender, smoking status, occupational exposure to dust and fumes, marital status, heart or lung diseases, or lung function. However, air pollution risk did appear to decreasing with increasing educational attainment. Extensive adjustment for occupation using aggregate indices of occupational “dirtiness” and occupational exposure to known lung carcinogens had little impact on the mortality risks associated with particulate air pollution. Our evaluation of population mobility indicated that relatively few subjects moved from their original city of residence. Attempts to identify critical exposure time windows were limited by the lack of marked interindividual variation in temporal exposure patterns throughout the study period. Overall, this extensive sensitivity analysis both supported the conclusions reached by the original investigators and demonstrated the robustness of these conclusions to alternative analytic approaches.

Authors

  • Krewski, D, Krewski D, McLaughlin Centre for Population Health Risk Assessment, Institute for Population Health, University of Ottawa, Ottawa, Ontario, Canada. dkrewski@uottawa.ca

  • Burnett, R T, Burnett RT,

  • Goldberg, M, Goldberg M,

  • Hoover, K, Hoover K,

  • Siemiatycki, J, Siemiatycki J,

  • Abrahamowicz, M, Abrahamowicz M,

  • Villeneuve, P J, Villeneuve PJ,

  • White, W, White W,

YEAR OF PUBLICATION: 2005
SOURCE: Inhal Toxicol. 2005 Jun-Jul;17(7-8):343-53. doi: 10.1080/08958370590929439.
JOURNAL TITLE ABBREVIATION: Inhal Toxicol
JOURNAL TITLE: Inhalation toxicology
ISSN: 0895-8378 (Print) 0895-8378 (Linking)
VOLUME: 17
ISSUE: 7-8
PAGES: 343-53
PLACE OF PUBLICATION: England
ABSTRACT:
Following the validation and replication of the Harvard Six Cities Study (Krewski et al., this issue), we conducted a wide range of sensitivity analyses to explore the observed associations between long-term exposure to fine particle or sulfate air pollution and mortality. We examined the impact of alternative risk models on estimates of risk, taking into account covariates not included in the original analyses. These risk models provided a basis for identifying covariates that may confound or modify the association between fine particle or sulfate air pollution and mortality, and for identifying sensitive population subgroups. The possibility of confounding due to occupational exposures was also investigated. Residence histories were coded for the study subjects and were used to examine temporal patterns of exposure and risk. Our sensitivity analyses showed the mortality risk estimates for fine particle and sulfate air pollution to be highly robust against alternative risk models of the Cox proportional hazards family, including models with additional covariates from the original questionnaires not included in the original published analyses. There was limited evidence of departures from the proportional hazards assumption. Flexible exposure-response models provided some evidence of departures from linearity at both low and high sulfate concentrations. Incorporating information on changes over time in cigarette smoking and body mass index had little effect on the association between fine particles and mortality. There was limited evidence of variation in risk with attained age, gender, smoking status, occupational exposure to dust and fumes, marital status, heart or lung diseases, or lung function. However, air pollution risk did appear to decreasing with increasing educational attainment. Extensive adjustment for occupation using aggregate indices of occupational "dirtiness" and occupational exposure to known lung carcinogens had little impact on the mortality risks associated with particulate air pollution. Our evaluation of population mobility indicated that relatively few subjects moved from their original city of residence. Attempts to identify critical exposure time windows were limited by the lack of marked interindividual variation in temporal exposure patterns throughout the study period. Overall, this extensive sensitivity analysis both supported the conclusions reached by the original investigators and demonstrated the robustness of these conclusions to alternative analytic approaches.
LANGUAGE: eng
DATE OF PUBLICATION: 2005 Jun-Jul
DATE COMPLETED: 20050816
DATE REVISED: 20220331
MESH DATE: 2005/08/17 09:00
EDAT: 2005/07/16 09:00
STATUS: MEDLINE
PUBLICATION STATUS: ppublish
OWNER: NLM

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Daniel Krewski

Chief Risk Scientist

Dr. Daniel Krewski is Chief Risk Scientist and co-founder of Risk Sciences International (RSI), a firm established in 2006 to bring evidence-based, multidisciplinary expertise to the challenge of understanding, managing, and communicating risk. As RSI’s inaugural CEO and long-time scientific...
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