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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution 4 Contributions of Relevant Health Studies to the Estimation of Reductions in Premature Mortality INTRODUCTION This chapter reviews evidence of ozone-mediated effects on mortality. It builds on the wealth of toxicologic and epidemiologic evidence showing the deleterious effects of ozone on an array of health effects, including oxidative damage to DNA, inflammation, oxidative stress, heart-rate variability, decrease in lung function, such respiratory conditions as bronchitis and wheezing, increase in medication use, and exacerbation of respiratory diseases leading to emergency-room visits and hospitalization. Those effects have consistently been found in toxicologic and epidemiologic studies, independently of study design and location, and therefore constitute compelling and well-accepted evidence that ozone adversely affects health. In contrast, until its regulatory impacts assessment (RIA) for the proposed ozone national ambient air quality standards (NAAQS) released in 2007, the Environmental Protection Agency (EPA) had not included mortality results in it primary estimates of the benefits of reductions in acute exposure to ambient ozone, because of uncertainty about the appropriate interpretation of those results. Previously, EPA had included epidemiologic studies that link ambient ozone concentrations with premature deaths in sensitivity analyses. The shift is attributable to consistent findings from multicity time-series studies and meta-analyses conducted over the past few years that suggested a modest but highly significant increase in mortality associated with relatively short-term exposure to ambient ozone. This chapter reviews evidence of ozone-related death with regard to its biologic plausibility and reviews findings from the multicity time-series studies and meta-analyses. It also assesses evidence of the existence of susceptible groups and discusses how such factors as personal and population average-
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution exposure error, epidemiologic designs and methods of analysis, measures of the effects of ozone exposure on death, and uncertainty contribute to our ability to estimate ozone-related mortality risk and to apply the estimates to risk and benefits analysis. BIOLOGIC PLAUSIBILITY The mechanisms by which ozone can damage health and possibly lead to mortality remain a subject of considerable clinical interest. Toxicologic studies have attempted to identify the mechanisms by using a variety of techniques, from ultrastructural, biochemical, and cytologic analyses to in vivo measurement of airflow mechanics. The techniques generally examine the effects of controlled ozone exposures of less than 8 h and, to a smaller extent, exposures of several days to increased ambient concentrations. The findings of a number of toxicologic studies provide insights to suggest the potential for a number of events by which ozone exposure could lead to increased mortality, including lung inflammation leading to local pulmonary compromise (Devlin et al. 1991; Holz et al. 1999; Koren et al. 1991; Ratto et al. 2006; Bosson et al. 2007), worsening of pre-existing cardiopulmonary disease, systemic release of mediators that affect adverse cardiovascular events (Hollingsworth et al. 2007), effects on the autonomic nervous system that could contribute to increased airway responsiveness (Chen et al. 2003) or reduced heart rate variability, and an increase in factors that lead to vascular changes (Chuang et al. 2007). Definitive proof of such occurrences leading to mortality are not found in the current scientific literature, however, there is ample evidence ozone can induce mechanisms through a sequence of events to trigger oxidative stress or inflammation pathways, which can contribute to release of pulmonary or systemic mediators. The events may further result in the exacerbation of a pre-existing respiratory or cardiovascular condition. Chen et al. (2004) found increased sensitivity to aeroallergens in a subgroup of asthmatics following exposure to 200 ppb ozone. There exists the biological plausibility that for a few individuals with pre-existing cardiopulmonary or chronic respiratory disease, such oxidative or inflammatory events could also cause death, via the onset of an asthmatic attack (Selgrade et al. 2008), myocardial infarction, or vascular event. Inflammatory events have been shown to occur for 20-30 h after inhalation of ozone even at ambient concentrations in the range of 0.08-0.10 ppm (Ratto et al. 2006; Chuang et al. 2007). There is less information on the airway inflammatory response to ozone at low concentrations, such as at or below 0.08 ppm. The oxidative stress and inflammation cascade is initiated by an ozone-mediated airway and lung tissue response (Chuang et al. 2007). Ozone can initiate the cascade immediately after inhalation when it comes in contact with epithelial lining fluids and cellular membranes, most often at nasal epithelial surfaces and at the junction of the bronchioles and the alveolar region (centriaci-
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution nar region). At the air-liquid interfaces, ozone can interact with unsaturated fatty acids to form lipid ozonation products, which in turn can activate lipases that lead to production and release of cell-signal transduction molecules and proinflammatory mediators. With oxygen species and reactive oxygen metabolites generated by exposure, those products of ozone exposure may lead to oxidative stress and the upregulation of transcription factors, such as NF-κB and proinflammatory genes. Correspondingly, antioxidant enzymes (such as glutathione enzymes, superoxide dismutase, and catalase) and nonenzymatic factors (such as ascorbic acid and α-tocopherol) that react with ozone directly have been shown to attenuate oxidant damage to airway lipid membranes. Biochemical evidence of ozone-mediated inflammation is provided by animal and human studies that show increases in downstream activation products of the innate immune system, including fibronectin, elastase, plasminogen activator, tissue factor, factor VIII, C3a fragment of complement, prostaglandins, interleukin-1 (IL-1), tumor-necrosis factor a, IL-6, IL-8, and granulocyte macrophage colony-stimulating factor (GM-CSF) in alveolar lavage fluid (Koren et al. 1989; Aris et al. 1993; Devlin et al. 1994). Inflammatory effects of ozone occur in people who are healthy and in people who have increased vulnerability because of host (genetic) factors or pre-existing cardiopulmonary disease, such as asthma. For example, ozone exposure at 100 ppb for 2 h leads to an acute neutrophilic inflammation of the airway in allergic asthmatic subjects (Depuydt et al. 2002). In addition, pre-exposure of these subjects (atopic asthmatics) to ozone potentiates the late-phase eosinophilic response to the allergen. The acute lung response to ambient ozone has many clinical features in common with asthma, and ozone exposure also leads to increase in proinflammatory cytokines (Koren et al.1989), cellular inflammation in airway tissues, and bronchial hyperresponsiveness (Foster et al. 2000). Perhaps as a result, exposure to ambient ozone can exacerbate pre-existing allergic asthma (White et al. 1994). Cultured human epithelial cells (HBECs) from asthmatic and nonasthmatic subjects exposed for 6 h to ozone at 100 ppb had increases in inflammation-associated mediators IL-8, GM-CSF, and intercellular adhesion molecule 1 (Bayram et al. 2001). HBECs from asthmatic but not nonasthmatic people also showed increased expression of the chemotactic cytokine CCL5. Increased expression of CCL5 suggests that ozone exposure may increase eosinophilic inflammation, exacerbate asthmatic symptoms, and lead to pathologic changes in the epithelium (Bayram et al. 2001). Support for that suggestion is provided by studies that show human asthmatic subjects to have increased eosinophilic inflammation of the lower airways after prolonged acute exposure to ozone at 160 ppb. Epithelial cytokine expression of IL-5, GM-CSF, and IL-8 has also been found to be higher in asthmatic subjects after laboratory exposure to ozone for 2 h at 200 ppb (Bosson et al. 2003). Numerous laboratory chamber studies have validated the reproducible nature of the inflammatory lung response (Devlin et al. 1991; Koren et al. 1991; Holz et al. 1999). That finding has been supported by additional studies in humans using therapeutic ablation of inflammatory effects, which have also helped
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution uncover essential mechanisms of injury. Although inhalation of the corticosteroid budesonide was not found to limit ozone-induced airway inflammation in healthy subjects, budesonide reduced neutrophilic infiltration in patients with mild asthma as evidenced by changes in the inflammatory cellularity of induced sputum (Nightingale et al. 2000; Vagaggini et al. 2001). Inhaled and oral corticosteroids have also been found to ablate ozone-induced neutrophilic inflammation in selected healthy subjects who were characterized as neutrophilic ozone-responsive (Holz et al. 2005). In mildly asthmatic subjects, pretreatment and posttreatment with apocynin aerosol, an inhibitor of the nictotinamide adenine dinucleotide phosphate (NADPH) oxidase complex present in membranes of inflammatory cells (eosinophils and neutrophils) and a source of reactive oxygen species, prevented ozone-induced airway hyperresponsiveness to methacholine (Peters et al. 2001). There has been relatively little research done on cardiovascular effects of ozone as compared with the amount done on pulmonary effects. Gong et al. (1998) used an ozone chamber study to monitored cardio-vascular effects in humans. In response to exposures to 300 ppb ozone, no major acute cardiovascular changes were found to be induced in either hypertensive or control subjects. It was noted, however, that ozone can increase myocardial work and impair pulmonary gas exchange. Together, those findings constitute supporting evidence that ozone exposure induces a cascade of events that increase oxidative stress and inflammation. As observed in numerous cohort and toxicologic studies, it is plausible that increased oxidative stress and inflammation can influence cardiac risk and ultimately mortality through increased autonomic dysregulation, vascular dysfunction, atherosclerosis, and arrhythmogenesis (Ridker et al. 1998, 2000; Pradhan et al. 2001, 2002). Those downstream effects may be most pronounced in people who have pre-existing diseases, in that ozone exposure may worsen a disturbed respiratory, vascular, or cardiac system, making them more vulnerable to ozone’s adverse effects. The adverse effects can occur after intermittent exposure to ozone, which is a typical pattern of exposure to this pollutant. Although the effects of ozone may accumulate over a lifetime, it is well established that gaps in ozone exposure lead to a decrease in innate resistance to its adverse effects. With the onset of each ozone-exposure episode, the injury process will be repeated, initiating once again the biologic events listed above. Such a cellular response to ozone means that each exposure event poses a renewed risk of a cascade of activities that could decrease resiliency and possibly enhance vulnerability, resulting in premature death. OZONE-MORTALITY STUDIES Given the evidence from toxicologic studies, it is biologically plausible that ozone exposures are also related to death in human populations. From a
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution biologic and epidemiologic perspective, there are two main ways in which air pollutants, such as ozone, may affect mortality: as a consequence of acute effects that cause death in the near term and as a consequence of chronic pathophysiologic changes that ultimately lead to death. The two may well overlap and be interrelated, but the distinction is useful because it is relevant to the interpretation and quantification of risks. Acute Studies Acute effects of ozone are those observed within a few hours or days of a rather short exposure. In those cases, exposure is typically defined as the maximum concentration on a given day, the mean across the 8 consecutive hours with the highest concentrations, or the 24-h average concentration. Under this acute-effect model, if death occurs, it is a consequence of the exposure. An acute exposure may also trigger a condition of poor health or frailty that can lead to death within a few days or weeks if intervention is not successful; in this delayed case, death may be considered a subacute effect of an acute (short-term) exposure. Time-series analysis is by far the most common approach to investigate the acute and subacute effects of ozone on mortality (see Box 4-1). The most systematic and comprehensive time-series analyses were two multicity studies (Bell et al. 2004; Ito et al. 2005) and three meta-analyses (Bell et al. 2005; Ito et al. 2005; Levy et al. 2005) solicited and commissioned by EPA.1 The three research teams conducting the meta-analyses were provided with the same databases from EPA but conducted the analyses separately and did not communicate with each other about their methods or findings until the studies were completed. Those studies examined ozone-mediated mortality while addressing previously unresolved issues related to confounding, exposure variability, and model specifications. Although the studies used different approaches, their major results were similar: each found a statistically significant relationship between ozone exposure and premature mortality that appears robust after controlling for exposure to particulate matter with a diameter of 10 μm or less (PM10). The similar estimates from these three meta-analyses suggest not only an indication of stable estimates in the literature, but also indicate that the meta-analytic approach is generally insensitive to analytical decisions, which provides support for the meta-analytical methods. Together, their results were cited by EPA as constituting strong evidence of a link between short-term exposure at concentrations below the NAAQS and premature mortality. However, many questions remain, specifically regarding the size and significance of the ozone-mortality effect and the implications of the findings for ozone benefits analysis. Study 1 The study by Ito et al. (2005) included both a meta-analysis and a time-series analysis; results from the time-series analysis were intended to help to explain issues identified in the meta-analysis.
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution BOX 4-1 Definitions of Time-Series Analysis and Meta-Analysis Time-series analysis describes and models the behavior of observations that are occurring sequentially and is analysis of the temporal relation between ozone and mortality data at different times. Moreover, time series analysis in air pollution studies is typically an approach in which daily mortality or morbidity counts are expressed as a function of covariates, including at least one indicator of air pollution in regression models, which can control for confounding effects of seasonality, long term trend and weather. The multicity time-series model has several advantages over multicity meta-analyses. Instead of having to rely on the different analytic approaches and assumptions used by researchers of completed studies, the multi-city time-series model provides the ability to use an identical model structure, exposure lags, control for confounders, and statistical criteria for data from all cities. Furthermore, the time-series model can include factors that explain differences in effect estimates among the cities, such as region, housing characteristics, and measurement method. Meta-analysis is a statistical technique used to aggregate, summarize, and review previous quantitative research. Through meta-analysis, a wide variety of questions can be investigated, assuming that a representative body of primary research exists. Selected parts of the reported results of primary studies (effect sizes or other characteristics) are analyzed as other data are: descriptively and then inferentially to test hypotheses. The appeal of meta-analysis is that it in effect combines research on a topic into one large study with many subjects. The danger is that in aggregating a large set of studies, the construct definitions can become imprecise and the results difficult to interpret fully (Neill 2006). Moreover, a major issue with meta-analysis is publication bias, which refers to the greater likelihood that studies with statistically significant positive results will be published as compared with studies reporting negative results. Thus, estimates from pooled meta-analysis may overestimate the association between ozone and mortality. Like multicity time-series analyses, meta-analyses use a multilevel model to examine pollution-effect associations. City specific estimates (level 2) are obtained from time series data, (level 1) for each city with a generalized linear model analysis. These are then pooled into a national average estimate using a Bayesian hierarchical model in which stages of the hierarchy have assumed normal distributions. descriptions, findings, limitations, and remaining issues related to the five comprehensive analyses are presented below. Multicity Time-Series Studies Two multicity time-series studies of ozone and mortality were conducted. Bell et al. (2004) used the National Morbidity, Mortality, and Air Pollution
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution Study (NMMAPS) database to conduct a large time-series analysis with data from 95 U.S. cities over the period 1987-2000. Ito et al. 2005 conducted a time-series study with data from seven U.S. metropolitan areas over the period 1985-1995. Bell et al. (2004). As shown in Table 4-1, Bell et al. used data and methods developed for the NMMAPS study to estimate a national average relative rate of mortality (noninjury mortality and cardiovascular and respiratory mortality) associated with short-term average ambient ozone concentrations in 1987-2000 in 95 large U.S. urban communities made up of almost 40% of the U.S. population. The 95 areas were chosen on the basis of availability of daily ozone data from EPA’s Aerometric Information Retrieval Service (now known as the Air Quality System database). Descriptive statistics on each community are provided at (iHAPSS 2005). For ozone, the 24-h average, maximum 8-h, and maximum hourly concentrations were calculated for each day. In several locations, ozone was measured only during the peak ozone season, April-October. A two-stage statistical model was used to estimate a national average association between short-term ambient ozone concentrations and mortality risks, accounting for weather, seasonality, long-term trends, and PM10. In the first stage, distributed-lag overdispersed Poisson regression models were used for estimating community-specific relative rates of mortality associated with exposure to ozone in the week prior to death. In the second stage, the community-specific relative rates were combined to generate a national average estimate of the association between ozone and mortality that accounts for within-community and across-community variability. Analyses were performed with multiple ozone-concentration metrics (1-h maximum, 8-h maximum, and 24-h average), which were highly correlated with each other; variations were most likely due to weather and sources of ozone. Temperature was modeled as a natural cubic spline (a type of mathematical function) of a day’s temperature and the average of the three previous days’ temperatures. Analyses were based on single-day lags and constrained and unconstrained distributed-lag models for all 95 communities, for all communities in warm months (April-October), and for the 55 communities on which yearly ozone data were available. The sensitivity of model results to choice of model, temperature, age (all ages and less than 65, 65-74, and over 75 years), and PM10 was also assessed. The sensitivity analysis with PM10 was limited to days for which PM10 and ozone data were available (1 in 6 days). Results showed that average short-term changes in ozone are significantly associated with premature mortality and that the statistical association is robust to adjustments for PM10, weather (temperature), and seasonality. It should be noted that robustness for PM10 may have been hindered by lack of daily monitoring data. Ozone-mediated risks were greater for cardiovascular and respiratory mortality than for total mortality, and effects were larger at lag 0 d than lag 1 or 2 d. Bell et al. examined the 95 communities using a constrained distributed-lag model and found a statistically significant 0.52% (95% posterior
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution TABLE 4-1 Summaries of Recent Studies of Acute Effects of Ozoneon Mortality Author Source Design/Number of Studies or Cities Period Exposure Metrics Health Outcomes Risk (95% Confidence Interval) per 10 ppb Bell, McDermott, Zeger, Samet, and Dominici al. JAMA 2004; 292(19): 2372-2378 Time-series study of 95 U.S. large urban areas 1987-2000 Cumulative exposure of previous week Noninjury mortality 0.52% (0.27-0.77%) Cardiovascular and respiratory mortality 0.64% (0.31-0.98%) Ito, Leon, and Lippmann Epidemiology 2005;16(4): 446-457 Meta-analysis of 43 studies (international) 1990-2003 24-h average Nonaccidental mortality 0.8% (0.55-1.0%) Time-series analysis of 7 U. S. cities 1985-1995 0- and 1-d lag, 24-h average 0.52-1.0%a Levy, Chemerynski, and Sarnat Epidemiology 2005;16(4): 458-468 Meta-regression of 28 time-series studies (international) Pre-October 2003 1-h maximum All-causes mortality 0.41% (0.32-0.52%) 1-h maximum: summer; 0.84% (0.57-1.09%) 1-h maximum: winter −0.04% (−0.34 to 0.28%) Bell, Dominici, and Samet Epidemiology 2005;16(4): 436-445 Meta-analysis of 39 time-series studies 1990-June 2004 0-, 1-, and 2-d lag or 2-d average of lags (0, 1, and 2 d) Total mortality 0.87% (0.55-1.18%) aRange of risk estimates without confidence intervals.
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution interval: 0.27%-0.77%) increase in non-accidental mortality for a 10 ppb increase in the previous week’s daily average ozone concentration. The increase in cardiovascular and respiratory mortality was somewhat higher at 0.64% (95% PI, 0.31%-0.98%). Interestingly, Bell et al. found a lower increase in total mortality of 0.39% (95% posterior interval: 0.13%-0.65%) in those communities during the ozone high season (April through October). Results were similar for the unconstrained models. The mortality effect of a single day of ozone exposure appeared to be distributed over several days. The study further suggested that ozone-mortality effects can be calculated separately from PM-mortality effects because ozone risk estimates were robust to adjustment for PM10. Bell et al. (2007) also reported the 95 Bayesian city-specific estimates of risk and the standard deviation of these city-specific estimates. The standard deviation for the constrained distributed lag model was 0.64%. Thus 95% of the true city-specific risk effects lie in the interval −0.73% to 1.77%. Bell at al. (2007) further investigated whether PM is a confounder of ozone and mortality using data for 98 U.S. urban communities from 1987 to 2000. They concluded that neither PM10 nor PM2.5 is a likely confounder of observed ozone and mortality relationships. They recommended that further investigation is needed of potential confounding of the short-term effects of ozone on mortality by PM chemical composition. As part of a larger study of ozone and mortality, Ito et al. (2005) conducted a time-series analysis with data from seven U.S. cities (Chicago, Detroit, Houston, Minneapolis-St Paul, New York City, Philadelphia, and St Louis) for the period 1985-1994 (Table 4-2). Those cities were chosen because of the availability of data on daily (or nearly daily) PM10, which went back to 1985 in most cities, and their relatively large populations. It was necessary to obtain daily rather than every-6th-day samples (the usual sampling frequency for most U.S. cities) of PM to obtain reasonable statistical power (Ito, personal communication, 12/04/07). In each of the cities, ambient ozone was measured year-round, and daily PM10 data were available for all cities except New York. PM2.5 data were available for selected years for Philadelphia (1992-1995) and St. Louis (1985-1989). Ito et al. (2005) used the data specifically to examine the sensitivity of ozone-mortality risk estimates to several factors, including season, alternative weather models and adjustments (of which four were examined), and confounding by PM. Results of the sensitivity analyses were intended to supplement a corresponding meta-analysis. To characterize the ozone-PM relationships across seasons, the authors computed the mean ozone concentration for each quintile of PM in summer and winter. To examine the sensitivity of ozone-mortality risk estimates to alternative weather-model specifications and temporal adjustments, they used a Poisson generalized linear model that adjusted for temporal trends, day of week, and weather effects. The average of 0- to 1-d lagged 24-h average ozone concentration was included. A smoothing function of days using natural splines was included to adjust for seasonal cycles and other temporal trends, and various weather models from the literature were investigated.
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution TABLE 4-2 Summaries of Recent Time Series Studies of Acute Effects of Ozone on Mortality Authors Bell, McDermott, Zeger, Samet, and Dominici. Ito, Leon, and Lippmann Study design (methods) Time-series study Time-series study Type of model(s) Hierarchic (mixed-effects), distributed Lag Poisson generalized linear model Numbers of studies or cities 95 U.S. large urban areas 7 U.S. large urban areas Study periods 1987-2000 1985-1995 Exposure level County level Metropolitan areas Exposure metric 24-h average Maximum 8-h average Maximum hourly concentration 24-h average Time of study April-October Whole year Whole year Health outcomes Non-injury-related mortality Cardiovascular and respiratory mortality Total nonaccidental mortality Lag time days in days 0, 1, 2, 3, up to a week Adjustment for temperature Yes Yes Adjustment for humidity No No Adjustment for season Yes Yes Consideration of age strata Yes Yes Adjustment for PM10 Yes Yes Adjustment for PM2.5 Yes Yes Adjustment for other pollutants No No RESULTS Non-injury-related mortality (per 10-ppb change) 0.39% (95% posterior interval, 0.13-0.65%) with up to a week lag (April-October) 1.0% (0 .55-1.40%) with 0-, 1-d lag.(year-round) 1-h maximum 8-h maximum 24-h average Cardiovascular and respiratory mortality (per 10-ppb change) 0.64% (0.31-0.98%) with up to a week lag 1-h maximum 8-h maximum 24-h average
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution Results from the multicity analysis show short-term associations between ozone and mortality with substantial heterogeneity across cities. Pooled analysis for the six cities with corresponding daily PM data resulted in an all-year, ozone-only mortality effect estimate of 2.0% (1.1-2.9%) for the quintile model and 1.0% (0.0-2.0%) for the model that used four smoothing terms per 20-ppb increase in the average of 0- and 1-d lag 24-h ozone. When stratified by season, the excess risk estimates were higher in summer than in the whole year and in cold seasons, when the estimates were low or null. The potential confounding between ozone and PM did not substantially affect ozone risk estimates. Results further showed that the use of different weather models could account for a twofold difference in overall effects estimates (0.24-0.49%) in analyses that included yearly data, with the quintile temperature model producing the largest estimate and the model that used four smoothing terms producing the smallest. Regardless of the adjustment for weather and for PM10, PM2.5, and season, however, large city-to-city variation in ozone-associated mortality risk estimates persisted. The heterogeneity was thought to be due to corresponding heterogeneity in factors known to vary with city, such as air-conditioning use, study population, ozone, and other photochemical oxidants. The relationship between ozone and PM10 was characterized by a positive slope in summer and a negative, shallower slope in winter. The relationships between temperature and ozone were generally J-shaped. Smoothing for temporal trend did not generally alter the risk estimates. In addition to the largely U.S.-based multicity studies (Bell et al. 2004 and Ito et al. 2005), Gryparis et al. (2004) collected data on daily ozone concentration, daily number of deaths, confounders, and potential effect modifiers for 23 European cities for at least three years since 1990. Effect estimates were obtained for each city with city-specific models and were then combined using second stage regression models. No significant effects were noted during the cold half of the year but for the warm season, an increase in the one hour ozone concentration by 10 ug/m3 was associated with a 0.33% increase in total daily number of deaths. When considering the number of cardiovascular deaths, there was a 0.45% increase. When considering respiratory deaths, there was a 1.13% increase. The corresponding figures for 8-h ozone levels were similar. Meta-analyses Three meta-analyses were carried out to obtain a summary or composite estimate of ozone-associated mortality risks while explaining observed heterogeneity in risk estimates. The meta-analyses used different statistical techniques and datasets to aggregate results of multiple time-series studies of changes in ozone and mortality (Tables 4-1, 4-2, and 4-3). Ito et al. (2005) considered 43 time-series studies in the U.S. and abroad that were conducted in 1990-2003. Levy et al. (2005) considered 48 risk estimates from 28 time-series studies
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution from observational networks. Errors and biases in these deterministic models are still inevitable because physical processes are simplified or neglected and because of the mathematical approximations used in assigning parameter values and inaccurate inputs. As a result of their own uncertainties, the models will add more uncertainty to the ozone-mortality risk-assessment estimates if they are used to characterize ozone exposures in future studies. Evaluation of these models and their uncertainties can help to quantify and characterize the magnitude of errors in the models. Although a full Bayesian analysis that incorporates all sources of information may be desirable in principle, it will be necessary in practice to make strategic choices about which sources of uncertainty justify such treatment and which sources are handled better through less formal means, such as consideration of how model outputs might change as some of the inputs vary through ranges of plausible values. A National Research Council report (NRC 2007b) describes in more detail different sources of uncertainty in air-quality numeric models and addresses the question of how to judge whether these models and their results are adequate for supporting regulatory decision-making. Effective communication of the different sources of uncertainty in the models requires a high level of interaction with the relevant decision-makers to ensure that they have the necessary information about the nature and sources of uncertainty and its consequences. Thus, if such models are used to assist in mortality risk assessment, uncertainty analysis and extensive discussion between analysts and decision-makers are needed. USE OF EPIDEMIOLOGIC INFORMATION IN OZONE-RELATED RISK AND BENEFITS ASSESSMENT Because death is inevitable, the question relevant to policy-makers, risk assessors, and the public is whether people who live in areas more highly exposed to air pollution experience death at an earlier age than people who live in communities that are less exposed. The effect of pollution on death may be quantified in terms of number of deaths in a given period or life months (or years) lost. Number of Deaths The “acute-effect studies” directly estimate the change in daily death rates due to short-term exposure (or a short pulse of exposure). Most models investigate the change in death rates for only one or a few days, whereas distributed-lag models look further ahead to capture delayed acute effects, often referred to as subacute effects. The expansions are useful in understanding the statistical distribution of time between an exposure pulse and the time pattern of occurrence of death. On a population level, it is extremely unlikely that all ozone-related deaths occur either immediately or within 1-2 d of exposure. A more plausible model assumes that susceptibility to death (or frailty) and the success
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution of intervention strategies follow a distribution wherein some people die immediately or within 1-2 d and others first suffer acute health ailments (such as an MI or pneumonia) and their deaths follow a period of unsuccessful treatment or as a result of the decompensation of defense mechanisms. The most complete assessment of the association between acute exposure and death originates in distributed-lag models that integrate the distribution of the time between exposure and death. However, both the usual time-series model and the distributed-lag models focus on a short window of exposure. Effects of long-term cumulated exposure are, by design, ignored in such models. In contrast, cohort studies focus on the associations between some metric of long-term exposure and death rates (as in the ACS study and the Harvard Six Cities Study). As a consequence, the increases in death rates associated with pollution may reflect the total effect of pollution on death, including life time lost because of acute or subacute effects and because of chronic conditions. For example, if pollution increases systemic inflammation, it may contribute to remodeling of airways and to obstruction or contribute to the development of atherosclerosis, and these chronic ailments increase the risk of premature death independently of any acute effects of pollution. One may argue that the current way of reconstructing long-term exposure in cohort studies is insensitive to short-term peaks and changes in exposure and that cohort studies may therefore miss some acute effects. Although cohort studies are likely to capture a large fraction of the effects of pollution on death—including most acute, chronic, and combined effects—some fraction of the immediate acute effects may not be contained in the effect signal, so the total effect of ozone might be larger than that observed in cohort studies. Years of Life Lost If one assumes that baseline probability of death or hazard is common to all members of the population at any given age, one can treat estimates of pollution-related risk based on time-series mortality studies in a manner similar to estimates obtained from cohort studies (Miller and Armstrong 2001; Burnett et al. 2003; Rabl 2006). That is, the risk estimates from time-series studies can be used to estimate the life years lost because of acute effects of pollution in the same way that risk estimates from cohort studies are used to derive the time lost because of the chronic, if not total, effects of pollution. However, there is probably a wide distribution of likelihood of death in any population on any given day. Current ambient ozone concentrations probably will not increase risk to a point at which death is likely for most of the population, and only people in a frail state (for example, having a chronic disease) would clearly be at risk of death from ozone exposure. It is assumed that large portions of the population are at risk of death because of longer-term exposure to air pollution, so it is more reasonable to apply a common baseline hazard function within the cohort design. Relative risks from
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution the cohort studies are then combined with common baseline hazard functions, in the form of life tables, for selected populations to estimate the amount of life lost because of exposure to air pollution (Coyle et al. 2003; Miller and Hurley 2003). The same life-table calculations can be used to estimate the number of people who will die over a fixed period because of changes in air pollution exposure. If the hazard and risk distributions in the population are not independent, estimates of excess deaths and life years lost in the entire population because of changes in ozone exposure based on time-series studies will not equal the average of estimates across all risk groups.5 The size of the difference is not known but could be estimated if risks for susceptible groups are obtained (Goldberg et al. 2005). Translation to Risk and Benefits Assessment Acute and chronic effects of urban air pollution, such as PM, on mortality have been well established. Risks based on cohort studies are some 10 times larger than those based on acute-effects studies that investigated only the influence of yesterday’s concentrations of PM2.5 on today’s death rates and some 3-5 times larger than the total acute effects, including death, distributed over several weeks. More recent risk assessments provided separate estimates of acute effects that occur within a few days of exposure and total effects. Such separation may be useful, given that the time between pollution abatement and health benefits may follow a distribution, with acute effects being reduced more quickly than effects due to chronic conditions (Röösli et al. 2005). Ozone-mortality risk assessment faces major challenges. As summarized above, evidence of long-term effects of ozone on mortality (or survival time) is presently weak, so the derivation of a relative risk to describe the association between ozone exposure and death is more difficult than in the case of PM. The translation of the results into number of attributable deaths is possible but leaves us with two main challenges. First, the assessment of acute effects would be incomplete if based solely on the usual time-series studies, given that subacute (delayed) effects are not captured with these studies; only one study has published estimates for distributed-lag models. Second, in the absence of abundant quantifiable evidence of chronic effects of ozone on mortality, total life time lost because of both acute and chronic effects cannot be estimated. The current evidence from cohort studies, although it is weak, supports the notion that the estimates of the risk of death due to ozone may be largely underestimated if based 5 In this context, the distribution of hazards among the population is the likelihood of death at any age; the distribution of risk is the association between ozone and death at any age.
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution solely on the main time-series studies that were at the center of EPA’s request for this report. While the current lack of a sufficient number of ozone cohort studies precludes a respective assessment, lessons learned from PM would suggest that estimations based on time-series study alone are far smaller than the overall long-term cumulated effects. The question of how to translate epidemiologic information into risk and benefit assessment is the subject of debates. Many risk assessments derive, as one intermediate step, the number of deaths attributable to air pollution on an annual basis. That approach has several limitations that are of concern particularly for chronic effects but conceptually also apply to acute effects, as is the case for the acute effects of ozone on death. Although it is true that pollution increases the mortality risk and thus the number of deaths, one has to emphasize that death is inevitable and that improvement in air quality only postpones death and does not prevent it. The concept of “attributable cases” is often interpreted as the corollary of “preventable cases,” which in the matter of death is certainly wrong. Another problem faced with “attributable death” originates in the fact that changes in death rates in any population lead to changes in the age structure of the population. That is, a reduction in air pollution will lead to longer life expectancy and increase the number of elderly people. Age-adjusted death rates are expected to decrease under cleaner conditions, but the absolute number of deaths will steadily increase as the population ages. As a consequence, the “attributable deaths” (or benefits) will not be the same throughout the years after an improvement in air quality. Instead, there will be a complex interplay between the distribution of acute vs chronic causes of premature death in which reduction in death rates caused by chronic exposures will take longer to materialize than reduction in death rates from acute effects and longer than the changes in the population age structure due to the removal or reduction of a risk factor. The net result of those dynamics is a continual adjustment of the expected annual change in the number of deaths attributable to a change in pollution. As shown by Miller and Hurley (2006), although the benefit (in absolute number of deaths) may steadily increase during a few years, it will later decrease for a couple of years and ultimately reach a time when the absolute number of deaths (per year) is larger than it was in the more polluted condition. Therefore, expression of benefits due to reduction in mortality rates can ultimately not be correctly expressed as a stable annual number of deaths prevented. For all those reasons, risk assessors omit the expression of “attributable cases of death” but prefer to derive years of life lost (YLL) due to some policy change. Although the derivation of YLL is based on the same input information—the risk changes derived from epidemiologic studies—the use of YLL is more appealing because one can derive the total YLL for the entire remaining life time of any cohort, whether dynamic or static, and express benefits in terms of annual YLL (Brunekreef et al. 2007). However, even though it may be more appealing to express mortality-risk change in YLL, the concept may be more
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution problematic for valuation purposes than that of “attributable deaths” (see Chapter 5). Another potential approach to the translation of epidemiologic information into risk and benefit assessment is to stop short of calculating annual numbers of deaths prevented and simply report the change in the annual mortality rate expected as a result of the change in ozone. Rabl (2006) shows the mathematical relationships between the change in mortality rate, the annual reduction in number of deaths, and the years of life saved. For an acute mortality effect as a result of short-term (daily) pollution-exposure changes and a stable population (in which births equal deaths), he shows that a permanent reduction in pollution temporarily reduces the number of deaths over some period because people who would have died from pollution live longer. Eventually, however, they die from something else, so the annual number of deaths returns to its previous level. However, there is a permanent increase in life expectancy, a larger population, and thus a permanently lower mortality rate. The valuation implications of this are discussed in Chapter 5. CONCLUSIONS AND RECOMMENDATIONS Overall Conclusions and Recommendations Human chamber and toxicologic studies have yielded strong evidence indicating that short-term exposure to ozone can exacerbate lung conditions, causing illness and hospitalization, and potentially lead to death. Although it is less abundant, the available evidence on ozone exposure and exacerbation of heart conditions points to another area of concern. Panel and epidemiologic studies have also found that exposure to ozone (as an indicator of a broad mix of photochemical oxidants) has those effects. The committee found that the four recent time-series analyses and meta-analyses of the relationship between exposure to ozone (and other photochemical oxidants) and premature mortality add to the evidence by providing robust statistical evidence of an association. Overall Conclusions On the basis of the broader available evidence and the additional insights obtained from its review of the new time-series studies, the committee concludes that short-term exposure to ambient ozone and the larger photochemical-oxidant mixture is likely to contribute to premature deaths. Although it is rarely possible to exclude the possibility of zero effect in such analyses, the committee concludes that an absence of any effect is highly unlikely. Despite some continuing questions about the evidence, the committee concludes that it is strong enough to be used in the estimation of the expected benefits of reductions in population mortality risk that would result from reducing exposure to ozone and/or the photochemical-oxidant mixture.
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution Overall Recommendation The committee recommends that ozone-related mortality, estimated on the basis of the results of the recent time-series analyses, be included in future estimates of health benefits of reducing exposure to ambient ozone. The committee further recommends that the greatest emphasis be placed on estimates based on systematic new multicity analyses using national databases of air pollution and mortality, such as was done in the National Morbidity, Mortality, and Air Pollution Study database, without excluding consideration of meta-analyses of previously published studies. Emphasis should also be placed on risk estimates obtained from analyzing data on multiple days so as to include delayed acute effects. Such health-benefits estimates should be accompanied by a broad array of analyses of uncertainty, while at the same time understanding that a zero value is highly unlikely. Strengths and Limitations of the Evidence In reaching its overall conclusions and recommendation, the committee identified a number of strengths and limitations of the evidence. On the basis of available evidence, the committee believes that deaths related to exposure to ozone (and other photochemical oxidants) are not likely to be restricted to people who are at very high risk of death within a few days. The evidence is provided by the recent analysis of time series in several U.S. cities that focused specifically on a mortality-displacement pattern in the time course of exposure and death (Zanobetti and Schwartz 2008). In that analysis, it was clear that short-term mortality displacement (or ‘harvesting’) could not fully explain the observed increase in death. The estimates steadily decreased with increasing lags, reaching the level of no effect approximately seven days after exposure but without reaching negative associations at any of these days as one would expected if all events were explained by short-term displacement among the pool of extremely sick and frail people. As discussed by Rabl (2006), if pollution affects both the extremely frail and others, the portion related to displacement cannot be quantified as one can only observe the net difference between short-term harvesting and all other acute effects. The pattern observed in Zanobetti and Schwartz (2008) indicates that at no lag until the disappearance of any effect (day 7) was the portion explained by mortality displacement larger than the rest. This evidence, albeit from only one study provides evidence that ozone-mortality effects are associated not just with those already near to death. In contrast with the PM literature, very few data are available from the use of distributed-lag models. Those available suggest that in the case of either ozone or PM, effect estimates steadily increase with increasing time of the investigated effects. Specifically, subacute (longer-term) effects that combine effects of several days or weeks of exposure are larger than immediate short-term effects, whereas estimates of effects from cohort studies are the largest. How-
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution ever, the increase in estimates is far larger for PM than for ozone. That may be a consequence of attenuation due to large errors in characterizing exposure to ozone, or it may reflect a more dominant role of acute pathologic conditions related to ozone exposure whereas the role of chronic pathologic conditions is more important in the effects of PM. As these interpretations rely on very few studies, further confirmation is warranted. In addition to the specific analyses in the time-series studies, there is only very weak, evidence from cohort studies of an association of premature mortality with longer-term exposure. Thus, the committee could not conclude at this time that exposure to long term ozone concentrations is related to mortality. Although the associations in the recent time-series studies appear sufficiently robust to provide a basis for estimating benefits, several factors need to be considered in interpretation: The committee found that short-term ozone exposure is likely to contribute to premature mortality in addition to the risks posed by weather and PM, but studies have not been sufficient to control fully for potential confounding by or interactions with condensed-phase constituents of airborne PM, such as sulfates, acids, carbon, and other elements. Controlling for such confounding is further complicated by the data from personal-exposure studies, which have found low correlations of monitored ambient ozone with personal ozone exposure. Detailed Conclusions and Recommendations In addition to its conclusions about the strengths and limitations of the new time-series evidence, the committee identified several kinds of additional needed research. Conclusion: On the basis of available evidence, the committee believes that deaths related to exposure to ozone (and other photochemical oxidants) are not likely to be restricted to those in people who are at very high risk of death within a few days. Because the evidence is based on results from only one study, it warrants confirmation by other studies. Recommendation: EPA and the scientific community should conduct additional studies to investigate short-term mortality displacement and include the use of alternative methods. An example of such methods is investigation of people who have diseases, such as diabetes and heart disease, which are known to induce high mortality risk associated with air pollution. Conclusion: If further confirmed, the weak current evidence from cohort studies of an association of premature mortality with longer-term exposure would tend to support the assumption that not all the effects seen in time-series studies are due to short-term mortality displacement.
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution Recommendation: The committee recommends that EPA, the National Institutes of Health (NIH), and the scientific community conduct further work with cohort studies to examine the association between long-term ozone exposure and mortality. The use of very large cohorts with long followup periods may be required because the long-term ozone-exposure mortality risk appears to be much smaller than that posed by fine PM. This may require pooling information from several cohorts to obtain sufficient statistical power. Long-term ozone-exposure models also need to be further developed to distinguish between variations in exposure not only on the between-cities and within-cities scales but at the individual level. Recommendation: To the extent that new cohort evidence is strengthened, EPA should consider including estimates based on that evidence in its benefits assessments. Conclusion: Epidemiologic studies have found that ozone-mediated risks were greater for cardiovascular mortality than for total mortality. However, there have been only a few toxicologic or human research studies directly evaluating cardiovascular effects of ozone exposure. Recommendation: EPA, NIH, and the scientific community should conduct further studies on the cardiovascular effects of ozone exposure, both in human and animal models. Studies should be designed to identify genetic susceptibility factors. Conclusion: Although the committee found that short-term ozone exposure is likely to contribute to premature mortality, the optimal way to quantify the effect is unavailable. The method that EPA uses now is appropriate only in very restricted situations that are not likely to be realistic. Recommendation: EPA should study emerging concepts and evaluate their use and implications in benefits assessments, including relationships between changes in mortality rates, annual deaths prevented, and years of life saved. The alternative approaches for expressing ozone mortality effects will lead to rather similar results if one is supposed to express only the most immediate (acute) effects of pollution. However, with the integration of subacute effects estimates and in particular in the case of use of long-term chronic-effect estimates, the discrepancies between the approaches increase, and the conceptual flaws of the “attributable-cases” model become more pronounced. Conclusion: Expected differences in susceptibility causes substantial uncertainty in estimating mortality risks on the basis of results of epidemiologic studies of total populations because of the lack of independence between pollution-related risk and baseline hazard. Recommendation: EPA and NIH should encourage more studies on potentially susceptible population groups, and EPA should explore the effects of uncertainty on risk assessments. To the extent that data are not available, models and assumptions can be used for sensitivity analysis.
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution Conclusion: Although the recent time-series studies have, to the extent possible, included analyses of alternative ozone metrics (such as 1-h maximum and 8-h maximum), it is important to further examine the relationship between those averaging times and to identify additional ozone metrics based on person exposures. That is important both to examine dose-response relationships, test potential confounding more effectively and to inform future regulatory choices among actions that might have differential effects on peak and multi-hour averages. Recommendation: EPA and the scientific community should design and conduct studies that use the full array of potential ozone metrics, including those that estimate population personal exposures. Conclusion: Control for confounding has not sufficiently accounted for geographic and seasonal variability in the relationship between ozone and is possible confounders. Further, data on PM speciation have not been sufficient to include in analyses of potential confounding; however such data are increasingly available from the Speciation Trends Network. Recommendation: EPA and the scientific community should account for seasonal and geographic variability in the relation between ozone and its confounders and should increasingly include the growing STN database in all future analyses of potential confounding of the ozone associations. To this end, EPA (through its PM Centers program), the Health Effects Institute (through its National Particle Component Toxicity Initiative [or NPACT]), and others (such as the Electric Power Research Institute) are supporting major new efforts in both time series and cohort epidemiology, to address this need. Further EPA should work with the scientific community to ensure that STN collects data frequently enough on the particle components most relevant to the potential for confounding. Conclusion: On the basis of its review of the evidence, the committee concludes that the association between short-term ozone changes in ozone concentrations and mortality is generally linear throughout most of the concentration range, although uncertainties make it difficult to determine whether there is a threshold for the association for the association at the lower end of the range. If there is a threshold, it is probably at a concentration below the current ambient air quality standards. Recommendation: EPA and the scientific community should further explore how individual thresholds may vary and the extent to which thresholds depend on the frailty of the individual at any given moment. The research should involve panel studies of individuals considered to be susceptible to premature death from ozone exposure, such as those with impaired lung function. Because it is not clear whether there is an association between ozone and mortality in the cooler months, warmer months should be examined separately. A sensitivity analysis should be conducted on concentration-response relation-
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution ships to capture more fully the uncertainties contributed by reliance on average fixed-site monitoring data to estimate population-average personal exposure. Conclusion: There is a lack of an observed association between ozone and mortality during the periods when exposure to ozone is expected to be low, and the ability to understand the lack is inhibited in part by the fact that monitoring is more limited during the winter periods. Better understanding of ozone-mortality relationships during winter is important for full exploration of (1) seasonal differences in risk, (2) how these seasonal risk differences vary spatially between communities with warmer and cooler winters, and (3) ozone-mortality relationships at lower ozone concentrations. Recommendation: EPA and the states should extend operation of ozone monitoring into winter and report the measurements. Conclusion: As has been the case with PM, ozone analyses conducted with distributed-lag models over several days appear to capture overall effects better, but there have been relatively few of them. Recommendation: EPA and the scientific community should seek out appropriate databases and conduct distributed-lag analyses as part of future epidemiologic investigations to understand the statistical distribution of time between an “exposure pulse” and the time pattern of occurrence of death. Conclusion: Uncertainty in the epidemiologic models is likely to introduce substantial uncertainty into ozone-mortality analyses. Recommendations: The committee identified several approaches to addressing the uncertainty: Results of the models should be presented with discussion of their reliability and of the estimated uncertainty about which model (if any) is reasonably correct. EPA should consider Bayesian approaches, including additional expert elicitation once the recent experience with PM has been evaluated, to uncertainty analysis. As EPA develops computational models and input distributions, it should intermittently conduct sensitivity analyses to focus resources on the most important inputs and parts of the models. EPA should distinguish between data-derived estimates of some components (such as the concentration-response function) and expert opinions about other components that are lacking in scientific data to achieve a better understanding of how existing data and expert judgment combine to produce estimates and of where new data would be most valuable. Time-series studies and meta-analyses should conduct additional sensitivity calculations, in particular to examine sensitivity of results to the structure of the cessation lag and sensitivity of the premature-mortality estimate to the
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Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution presence of a potential threshold concentration of ozone below which mortality effects are not observable. EPA should present multiple results from each study and characterize the different sources of error in the studies in a final uncertainty estimation on their benefits analysis. Air-quality numeric models (such as CMAQ) should be considered for use in ozone epidemiologic studies to extend the spatial scale of available data. However, the uncertainty associated with the models needs to be carefully considered before inferences are drawn from the simulation models for mortality risk assessment.