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Biomedical subjects

Daniel Krewski

Publications and source records attributed to Daniel Krewski.

At least 73 records · Page 4Linked to original sources
PubMed2002

Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution.

CONTEXT: Associations have been found between day-to-day particulate air pollution and increased risk of various adverse health outcomes, including cardiopulmonary mortality. However, studies of health effects of long-term particulate air pollution have been less conclusive. OBJECTIVE: To assess the relationship between long-term exposure to fine particulate air pollution and all-cause, lung cancer, and cardiopulmonary mortality. DESIGN, SETTING, AND PARTICIPANTS: Vital status and cause of death data were collected by the American Cancer Society as part of the Cancer Prevention II study, an ongoing prospective mortality study, which enrolled approximately 1.2 million adults in 1982. Participants completed a questionnaire detailing individual risk factor data (age, sex, race, weight, height, smoking history, education, marital status, diet, alcohol consumption, and occupational exposures). The risk factor data for approximately 500 000 adults were linked with air pollution data for metropolitan areas throughout the United States and combined with vital status and cause of death data through December 31, 1998. MAIN OUTCOME MEASURE: All-cause, lung cancer, and cardiopulmonary mortality. RESULTS: Fine particulate and sulfur oxide--related pollution were associated with all-cause, lung cancer, and cardiopulmonary mortality. Each 10-microg/m(3) elevation in fine particulate air pollution was associated with approximately a 4%, 6%, and 8% increased risk of all-cause, cardiopulmonary, and lung cancer mortality, respectively. Measures of coarse particle fraction and total suspended particles were not consistently associated with mortality. CONCLUSION: Long-term exposure to combustion-related fine particulate air pollution is an important environmental risk factor for cardiopulmonary and lung cancer mortality.

Adult↗
PubMed2002

Obesity may increase the incidence of asthma in women but not in men: longitudinal observations from the Canadian National Population Health Surveys.

To investigate the possibility of gender specificity for the effect of body mass index (BMI) on development of asthma, the authors used the longitudinal data from the first and second cycles of the National Population Health Survey, conducted in Canada in 1994-1995 and 1996-1997, respectively. Data from 9,149 subjects (4,266 men and 4,883 women) aged 20-64 years who reported no asthma at baseline were used in this analysis. The 2-year cumulative incidence of asthma was estimated by using a bootstrap procedure to take sampling weights and design effects into account. During the 2-year study period, 1.6% of the men and 2.9% of the women developed asthma. Average changes in body weight and BMI over the 2-year observation period were relatively small and were not associated with asthma incidence. However, baseline BMI was a significant predictor for asthma incidence in women. The adjusted odds ratio for women whose baseline BMI was at least 30.0 kg/m(2) versus 20.0-24.9 kg/m(2) was 1.9 (95% confidence interval: 1.1, 3.4), whereas the corresponding odds ratio of 1.1 (95% confidence interval: 0.3, 3.6) for men was not significantly different from unity. The authors concluded that obesity was related to development of asthma in women but not in men.

Adult↗
PubMed2002

Fine particulate air pollution and all-cause mortality within the Harvard Six-Cities Study: variations in risk by period of exposure.

PURPOSE: We used Poisson regression methods to examine the relation between temporal changes in the levels of fine particulate air pollution (PM(2.5)) and the risk of mortality among participants of the Harvard Six Cities longitudinal study. METHODS: Our analyses were based on 1430 deaths that occurred between 1974 and 1991 in a cohort that accumulated 105,714 person-years of follow-up. For each city, indices of PM(2.5) were derived using daily samples. Individual level data were collected on several risk factors including: smoking, education, body mass index (BMI), and occupational exposure to dusts. Time-dependent indices of PM(2.5) were created across 13 calendar periods (< 1979, 1979, 1980, em leader, 1989, >/= 1990) to explore whether recent or chronic exposures were more important predictors of mortality. RESULTS: The relative risk (RR) of mortality calculated using Poisson regression based on average city-specific exposures that remained constant during follow-up was 1.31 [95% confidence interval (CI) = 1.12-1.52] per 18.6 microg/m(3) of PM(2.5). This result was similar to the risk calculated using the Cox model (RR = 1.26, 95% CI = 1.08-1.46). The RR of mortality was attenuated when the Poisson regression model included a time-dependent estimate of exposure (RR = 1.19, 95% CI = 1.04-1.36). There was little variation in RR across time-dependent indices of PM(2.5). CONCLUSIONS: The attenuated risk of mortality that was observed with a time-dependent index of PM(2.5) is due to the combined influence of city-specific variations in mortality rates and decreasing levels of air pollution that occurred during follow-up. The RR of mortality associated with PM(2.5) did not depend on when exposure occurred in relation to death, possibly because of little variation between the time-dependent city-specific exposure indices.

Air Pollutants↗
PubMed2002

Optimal designs for estimating the effective dose in developmental toxicity experiments.

Recent advances in risk assessment have led to the development of joint dose-response models to describe prenatal death and fetal malformation rates in developmental toxicity experiments. These models can be used to estimate the effective dose corresponding to a 5% excess risk for both these toxicological endpoints, as well as for overall toxicity. In this article, we develop optimal experimental designs for the estimation of the effective dose for developmental toxicity using joint Weibull dose-response models for prenatal death and fetal malformation. Based on an extended series of developmental studies, near-optimal designs for prenatal death, malformation, and overall toxicity were found to involve three dose groups: an unexposed control group, a high dose equal to the maximum tolerated dose, and a low dose above or comparable to the effective dose. The effect on the optimal designs of changing the number of implants and the degree of intra-litter correlation is also investigated. Although the optimal design has only three dose groups in most cases, practical considerations involving model lack of fit and estimation of the shape of the dose-response curve suggest that, in practice, suboptimal designs with more than three doses will often be preferred.

Abnormalities, Drug-Induced↗
PubMed2002

The influence of ambient coarse particulate matter on asthma hospitalization in children: case-crossover and time-series analyses.

In this study, we used both case-crossover and time-series analyses to assess the associations between size-fractionated particulate matter and asthma hospitalization among children 6-12 years old living in Toronto between 1981 and 1993. Specifically, we used exposures averaged over periods varying from 1 to 7 days to assess the effects of particulate matter on asthma hospitalization. We calculated estimates of the relative risk of asthma hospitalization adjusted for daily weather conditions (maximum and minimum temperatures, and average relative humidity) for an incremental exposure corresponding to the interquartile range in particulate matter. Both bidirectional case-crossover and time-series analyses revealed that coarse particulate matter (PM10-2.5) averaged over 5-6 days was significantly associated with asthma hospitalization in both males and females. The magnitude of this effect appeared to increase with increasing number of days of exposure averaging for most models, with the relative risk estimates stabilizing at about 6 days. Using a bidirectional case-crossover analysis, the estimated relative risks were 1.14 [95% confidence interval (CI), 1.02, 1.28] for males and 1.18 (95% CI, 1.02, 1.36) for females, for an increment of 8.4 microg/m(3) in 6-day averages of PM10-2.5. The corresponding relative risk estimates were 1.10 and 1.18, respectively, when we used time-series analysis. The effect of PM10-2.5 remained positive after adjustment for the effects of the gaseous pollutants carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3). We did not find significant effects of fine particulate matter (PM2.5) or of thoracic particulate matter (PM10) on asthma hospitalizations using either of these two analytic approaches. For the most part, relative risk estimates from the unidirectional case-crossover analysis were more pronounced compared with both bidirectional case-crossover and time-series analyses.

Air Pollutants↗
PubMedDate not supplied

Neuropathology, tremor and electromyogram in rats exposed to manganese phosphate/sulfate mixture.

In Canada, Methylcyclopentadienyl manganese tricarbonyl (MMT) replaced tetraethyl lead in gasoline as an antiknock agent from 1976 until 2003. The combustion of MMT leads to increased manganese (Mn) concentrations in the atmosphere, and represents one of the main sources of human exposure to Mn. The nervous system is the major target of the toxicity of Mn and Mn compounds. The purpose of this study was to investigate exposure-response relationships for neuropathology and tremor, and the associated electromyogram (EMG), following subchronic inhalation exposure of rats to a mixture of Mn phosphate/sulfate particles. Rats were exposed 6 h per day, 5 days per week for 13 consecutive weeks at 30, 300 or 3000 microg m(-3) Mn phosphate/sulfate mixture and compared with controls. Half of the rats had EMG electrodes implanted in the gastrocnemius muscle of the hind limb to assess tremor at the end of Mn exposure. Two days after the end of Mn exposure, rats were killed by exsanguination and Mn concentrations in the brain (caudate putamen, globus pallidus and frontal cortex) were determined by neutron activation analysis while neuropathology was assessed by counting neuronal cells in 2.5 mm x 2.5 mm grid areas. Increased Mn concentrations were observed in all brain sections at the highest level of exposure. The neuronal cell loss was significantly different in the globus pallidus and the caudate putamen at the highest level of exposure (3000 microg m(-3)). No sign of tremor was observed among the rats. In conclusion, exposure to a high level of Mn phosphate/sulfate mixture brought on neuropathological changes in a specific area of the brain; however, no sign of tremor was observed.

Administration, Inhalation↗
PubMedDate not supplied

Risk management frameworks for human health and environmental risks.

A comprehensive analytical review of the risk assessment, risk management, and risk communication approaches currently being undertaken by key national, provincial/state, territorial, and international agencies was conducted. The information acquired for review was used to identify the differences, commonalities, strengths, and weaknesses among the various approaches, and to identify elements that should be included in an effective, current, and comprehensive approach applicable to environmental, human health and occupational health risks. More than 80 agencies, organizations, and advisory councils, encompassing more than 100 risk documents, were examined during the period from February 2000 until November 2002. An overview was made of the most important general frameworks for risk assessment, risk management, and risk communication for human health and ecological risk, and for occupational health risk. In addition, frameworks for specific applications were reviewed and summarized, including those for (1)contaminated sites; (2) northern contaminants; (3) priority substances; (4) standards development; (5) food safety; (6) medical devices; (7) prescription drug use; (8) emergency response; (9) transportation; (10) risk communication. Twelve frameworks were selected for more extensive review on the basis of representation of the areas of human health, ecological, and occupational health risk; relevance to Canadian risk management needs; representation of comprehensive and well-defined approaches; generalizability with their risk areas; representation of "state of the art" in Canada, the United States, and/or internationally; and extent of usage of potential usage within Canada. These 12 frameworks were: 1. Framework for Environmental Health Risk Management (US Presidential/Congressional Commission on Risk Assessment and Risk Management, 1997). 2. Health Risk Determination: The Challenge of Health Protection (Health and Welfare Canada, 1990). 3. Health Canada Decision-Making Framework for Identifying, Assessing and Managing Health Risks (Health Canada, 2000). 4. Canadian Environmental Protection Act: Human Health Risk Assessment of Priority Substances(Health Canada, 1994). 5. CSA-Q8550 Risk Management: Guidelines for Decision-Makers (Canada Standards Association, 1997). 6. Risk Assessment in the Federal Government: Managing the Process (US National Research Council, 1983). 7. Understanding Risk: Informing Decisions in a Democratic Society (US National Research Council, 1996). 8. Environmental Health Risk Assessment (enHealth Council of Australia, 2002). 9. A Framework for Ecological Risk Assessment (CCME, 1996). 10. Ecological Risk Assessments of Priority Substances Under the Canadian Environmental Protection Act (Environment Canada, 1996).11. Guidelines for Ecological Risk Assessment (US EPA, 1998b). 12. Proposed Model for Occupational Health Risk Assessment and Management (Rampal & Sadhra, 1999). Based on the extensive review of these frameworks, seven key elements that should be included in a comprehensive framework for human health, ecological, and occupational risk assessment and management were identified: 1. Problem formulation stage. 2. Stakeholder involvement. 3. Communication. 4. Quantitative risk assessment components. 5. Iteration and evaluation. 6. Informed decision making. 7. Flexibility. On the basis of this overarching approach to risk management, the following "checklist" to ensure a good risk management decision is proposed: - Make sure you're solving the right problem. - Consider the problem and the risk within the full context of the situation, using a broad perspective. - Acknowledge, incorporate, and balance the multiple dimensions of risk. - Ensure the highest degree of reliability for all components of the risk management process. - Involve interested and effected parties from the outset of the process. - Commit to honest and open communication between all parties. - Employ continuous evaluation throughout the process (formative, process, and outcome evaluation), and be prepared to change the decision if new information becomes available. Comprehensive and sound principles are critical to providing structure and integrity to risk management frameworks. Guiding principles are intended to provide an ethical grounding for considering the many factors involved in risk management decision making. Ten principles are proposed to guide risk management decision making. The first four principles were adapted and modified from Hattis (1996) along with the addition of two more principles by Hrudey (2000). These have been supplemented by another four principles to make the 10 presented. The principles are based in fundamental ethical principles and values. These principles are intended to be aspirational rather than prescriptive--their application requires flexibility and practical judgement. Risk management is inherently a process in search of balance among competing interests and concerns. Each risk management decision will be "balancing act" of competing priorities, and trade-offs may sometimes have to be made between seemingly conflicting principles. The 10 decision-making principles, with the corresponding ethical principle in italics are: 1. Do more good than harm (beneficence, nonmalificence).- The ultimate goal of good risk management is to prevent or minimize risk, or to "do good" as much as possible. 2. Fair process of decision making (fairness, natural justice). - Risk management must be just, equitable, impartial, unbiased, dispassionate, and objective as far as possible given the circumstances of each situation. 3. Ensure an equitable distribution of risk (equity). - An equitable process of risk management would ensure fair outcomes and equal treatment of all concerned through an equal distribution of benefits and burdens (includes the concept of distributive justice, i.e., equal opportunities for all individuals). 4. Seek optimal use of limited risk management resources (utility). - Optimal risk management demands using limited resources where they will achieve the most risk reduction of overall benefit. 5. Promise no more risk management that can be delivered (honesty).- Unrealistic expectations of risk management can be avoided with honest and candid public accounting of what we know and don't know, and what we can and can't do using risk assessment and risk management. 6. Impose no more risk that you would tolerate yourself (the Golden Rule). - The Golden Rule is important in risk management because it forces decision makers to abandon complete detachment from their decisions so they may understand the perspectives of those affected. 7. Be cautious in the face of uncertainty ("better safe than sorry"). - Risk management must adopt a cautious approach when faced with a potentially serous risk, even if the evidence is uncertain. 8. Foster informed risk decision making for all stakeholders (autonomy). - Fostering autonomous decision making involves both providing people with the opportunity to participate, and full and honest disclosure of all the information required for informed decisions. 9. Risk management processes must be flexible and evolutionary to be open to new knowledge and understanding (evolution, evaluation, iterative process). - The incorporation of new evidence requires that risk management be a flexible, evolutionary, and iterative process, and that evaluation is employed at the beginning and througthout the process. 10. the complete elimination fo risk is not possible (life is not risk free).- Risk is pervasive in our society, and cannot be totally eliminated despite an oft-expressed public desire for "zero risk". However, the level of risk that may ve tolerable by any individual is dependent on values of beliefs, as well as scientific information. Each agency must continue to employ a process that meets the needs of their specific application of risk management. A single approach cannot satisfy the diverse areas to which risk decisions are being applied. However, with increasing experience in the application of the approaches, we are evolving to a common understanding of the essential elements and principles required for successful risk assessment, risk management, and risk communication. Risk management will continue to be a balancing act of competing priorities and needs. Flexibility and good judgement are ultimately the key to successfully making appropriate risk decisions.

Canada↗
PubMedDate not supplied

Overview of the reanalysis of the Harvard Six Cities Study and American Cancer Society Study of Particulate Air Pollution and Mortality.

This article provides an overview of the Reanalysis Study of the Harvard Six Cities and the American Cancer Society (ACS) studies of particulate air pollution and mortality. The previous findings of the studies have been subject to debate. In response, a reanalysis team, comprised of Canadian and American researchers, was invited to participate in an independent reanalysis project to address the concerns. Phase I of the reanalysis involved the design of data audits to determine whether each study conformed to the consistency and accuracy of their data. Phase II of the reanalysis involved conducting a series of comprehensive analyses using alternative statistical methods. Alternative models were also used to identify covariates that may confound or modify the association of particulate air pollution as well as identify sensitive population subgroups. The audit demonstrated that the data in the original analyses were of high quality, as were the risk estimates reported by the original investigators. The sensitivity analysis illustrated that the mortality risk estimates reported in both studies were found to be robust against alternative Cox models. Detailed investigation of the covariate effects found a significant modifying effect of education and a relative risk of mortality associated with fine particles and declining education levels. The study team applied spatial analytic methods to the ACS data, resulting in various levels of spatial autocorrelations supporting the reported association for fine particles mortality of the original investigators as well as demonstrating a significant association between sulfur dioxide and mortality. Collectively, our reanalysis suggest that mortality may be attributable to more than one component of the complex mixture of ambient air pollutants for U.S. urban areas.

Air↗
PubMedDate not supplied

Selection of ecologic covariates in the American Cancer Society study.

The American Cancer Society (ACS) Study of the effects of long-term exposure to ambient air pollution on mortality used metropolitan areas to assign exposures to individual cohort members (Pope et al., 1995); these authors did not, however, control for any other place-specific variables in their analysis. Consequently, the study has been criticized on the basis that the association observed between air pollution and mortality may be confounded by other unmeasured ecologic covariates. To address this criticism, the reanalysis team selected a set of place-specific variables that measured determinants of health ranging from the biophysical environment to the social environment and the healthcare system. This article outlines the process by which place-specific ecologic covariates were selected; data measuring these variables were obtained and geographic boundaries for places were delineated. Issues involved in obtaining and using geographically based ecological data are examined within the context of the reanalysis of the ACS study. Both the ecological fallacy and the atomistic fallacy are addressed and an argument is made for the importance of studying the effects of place-specific variables that are integral or contextual in nature. Issues relating to the Modifiable Areal Unit Problem (MAUP) are explored with reference to using ZIP codes and data from a variety of sources. It is argued that differences in the geographical scale of variability for various pollutants may prove to be the key to distinguishing between their relative impacts on health and that multilevel analyses are essential for understanding the impact of social and environmental determinants of health. A number of determinants of health are then briefly examined in terms of their association with mortality, the appropriateness of their being measured at the metropolitan scale, and the availability of data for the 1980s from U.S. sources. Finally, the article presents the database of place-specific ecologic covariates that was incorporated into the ACS models during the reanalysis in order to account for the influence that place may have above and beyond ambient air pollution.

Air Pollutants↗
PubMedDate not supplied

Flexible modeling of exposure-response relationship between long-term average levels of particulate air pollution and mortality in the American Cancer Society study.

Accurate estimation of the exposure-response relationship between environmental particulate air pollution and mortality is important from both an etiologic and regulatory perspective. However, little is known about the actual shapes of these exposure-response curves. The objective of this study was to estimate the exposure-response relationships between mortality and long-term average city-specific levels of sulfates and fine particulate matter (PM(2.5)). We reanalyzed the data derived from the American Cancer Society (ACS) Cancer Prevention Study II, a large prospective study conducted in the United States between 1982 and 1989. Exposure to particulate air pollution was assessed prior to entry into the cohort. Mean sulfate concentrations for 1980 were available in 151 cities, and median PM(2.5) levels between 1979 and 1983 were available in 50 cities. Two sampling strategies were employed to reduce the computational burden. The modified case-cohort approach combined a random subcohort of 1200 individuals with an additional 1300 cases (i.e., deaths). The second strategy involved pooling the results of separate analyses of 10 disjoint random subsets, each with about 2200 participants. To assess the independent effect of the particulate levels on all-causes mortality, we relied on flexible, nonparametric survival analytical methods. To eliminate potentially restrictive assumptions underlying the conventional models, we employed a flexible regression spline generalization of the Cox proportional-hazards (PH) model. The regression spline method allowed us to model simultaneously the time-dependent changes in the effect of particulate matter on the hazard and a possibly nonlinear exposure-response relationship. The PH and linearity hypotheses were tested using likelihood ratio tests. In all analyses, we stratified by age and 5-yr age groups and adjusted for the subject's age, lifetime smoking exposure, obesity, and education. For both fine particles (PM(2.5)) and sulfates, there was a statistically significant (at.05 level) departure from the conventional linearity assumption. The adjusted effect of fine particles on mortality indicated a stronger relationship in the lower (up to about 16 microg/m(3)) than in the higher range of their values. Increasing levels of sulfates in the lower range (up to about 12 microg/m(3)) had little impact on mortality, suggesting a possible "no-effect threshold." For body mass index (BMI), the risks were lowest in the middle range and increased for both very obese and very lean individuals. It was concluded that flexible modeling yields new insights about the effect of long-term air pollution on mortality.

Air Pollutants↗
PubMedDate not supplied

Controlling for potential confounding by occupational exposures.

Occupational exposure is an important potential confounder in air pollution studies because it is plausible that individuals who live in highly polluted areas also work in more polluted environments. While the original investigators made some efforts to control for possible confounding by occupational variables, it was felt that these could be improved upon. The reanalysis team attempted to control for occupational confounding by supplementing the original data sets with two new variables, an indicator of the "dirtiness" of a subject's job and an indicator of possible exposure to occupational lung carcinogens. The attribution of these variables was based on the job title recorded by the original investigators and on the judgment of our experts concerning typical exposure patterns in different occupations. We fitted Cox proportional-hazards models identical to those that had been used by the original investigators while also including one or both of the new occupational covariates in the models. In none of the analyses did the inclusion of the occupational variables materially change the results. It would therefore appear that, in general, the results reported by the original investigators were not distorted by inadequate control of occupational variables. We also carried out some analyses using the dirtiness index as a stratification variable to assess effect modification. There was some indication, albeit inconsistent, that the effect of air pollution on mortality was greater among subjects with dirty jobs than among those with clean jobs.

Adult↗
PubMedDate not supplied

The association between sulfate air pollution and mortality at the county scale: an exploration of the impact of scale on a long-term exposure study.

The American Cancer Society (ACS) Study and its reanalysis are built upon in order to examine the impact of scale on the observed relationship between sulfates and mortality. The limitations of the original ACS Study (Pope et al., 1995) and the reanalysis of this study (Krewski et al., 2000) are discussed; while the latter dealt with some issues in using ecological data, it did not address scale. Next, the article outlines the county-scale study, the methods used to aggregate data, and the two-stage analysis used to derive relative risk (RR). Finally, the results of working at the county scale are compared with those obtained by the reanalysis team using larger metropolitan areas. Less than half of the cohort used in the metropolitan study were used at the county scale because of the limited availability of sulfate monitors and because five-digit ZIP codes more accurately assigned individuals to geographical areas. Therefore, the county data should be considered as new and not as a reorganization of the original data set. The reanalysis and the county studies should be considered as two separate studies that took different scales as their basic organizing principle. The RR of all-cause mortality from sulfate exposure at the county scale was 1.50 (1.30, 1.73) compared with 1.25 (1.13, 1.37) at the metropolitan scale; for cardiopulmonary mortality, the RR was 1.75 (1.48, 2.08) at the county scale compared with 1.29 (1.15, 1.46) at the metropolitan scale. Because lung cancer mortality was low in some counties, the two-stage random effects model became unstable. At the county scale, the RR from sulfates was more robust to the inclusion of ecologic covariates. Other place-specific ecologic covariates were either insignificant or barely significant (with a lower 95% confidence limit near 0.99 or 1.00) when included in the two-stage regression model for all-cause mortality with sulfates. Moreover, no ecologic covariate changed the RR of all-cause mortality from sulfates by 25% or more. Both population change and unemployment rate affected the RR for cardiopulmonary mortality from sulfate exposure by 25% or more in the county-scale analysis. However, when these two variables were entered into a multiple covariate analysis, the RR from sulfates decreased but remained strongly significant. Sulfur dioxide was not an important covariate at the county scale. Thus, at the county scale, long-term exposure to sulfates appears to be more strongly associated with increased risk of all-cause and cardiopulmonary mortality than previously indicated by the ACS study and its reanalysis.

Air Pollution↗
PubMedDate not supplied

Spatial analysis of the air pollution-mortality relationship in the context of ecologic confounders.

Lack of control for confounding by ecological covariates that may relate to sulfate air pollution and mortality was a key criticism of the two studies that were the focus of the Particle Reanalysis Project. To assess the validity of this criticism, we address the question: "Does sulfate air pollution exert health effects when the impact of other individual and ecologic variables thought to influence health is taken into account?" A related question arises from the possibility of autocorrelation in the mortality risks and ecologic covariates. Failure to control for autocorrelation can lead to false positive significance tests and may indicate bias resulting from a missing variable or group of variables. We control for more than 25 individual risk factors and for 20 ecologic variables representing environmental, socioeconomic, demographic, health- care, and lifestyle determinants of health in a two-stage multilevel analysis. Four modeling strategies are used to control for spatial autocorrelation. Of the 20 ecologic variables tested, only sulfate and sulfur dioxide are significant in models that incorporate spatial autocorrelation. Accounting for autocorrelation also reduces the size and certainty of the sulfate effect on mortality when compared to results generated from Cox models where independent observations are assumed. Confidence limits for the sulfate relative risk include unity in models that simultaneously control for sulfur dioxide and autocorrelation.

Air Pollution↗
PubMedDate not supplied

Retrospective data quality audits of the Harvard Six Cities and American Cancer Society studies.

The Harvard Six Cities (6-Cities) and American Cancer Society (ACS) studies are longitudinal cohort mortality studies of large populations that provided important information about the human health effects associated with long-term exposure to fine particulate air pollution. Possible changes to federal regulation of particulates prompted a review of data collection methods, analysis, and reported results from these two studies. This article describes the methodology used to conduct quality assurance audits of both studies and summarizes the audit findings. Statistically based, randomly selected samples of 250 health questionnaires and 250 death certificates from each study were audited against data from analysis files. In cases where study-specific data could not be located, validation was performed using information and data from other sources. Some errors were found in programming and data transformation in both studies, but none affected the results of the original investigations. Both audits confirmed that the published studies are an accurate representation of the collected data. The audits also underscored the importance of adequate attention to documentation and record-keeping practices during the conduct of all studies and proper archiving at their conclusion.

Air Pollution↗
PubMedDate not supplied

Spatial regression models for large-cohort studies linking community air pollution and health.

Cohort study designs are often used to assess the association between community-based ambient air pollution concentrations and health outcomes, such as mortality, development and prevalence of disease, and pulmonary function. Typically, a large number of subjects are enrolled in the study in each of a small number of communities. Fixed-site monitors are used to determine long-term exposure to ambient pollution. The association between community average pollution levels and health is determined after controlling for risk factors of the health outcome measured at the individual level (i.e., smoking). We present a new spatial regression model linking spatial variation in ambient air pollution to health. Health outcomes can be measured as continuous variables (pulmonary function), binary variables (prevalence of disease), or time-to-event data (survival or development of disease). The model incorporates risk factors measured at the individual level, such as smoking, and at the community level, such as air pollution. We demonstrate that the spatial autocorrelation in community health outcomes, an indication of not fully characterizing potentially confounding risk factors to the air pollution--health association, can be accounted for through the inclusion of location in the deterministic component of the model assessing the effects of air pollution on health or through a distance-decay spatial autocorrelation function in the stochastic component of the model, or both. We present a statistical approach that can be implemented for very large cohort studies. Our methods are illustrated with an analysis of the American Cancer Society cohort to determine whether the prevalence of heart disease is associated with concentrations of sulfate particles. From a statistical point of view, it appears that a location surface in the deterministic component of the model was preferred to a distance-decay autocorrelation structure in the model's stochastic component.

Air Pollution↗
PubMedDate not supplied

Impact of particulate air pollution on quality-adjusted life expectancy in Canada.

Air pollution and premature death are important public health concerns. Analyses have repeatedly demonstrated that airborne particles are associated with increased mortality and estimates have been used to forecast the impact on life expectancy. In this analysis, we draw upon data from the American Cancer Society (ACS) cohort and literature on utility-based measures of quality of life in relation to health status to more fully quantify the effects of air pollution on mortality in terms of quality-adjusted life expectancy. The analysis was conducted within a decision analytic model using Monte Carlo simulation techniques. Outcomes were estimated based on projections of the Canadian population. A one-unit reduction in sulfate air pollution would yield a mean annual increase in Quality-Adjusted Life Years (QALYs) of 20,960, with gains being greater for individuals with lower educational status and for males compared to females. This suggests that the impact of reductions in sulfate air pollution on quality-adjusted life expectancy is substantial. Interpretation of the results is unclear. However, the potential gains in QALYs from reduced air pollutants can be contrasted to the costs of policies to bring about such reductions. Based on a tentative threshold for the value of health benefits, analysis suggests that an investment in Canada of over 1 billion dollars per annum would be an efficient use of resources if it could be demonstrated that this would reduce sulfate concentrations in ambient air by 1 microg/m(3). Further analysis can assess the efficiency of targeting such initiatives to communities that are most likely to benefit.

Adolescent↗