A Critical Assessment of Studies on the Carcinogenic Potential of Diesel Exhaust

Critical Reviews in Toxicology, 36:727–776, 2006Copyright c© Informa HealthcareISSN: 1040-8444 print / 1547-6898 onlineDOI: 10.1080/10408440600908821

A Critical Assessment of Studies on the CarcinogenicPotential of Diesel Exhaust

Thomas W. Hesterberg and William B. Bunn IIIInternational Truck and Engine Corporation, Warrenville, Illinois, USA

Gerald R. ChaseConsultant in Statistics and Epidemiology, Larkspur, Colorado, USA

Peter A. ValbergGradient Corporation, Cambridge, Massachusetts, USA

Thomas J. SlavinInternational Truck and Engine Company, Warrenville, Illinois, USA

Charles A. LapinLapin and Associates, Glendale, California, USA

Georgia A. HartToxicology Consultant, Englewood, Colorado, USA

After decades of research involving numerous epidemiologic studies and extensive investigationsin laboratory animals, a causal relationship between diesel exhaust (DE) exposure and lungcancer has not been conclusively demonstrated. Epidemiologic studies of the transportationindustry (trucking, busing, and railroad) show a small elevation in lung cancer incidence(relative risks [RRs] generally below 1.5), but a dose response for DE is lacking. The studiesare also limited by a lack of quantitative concurrent exposure data and inadequate or lackof controls for potential confounders, particularly tobacco smoking. Furthermore, prior todieselization, similar elevations in lung cancer incidence have been reported for truck drivers,and in-cab diesel particulate matter (DPM) exposures of truck drivers were comparableto ambient highway exposures. Taken together, these findings suggest that an unidentifiedoccupational agent or lifestyle factor might be responsible for the low elevations in lungcancer reported in the transportation studies. In contrast, underground miners, many of whomexperience the highest occupational DPM exposures, generally do not show elevations in lungcancer. Laboratory studies must be interpreted with caution with respect to predicting thecarcinogenic potential of DE in humans. Tumors observed in rats following lifetime chronicinhalation of very high levels of DPM may be attributed to species-specific overload mechanismsthat lack relevance to humans. Increased tumor incidence was not observed in other species(hamsters or mice) exposed to DPM at very high levels or in rats exposed at lower levels (≤2000µg/m3). Although DPM contains mutagens, mutagenicity studies in which cells were exposed toconcentrated extracts of DPM also have limited application to human risk assessment, becausesuch extracts can be obtained from DPM only by using strong organic solvents, agitation, andheat. Most studies have shown that whole DPM itself is not mutagenic because the adsorbedorganic compounds are minimally bioavailable in aqueous-based fluids. In the past two decades,dramatic changes in diesel engine technology (e.g., low-sulfur fuel and exhaust after-treatment)have resulted in >99% reduction in DPM and other quantitative and qualitative changes inthe chemical and physical characteristics of diesel exhaust. Thus, the current database, whichis focused almost entirely on the potential health effects of traditional diesel exhaust (TDE),has only limited utility in assessing the potential health risks of new-technology diesel exhaust

Accepted 1 July 2006.Address correspondence to Thomas W. Hesterberg, International Truck and Engine Corporation, 4201 Winfield Road, P.O. Box 1488,

Warrenville, IL 60555, USA. E-mail: [email protected]

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728 T. W. HESTERBERG ET AL.

(NTDE). To overcome some of the limitations of the historical epidemiologic database on TDEand to gain further insights into the potential health effects of NTDE, new studies are underwayand more studies are planned.

Keywords: Diesel, Engine Exhaust, Epidemiology, Lung Cancer, Risk Assessment

Internal combustion engines were developed just over acentury ago. The gasoline-fueled engine, invented in the 1870s,uses a spark ignition system, while the diesel engine, invented inthe 1890s, uses high compression instead of a spark to ignite thefuel. After World War II, gasoline fueled-engines were usedextensively to power passenger vehicles, and diesel enginessoon became the power source of choice for heavy-duty trucks,railroad locomotives, and heavy off-road applications such asagricultural and construction activities. Today, diesel enginesplay a prominent vital role in the world economy, especiallyin transportation. Compared to gasoline engines, diesel enginesmay last longer, have lower maintenance, and have better fueleconomy, but in the past have had higher emission levels (U.S.EPA, 2002 chap. 2). However, as discussed later in this review,new technologies have dramatically reduced emissions fromdiesel engines.

CHARACTERISTICS OF DIESEL ENGINE EXHAUSTSDiesel engine emissions (referred to here as diesel exhaust

or DE) are highly complex mixtures that vary widely dependingupon engine type, fuel type, and operating conditions. Tradi-tional diesel exhaust (TDE), the primary focus of this review, iscomposed of gaseous and vapor phases of numerous chemicalsand of particles (the latter are termed diesel particulate matter,DPM). As used in this review, TDE refers to the exhaustfrom diesel technology typical of the engines, fuel injectionsystems, fuels, and lubricants in use prior to 1988, when exhaustemissions from diesel were not regulated in the United States.By far, the vast majority of the total mass of TDE is composedof gas and vapor phases, which are typically composed ofup to 98% carbon dioxide and also include nitrogen oxides,sulfur dioxide, carbon monoxide, methane, and nonmethanevolatile organic carbon compounds. The DPM emitted from atraditional diesel engine running on high sulfur fuel is typicallyless than 1% of the total DE mass (McDonald et al., 2004b).This DPM will be essentially completely eliminated fromnew-technology diesel exhaust (NTDE) starting in 2007. In thisreview, the term NTDE refers to the diesel exhaust from newintegrated systems (engines, fuel injection systems, ultra-low-sulfur fuels, lubricants, and exhaust after-treatment) intended forintroduction in 2007 to meet stringent new U.S. EnvironmentalProtection Agency (EPA) standards for particulate matter andnitrogen oxides (NOx), which go into effect beginning in2007 (U.S. EPA, 2002). In addition to an almost completeelimination of DPM, as discussed later in this review, thechemical composition of the gases released from NTDE isqualitatively and quantitatively different from TDE.

Most of the DPM emitted in TDE develops during thecombustion process, with a smaller portion resulting fromcondensation of semivolatile gases in the exhaust. During fuelcombustion, ultrafine particles of elemental carbon (EC) formand combine or agglomerate into larger particles; as the particlesgrow in size, they adsorb organic carbon (OC) compounds. Thiscombustion DPM from TDE consists of a solid core of EC(approximately 65–70%), with adsorbed OC (approximately30–35%) and sulfate/nitrate (4–5%) (McDonald et al., 2004a,2004b). Ninety-five percent of the particles are submicron in di-ameter. The aerodynamic diameter of combustion DPM (some-times referred to as diesel exhaust soot) is typically 50 nm to1000 nm. Condensation particles are <50 nm in aerodynamic di-ameter (in the nanoparticle range), and are actually more numer-ous in DPM than the larger EC carbonaceous particles, but area much smaller mass fraction; these particles are composed pri-marily of hydrocarbons or sulfate and form by nucleation in DEduring cooling and dilution (Kittelson, 1998). This nanoparticlePM (particulate matter) will be virtually eliminated by the 2007technology diesel systems and thus will not be found in NTDE.

Because the particles in DPM released in TDE are highlyrespirable, and because extraction processes using heat andorganic solvents can yield mutagenic compounds from DPMparticles, concerns have been raised regarding the cancer-causing potential of DE exposure, and, in particular, of DPM.In 1954, Kotin published the first cell culture studies testingthe toxicity of DE (Kotin et al., 1954, 1955); in the 1980s thetoxicity and carcinogenicity of DE were tested in a number ofstudies using laboratory animals (reviewed in Hesterberg et al.,2005); during the last two decades, epidemiology studies haveinvestigated the association between occupational exposureto DE and health effects. Various agencies have evaluatedthis research, one of which is IARC (International Agencyfor Research on Cancer, an agency of the World HealthOrganization).

ASSESSMENTS OF THE POSSIBLE CARCINOGENICITYOF DIESEL EXHAUST

Over the years, a number of authors as well as someregulatory agencies have concluded that the weight of theevidence supports a causal role for DE in the risk of lung cancer(Wichmann, 2006; U.S. EPA, 2002; Lloyd and Cackette, 2001;IARC, 1989). However, other assessments of the DE epidemio-logic database have concluded that the existing epidemiologicalstudies are unable to predict potential human health effects fromexposure to DE or to link DE to increases in lung cancer (Muscatand Wynder, 1995; Stober and Abel, 1996; Cox, 1997; Morgan

ASSESSMENT OF DIESEL EXHAUST CARCINOGENESIS STUDIES 729

et al., 1997; Bunn et al., 2004). This conclusion was related tothe finding of various limitations in the epidemiology database,such as the lack of good historical exposure estimates andpossible confounding factors. In a recent study, which found nosignificant association between occupational exposure to dieselexhaust and lung cancer, the authors provided a detailed discus-sion of the potential limitations of earlier studies, including thefailure to adequately estimate exposure and adjust for potentialconfounders (Richiardi, L., Mirabelli, D., et al., 2006). One ob-jective of the present critical assessment is to discuss and clarifysome of those limitations. Even though parts of previous DEcancer assessments are discussed here, readers are encouragedto refer to the cited documents for the complete discussions.

In 1989, IARC listed traditional diesel engine exhaust (TDE)as a probable human carcinogen (group 2A) (IARC, 1989).The 2A classification was based on the findings of a panelof expert scientists that the evidence for the carcinogenicityof DE was limited in humans but sufficient in animals. Thepanel arrived at these conclusions following a review of thepublished peer-reviewed literature that was available at thattime, which included epidemiologic studies of people whoworked in occupations that have a potential for higher thanambient exposure to DE (e.g., railroad workers, professionaldrivers, and dock workers), as well as laboratory studies ofanimals and cells grown in culture.

The finding of limited evidence from studies of humansfor carcinogenicity of DE rested primarily on studies ofrailroad workers, especially those reported by Garshick et al.

(1987, 1988), in part because these studies had some quan-titative exposure data available from which they attemptedretrospectively to estimate historical worker exposures (Woskieet al., 1988a, 1988b). The IARC panel reserved judgment onpreliminary studies of Teamsters (International Brotherhood ofTeamsters; mostly truck drivers), because data were not yetcompletely reported. The panel noted in the monograph thatin the epidemiologic studies it reviewed, there were no directdata for the workers’ DE exposures; historical exposures wereeither assumed based on job title or were estimated from morerecent exposure assessments (IARC, 1989, Vol. 46, p. 132). Theunderground mining industry also included many workers thatwere (and are) exposed to above-ambient levels of DE. However,the IARC panel, for the most part, considered studies of theseworkers to be unsuitable for evaluating the health effects of DEbecause underground mining includes multiple exposures thatcould not be distinguished from DE.

The IARC finding of sufficient evidence from animal studiesfor carcinogenicity of DE was based primarily on studies inwhich rats (but not mice or hamsters) developed tumors afterlifetime inhalation of very high concentrations of DE (≥2200µg/m3 DE particulate). At the time of the IARC review,strong evidence had not yet been developed regarding therole of a rat-specific lung clearance overload mechanism inthe association between high exposure rates to DE and lungcancer in the rat and thus this could not be considered bythe IARC panel. This evidence is briefly reviewed later in thisarticle. Any future updated review by IARC of the carcinogenic

FIG. 1. Reductions in diesel particulate matter emissions in the United States. U.S. EPA standards for particulate emissions fromheavy-duty diesel trucks (t) or urban buses (ub), calculated as grams particulate matter emitted per brake-horsepower-hour (g/bhp-hr) and adjusted relative to pre-1988 unregulated engine emissions. From U.S. EPA Health Assessment Document for DieselEngine Exhaust (2002, Tables 2–4, p. 2–16).


potential of TDE should evaluate these mechanistic findings inmaking a decision on the weight of the evidence from laboratoryanimal studies. Furthermore, as recommended by the U.S. EPA(2002), new-technology diesel emissions (NTDE) should beevaluated independently of TDE. In that document, the U.S.EPA emphasized that the 2002 health assessment applied onlyto engines that were manufactured before 1995, and that newertechnology engines would require a reevaluation with regard topotential health impacts (U.S. EPA, 2002).

CHANGES IN DIESEL TECHNOLOGIES HAVE RESULTEDIN DRAMATIC REDUCTIONS IN EMISSIONS

In a review of research on the carcinogenicity of DE, it isimportant to recognize that past research has been conductedalmost entirely on TDE, and that NTDE is quantitatively andqualitatively very different from TDE. Advances in dieseltechnology, starting 18 years ago, have resulted in progressivereductions in diesel engine emissions (U.S. EPA, 2002) (Figs. 1and 2). Diesel engines built in 1988 showed a 40% reduction inparticulate matter (PM) mass emissions compared to emissionsfrom unregulated, pre-1988 diesel engines (TDE). A “transi-tional diesel” phase, 1988–2006, showed further reductions inparticle emissions. In 1994, advances in diesel technology (e.g.,electronic engine controls) resulted in a 90% reduction in PMmass emissions compared with pre-1988 engines. In the presentarticle, the terms “traditional” (pre-1988) and “transitional”(1988–2006), like the term “NTD” (post-2006), are used toroughly categorize engines that comply with various emissions

FIG. 2. Reductions in diesel nitrogen oxide (NOx) emissions inthe United States. U.S. EPA standards for NOx emissions fromheavy-duty diesel engines, calculated as grams NOx emittedper brake-horsepower-hour (g/b hp-hr). From U.S. EPA HealthAssessment Document for Diesel Engine Exhaust (2002, Tables2–4, p. 2–16).

standards; in actuality, each term encompasses a variety of dieselengine technologies and fuel types.

Diesel engines have undergone similar reductions in nitrogenoxide (NOx) emissions (U.S. EPA, 2002) (Fig. 2). In 2007 muchmore stringent engine emissions standards promulgated by theU.S. EPA and the California Air Resources Board (CARB)will go into effect, which will require reductions in PM andNOx emissions by approximately 99% from the pre-1988 levels(Table 1) (CalEPA, 1998; U.S. EPA, 2002). Also in 2007, theU.S. EPA and CARB standards will result in further reductionsin CARB-listed TACs (toxic air contaminants, see Table 2).Tables 1 and 2 demonstrate that not only the regulated but alsomany related nonregulated emission levels are much lower inNTDE than in transitional DE and are comparable to or lowerthan levels in exhaust from compressed natural gas (CNG),which is generally considered to be “clean.” The exhaust fromengines that comply with the 2007 emissions standards (NTDE)is not only quantitatively very different from traditional DE, butit is also qualitatively very different (Figs. 3 and 4) (Ullmanet al., 2003).

AMBIENT PARTICULATE MATTERSome epidemiologic studies correlating levels of ambient

airborne fine particulate matter (PM10 and PM2.5, with aero-dynamic diameter <10 µm and <2.5 µm, respectively) withdisease statistics have reported associations between ambientPM concentrations and lung cancer risk. There are manyuncertainties in these associations, and their causal basis isunknown, but some may wonder whether DPM plays a rolein correlations between ambient-PM and lung cancer risk. It isbeyond the scope of this article to review the lengthy healthliterature on airborne respirable PM, either PM10 or PM2.5; anin-depth and current review of this topic has been providedelsewhere (Pope and Dockery, 2006). However, three factsshould be noted on this topic: (1) DPM constitutes about 1%to 2% of ambient PM, even in urban air (Kleeman et al., 2000;Kim and Hopke, 2006); (2) dieselization of heavy-duty vehicles(class 8) in the United States is estimated to have occurredbetween 1965 and 1970 and of medium-duty engines (class5–7) in the late 1970s; and (3) the minimum latency (i.e.,time between exposure and cancer diagnosis) is estimated to be15–20 years for lung cancer. Hence, the potential magnitude forDPM’s role in any ambient-PM associations with lung cancer ismarginal. Moreover, studies of population lung cancer statisticsfor the 1980s and 1990s would have inadequate latency toexhibit DPM effects, if any. Furthermore, DPM is similar tothe PM from numerous other combustion sources, and accurateseparation and measurement of the DPM portion of ambientcombustion PM is not possible at this time (Schauer, 2003);therefore, when PM levels increase, it is not known whether theDPM level is also increased. Thus, exposure to DPM in ambientPM has been quite low and not far enough in the past to play a


TABLE 1Measured engine emissions for regulated and related unregulated emissions of school buses fitted with one ofthree engine configurations: Transitional diesel exhaust (Trans DE), which is from a 2001 engine powered byconventional diesel fuel; new technology diesel exhaust (NTDE), which is from a 2001 engine retrofitted with

catalyzed diesel particulate filter and low NOx engine control module and powered by ultra-low sulfur fuel; andcompressed natural gas (CNG)-powered engine

Emissions in g/mile (standard deviation)

EmissionTransitional dieselexhaust (Trans DE)

New technology dieselexhaust (NTDE)

Compressed naturalgas (CNG)

%Reductionb:NTDE vs. Trans DE

NOx 14.1 (0.30) 10.1a (0.09) 16.2 (0.73) −29%NO 12.7 (0.07) 4.8a (0.07) 14.3 (1.0) −62%NO2 1.5 (0.2) 5.3a (0.04) 1.8 (0.4) +270%PM 0.18 (0.003) 0.01a (0.004) 0.05 (0.004) −95%SOF 0.079 (0.004) 0.007a (0.003) 0.047 (0.006) −91%SO4 0.0003 (0.0000) ND ND −100%THC 0.39 (0.04) NDa 9.34 (0.12) −100%NMHC 0.39 (0.04) NDa 0.65 (0.13) −100%CH4 0.001 (0.002) 0.01a (0.004) 8.69 (0.13) +650%CO 1.76 (0.05) NDa 4.78 (0.06) −100%CO2 1530 (5) 1620 (4) 1200 (6) +6%

Note. ND, none detected. NMHC, non methane hydrocarbons. PM, Particulate matter. THC, Total hydrocarbons. Emissionrates reported by Ullman, Table 10, p. 20 (Ullman et al., 2002) (also reported in Ullman et al., 2003; Bunn et al., 2004)

aNTDE emission levels that are statistically lower than or similar to CNG levels.b% Reduction NTDE vs. Trans DE = [(NTDE − Trans DE) × 100]/Trans DE.

role in lung cancer associations with ambient PM levels (Ladenet al., 2006a).

SCOPE OF THIS REVIEWThe next several sections review the most important compo-

nents of the database on the potential carcinogenicity of DE,which consists of laboratory studies (in vivo and in vitro) andepidemiologic studies. Laboratory studies of the carcinogenicpotential of DE have recently been reviewed in detail elsewhere(Hesterberg et al., 2005); thus, this article focuses more on acritical review of human epidemiologic studies. Following thereview of the database are sections that summarize differencesbetween traditional diesel exhaust (TDE) and new technologydiesel exhaust (NTDE) and discuss current ongoing and plannedresearch on potential DE health effects.

LABORATORY STUDIES

Animal Inhalation BioassaysCompelling arguments have been made that the only relevant

animal studies for the assessment of human carcinogenic riskof airborne respirable particulates are those in which exposurewas by inhalation (CRARM, 1997; CASAC, 2000; ILSI, 2000;Mauderly, 2000; Hesterberg et al., 2005). Studies using abnor-mal routes of exposure (intratracheal injection, intraperitonealinjection, intrapleural implantation), while possibly providing

mechanistic information, have little relevance for human riskassessment because these exposures present problems withuneven dispersal of test material, unrealistically large dosesdelivered to the lung, inclusion of nonrespirable particulate,and/or inhibition or absence (in the case of intraperitonealinjection) of normal lung clearance. Furthermore, in the caseof intraperitoneal injection, the normal target tissue—lungepithelium—is not evaluated.

Effects of inhalation of DE in laboratory animals recentlyhave been reviewed elsewhere (Hesterberg et al., 2005). Ofspecies chronically exposed to DE by inhalation (rats, hamsters,mice, monkeys, and cats), only rats consistently developedlung tumors and only following inhalation exposure to highlevels of diesel particulate matter (>2000 µg/m3 DPM) thatwere greater than human occupational exposures (mean humanexposures measured as elemental carbon (EC) typically rangefrom 1.4 µg/m3 for ambient to 460 µg/m3 (approximately 900µg/m3 DPM) for certain underground mines (see AppendixTable A-2). Rats did not develop elevated tumor incidences afterbeing exposed to lower DE levels that were more comparableto occupational and environmental exposure levels in humans.Exposure of rats to high levels of other inert particles, includingTiO2, talc, and carbon black, also resulted in lung overload,inflammation, and eventually lung tumors.

Numerous analyses point to a lack of relevance of data fromlung-overloaded rats for risk calculations in humans exposed at


TABLE 2Measured engine emissions for CARB-listed toxic air contaminants (TACs) (as for Table 1)

Emissions in mg/mile (standard deviation)

Toxic air contaminantaTransitional dieselexhaust (Trans DE)

New technology dieselexhaustb (NTDE)

Compressed naturalgas (CNG)

%ReductionNTDE vs. Trans DEc

Acetaldehyde 9.5 (0.82) 2.7 (0.18) 24 (2.5) −72%Acrolein 3.3 (0.65) 0.45 (0.33) 4.9 (0.59) −86%Benzene 4.7 (0.36) ND 4.3 (0.31) −100%Biphenyl 0.410 (0.021) 0.004 (0.001) 0.005 (0.005) −99%Bis[2-ethylhexyl]phthalate 0.0017 (0.0029) 0.0010 (0.0017) 0.0016 (0.0028) −41%Butadiene, 1,3- ND 1.3 (2.3) 4.5 (1.8) NCCresol isomers 0.190 (0.022) 0.049 0.004) 0.073 (0.053) −74%Cyanide compounds 0.33 (0.27) 0.11 (0.20) 0.29 (0.50) −67%Di-n-butylphthalate 0 0.007 (0.002) 0.005 (0.006) NCDioxins & furans × 10−6 0.26 (0.07) 0.26 (0.17) 0.25 (0.14) 0%Formaldehyde 27 (1.7) 5.2 (2.1) 500 (25) −81%Hexane ND 0.39 (0.67) ND NCMethanol 10 (10) 23 (29) 30 (8) 130%Methyl ethyl ketone 0.51 (0.11) 0.02 (0.03) 0.28 (0.06) −99%Naphthalene 0.73 (0.04) 0.07 (0.04) 0.07 (0.08) −90%Phenol 0.65 (0.05) 0.15 (0.02) 0.17 (0.15) −77%Phosphorus 0.13 (0.23) ND 0.30 (0.26) −100%POM (PAHs+derivatives) 2.8 (0.21) 0.076 (0.027) 0.16 (0.13) −97%Propionaldehyde 3.0 (0.06) 0.35 (0.26) 6.9 (0.85) −88%Toluene 4.3 (0.2) 2.0 (0.92) 3.2 (2.1) −53%

Note. CARB, California Air Resources Board. NTDE, new-technology diesel exhaust, which is from a 2001 engine retrofitted with catalyzeddiesel particulate filter and low NOx engine control module and powered by ultra-low sulfur fuel. Trans DE, transitional diesel exhaust, which isfrom a 2001 engine powered by conventional diesel fuel. NC; not calculable, division by zero is undefined. ND. none detected. Emission ratesreported by Ullman et al. (2002, Table 13, p. 26; also reported in Ullman et al., 2003; Bunn et al., 2004).

aOf the 41 TACs listed by CARB, only the 20 herein listed were detected in any of the three engine emissions.bAll data in this column are NTD emission levels that are statistically lower than or similar to CNG levels.c%Reduction NTD vs. TD = [(NTD−TD) × 100]/TD.

environmental or ambient levels of DE (e.g., HEI, 1999; U.S.EPA, 2002; Greim et al., 2001; ILSI, 2000). At realistic humanlevels of exposure to DE, no lung cancer hazard is anticipatedbased on these rat data (ILSI, 2000). The general consensus isnow that the tumorigenic effects observed in the high-DE-doserat studies were primarily due to a rat-specific lung clearanceoverload mechanism that is not applicable to humans (Heinrichet al., 1986; Lewis et al., 1986; Stober, 1986; Heinrich et al.,1989, 1995; Mauderly et al., 1996; McClellan, 1996; Mauderly,2000).

Moreover, a review of responses to inhaled DE particles atthe cellular level in the rat lung suggests that the mechanisticseries of steps related to tumorigenesis in rats is not likely to berelevant to humans (Watson and Valberg, 1996). These authorsconcluded that the unique sensitivity of the rat to particle-induced tumorigenesis relates to a rat-specific exaggeratedinflux of leukocytes, which produce oxygen free radicals.They further concluded that rat tissues are not able to protectthemselves adequately against oxidative damage. Thus, the free

radicals stimulate epithelial cell proliferation and contributeto DNA damage. In the rat, DNA repair mechanisms areapparently unable to keep up with the chronic damage to thegenome. The authors suggest that “Even though differencesin dosimetry may contribute some to species differences inresponse, the available evidence indicates that species-specific(i.e., rat-specific) reactions dominate.”

A recent study provided further evidence that the mechanismof tumor development in rats following inhalation of DEwas lung particle overload. Rats were exposed by nose-onlyinhalation to DE at particulate concentrations of 3,000 or 10,000µg/m3 for 6 h/d, 7 d/w, for 2 yr. and were maintained foran additional 6 months without exposure (Stinn et al., 2005).DE exposure was associated with dose-related pulmonaryinflammation, fibrosis, and an elevated incidence of lungtumors. However, the incidence of bulky DNA adducts wasnot significantly increased by exposure to either of these DElevels. Lung tumor incidences were 23% in rats exposed at3000 µg/m3, 46% in rats exposed at 10,000 µg/m3, and 2% in


FIG. 3. Low-molecular weight (“light”) PAH emissions from transitional diesel exhaust (1988–2006) vs. new-technology dieselexhaust (NTDE): quantitative and qualitative differences. “Transitional diesel” emissions were from a 2001 diesel engine poweredby high-sulfur fuel. NTDE was from an engine with a particle trap and was powered by ultra-low-sulfur fuel. Adapted from Ullmanet al. (2003).

air control rats. The authors concluded that chronic exposureto high levels of DE resulted in the following series of events:particle deposition in lungs → lung “overload” → pulmonaryinflammation → tumorigenesis. The lung tumor incidence

of 46% in rats chronically exposed to 10,000 µg/m3 wascomparable to those reported previously for similar exposuresto 7000 µg/m3: 12.8% (Mauderly et al., 1987) and 38.5%(Brightwell et al., 1989). Interestingly, there was no increase

FIG. 4. High-molecular-weight (“heavy”) PAH emissions from transitional diesel exhaust (1988–2006) vs. new-technology dieselexhaust (NTDE): quantitative and qualitative difference. “Transitional diesel” emissions were from a 2001 diesel engine poweredby high-sulfur fuel. NTDE was from an engine with a particle trap and was powered by ultra-low-sulfur fuel. Adapted from Ullmanet al. (2003).


in lung cancer in rats exposed to similar levels of sidestreamenvironmental tobacco smoke (ETS). This is not unexpectedsince DPM contains 50% insoluble elemental carbon (EC) byweight, while ETS contains negligible amounts of this insolublematerial. Thus, in ETS-exposed lungs, there is no opportunityfor the progressive buildup of insoluble particles, which hasbeen related to lung overload and tumorigenesis in rats exposedto very high levels of insoluble particles such as TiO2, talc,carbon black, and DE.

In 1999, Valberg and Crouch combined tumor data from eightchronic inhalation studies in rats (Valberg and Crouch, 1999).Exposure-response analysis of rats showed no tumorigeniceffect for exposures less than 600 µg/m3 average continuouslifetime concentration. In fact, the maximum likelihood estimateof the cancer slope factor at low DE concentrations was negative(but not statistically different from zero). This meta-analysis ofstudies exposing rats to DE gave no evidence that DE exertsa tumorigenic effect at low exposures even in rats. The ratdata predict that ambient and modest levels of occupationalexposures to diesel exhaust are consistent with no increases inlung tumor risk.

Mutagenicity of DPM-Associated Organic CompoundsOrganic carbon compounds (OC) can be extracted and

concentrated from DPM using strong, nonaqueous solvents,such as dichloromethane (DCM), in combination with agitation,heat, and ultrasonic energy. Among the OC that can be isolated inthis manner are several known mutagens, including polycyclicaromatic hydrocarbons (PAHs). Differences in the extractionconditions can result in differences in the mutagenic activityof the concentrated extract (Claxton et al., 1992). Considerableattention has focused on whether the presence of mutagenicOC extractable from DPM may be the basis for the lungtumors observed in rats exposed for a lifetime to high levelsof traditional DE. Three mechanistic hypotheses have beenconsidered as a basis for rat lung tumors: (1) The OC compoundsadsorbed onto DPM dissolve in lung fluids and interact directlywith lung-cell DNA to initiate adduct formation, leading tomutations and tumorigenesis; (2) long-term inhalation of allpoorly soluble particles at high concentrations (including DPM)causes (in rats) chronic inflammation and formation of freeradicals that can lead to DNA adducts, along with tissue injurythat increases cell proliferation, with both actions promotingtumorigenesis; and (3) the combination of both (1) and (2)(dissolved OC compounds and promoting action of particle-induced inflammation) leads to rat lung tumorigenesis.

Reviews of in vitro mutagenicity studies of DPM extracts areavailable elsewhere (Vostal, 1983; IARC, 1989; Rosenkranz,1993, 1996; Valberg and Watson, 1999; ACGIH, 2000;Mauderly, 2000). In brief, these reviews report on in vitro studiesshowing that concentrated organic-solvent extracts of DPM caninduce gene mutations in Salmonella bacteria and in mammaliancells. Also, OC extracts of DPM, applied topically to the skinof mice, induced DNA adducts and tumorigenesis in the skin

(Schoket et al., 1989; Nesnow, 1990). A recent study showed thatthe OC extracted from DPM and the OC extracted from gasoline-engine exhaust particulate matter (GPM) were comparablepositive mutagens in a bacterial assay (Liu et al., 2005). GPMOC was somewhat more active on per unit mass basis, andDPM OC was somewhat more active on a mass-per-mile basis.In terms of a chromosomal-damage (micronucleus) assay, DPMOC were about one-tenth as active as GPM OC on a mass basis,but comparable on a per-mile basis. The investigators also testedvapor-phase semivolatile organic compounds (SVOC) from DEand GE. Diesel SVOC was inactive, but gasoline SVOC wasactive and had much higher toxicity. That is, some degree ofpositive in vitro genotoxicity, as estimated by standard assaysystems, is not unique to diesel exhaust.

Levels of lung-cell DNA adducts in laboratory animalsfollowing inhalation of DE or other particles have been used toestimate in vivo DNA toxicity. It has been reported (Shirname-More, 1995) that chronic inhalation of high levels of DE causesincreases in the numbers of DNA adducts in the lung cells ofrodents. However, inhalation exposure to high levels of manydifferent types of particles increases the frequency of lung DNAadducts, and the types of adducts formed are not the same as themutations induced by PAH. This suggests that adduct formationfollowing particle inhalation may be a nonspecific PM response,rather than a specific chemical effect of DE PAHs. In one groupof studies, rats exposed by inhalation to DE for 12 weeks (Bondet al., 1990a, 1990b, 1990c) or chronically (Randerath et al.,1995) showed an approximately 2- to 4-fold elevation in lungcell total DNA adducts (compared to air controls); however,carbon black (CB)-exposed rats showed similar elevations inadducts. Although the DPM and CB in these experiments hadsimilar EC cores, the DPM contained up to 30% adsorbed OC byweight, while the CB contained only 0.04% adsorbed OC. Thefact that both of these particle types induced similar lung DNAadduct levels suggests that the adduct effect was associated withthe particles per se, and not with the adsorbed OC. The adductfrequency in DE- and CB-exposed rats was not dose dependentand declined rapidly after cessation of the 12-week exposure. Incontrast to the Bond et al. results, a study reported by Gallagheret al. (1994) found no significant increases in the numbers ofPAH-associated DNA adducts or in total DNA adducts in lungcells (relative to air controls) of rats that had been exposedto DE (7,500 µg/m3), CB (11,300 µg/m3), or TiO2 (10,400µg/m3) for up to 2 years. Notably, these researchers reporteda unique “nuclease-sensitive” adduct in DE-exposed rats, butnot in controls. They speculated that this adduct might havebeen caused by nitro-PAHs. However, a key study by Areyet al. provides insight on the bacterial mutagenicity of DPMextracts possibly being artifactual (Arey et al., 1988). That is, themutagenicity of DPM that has been attributed to nitro-aromaticsmay arise artificially from the passing of NOx gasses overthe aromatic hydrocarbons deposited on the filter during thecollection of DPM, and these nitrocompounds are not presentin ambient particulate prior to collection.


Working with the Health Effects Institute (HEI), Randerathet al. (1995) reviewed the findings of lung cell DNA adductsin rats following inhalation of particles and concluded that“endogenous precursors rather than inhalation of exogenouschemicals gave rise to the observed adducts.” The authors stated,“These results imply that, although the organic compounds indiesel exhaust are capable of damaging cellular DNA, suchdamage did not occur under the conditions of the inhalationbioassay.” HEI concluded that although diesel extracts havebeen shown to cause genetic mutations in vitro, the majorityof experiments using whole DPM have shown no such in vitromutagenic activity, again suggesting that potentially mutagenicOC on DPM are poorly bioavailable (HEI, 1995). Furthermore,the fact that lung tumors can be induced in rats exposed byinhalation to >2000 µg/m3 ultrafine particles with virtually noadsorbed OC (e.g., TiO2) supports the idea that PM per se, andnot the OC bound to DPM, is responsible for lung tumors in ratsexposed to overloading levels of DE.

Bioavailability of DPM-Associated Organic CompoundsAs already noted, OC on DPM can be extracted efficiently

(close to 100%) with organic solvents such as DCM, andthese organic-solvent derived extracts have been found to bemutagenic. However, bioavailability of these OCs in biologicalfluids in the respiratory tract appears to be minimal. Indeed,studies of 14C-labeled DPM incubated in DCM, blood, serum,or saline showed almost 100% OC extraction in DCM, whileonly 50% in serum, and less than 5% in saline (King et al.,1981; McClellan et al., 1982; Brooks et al., 1984). Moreover,in contrast to DCM extracts of DPM, extracts of DPM obtainedin serum, lavage fluid, or saline had very low levels ofmutagenicity (i.e., comparable to background) (Brooks et al.,1980). One hypothesis is that the OC extracted using serumor other biological fluids become inactivated. This theory issupported by an in vitro test in which a DCM extract aloneshowed high mutagenicity and toxicity, but when serum or lungcytosol was added to the extracted material, the effects weresignificantly reduced (McClellan et al., 1982). The potentiallylow bioavailability of OC adsorbed on the surface of DPM isconsistent with the pharmacologic principle that the activityof any drug or compound introduced into the body dependson the solubility of the administered compound in biologicalfluids (Vostal, 1983). When a compound is administered in aninsoluble form, the chemical will not reach the target organ,and the response seen for a soluble form cannot be expected tooccur.

The bioavailability of PAHs on the surface of DPM wasrecently studied by Borm et al. (2005). They assessed therelease and bioavailability of PAHs from CB (containingbenzo[a]pyrene levels of 0 to 6.8 mg/kg) as well as froma DPM NIST standard (SRM 2975) containing 0.052 mg/kgbenzo[a]pyrene. The NIST DPM standard has low levels of OC,and may not be representative of typical DPM. No leaching of

PAHs was detectable in saline or surfactant-containing salinefrom either CB or the NIST DPM. DPM and three differenttypes of CBs did not induce formation of DNA-adducts in theA549 human lung cell line in vitro. A solvent extract fromone of the CB types that contained the highest amount ofbenzo[a]pyrene (BaP) (6.8 mg/kg) did induce DNA adductsin vitro in A549 cell cultures. Borm et al. concluded. “However,the in vitro conditions showing this effect [of the CB extract]will not be encountered in vivo and renders this mechanismin particle-induced lung cancer at in vivo exposures highlyunlikely.” Moreover, lung DNA from rats exposed by inhalationfor 13 weeks to high levels of the same CB type did not showelevated adducts. That is, rats exposed to filtered air had thesame types and incidences of adducts as rats exposed to CB atexposure levels up to 50,000 µg/m3. The Borm et al. resultssuggest that DPM and CB PAHs are very tightly bound tothe particles, and only by using organic solvent extraction andconcentration do the PAHs become available at high enoughconcentrations to form PAH–DNA adducts.

Most bioavailability studies test the mutagenicity of thefluid phase of organic-solvent or biological-fluid extracts, andnot DPM per se. There is less evidence that whole DPM (asopposed to solvent extracts of DPM) is mutagenic in vitro,indicating that the OCs (and associated PAHs) extracted fromDPM are poorly bioavailable in lung fluids (Randerath et al.,1995). Some studies have focused on the particle phasewhen combined with surfactant-like substances (Wallaceet al., 1987; Keane et al., 1991; Gu et al., 1992, 2005), andhave reported in vitro mutagenic activity for DPM suspended ina phospholipid emulsion that simulates pulmonary surfactants.In one study, diesel soot scrapings from the inside of an exhaustpipe were either extracted with DCM, dispersed in saline, oremulsified in dipalmitoyl lecithin (DPL), an artificial pulmonarysurfactant (Wallace et al., 1987). The emulsification requiredultrasonic agitation, a nonphysiological treatment. The dieselsoot gave mutagenic results in bacteria both for DCM extractsand the DPL emulsion, and the response was dose dependent.However, when the supernatants versus the sediments of thesetest systems were separately assayed for mutagenic activity, theactivity was found exclusively in the supernatant for the DCMextracts and exclusively in the sediment for the DPL emulsions.Similar results have been found using other genotoxicity testssuch as the sister chromatid exchange assay (Keane et al.,1991), the micronucleus induction assay (Gu et al., 1992), andother assay systems (Gu et al., 2005). The results suggest thatthe in vitro mutagenic activity of DPM may be increased bythe particles being dispersed in a lung-surfactant-like medium,and that the particles themselves, rather than any extractedfraction, are responsible for this mutagenic response. Threecaveats of interpretation for these studies are that (1) the DPMevaluated was derived from diesel engines of the 1980s era,(2) preparing the DPM–surfactant emulsion required dispersionwith ultrasonic vibration energy, and (3) the authors did notverify that application of their test system to control particles


(e.g., carbon black or titanium dioxide without OC) yielded anull result.

Assuming that all of the DCM-extractable mutagenic ac-tivity of DPM is bioavailable, one can compare DE-deliveredmutagenic activity with that of other sources of mutagens.Valberg and Watson used a comparative potency approach torank the mutagenicity of DPM extracts relative to cigarettesmoke condensate (CSC) (Valberg and Watson, 1999). Theydetermined that the quantity of DPM, the extract from whichhad the same mutagenicity as CSC from one cigarette, rangesfrom 63 to 181 mg, depending on the source of CSC and theDPM. This suggests that, at ambient urban levels of DPM (∼2µg/m3) and assuming complete bioavailability of DPM OC, aperson would have to breathe DPM in ambient air (∼20 m3/day)for 4 to 12 years to reach the mutagenic level equivalent to CSCfrom smoking 1 cigarette. At 5% bioavailability, it would take80–240 years of ambient DPM inhalation.

Another quantitative comparison of this kind relates to theamount of the mutagen 1-nitropyrene (1-NP) in DPM versusthe diet. Of the mutagens present in organic solvent extracts ofDPM, 1-NP is a major contributor, accounting for about 10%of the mutagenic activity (Pederson and Siak, 1981; Nakagawaet al., 1983). The content of 1-NP in DPM is such that ambientlevels (∼2 µg/m3) would be expected to have about 0.30 pg/m3

of 1-NP (Scheepers et al., 2003). By comparison, the contentof 1-NP in grilled chicken is about 20 ng/g (Kinouchi et al.,1986). Hence, ingesting a single serving of grilled chicken (3.5oz) would deliver about 2000 ng 1-NP. A person would have tobreathe ambient levels of DPM for 1000 years to receive thatamount of 1-NP. Although this is a comparison across differentroutes of entry, 1-NP has been shown to be rapidly absorbedfrom the gut (van Bekkum et al., 1999). This calculation againsuggests that mutagens in DPM, even if completely bioavailable,are markedly lower in quantity that what is received from othersources.

Interestingly, in one of the very few studies of dieseloccupations in which a range of DPM exposures in a groupof 87 railroad workers was compared to mutagenic activity intheir urine, no association was found between personal DPMexposure and urinary mutagenicity (Schenker et al., 1992).

In summary: (1) Biological fluids are far less efficient atextracting potentially mutagenic OC from DPM than organicsolvents, (2) mutagenic chemicals tightly adherent to DPMare not likely to be bioactive in vivo, and (3) biologic fluids(e.g., serum, surfactants) may mitigate the mutagenic activity ofextracted OC such as PAHs, but (4) some evidence suggests thatDPM coated with surfactant may have mutagenic activity. Quan-titatively considering the organic-solvent-extracted mutagenicpotential of OC from DPM shows that continuous exposure toDPM at ambient concentrations delivers a far lower dose ofmutagenicity than that received from other common sources ofhuman exposure to mutagens. Thus, even for traditional DE, itappears that genotoxicity of DPM is unlikely to increase lungcancer risk.

Summary of Laboratory StudiesIn summary, the apparent mechanism whereby lifetime in-

halation of very high concentrations of DE leads to lung tumorsin rats is: Deposition of high levels of particles in the lungsoverloads clearance mechanisms and initiates an inflammatoryresponse to which rats are particularly vulnerable; chronicinflammation, with ongoing release of oxygen free radicalsfrom pulmonary macrophages and neutrophils, damages lungtissues and stimulates tissue repair, increasing the chances ofDNA mistakes and failure of DNA repair mechanisms; at thesame time, oxygen free radicals act as direct mutagens. Thespecies-specific carcinogenic process appears to occur onlyat very high doses and to be a particle and not a chemicaleffect. Neither the animal nor the cell culture studies of DEprovide convincing evidence of a mechanism involving a directexogenous mutagen.

Mutations have been demonstrated in cells that have beendirectly treated (in vitro or ex vivo from rodents intratracheallyinstilled) with OC extracted from DPM by organic solvents.However, these results are not likely relevant to DE tumori-genicity observed in rats, because DPM mutagens are relativelynon-bioavailable and low in quantitative activity compared toother sources. Mutagenic OC can be extracted from DPMonly by the use of heat, ultrasonication, and organic solvents,processes that do not occur in a living organism. Althoughsome evidence exists that DPM coated with surfactant may havemutagenic activity, the interpretation of these results is unclear.In summary, both the animal and the in vitro laboratory studiesof DPM are not adequate for predicting that inhalation of DEleads to an increased risk of lung cancer in humans.

EPIDEMIOLOGIC STUDIES

Introduction to Epidemiologic StudiesWhile there have been numerous epidemiologic studies of

occupational groups with potential or known exposure to DE,only some of them have been undertaken with the investigationof DE as an a priori objective. Among those studies with such anobjective, many have concluded that DE exposure is or may bea factor in the risk of lung cancer. Similarly, among authors orpanels that have reviewed studies of such occupational groups,whether or not the investigation of DE was an original studyobjective, many have concluded that there is at least a weakassociation between long-term occupational exposure to DEand the risk of lung cancer. The objective of this section is tosummarize and critically assess the assumptions and conclu-sions of the topics considered most relevant: studies of railroadworkers, on-road transportation workers, and undergroundminers; associated exposure information; and selected reviews.

Assessment of Exposure to Diesel Engine ExhaustBefore reviewing the epidemiologic studies, some back-

ground information on the assessment of diesel exposure willbe helpful.


A major problem in estimating DE exposure is that most DE-exposed work areas also include airborne particles from manyother sources, including carbon compounds from nondieselsources (e.g., tobacco smoke, gasoline engine exhaust, othersources of combustion, solvents, pollen, paper, dust, etc.).The exhausts of engines (both gasoline- and diesel-powered)share similar physical and chemical characteristics with eachother and with airborne materials from many other combustionsources. There is no known marker for distinguishing DPM fromother types of carbon-based dust. Thus, it has been difficult,if not impossible, to quantify the portion of an individual’stotal airborne particulate exposure that derives from engineexhaust, and even more difficult to quantify the portion thatis specifically related to diesel exhaust. Indeed, the followingsections of this work describe research that suggests that DE andgasoline engine exhaust exposures are present together and areinseparable in the trucking industry, but not in the undergroundmining industry.

As discussed in the introduction, DPM develops during thecombustion process; ultrafine particles of EC form, agglomerateinto larger particles, and adsorb OC compounds as they grow insize. Typically, high levels of airborne OC particulate indicateone or more non-DE sources. For example, the total carbon(TC = EC + OC) in cigarette smoke is >98% OC and <2% EC.In contrast, the TC in DPM is only 15–65% OC (35%–85% EC),depending on fuel type, engine type, and operating conditions(Zaebst et al., 1991; Sirianni et al., 2003). There are also manyother sources of EC and OC, such as gasoline engines, cooking,industrial boilers and manufacturing processes (Rogge et al.,1991, 1993a, 1993b, 1993c, 1993d, 1994, 1997a, 1997b, 1998).

Because DE is a complex mixture, it cannot be measureddirectly. Markers, or surrogates, that have been measured in thefield in order to estimate DE exposure in occupational settingsinclude the following:

• Carbon monoxide.• Nitrogen dioxide.• Coal tar pitch volatile organic compounds.• Respirable particulate matter (RPM; particles with

median aerodynamic diameter 3.5 µm).• Respirable combustible dust (RCD, i.e., RPM that is

pyrolized to obtain the organic fraction).• Adjusted respirable particulate matter (ARPM, i.e.,

RPM minus the estimated tobacco-related component).• Submicrometer particulate matter (also referred to as

DPM; aerodynamic diameter <1 µm, or in some cases<0.8 µm).

• Total carbon (TC).• More recently, elemental carbon (EC).

Of the identified surrogates, the EC exposure measurementprovides the most specific representation of historic DEexposure. EC is a relatively good surrogate for traditionalDPM, because DPM has a relatively high fraction of EC formany occupational environments. However, as discussed in the

introduction of this article, DPM is typically less than 1% ofthe mass of total DE; thus, EC, although the best of the knownsurrogates for DE, is still not ideal. Moreover, newer engines(that comply with 2007 emissions regulations) have particulatetraps that virtually eliminate all EC from the exhaust and alterthe emission profile in other ways, thus further limiting theutility of EC as an effective surrogate for DE in the future.

For EC analysis, NIOSH method 5040 uses a thermal processto separately measure the EC and OC components of air samplescollected in DE-exposed workplaces (Birch and Cary, 1996;Birch and Noll, 2004). Current assessments of DE exposurecommonly measure EC as a marker to help distinguish dieselexhaust from other types of airborne particles (especially fromtobacco smoke). Even this approach, however, cannot fullydifferentiate DE exposure from exposure to other combustionsources. For example, gasoline exhaust typically consists of20–35% or more (in late-model vehicles) EC (Norbeck et al.,1998). EC is commonly present in many different combustionproducts (though at lower concentrations than in DE) and isalso produced by some other sources such as iron foundries,cooking, and agricultural burning.

In 2003, HEI convened a panel of world experts to identifya marker for diesel. The panel concluded: “Better measuresof exposure to constituents of diesel emissions, with carefulattention to selection of the sample studies, are needed. Ofparticular importance are the selection and validation of achemical marker of exposure to the complex mix of dieselexhaust emission” (HEI, 2003).

In the epidemiologic studies discussed next, various markersand methodologies have been used to estimate DE exposure.Table A-2 lists DE exposure studies for various occupationalgroups and compares results of different DPM measurementtechniques. The accuracy and appropriateness of the DE-exposure assessments in each study have a major impact on thevalidity of the findings with regard to associating DE-exposureto lung cancer mortality.

Railroad WorkersRelevant studies of U.S. railroad workers that bear on DE

exposure and its possible relationship to lung cancer risk includecase-control and retrospective cohort mortality studies reportedby Garshick et al. (1987, 1988, 2004, 2006b); an industrialhygiene survey of DE exposures in railroad jobs (Woskieet al., 1988a, 1988b); a reanalysis of the epidemiologic databy Crump (1999); and later assessments of DE-exposures ofU.S. train crews by Liukonen et al., Seshagiri, and Verma(Liukonen et al., 2002; Seshagiri and Burton, 2003; Vermaet al., 2003). The railroad epidemiologic studies were based oncomputerized work records maintained since 1959 by the U.SRailroad Retirement Board (RRB). By 1959, the transition fromcoal-powered to diesel-powered locomotives was 95% completein the United States.


FIG. 5. Railroad worker exposure to respirable particulate matter, elemental carbon, and environmental tobacco smoke.Comparison of railroad worker exposure measurements of Woskie (1988a) and Verma et al. (1999). Height of bar representsrespirable particulate matter (RPM). The five bars on the left show the relative proportion of environmental tobacco smoke (ETS)and other (adjusted) respirable particulate matter (ARPM) estimated by Woskie et al. The four bars on the right show the proportionof elemental carbon (EC) and other respirable particulate matter measured by Verma et al.

Woskie et al. Assessment of DE Exposure of Railroad WorkersThe Garshick epidemiologic studies classified various rail-

road job categories as either DE-exposed or nonexposed basedon an industrial hygiene survey conducted during 1981–1983to evaluate the then-current exposure of railroad workers toDE (Woskie et al., 1988a, 1988b). The survey measuredconcentrations of airborne respirable particulate matter (RPM;3.5 µm mass median aerodynamic diameter), adjusted forcigarette smoke, as a marker of DE exposure in four smallnortheastern U.S. railroads, for more than 530 workers in 39common jobs, over a period of 3 years. (It may be noteworthythat the DE exposure period in the Garshick epidemiologicstudy was 1959–1980, whereas the DE exposure assessmentperiod in the Woskie study was 1981–1983. Furthermore,the epidemiologic study population worked throughout theUnited States, whereas the Woskie study was conducted in thenortheastern United States.) In many of the exposure samplesthe investigators estimated that 20–90% of the RPM wasderived from cigarette smoke (Fig. 5); thus they subtractedfrom the RPM measurements the estimated fraction due tocigarette smoke to obtain an adjusted respirable particulatematter (ARPM) value. The ARPM levels for the job categoriesfell into three exposure groups: clerks and signalmen, lowexposure; train crews, medium exposure; shop workers, highexposure. The adjusted ARPM exposures ranged as follows(geometric means, µg/m3): “Unexposed” jobs were 17 for clerksand 49 for signalmen; “DE-exposed” jobs were 39–92 for train

crew other than hostler; 191 for hostlers (highest exposure); and114–134 for shop workers (Table 3). The Woskie et al. studyfound notable variations in exposure results between differentrailroads and with weather changes. Based on limited historicalexposure data, Woskie et al. assumed that DE exposure wasapproximately constant from 1959 to 1983.

Garshick Case-Control Study, 1981–1982The initial study published by Garshick and his investigative

team was a case-control study in which the cases were lungcancer deaths of railroad workers who were born during or after1900, had at least 10 years railroad service, and died betweenMarch 1981 and February 1982 (Garshick et al., 1987). Deathcertificates were located for about 13,000 deaths during this 1year, including 1256 lung cancer deaths (cases). The controlswere randomly selected from the remaining RR worker non-lung-cancer deaths, subject to eligibility criteria, and matched tothe cases for age at death and date of death. Exposure to DE wasmeasured in years of working in DE-exposed jobs (Woskie et al.,1988b) since 1959. Multiple conditional logistic regressionmodels, with adjustments for smoking (including pack-years,categories of pack-years, cigarettes per day, years of smoking,and years of smoking and years since stopped) and asbestosexposure (including yes/no, estimated years of exposure, andcategories or regular, intermittent and none), were used for theanalyses. The authors reported the following: (a) Workers who


TABLE 3Railroad industry: Personal exposures to adjusted respirable particulate matter by job

group and lung cancer mortality based on U.S. rates

Exposure Lung cancer mortality

Job category n

Adjusteda respirableparticulate matterb

(µg/m3, geometric mean) n Relative riskd

UnexposedClerks 59 17 315e 0.98e

Signal Men 13 49Exposed

Engineers/firemen 128 39–73c 298 1.23Conductors/brakemen 158 52–92c 437f 1.20f

Hostlers 8 191Shop workers 174 114–134c 318 1.08

aFor each air sample, estimated fraction of cigarette smoke was subtracted from total respirableparticulate matter; adjusted data are presumed to reflect the concentration of airborne DE particulate(Woskie et al., 1988b).

bRPM median aerodynamic diameter 3.5 µm.cRanges for various subcategories within this job category.dBased on U.S. lung cancer mortality rates (Crump, 1999).eClerks and signal men combined.fConductors/brakemen and hostlers combined.

were less than 65 years of age at time of death and had workedin a DE-exposed job for 20 years had a statistically significantincreased odds ratio for lung cancer, which was calculated tobe 1.40. (b) Risk for lung cancer was not elevated in workerswho were 65 years of age or older at time of death (the oddsratio was calculated to be 0.91 for 20 years of service), because(the authors concluded) “many of these men retired soon afterthe 1959 transition to diesel locomotives.” The investigatorsconcluded, “The relative risk obtained in this current studyis low. Some believe that at relative risks of this magnitude,epidemiologic methods cannot be used to establish risk.” Theyalso concluded, “Our findings suggest that other groups withoccupational exposures (underground workers exposed to dieselexhaust) may be at excess risk of lung cancer.”

Garshick Retrospective Cohort Study Through 1980One year after publishing their case-control study, Garshick

et al. reported on their retrospective cohort mortality study forthe follow-up period of 1959 through 1980 (Garshick et al.,1988). The cohort consisted of approximately 55,000 Whitemale railroad workers 40 to 64 years of age in 1959, with 10 to20 years of service by 1959. As in the case-control study alreadydescribed, jobs were again classified as either “DE-exposed”or “nonexposed” according to yearly job records from 1959 todeath or retirement. No adjustments for smoking were made, andthe authors cited data on a subset that indicated no differencein smoking prevalence between workers with and without DE

exposure. The cohort was selected to minimize possible asbestosexposure. Directly standardized rates and a proportional hazardsmodel were used to calculate the relative risk of lung cancerbased on work in a job with DE exposure beginning in 1959.DE exposure was considered to be a dichotomous (yes/no)variable. Death certificates were obtained for 88% of 19,396deaths, including 1694 lung cancer deaths.

The authors reported the following results: (a) The relativerisk of lung cancer was progressively higher among workers whowere younger in 1959 and who thus had potentially longer DEexposures or at least longest elapsed time since first exposure.For workers aged 40–44 years in 1959, the relative risk was 1.45(Table 4); for the workers aged 60–64 in 1959, the relative riskwas 0.99. Garshick et al., concluded, “Workers with 20 years ormore elapsed since 1959, the effective start of diesel exposurefor the cohort, had the highest relative risk.” (b) The authorsalso reported that the relative risk of lung cancer increased withincreasing cumulative years of DE exposure from 1959 on. Theauthors concluded that these results “support the hypothesis thatoccupational exposure to DE results in a small but significantlyelevated risk for lung cancer.”

Crump Analysis of Garshick StudiesIn response to a request from the U.S. EPA, Crump conducted

a quantitative risk assessment for DE based on the data from theGarshick 1988 cohort study and pointed out several importantfindings (Crump et al., 1991; Crump, 1999, 2001). (a) First,


TABLE 4Railroad industry: Relative risk for lung cancer mortality,

1959–1980

Relative risk for lung cancer mortality

Worker age(yr) in 1959

Exposed vs.unexposeda

Exposed vs.U.S. ratesb

Unexposed vs.U.S. ratesb

40–44 1.45 0.66 1.0345–49 1.33 0.84 1.0850–54 1.12 0.96 1.1755–59 1.18 1.23 1.3960–64 0.99 1.25 1.23

Note. Diesel exposure, yes or no, based on job classification in 1959.aGarshick et al. (1988).bCrump (1999).

Crump reported evidence that follow-up was incomplete for thestudy; that is, “a sizable fraction of deaths during the last fouryears of follow-up evidently were not identified” (apparentlydue to incomplete transmittal of data from the RRB). Theshortfall of data effectively ended the follow-up at 1976, insteadof 1980 as originally intended. (b) In contrast to the Garshicket al. (1988), finding that relative risk for lung cancer increasedwith duration of exposure, Crump did not find a plausibledose-response for DE. Crump concluded that, “A positive,monotone dose-response trend in lung cancer mortality withincreasing duration of exposure . . . was not present when agewas controlled more carefully and years of exposure quantifiedmore accurately. Instead, a negative dose-response trend forlung cancer was seen among exposed workers based on eitherduration of exposure or quantitative measures of cumulativeexposure.” (c) In contrast to the Garshick 1988 finding of adecreased lung cancer risk with increasing age at 1959, Crumpreported opposite trends when U.S. rates were used as the basisof comparison; lung cancer mortality was higher among workerswho were older in 1959 (and therefore had less DE exposure)(Table 4). (d) Crump reported that although the engineers andconductors had similar DE exposures (based on airborne RPMlevels adjusted for tobacco smoke), convincing evidence existsthat shop workers had higher DE exposures (perhaps twicethat of the train crews). Crump pointed out that although traincrews (exposed) had significantly elevated lung cancer mortalityrelative to clerks and signalmen (assumed to be unexposed),shop workers (the most highly DE-exposed group) did not havean elevated risk (Table 3). Crump noted that shop workersalso were exposed to other industrial lung carcinogens suchas asbestos and welding fumes, and the fact that lung cancermortality in these workers was no different from that of clerksand signalmen argues against a causal effect of diesel exposurein this cohort. Based on their findings, Crump and colleaguesrecommended to the U.S. EPA that the railroad study reported

by Garshick et al. (1988) did not constitute an appropriate basisfor a risk assessment of DE (Crump, 2001).

Garshick Cohort Study Update Through 1996In 2004, Garshick and colleagues updated the cohort mortal-

ity experience to cover the 37 years from 1959 through 1996,during which time there were nearly 44,000 deaths with knowncause of death, including 4351 lung cancer deaths (Garshicket al., 2004). The update confirmed and corrected theirincomplete follow-up through 1980, which Crump had reported(Crump et al., 1991; Crump 1999), adding several thousand pre-1981 deaths that inadvertently had been excluded in the original1959–1980 cohort study. In their 2004 paper, after “adjustingfor a healthy worker survivor effect and age,” Garshick et al. re-ported an elevated lung cancer relative risk of 1.40 for train crews(engineers, firemen, conductors, and brakemen; jobs identifiedas DE exposed) compared with railroad workers in unexposedjobs (clerks and station agents). Indirect adjustment for smokingusing Schlesselman and Axelson methods (Schlesselman, 1978;Axelson and Steenland, 1988; Larkin et al., 2000) attenuated therelative risk to between 1.17 and 1.27. The job-specific smokinghabits were estimated from the case-control study and a surveyof 514 white male workers at a small railroad in 1982. Shopworkers, who reportedly were exposed to the highest levels ofARPM but did not show elevated lung tumor incidence, wereomitted from this comparison. The reasons given were that “thejob codes of shop workers were not specific to work in areas withlocomotive exhaust, so diesel exposures of these job codes couldnot be specified,” and “in addition, it was possible that some ofthese workers had previous asbestos exposure in steam enginerepair shops.” Garshick et al. further reported that “lung cancermortality did not increase with increasing years of work in thesejobs,” which confirmed the Crump (1999) finding and reversedtheir own 1988 reported finding. They concluded “Although acontribution from exposure to coal combustion products priorto 1959 cannot be excluded, these results suggest that exposureto diesel exhaust contributed to lung cancer mortality in thiscohort.”

Using a different approach to estimate smoking patterns intheir cohort, Garshick and his team recently published (Garshicket al., 2006b) an analysis of a subset of the full cohort reportedin Garshick et al. (2004). The subset is made up of 39,388railroad workers who died from 1959 to 1996. Using smokinginformation from their case-control study, they “imputed”smoking histories (i.e., estimated by randomly selecting fromthe case-control workers for whom smoking information wasavailable) for the 39,388 who died. They reported, “The smokingadjusted relative risk of lung cancer in railroad workers exposedto diesel exhaust compared to unexposed workers was 1.22(95% CI = 1.12–1.32), and unadjusted for smoking the relativerisk was 1.35 (95% CI = 1.24–1.46).” It was concluded that“In this cohort, small differences in smoking behavior betweendiesel exposed and unexposed workers did not explain the


elevated lung cancer risk.” Their innovative approach illustrateshow smoking adjustments can lower relative risks. However,estimates based on case-control data are not unbiased, leavingthe possibility for uncontrolled confounding. As Marsh et al.(2001) noted in their study of man-made vitreous fiberproduction workers, “Because the case-control studies were notbased on random samples of cohort members, however, theycould not provide unbiased estimates of smoking rates in thetotal cohort” (Marsh et al., 2001).

Laden et al., 2006b, recently published a report using aninnovative exposure intensity characterization by using histor-ical data on dieselization of individual railroads and emissionfactors and constants suggested by the US EPA (1996b). WhileRRs for lung cancer remained elevated, as expected, there wasno evidence of an exposure-response relationship using themeasures of exposure based on the intensity measure. They alsoreported on measures of duration of exposure going back to1945. (Earlier reports started in 1959.) They reported evidenceof an exposure-response for workers first hired from 1945–1949using years of exposure. However, there was no evidence of sucha response for the full cohort or the much larger group of workersfirst hired from 1939–1944.

Critique of DE Exposure AssessmentsIn commenting on the railroad worker cohort investigation

reported by Garshick in 1988, Crump (1999) noted that “evenif the problem of incomplete follow-up was corrected, and evenif follow-up was extended to additional years, this would notaddress the limitations of the exposure data for this cohort.” TheGarshick 2004 update did just that: the incomplete follow-upfor 1959–1980 was corrected and the follow-up was extendedthrough 1996, but the limitations of the exposure data for thecohort were not addressed.

Garshick excluded shop workers from the “exposed group”of conductors and engineers. However, Crump concluded that“based on all the available evidence, it appears highly likelythat the shop workers (90% of whom were machinists andelectricians) had the highest DPM exposures of any group ofworkers in the Garshick et al. cohort.” Garshick does not refutethat conclusion. Crump’s important observation is ignored inspite of his warning that the fact that “lung cancer mortalityin these workers was no different from that of clerks andsignalmen argues against a causal effect of diesel exposure inthis cohort.” Given that there was essentially no increase in lungcancer risk among shop workers, potential asbestos exposuredoes not justify considering that group separately. Furthermore,the EC levels provided in subsequent manuscripts by Vermaet al. (1999, 2003), Liukonen et al. (2002), Seshagiri (2003),and Seshagiri and Burton (2003), collectively, suggest that theshop worker (machinists and electricians) exposures to DE wereat least comparable to that of conductors and engineers, andmay well have been substantially greater (thus corroboratingCrump’s discussion and conclusion) (Fig. 6). The 2004 Garshick

follow-up shows essentially the same results for shop workers,with an average RR of about 1.04.

More recent industrial hygiene studies of exposure to dieselexhaust in the Canadian railroad work environment (Vermaet al., 1999, 2003; Seshagiri 2003; Seshagiri and Burton, 2003)found total respirable particulate matter (RPM) concentrationsin the same range as those reported by Woskie et al. (1988a,1988b). However, as shown in Fig. 5, the Canadian studyobserved low EC levels for the DE-exposed job groups (onboard, turnaround, and repair). Importantly, the Canadian studyshowed that EC constituted only a minor part (2–16%) of totalrailroad worker RPM exposures. In contrast, Woskie et al.using ARPM as their estimate of DPM, concluded that DPMconstituted 73–84% of total RPM. The exposure findings of themore recent Canadian studies, and the lack of a more specificindicator of DPM exposure (like EC) in the earlier Woskiestudies, suggest that the Woskie studies overestimated the DPMcontent of the RPM exposure. The EC content of DPM varieswith engine age, condition, fuel, etc. (as discussed earlier).However, in the Verma study, even if the DPM mass in thesamples were equal to twice that measured for EC, DPM wouldstill be a small fraction of the RPM exposure. The Canadianstudies show that the RR worker RPM contained much non-DEmaterial, and this likely would be true also for the Woskie U.S.studies, even after adjustment for environmental tobacco smoke(ETS).

The more recent railroad worker exposure studies (Liukonenet al., 2002; Seshagiri, 2003; Seshagiri and Burton, 2003;Verma et al., 2003) use NIOSH Method 5040 (developedsubsequent to the Woskie studies) to measure airborne EClevels (Fig. 6). For engineer and conductor exposures, resultsdepend on season and location in the train. For workers in thelead locomotive, Liukonen found train crew exposure to DEcomparable to background urban exposures. Geometric meanexposure levels were 3.7 µg/m3 for EC inside the operatinglocomotives compared to a background range of up to 8 µg/m3

for EC. For trailing locomotives, Seshagiri found that higherlevels of EC were also associated with open windows duringthe summer and proximity of exhaust stack. These more recentstudies using EC as the comparison metric indicate that levels ofDE for train crews are not much different from, and on averagemay be less than, exposures for mechanics and repair operations.These data appear to further weaken the Garshick finding of anassociation between DE and lung cancer risk among train crews,which was based on a presumed higher DE exposure of traincrews.

Healthy Worker EffectIn 2004, Garshick et al. acknowledged that their original

1988 conclusion, stating that “lung cancer risk increased withincreasing years of work in diesel-exposed jobs,” was in errorand that “subsequent re-analyses of these data, with adjustmentfor attained age, indicated decreased risk with more years


FIG. 6. Airborne diesel exhaust levels in railroad work environments measured as elemental carbon. Elemental carbon (EC)sampling results (arithmetic means) for various job categories and locations. First letter indicates reference: A, Verma et al. (2003);B, Liukonen et al. (2002); C, Seshagiri (2003); D, Seshagiri and Burton (2003). Area = area sample; pers. = personal sample.(References A, B, and C noted that on-board area samples were considered equivalent to personal samples if crew members werepresent.) [n] = sample size. Some values were calculated from data in the articles (e.g., mean was estimated using geometric meanand geometric standard deviation).

worked,” agreeing with Crump (1999). Garshick et al. (2004)further reported, “Analysis in this updated cohort with longerfollow-up also indicates that lung cancer mortality is inverselyrelated to total years worked.” Garshick et al., suggested that thisinverse association between lung cancer and exposure durationmight be explained by a healthy worker survivor effect.

Some comments on the “healthy worker effect” are in orderhere to clarify how this effect might impact evaluations ofthe potential risks arising from employment. The “healthyworker effect” is comprised of several factors, including: (1)those who are hired tend to be healthier, the healthy hireeffect; and (2) healthier individuals tend to remain employed,the healthy worker survivor effect (Checkoway et al., 1989;Arrighi and Hertz-Picciotto, 1994). Garcia and Checkowayexplained the “healthy worker survivor” as the effect that “refersto the selection process by which workers affected by theiroccupational exposure terminate prematurely their working lifeor transfer from higher to lesser exposure jobs, generally leading

to under-estimation of risks and dose-response estimation”(Garcia and Checkoway, 2003). In such a scenario, job statusmay be viewed as an “intermediate variable” or a “mediatorvariable” that is influenced by the occupational exposure andmay be associated with the health outcome of interest. They alsonoted that the healthy worker survivor effect “is most prominentin cross sectional studies of disease prevalence and exposure.”The Garshick et al. railroad worker study is not a cross sectionalstudy, it is a cohort study with both retrospective and prospectivecomponents. Last, in part, defined the “healthy worker effect”by noting that “Workers usually exhibit lower overall death ratesthan the general population, due to the fact that the severely illand disabled are ordinarily excluded from employment” (Last,1988).

Monson suggested that the “healthy worker effect” is“somewhat of a misnomer, since similar deficits are foundwhen other non-hospitalized groups are followed, e.g., religiousgroups” (Monson, 1990). Monson suggested a more general


term, “healthy person effect.” As Monson explained, “Generalpopulations are made up of two groups: the healthy and the ill.Those who are healthy tend to be employed and those who are illtend to be hospitalized. Each, however, contributes to the overallmortality rate of the general population.” It is perhaps intuitivelyunderstandable that if a cohort of active workers is identified andfollowed from January 1, 1959, forward (the Garshick cohortwas identified as workers who were active in 1959 with 10 to20 years of experience), it would not include former workerswho had stopped work in 1957 or 1958 because they were toosick to work (e.g., disabling respiratory or heart disease, orterminal cancer). As a result, the mortality in the cohort fromthose diseases would likely have been initially lower than in thegeneral population. Conversely, some causes of death, such asaccidents, may be seen in greater numbers than in the generalpopulation. The combined effect of healthier persons making upthe cohort often results in lower overall death rates, hence the“healthy worker effect.” In fact, Garshick et al., reported justthat: The SMR for all observed deaths in the cohort was 0.81in 1959, consistent with a healthy worker effect, and by 1967the yearly overall SMR in the cohort had risen to 1.01. Thisincrease in overall SMR in the cohort for 1959–1967 is alsoshown in Fig. 1 of Crump (1999) (“Observed deaths dividedby expected deaths based on U.S. Rates”). The “healthy workersurvivor effect” can be subtler than the generally recognizedfact that workers tend to have better health than the generalpopulation because better health enhances employment. For thehealthy worker effect to have an impact on the disease outcomeof interest, the risk of the disease must be different for thosewho have ceased employment than for those who continueemployment. If such is the case, an adverse risk of exposure maybe attenuated.

How does the healthy worker effect manifest with lungcancer? Howe et al. found that “the healthy worker effect isless for lung cancer than for other cancers, and, in turn, this isless than for all causes of death” (Howe et al., 1988). Arrighiand Hertz-Picciotto remarked, “A common belief is that thehealthy worker effect is small for cancer, especially lung cancer”(Arrighi and Hertz-Picciotto, 1994). They went on to note thatalthough smaller than for cardiovascular mortality, particularlyin the period shortly after hire, some empirical results consistentwith the effect have been reported for cancers. If the Garshicket al. cohort had been initially made up of workers who werecancer-free (or who had not yet been diagnosed), the numberof deaths from lung cancer would be expected to be less in thecohort than in the general population. That is because only afraction of those that were diagnosed in 1959 would have diedin 1959 (some would have died in 1960, etc., and some wouldhave died from other causes). However, because survival forlung cancer victims is low, most probably in only a few yearsthere would be little or no effect from the initial cancer-freestatus of the cohort. The formulas given by Sasieni can be usedto illustrate that any healthy person effect for lung cancer shouldbe essentially gone within 5 to 7 years, definitely before 10 years

(Sasieni, 2003). Such calculations illustrate that from that pointforward, the number of expected lung cancer deaths for thecohort is essentially that of the general population, even thoughthe cohort was cancer-free initially.

Garshick et al. (2004) offered no explanation as to howsuch an effect could produce an inverse relationship in therailroad worker study for a follow-up period of 38 years. Aplausible healthy worker explanation for the consistent inverserelationship between duration of employment and lung cancermortality found in this cohort of 55,000 men over a period of38 years is deemed extremely unlikely.

Health Effects Institute Review of Railroad StudiesThe HEI Diesel Epidemiology Expert Panel (HEI, 1999)

conducted a detailed review of the raw Garshick data and variousanalyses of those data, including the Crump assessment. Thispanel was assisted by leading investigators who had conductedepidemiologic research on diesel exhaust, and by expert analystswho had conducted critical reviews of that research. Thepanel reviewed data on the three broad categories of railroadworkers—train workers (engineers, conductors), shop workers(machinists, electricians), and clerks and signalmen—and con-cluded that lung cancer risks for train workers were higher thanfor clerks/signalmen (unexposed), with shop workers exhibitingintermediate risks. However, the panel’s analysis also found thatwithin each category of worker, the risk of lung cancer decreasedwith increasing duration of employment, and, further, that thedecrease was statistically significant for clerks/signalmen andtrain workers. The HEI report therefore concludes:

These findings are not consistent with a steadily increasingassociation between cumulative diesel exposure and lung cancerrisk. Furthermore, if the difference in risk between train workersand clerks/signalmen was due primarily to differences in exposureto diesel emissions, one would expect the relative risk for trainworkers compared with that for clerks and signalmen to be reducedor even eliminated after adjusting for exposure. In fact, adjustmentfor exposure increased this relative risk. Such a systematic patternof decreasing risk with increasing exposure suggests that some formof bias is present in the data.

The report notes that the negative exposure-response relation-ship could be due to a number of possible reasons, includingunmeasured confounding variables and/or “other sources ofpollution” that could have been responsible for the observedeffect.

The HEI Panel noted that the conclusions initially reachedby Garshick (i.e., a positive exposure–response relationship)resulted entirely from the baseline differences in risk betweenthe two job categories (train workers and clerks/signalmen). ThePanel concluded:

These patterns are not consistent with a monotonically increasingassociation between cumulative exposure to diesel exhaust and lungcancer risk. If risk increased consistently with increasing exposure,a positive trend with duration of employment would be expected


for the exposed groups (including train workers), even if exposuremagnitudes were incorrect.

In short, the current weight of evidence suggests that in theGarshick study, any occupational increase in lung cancer amongtrain riders was not due to diesel exposures.

The phrase “confounding variable” and associated termsare found throughout this assessment and the various citationsherein. A brief discussion of a selection of those concepts isoffered here for interested readers who do not customarily inter-pret epidemiologic literature. The lay definition of confoundingas “confusing” is helpful in understanding the scientific usesof the term; a confounding factor may complicate or mix upthe interpretation of the data. Monson (1990) used the term“confounding bias” to refer to a confounding factor as “one thatis associated with the exposure and independently is a causeof the disease.” Last (1988) defined a confounding variable as“a factor that distorts the apparent magnitude of the effect of astudy factor on risk; such a factor is a determinant of the outcomeof interest and is unequally distributed among the exposed andthe unexposed.” Smoking is a prominent potential confounder,particularly when the main health outcome of interest is lungcancer. If smoking histories of exposed workers differ fromthe comparison group, whether that is unexposed workers orthe general population, it is likely to be intuitively apparentthat there is an inherent bias, depending on how the smokingpatterns differ. There are various methods intended to adjust forthe differences, depending on the type of study, available detailsof the smoking histories, and analytical techniques.

A related concept is when the risk of disease depends not onlyon the exposure of interest, but the presence of another factor.For example, for workers with a history of both occupationalexposure to asbestos and cigarette smoking, the risk of lungcancer is far greater than would be explained by the risk of lungcancer among workers with a history of one or the other factors,but not both. Such an effect of another factor may be referred toas “effect modification,” “synergism,” or “interaction.”

On-Road Transportation Workers (TeamstersUnion Studies)

The most relevant published investigation of lung cancerdeaths among on-road transportation workers was conductedusing information obtained from the Central States Conferenceof the International Brotherhood of Teamsters. The investigationincluded: a case-control study of lung cancer deaths amongteamsters during 1982–1983 (Steenland et al., 1990, 1992);an assessment of DPM exposure for selected Teamster jobcategories during 1990 (Zaebst et al., 1991); and finally anexposure-response analysis and risk assessment of the case-control population based on the exposure data (Steenland et al.,1998). The paragraphs that follow present brief summaries ofthese three studies followed by a critique.

Steenland et al. Case-Control StudyTo investigate the hypothesis that truck drivers have an excess

risk of lung cancer, Steenland et al. conducted a case-controlstudy in which they compared the work histories of maleTeamster Union members who died of lung cancer during1982–1983 with those of controls selected from Teamsterswho died of other causes (excluding deaths associated withbladder cancer or motor vehicle accident) during the same period(1288 cases and 1452 controls) (Steenland et al., 1990). Foreach case and control subject, DE exposure was consideredto be a yes/no (ever/never) variable based on the job categoryin which the subject had worked the longest. Four Teamsterjob categories were assumed to be DE-exposed: long-haultruck drivers, short-haul truck drivers, mechanics, and dockworkers (loading dock and warehouse workers). Subjects whohad worked in office jobs were considered to be unexposed.Work histories before and after dieselization of trucks (estimatedto have taken place between 1960 and 1965) were based onTeamster records and next-of-kin recollections. Teamster Uniondata did not state whether the drivers were driving truckspowered by gasoline or by diesel; this information was obtainedfrom next-of-kin recollections. Information on smoking habitsand asbestos exposure was also obtained from next of kin. Theresearchers considered a number of possible confounders andeffect modifiers. The only factors included in the final modelwere age (five categories), smoking (six categories), asbestos(yes/no), and a dichotomous variable for having held other jobswith potential diesel exposure.

Using unconditional logistic regression analyses, lung cancerodds ratios were estimated for the four presumed DE-exposedoccupations using the non-exposed Teamsters members (officeworkers, etc.) as the reference group. The odds ratios for lungcancer were elevated (but not statistically significantly) fordrivers and mechanics but not for dock workers using propane-powered forklifts. (Dock workers primarily used propane-powered forklifts until the early 1980s, when diesel-poweredforklifts were introduced.) The lung cancer odds ratios, adjustedfor tobacco smoking, were as follows: dock workers (propane),0.92; long-haul drivers, 1.27; short-haul drivers, 1.31; andmechanics, 1.69 (Table 5).

Duration of employment in a presumed DE-exposed occupa-tion was used as a surrogate for cumulative DE exposure. Whenboth pre- and postdieselization employment was considered,no significant trend of increased lung cancer with increasedduration of employment was observed in any of the jobcategories. In contrast, when only employment after 1959was considered (Table 6), both long- and short-haul driversshowed increased odds ratios related to duration of employment;however, mechanics (also presumed to be DE-exposed) didnot show this trend. When only employment after 1964 wasconsidered, results were similar; lung cancer odds ratios were1.55 for long-term, long-haul truckers, and 1.89 for long-termdrivers of primarily diesel trucks (per next of kin).


TABLE 5Trucking industry: Diesel exhaust exposure and lung cancer odds ratios in Teamsters

Union members

Carbon particulate exposures, 1990

JobElementala

µg/m3 (SD)Organica, b

µg/m3 (SD)EC/TC ratio,c

% (SE)

1982–1983d

Lung cancerodds ratio

Dock workers, all 13.8 (3.59)f 35.1 (2.0) 47.3 (1.89) n.d.Mechanics 12.1 (3.67)f 44.5 (1.9) 34.2 (2.62) 1.69Driver, short-haul 4.0 (2.01)e 25.3 (2.2) 42.2 (13.8) 1.31Driver, long-haul 3.8 (2.31)e 21.8 (2.3) 33.4 (4.25) 1.27Dock workers, propane 1.3 (1.97) n.d. n.d. 0.92Ambient, roadside 2.5 (2.36) 3.4 (4.2) n.d. n.a.Ambient, residential 1.1 (2.03) 2.0 (4.2) n.d. n.a.

Note. n.a., Not applicable; n.d., no data reported; SD, standard deviation; SE, standard error.aGeometric mean (SD). Submicrometer-size particulate (Zaebst et al., 1991).bNonsmoking samples only—242 total job samples.cNonsmoking samples (63), excluding samples with <10 µg/m3 EC. Mean EC/TC (elemental

carbon/organic carbon) as% (Zaebst et al., 1991).dSteenland et al. (1990, 1989). Cases vs. controls. Reference group is unexposed Teamsters.eStatistically significantly elevated over ambient residential but not over ambient roadside.fStatistically significantly elevated over ambient and driver levels.

Steenland et al. concluded that their results “suggest thatdiesel truck drivers have an excess risk of lung cancer comparedto other Teamsters in jobs outside the trucking industry.” Theauthors cautioned that the principal limitation of their study wasa lack of DPM exposure data. They also noted other limitations:a lack of sufficient latency for the development of a detectableincidence of lung cancer from DE, a relatively small nonexposedpopulation, and possible misclassification of smoking habits and

TABLE 6Trucking industry: Length of employment and lung cancer

odds ratios in teamsters, using data for Teamster Unionmembers who were exposed during 1960–1983 and died

during 1982–1983 (Steenland et al., 1990)

Job categoryYears of

employmentLung cancerodds ratio

Long-haul driver 1–11 1.08a

12–17 1.41a

18 or more 1.55a

Short-haul driver 1–11 1.11a

12–17 1.15a

18 or more 1.79a

Truck-mechanic 1–11 1.8312–17 2.08

18 or more 1.50

aSignificant trend of increased lung cancer risk relative to increasedduration of employment.

DE exposure (i.e., whether drivers drove diesel- or gasoline-powered trucks) by next of kin.

Zaebst et al. DPM Exposure AssessmentsZaebst et al. conducted industrial hygiene surveys to estimate

DPM exposure for workers in the various Teamster jobcategories that Steenland et al. had considered to be DE-exposedin their case-control study (Zaebst et al., 1991). Dock workerswere subdivided into those who operated propane-poweredforklifts vs. those who operated diesel- or gasoline-poweredforklifts. Zaebst et al., collected submicrometer airborne dustsamples (DPM) and used a thermal–optical method (NIOSHMethod 5040) to obtain three mass measures for each air sample:elemental carbon (EC), organic carbon (OC), and total carbon(TC = EC + OC). They found that DPM carbon typically wascomposed of 60–80% EC, while carbon from tobacco smoke, animportant potential confounder, contained <2% EC (averaged>98% OC). Thus, the investigators determined that EC was auseful surrogate for DPM because it was present in substantialamounts in DPM and was fairly specific to combustion sources,especially diesel.

Zaebst et al., found that the EC levels to which truck drivers(both long- and short-haul) were exposed were essentiallyequivalent to highway background levels and significantlyelevated over residential levels (Table 5). The total dockworker group (including operators of forklifts powered bypropane, diesel, or gasoline) and mechanics had significantlyhigher geometric mean EC exposures (13.8 and 12.1 µg/m3,respectively) compared to truck drivers (3.8–4 µg/m3). EC


exposure was similar to residential background levels forpropane forklift operators, but much higher for diesel forkliftoperators (27.2 µgm3). Differences in EC levels in each jobgroup were observed between warm and cold weather.

Steenland subsequently discussed the 1990 case-controlfindings in light of the Zaebst et al., report and concludedthat the DE exposure findings are generally consistent withthe epidemiologic study (Steenland et al., 1992). However, theauthors noted that “the lack of actual exposure data on thestudied population is typical of retrospective studies, and is evenmore of a problem in the case of diesel exhaust because of thelack of historical sampling data and lack of a standard methodof measuring diesel exhaust.” They also noted “inadequatehistorical exposure data in diesel exhaust studies remain a majorlimitation in evaluating the epidemiology data.”

In an effort to conduct a quantitative risk assessment of DEas a cause of lung cancer in the trucking industry, Steenland etal. used the Zaebst study data to estimate historical exposuresof the subjects in the original 1982–1983 case-control studyof lung cancer deaths. Historical DE exposures were assumedto be a function of (1) the number of heavy-duty trucks onthe road, (2) the particulate emissions (grams/mile) of dieselengines over time, and (3) for long-haul drivers, the quantity ofDE leaking from exhaust systems into drivers’ compartments.The authors assumed that worker exposure to DPM increasedin proportion to increased use of diesel engines and also thatuse of heavy-duty trucks was a good surrogate for total dieseluse. To estimate worker exposures, the authors multiplied milestraveled by heavy duty trucks from 1949 to 1990 by estimatedemissions per mile. They assumed that after 1949 all heavy dutytrucks on the road were diesel-powered. They further assumedthat engine performance improved over time and that driverswho owned their own trucks had higher exposures than thosewho did not.

Using the estimated historical exposure for subjects inthe Steenland 1982–1983 case control study, analyses wereconducted via logistic regression and were adjusted for age, race,smoking (five categories), diet, and reported asbestos exposure.Estimates of lung cancer risk were calculated only for long-hauldrivers, the largest job category. The analyses resulted in a 1.6%lifetime excess risk of lung cancer death from exposure to 5µg/m3 EC (through age 75) for a male truck driver (i.e., anexcess of 1.6 lung cancer deaths per 100 men). Assumptions inthe estimate were that emissions in 1970 were 4.5 g/mile and thatthe worker had 45 years exposure (from age 20 to 65) at 5 µg/m3

EC. The authors cautioned, “Our results should be regarded withappropriate caution because our exposure estimates are basedon broad assumptions rather than actual measurements.”

Additional Assessment of Teamster StudiesIt is notable that the Zaebst exposure assessment was

performed seven years after the Steenland study period andin a different region of the U.S. The studies of Steenland et al.

have been cited as a basis for quantitative risk assessment oflung cancer from DE exposure. Several aspects of the Steenlandet al. Teamster studies raise concerns about the relevancy andadequacy of these studies for an assessment of an associationbetween exposure to DE and increases in lung cancer risk. Theseitems of concern are discussed next and include limitations ofDE exposure estimates, the fact that truckers are exposed toemissions from gasoline- as well as diesel-powered vehicles,and inadequacy of latency period.

Limitations of DE Exposure Estimates in the Trucking IndustryEC/TC Ratio. An important aspect of the Teamster expo-

sure data—the ratio EC/TC—suggests that DE was not the onlysource of airborne particulate matter in these studies and wasprobably not the primary one. As discussed above, the carbon inDPM is predominantly EC (60–80%), while gasoline exhaust ispredominantly OC and cigarette smoke is >98% OC. Thus, in aDE-exposed occupational setting, a high EC/TC ratio suggeststhat the exposure is predominantly DE, while a moderate orlow ratio suggests that non-DE sources of carbon are presentand are a substantial part of the exposure. To investigate theEC/TC percentage in their DE-exposed job samples, Zaebst et al.selected a subset of 63 samples (from their total of 199 samplesfrom nonsmoking, DE-exposed workers) that represented thefour DE-exposed job categories; the subset of 63 excluded allsamples with <10 µg/m3 EC, to improve the regression analysisat higher DE exposure levels. In these 63 samples, Zaebst et al.reported that on average the total carbon consisted of 41%EC (Table 5). However, this figure largely overrepresents theactual proportion of EC in the total 199 nonsmoker samples,because it does not include the 136 low-EC nonsmoker samples(a large majority of the samples). The data shown in columnsone and two of Table 5 (which do include the 136 sampleswith <10 µg/m3 EC) suggest that EC was only 16–28% of theTC (% EC based on geometric means of EC/(EC+OC). If thesmoker samples had also been included, the OC content wouldhave been much greater, making the EC/TC ratio even smaller.Thus, in the 1990 Zaebst exposure data, the large OC contentcompared to EC indicates that these workers were exposed tosubstantial amounts of organic carbon particulate matter thatwas not from DE. Applying that finding to the Steenland etal. 1981–1983 worker population, who were employed in atrucking fleet prior to 1984 with a much smaller proportion ofdiesel trucks (compared to 1990), indicates that diesel was notthe primary exposure variable in the Teamster studies. Otherlikely carbon exposures sources in these studies, according toZaebst, would be “gasoline exhaust, sidestream tobacco smoke,diesel fuel, degreasing solvents, and grease and oil. . . . Evenwhere a personal sample was recorded as having been obtainedfrom a nonsmoking employee, those employees invariably spentpart of each shift in a smoke-filled break room” (Zaebst et al.,1991).


TABLE 7Airborne concentrations of elemental carbon (EC) and organic

carbon (OC) in work areas of a trucking terminal in Detroit,MI, winter 2003 (Lee et al., 2005)

Airborne concentrations, µg/m3

Area (job) EC OC EC/TC% PM2.5

Shop (mechanic) 17.4 55 23 83Short-haul (truck driver) 1.8 27 7 42Dock (forklift driver) 1.1 13 7.5 35Long-haul (truck driver) 0.6 17 4 28Yard (hostler) 0.6 8 6 19Office 0.3 15 2 13

Note. Long- and short-haul drivers’ area samples were collectedinside the cab, near the drivers’ breathing zone.

EC, elemental carbon; OC, organic carbon; TC, total carbon (EC +OC).

Findings from a recent study of airborne particulate levels inthe trucking industry parallel the Zaebst et al. DE-exposure dataand confirm the very low EC/TC ratios in this industry, againsuggesting that non-DE particulates dominated the exposures(Lee et al., 2005). Airborne levels of EC, OC, and PM2.5 (fineparticulate matter less than 2.5 µm aerodynamic diameter)were investigated in two Detroit, MI, trucking terminals for5 consecutive days during February 2003. Personal and areasamples were collected for 6 job categories (Table 7). The EClevels for the job categories fell into three groups (arithmeticmeans): Highest level was 17.4 µg/m3 for shop mechanic;intermediate level was 2 µg/m3 for short haul truck driver;low exposures were 0.3–1.1 µg/m3 for dock worker (forkliftoperator), long haul truck driver, yard worker (hostler), andoffice worker. Correlations were observed between levels of OCand PM2.5, but—notably—not between EC and either of the

other two parameters. Smokers’ levels compared to those ofnon-smokers were significantly higher for OC and PM2.5, butnot for EC. The EC concentrations reported by Lee et al. for2003 parallel those reported by Zaebst et al. for 1990, in thatairborne levels of EC for truckers were low and similar to orslightly elevated over background (or office) levels, while EClevels for shop mechanics were significantly elevated over thoseof truckers. Findings from the two studies differed somewhat, inthat mean EC levels in the Lee study were lower for drivers (<2µg/m3) and higher for mechanics (17 µg/m3) compared to theZaebst study (drivers ∼4 µg/m3, mechanics ∼12 µg/m3). TheLee study, like the Zaebst study, found very low EC/TC ratiosof 2% to 23% for these job categories (Table 7).

An exposure assessment at a diesel truck and enginemanufacturing facility illustrates how a small ratio of EC:OCcan indicate that carbon particle exposures are predominantlyof non-DE origin—even in a work area in which one mighteasily presume that the predominant exposure would be DE(Sirianni et al., 2003). Sirianni et al. used NIOSH Method5040 to analyze the carbon content of airborne RPM in twomachining work areas without known diesel exposure (one withhigh oil mist levels and one without oil mist) and one workarea with DE exposure (test cell area; some oil-mist present)(Table 8). All three work areas had very low EC levels. Themachining/oil mist and test cell areas had high OC levels, butthe non-oil-mist area had very low OC. The high OC in the testcell area was presumably a result of the oil mist that was noted inthis area. Sirianni et al. concluded, “These findings demonstratethe capacity for non-diesel organics to overwhelm and obscurethe [relatively low] levels of OC expected from diesel engines.. . . [The] use of OC or TC levels as DPM surrogates is likely tolead to erroneous conclusions about diesel exposure levels.” Inother words, the high levels of OC from non-DE environmentalsources can and often does overwhelm the low levels of OC indiesel. Even though DE does contain OC, there are too many

TABLE 8Trucking industry: Airborne respirable carbon particles in a diesel engine and truck assembly plant, using

data from area air samples collected and analyzed using NIOSH Method 5040 (Sirianni et al., 2003)

Respirable carbon particles, range ofairborne concentrations, µg/m3 Percent of Samples with

Location n Elemental carbon Organic carbon TCa >50 µg/m3 ECb >20 µg/m3

No DEOil mist areac 66 0.05–5.70 10.0–1600 71% 0Non-oil mistc 27 0.38–0.70 14.0–940 63% 0

High DETest cellsd 10 0.50–6.30 55.0–226 100% 0

aTC, total carbon. 50 µg/m3 TC was proposed by ACGIH as the TLV (threshold limit value) in 2000 (ACGIH, 2000).bEC, elemental carbon.cMachining work areas, no diesel equipment; presumed DE-free.dEngine testing area; substantial diesel engine use; presumed DE exposure. Oil mist present.


other sources of OC for the DE-derived OC to be meaningful.Sirianni et al. suggest that the EC:TC ratio for DPM should berelatively high, 35–85%; a lower ratio indicates confounding bynon-DE carbon sources. In the diesel truck plant, the EC/TCratio in each of the three work areas was less than 1%.

Diesel Exhaust Is Not the Only Source of Elemental Carbon.The Steenland studies and risk assessment reflect the underlyingassumption that DE, as measured by EC, represents the greaterpart of PM exposure for truckers. There is substantial evidence,however, that such an assumption is not valid. Other sourcesof EC include gasoline engines, tire and brake wear, stationarycombustion sources, and industrial processes (HEI, 1999). Thecarbonaceous component from gasoline engine exhaust hasbeen reported to contain 20–35% EC (Norbeck et al., 1998).Recently, while investigating the uncertainties in the historicalDE exposure estimates used in the Teamster mortality studies,Bailey et al. also concluded that the proportion of DE relative toother emissions was much lower in these studies than originallyestimated (Bailey et al., 2003). Bailey et al., noted numerousunderlying assumptions in both their own exposure predictionmodel and the model used by Steenland et al. (1998). Two oftheir major assumptions were: (1) EC was used as a markerfor DE exposure based on studies indicating that DPM isprimarily composed of EC and is the primary source of EC; and(2) DPM exposures were assumed to be proportional to dieseltruck emission rates (i.e., the proportion of EC in DPMemissions was assumed to be constant over time) and to thedieselization of the truck fleet. Bailey et al. further suggestedthat gasoline may make a greater contribution to airborne ECthan has been assumed.

Truck Drivers Are Exposed to Both Gasoline and DieselEngine Emissions

In most, if not all, of the epidemiologic studies of trans-portation workers that associate DE with lung cancer, theworkers were exposed to mixed (and inseparable) gasoline anddiesel exhausts, which, evidence suggests, were predominantlygasoline. The truckers drove on highways where most vehicleswere gasoline-fueled. Truck drivers, particularly on highways,are not likely to be exposed to own-truck exhaust emissions,because the exhaust pipe on a diesel truck is above and behindthe driver. Indeed, Zaebst et al. found that EC levels inside thetruck were not significantly elevated over ambient roadside EClevels, but the in-cab OC levels (nonsmokers) were about 8-foldelevated over outdoor levels (Table 5) (Zaebst et al., 1991). Theyconcluded that if truck drivers experience an increased incidenceof cancer as a consequence of diesel exhaust, “It may be becausethey spend more time on the highway and not because the truckthey are driving is exposing them to diesel exhaust.”

In another more recent study, nondetectable to very low levelsof EC were measured inside a diesel-powered school bus testedon an automotive test track (Borak et al., 2003). These findingssuggest that truckers are not likely to be primarily exposed to

emissions from their own vehicles, but are instead exposed toemissions from other on-road vehicles. Since the other onroadvehicles during the Steenland et al. study period (1960–1983)were predominantly gasoline, the truckers were likely exposedpredominantly to gasoline exhaust. Indeed, during the 1960s (thecritical years of the Steenland study from a latency perspective),diesel fuel represented only 4–7% of the total fuel sales (carsand trucks) (HEI, 1999). Moreover, in the 1960s, gasoline-fueledvehicles had no exhaust after-treatment, and quite likely wouldhave contributed as much or more to mobile source air pollutionas diesel vehicles. Accordingly, HEI has cautioned that “the lackof data to reconstruct gasoline exhaust emissions, particularlyfor years earlier than 1990, will significantly limit attempts tocalculate risks from diesel as opposed to other sources, as wellas any epidemiologic study of DE” (HEI, 2000).

In another recent study, Ireson et al., recognizing the lowspecificity of EC for identifying the source of EC-containingparticulate matter, used a fuel-borne tracer (iridium) to estimatethe DPM inside a school bus during normal operation (Iresonet al. 2004). The bus was fueled with iridium-tagged dieselfuel. The mass ratio of DPM:iridium in the bus exhaust wasestablished from emissions tests. Iridium levels were measuredinside the bus during normal operations to estimate the levelsof in-bus DPM that was derived from the bus exhaust. Ireson etal. noted that some previous studies attributed in-bus airbornefine particle concentrations of over 30 µg/m3 to the same bus’sexhaust. In contrast, the Ireson et al., study, using the iridiumtracer (high sensitivity), reported an average DPM concentrationof 0.22 µg/m3 from the same bus’s exhaust, which is about 1%of the previous estimates.

One more observation should be noted in regard to exposuresfrom emissions from diesel versus gasoline engines. Table 6demonstrates that, after 18 or more years of service, short-hauldrivers (i.e., deliveries within a city) had a higher apparentincrease in lung cancer risk than did long-haul drivers (oddsratio of 1.79 versus 1.55, respectively). These smaller trucks,however, were not dieselized until the late 1970s and 1980s(Bunn and Slavin, 2001).

In conclusion, the findings summarized in this section callinto question the categorization of the health effects of dieselexposure based on assessments of the transportation industry,because diesel exposure is likely to be a small part of the overallexposure within this industry.

Inadequate Latency PeriodHEI concluded that the Steenland study quite likely suffers

from an inadequate latency period, making it unsuitable forreaching any qualitative or quantitative conclusions about anassociation between DE exposure and lung cancer (HEI, 1999).Specifically, the Steenland researchers assumed that trucks weredieselized by 1960; the case-control study analyzed lung cancermortality in 1982–1983. However, data submitted to the U.S.EPA suggested that a more accurate date of dieselization is


between 1965 and 1970 for heavy-duty (class 8) trucks andafter 1980 for medium-duty (class 5–7) trucks (Bunn and Slavin,2001). The U.S. EPA, in a reanalysis, then picked 1963 as thedate when 50% of vehicle miles traveled (by commercial trucks)were in diesel vehicles (U.S. EPA, 2002). Given that the latencyperiod for lung cancer is estimated to be at least 15+ years(Peto et al., 1977), the Steenland study (1981–1983 mortalityperiod) did not allow a sufficient latency period if the date ofdieselization was 1970; latency would still be inadequate ifthe dieselization occurred in 1963. The HEI recognized thisproblem, stating that “the latency period may not be sufficientto demonstrate an excess of lung cancer due to diesel exposurefor all workers” (HEI, 1995).

Associations of Gasoline Exhaust Exposure With LungCancer Risk

Crump and coworkers (2000) reanalyzed the data utilizedby Steenland et al. (1998) in their epidemiologic studies oftransportation workers and found a statistically significantrelationship with cumulative gasoline exposure. Crump con-ducted statistical analyses of the long-haul trucker data fromthe Steenland studies to investigate a possible relationshipbetween exposure to gasoline engine exhaust and increasedincidence of lung cancer in this data set (International, 2000;Bunn and Slavin, 2001). Exposures from DE and from gasolineemissions were estimated from 1949 forward, lagged 5 years.For DE exposures, Crump used the original Steenland exposureestimates (Steenland et al., 1998) as well as the U.S. EPAreconstruction of those exposure estimates (U.S. EPA, 2000).For gasoline exposures, Crump used estimates of carbonaceousPM10 emitted from gasoline vehicles in tons per year. Theanalysis then evaluated lung cancer incidence for long-haultruckers against cumulative exposure, while controlling forsmoking, age and asbestos exposure. Cumulative gasolineexhaust exposure, like cumulative DE exposure, showed astatistically significant relationship to increased lung cancerincidence.

Preliminary results from a recently initiated trucking studyshowed that PM exposures were from mobile sources, includinggasoline exhaust, and not diesel exhaust alone (Garshick et al.,2006a). The cohort included 769 lung cancer deaths. Lungcancer standardized mortality ratio (SMR) (95%CI) for long-haul drivers was 1.09 (0.97–1.22), for local drivers was 1.17(1.01–1.37), and for dock workers was 1.11 (0.95–1.31). Theabstract stated: “Cox regression models suggested an increasinglung cancer risk with greater years of employment in workerswith mobile source exposures. Local sources significantlycontributed to terminal exposures, and EC values were similar inlocal and long haul drivers. Lung cancer mortality was elevatedin trucking company workers with regular exposures to PM onloading docks, local roads, and highways and was not relatedto historical differences in operating diesel equipment. Thissuggests that a mix of mobile-source PM from a variety of

sources [including gasoline-powered vehicles] may result in anelevated lung cancer risk.”

In addition, there are a number of older studies in which theincreased lung cancer incidence was confined to populationswho had had, at most, a few years of diesel exposure atthe very end of their professional driving careers. In thesepre-diesel era drivers, it appears that something other thandiesel exhaust in their work or lifestyle was increasing theirlung cancer risk (Table 9). There are seven studies datingback to 1947 that showed a statistically significant increasein lung cancer risk among truckers prior to dieselization ofthe U.S. trucking fleet. Importantly, the U.S. EPA incorrectlyclaimed that a sufficient latency period existed by comparingthe follow-up periods for cancer ascertainment with the dateof dieselization (International, 2000). The workers themselvesneed to be employed during the diesel era for a sufficient latencyperiod to exist. CASAC specifically urged the U.S. EPA to reviseits latency analyses accordingly (CASAC, 2000).

A few of these trucker studies with critical exposure periodsoccurring prior to dieselization are particularly illustrative andwarrant a more in-depth discussion. The Damber and Larssonstudy was a case-referent study of 600 cases of male lung cancerin northern Sweden with a focus on the risk of lung cancer inprofessional drivers (Damber and Larsson, 1985). The studysubjects drove in the most northern part of Sweden, where,according to the study researchers, the air in vehicle cabins islikely to contain unusually high concentrations of combustionproducts. The study showed that drivers over the age of 70 had asignificantly increased risk of lung cancer, but drivers under 70,with similar average duration of employment, had no increasedrisk of lung cancer. The subjects of the Damber study wereall registered as suffering from lung cancer between 1972 and1977. Given that the increased risk of lung cancer was onlyamong those drivers aged 70 and older, the youngest possiblesubject was 63 in 1970. By that point, the majority of driversin the “at-risk” population had either retired or were on theverge of retiring. They did the bulk of their driving well before1970. The critical exposure period for these drivers (≥20 yrprior to lung cancer diagnosis) was, at the latest, 1937–1957,which was well before the advent of dieselization in the truckingindustry. In fact, the critical exposure period might have beenmuch earlier—the subjects were registered between 1972 and1977 and thus might have been diagnosed several years before.Nonetheless, Damber’s subjects who were 70 or older were fivetimes more likely to suffer from lung cancer than the referentsample. A risk ratio of 5.0 is very high in comparison to therisk ratios found in other studies. However, this risk ratio wasobserved exclusively among older drivers while other studies’risk ratios were observed among a combination of older andyounger drivers. Damber’s study found no increased risk oflung cancer among drivers under the age of 70. Therefore, anassessment of Damber’s older and younger drivers would leadto a risk ratio much lower than 5.0 and much closer to the riskratios (1.2–1.6) found in other studies.


TABLE 9Lung cancer in truck drivers prior to dieselization

Risk ratio Risk ratio typeDate of diagnosis

(or death)Critical exposure

perioda Reference

1.49b 1921–1938 1898–1918 (Kennaway and Kennaway, 1947)6.0b,c 1955 1915–1935 (Mills, 1960)1.08 1950 1910–1930 (Enterline and Mckiever, 1963)2.16 SMRb 1966 1926–1946 (Hueper, 1966)1.2 SMRb 1961 1921–1941 (Registrar-General, 1971)1.34 1977 1937–1957 (Williams et al., 1977)1.65 1970–1973 1933–1953 (Menck, 1976)1.21 SMR 1976 1936–1956 (Leupker, 1978)1.29 PMR 1959–1961 1921–1941 (Petersen and Milham, 1980)1.3–1.6 Case-control ratio 1958–1962 1922–1942 (Milne et al., 1983)1.25 RR 1977 1937–1957 (Dubrow and Wegman, 1983)1.18 1950–1979 1939–1959 (Milham, 1983)1.4 RR 1980–1982 1942–1962 (Hall and Wynder, 1984)1.65–1.78 1971–1973 1933–1953 (Dubrow and Wegman, 1984)1.49–1.53 SMR 1954–1974 1934–1954 (Walrath et al., 1985)5.0 RR 1972–1977 1937–1957 (Damber and Larsson, 1987)1.5 OR 1976–1983 1943–1963 (Hayes et al., 1989)

aPeriod during which there must have been DE exposure (or other pollutant exposure) for a sufficient latency period toexist

bStudy subjects were motor vehicle drivers, but not necessarily truck drivers.cStudy compared urban drivers, who drove more than 12,000 miles, to urban drivers, who drove less than 12,000 miles.

Menck relied on death certificates from 1968 to 1970 andincident cases from 1970 to 1973 to assess the relative risk oftruck drivers contracting lung cancer (Menck, 1976). Althoughdata regarding the incident cases were collected in the 1970s,the drivers drove for at most 3 years post-1970. Even for thesedrivers, the critical exposure period was 1933–1953 at the latest.The drivers were 65% more likely to contract lung cancer thanthe general population.

Dubrow and Wegman aggregated the data from 9 surveillancestudies, conducted in Britain and in the United States, todetermine the relative risk of truck drivers contracting lungcancer (Dubrow and Wegman, 1983). The latest data used in thestudy was from 1977. The critical exposure period, therefore,was 1937–1957 at the latest—again, prior to dieselization of thetrucking industry. Upon aggregating the data from the studies,Dubrow found a 25% greater incidence of lung cancer amongtruck drivers than expected in the population at large.

Milham assessed the relative risk of truck drivers contractinglung cancer based on death certificates from between 1950 and1979 (Milham, 1983). Thus, in this study, the critical exposureperiod was 1939–1959 at the latest. The drivers were 18%more likely than the population at large to suffer from lungcancer (proportionate mortality ratio of 1.18). Drivers who diedbetween 1950 and 1959, and for whom the critical exposureperiod was between 1919 and 1939 at the latest, were 52%

more likely than the population at large to suffer from lungcancer (proportionate mortality ratio 1.52).

Hayes assessed the risk of New Jersey, Florida, and Louisianatruck drivers contracting lung cancer (Hayes et al., 1989). Thedrivers were interviewed between 1976 and 1983. Although thedrivers were studied after 1970, the critical exposure period forthem was 1943–1963. Hayes determined that drivers with 10 ormore years of experience were 50% more likely to contract lungcancer than the population at large (odds ratio 1.5).

Summary of On-Road Transportation StudiesIn summary, EC/TC mass ratios suggest that, in addition to

DE, a variety of other agents contribute to exposures in thetrucking industry, including tobacco smoke, gasoline exhaust,solvents and fuel. There is no way to separate the DE exposurefrom other particulate exposures, especially gasoline exposures.Data on dieselization indicate that the truckers studied mayhave been exposed to more gasoline exhaust than dieselexhaust. In addition, at least 17 epidemiologic studies showan increased risk of lung cancer among truck drivers for whomthe critical exposure period occurred before the trucking fleetwas dieselized. These data suggest a significant likelihood thatany increased lung cancer risk in the trucking industry couldbe due to an etiology other than DE. Indeed, unless and until


the factor that caused an increased lung cancer incidence priorto dieselization is identified and controlled for, one cannotproperly conclude that exposure to DE is causally related toan increased incidence of lung cancer in the trucking industry.Moreover, as is apparent from comparing the relative risksfrom the prediesel trucking studies with the postdiesel truckingstudies, there was no increase in relative risk following theadvent of dieselization. There is no plausible explanation forhow DE can be a carcinogen in the trucking population when itdid not increase the risk of cancer after the onset of the dieselera.

Mining Industry Worker EpidemiologyMining Industry and Diesel Exhaust Exposures

If there is an empirical basis for associating DE withlung cancer in humans, this association should appear mostclearly in the underground mining industry, which includesoccupations that undoubtedly have the highest potential for DEexposure. However, while not definitive, underground miningepidemiology studies are generally negative for lung cancer,despite potential confounding in some underground mines byother factors such as radon and silica that would tend to increaselung cancer incidence in the study populations.

There are several reasons why underground mining studiesshould be included in an assessment of the potential lung cancerhazard of DE. First, historical airborne levels of DPM in someunderground mines are quite high compared with airborne levelsfound in other occupational studies of DE-exposed workers,ranging up to two orders of magnitude higher than exposuresreported for truckers and railroad workers (Appendix, TableA-2). Using EC as the indicator of DE exposure, mean or medianairborne levels of 81 to 420 µg/m3 EC have been reportedin underground coal mines. In contrast, mean airborne levelsof approximately 0.4 to 25 µg/m3 EC have been reported fortruckers and railroad workers (MSHA, 2001a). Undergroundcoal mining studies are particularly useful in the DE-versus-lung cancer assessment, in that IARC has evaluated coal miningfor cancer risk (IARC, 1997). However, metal and nonmetalunderground mines have airborne levels of DPM comparable tothe underground coal mines and provide further opportunity forinvestigating DE (MSHA, 2001b).

Second, some nonmetal underground mining operations(e.g., potash mining), like underground coal mining, arerelatively free of potential confounders such as arsenic andradiation, which are more common in underground metal mines.

Third, unlike many of the studies of other DE-associatedoccupations, a number of published and ongoing mining studiesprovide latency periods that are quite sufficient for excess risksfor lung cancer to become detectable, if such risks do indeedexist. To illustrate, some coal mines of Europe and the UnitedKingdom were dieselized more than 60 years ago (Rice andHarris, 1936). Australian coal mines have been dieselized formore than 50 years, providing latency periods that clearly are

also sufficient (Pratt et al., 1997). Underground coal minesin the United States were more recently—and only in someregions—dieselized (MSHA, 1998a, 2001a). In contrast to thelong history of diesel use in underground mining in variousregions of the world, the U.S. railroad and trucking industrieswere gradually dieselized beginning in approximately 1960 and1970, respectively.

Fourth, unlike the railroad and trucking industries in par-ticular, workplace exhaust exposures for miners in Europe andAustralia were basically limited to DE, since very few gasolineengines were used in these mines due to concerns about firesand carbon monoxide emissions. Further, particularly for coalminers, the assortment of DE-exposed and nonexposed the rangeof latencies offer the opportunity for comparisons between thosestudies (i.e., comparisons of DE-exposed miners vs. miners notexposed to DE) as well as with the general populations. For thesecompelling reasons, underground mining studies are much moreuseful than studies of other occupational groups for investigatingthe potential carcinogenic effects of DE.

Overview of Diesel Use in MiningAs noted earlier, the United States lagged behind Europe

and Australia in the introduction of diesel technology in itsunderground mining industry. The European mining communitybegan using diesel engines in significant numbers by the 1930s,and various reports on the subject were published during thatdecade. According to a 1936 summary of these reports (Riceand Harris, 1936), the diesel engine had been introducedinto German mines by 1927. By 1936, diesel engines wereused extensively in coal mines in Germany, France, Belgium,and Great Britain. Diesel engines were also used in potash,iron and other mines in Europe. Their primary use was inlocomotives for hauling material (MSHA, 1998a). The situationwas apparently quite different in the United States: A 1935U.S. Bureau of Mines report on ventilation in metal mines didnot even mention ventilation requirements for diesel-poweredequipment, suggesting that diesel use was so low or nonexistentin the United States that it was not yet of concern. Approximately1300 diesel mine locomotives were reported to be in use inEuropean underground mines as of January 1, 1947 (Harringtonand East, 1947). (For more details on diesel use in the UnitedStates, Europe, and Australia, see Appendix 1.)

IARC Review of Coal Miner Cancer RiskEight years after the publication of their monograph on

diesel exhaust, IARC issued a monograph on the cancer riskfor coal miners (IARC, 1989, 1997). In the 1997 monograph,IARC reviewed studies of coal miners and determined thatevidence was inadequate for the carcinogenicity of coal dust;IARC classified coal dust as Group 3, “cannot be classified asto its carcinogenicity to humans.” This conclusion is deemedimportant in this discussion of diesel for two reasons: (1) Thestudies in the IARC review included coal miner cohorts


of workers who historically inhaled some of the highestoccupational concentrations of total airborne particulates amongall working environments, and (2) as noted earlier, hundredsof underground coal mines, particularly outside the UnitedStates, have used diesel equipment for many decades, exposingthose coal miners to DPM as well as to coal dust. As theU.S. EPA concluded in its Health Assessment Document fordiesel exhaust, “The highest occupational exposures to DPMare for workers in coal and non-coal mines using diesel-poweredequipment” ((U.S. EPA, 2002, p. 2-107).

Because coal miners’ lungs are known to show evidence ofheavy loads of inhaled particulate (leading to noncancer disease,primarily coal miners’ pneumoconiosis, or “black lung”), the1997 IARC analysis of coal miner populations offers theopportunity to evaluate in a human population the combinedeffect of possible “lung overloading” (with coal dust) plusexposure to the highest occupational levels of DPM. Like DPM,the primary constituent of coal dust is carbon. Like DPM, coaldust contains organic carbons, some of which are PAHs. Yet forcoal miners, the occupational group exposed to elevated concen-trations of both coal dust and DPM, the 1997 IARC monographconcluded there was “inadequate evidence” for carcinogenicity.It reasonably follows that the IARC conclusion on coal minersis consistent with a lack of carcinogenicity for DPM.

Strengths and Weaknesses of Underground Mining Studiesfor DE Evaluation

In reviewing underground mining studies, it should be keptin mind that they are not definitive, either collectively orindividually, for an assessment of possible lung cancer risk fromDE exposure. The strengths and weaknesses of epidemiologicstudies depend on a number of factors. For example, most ofthe studies of interest here were not undertaken to investigatepossible associations between DE exposures and lung cancer.Therefore, a study that might be considered very informative forrisks associated with coal dust may provide more limited insightfor DE. Unlike controlled laboratory experiments, epidemiologyis an observational science; researchers can only observe whatis happening or has happened—they cannot control or alter therelevant factors. For example, it is well known that blue-collarworkers, as a group, tend to smoke cigarettes more than thegeneral population (i.e., a greater percentage of blue-collarworkers smoke and often start younger). If such is the casewith a particular cohort, the workers would likely have anelevated lung cancer risk, and the associated risk would havenothing to do with their working environment. Alternatively,if for some reason, perhaps simply by chance, one part of aworkforce smokes less than another part, by comparing thetwo groups it would be more difficult to detect an excessrisk of lung cancer among the lesser smoking group merelybecause the underlying lung cancer risks in the two groups arenot similar. Such “confounding” can result in seeming risksthat are superficial or mask risks that are real. Particularly in

investigating lung cancer, smoking patterns can be extremelyimportant. There is reliable evidence that underground miners insome studies do, in fact, smoke more than the general population(Goldman, 1965; Waxweiler et al., 1973; Morfeld et al., 1997).

In commenting on the ability of epidemiologic studies todetect risks, Monson concluded that at one extreme, “if thetrue association between exposure and disease is very weak,the detection of such an association by non-experimental datais unlikely” and at the other, “if the true association betweenexposure and disease is very strong, no epidemiologic expertiseis necessary to detect it” (Monson, 1990). Monson’s guidelinesfor strength of positive association, that he described as “totallyempiric and based on experience,” ranged: 1.0 to 1.2 (i.e., up toa 20 percent increase in risk), “none”; 1.2 to 1.5, “weak”; 1.5 to3.0, “moderate”, 3.0 to 10.0, “strong”; and >10.0, “infinite.”While such subjective guidelines predictably differ betweenresearchers, they are given here to caution interpretation of weakassociations, even if statistically significant, or, conversely, sug-gested strong associations, even if not statistically significant.

What is a pragmatic minimum latency for epidemiologicstudies of lung cancer (period of time from first exposure to thecarcinogen until detection of lung cancer)? Depending on thecarcinogen and the levels of exposure, a few cases may developas soon as 10 years, with the excess risk of developing the diseasecontinuing to increase for a further 20 years and possibly longer(Doll and Peto, 1981; HEI, 1999). However, for the excess lungcancer risk to reach a level that can be effectively detectedusing epidemiologic techniques, at least 15 years should beconsidered a minimum latency period, with perhaps 20 yearsfulfilling the criteria best. With the power of studies dependenton such factors as the intensity of exposure(s), the duration ofexposure(s), the size of the cohort, etc., no one latency period isapplicable in all situations, but 15 is considered here to be at thelow end for a pragmatic minimum latency, with 20 years betteryet. Another important consideration in evaluating studies is thedetail of the characterization of DE exposures. It can range fromthe minimum of just knowing who worked in the mine to fullknowledge of dates, individual job assignments, and estimatesof actual airborne levels, enabling estimates of exposure for allindividuals. The likelihood that a study will actually find a risk,if in fact it exists, is referred to as the power of a study. Thepower is influenced by many factors, including the number ofworkers being studied, the magnitude of the risk, availabilityof work histories, exposure estimates, potential confounders,detailed knowledge of potential confounders, possible healthyworker effects, use of personal protective equipment, and others.With regard to DE, essentially all of the studies cited here haveweaknesses related to these factors.

A Look at Several Underground Mining Studies With LikelyDE Exposure

Atuhaire et al., reported a study of coal miners in the RhondaFach valley in South Wales; this study was included in the


IARC review of coal mining (Atuhaire et al., 1985). The cohortwas originally defined in 1950–1951 to study an entire miningcommunity (2139 nonminers and 6387 miners and ex-miners)regarding progressive massive fibrosis (PMF) as it relates topneumoconiosis and tuberculosis, so it is an example of agroup of workers originally identified to look at morbidity,not mortality. Subsequently the records were used to trace themortality of those miners as it relates to their work in the coalmines. We are now trying to glean something from this studyrelating to possible DE associations with lung cancer, becauseof the possibility or likelihood that some of the miners wereexposed to DE. Several mines in the valley operated duringthe period of rapid dieselization after 1947, but no specificinformation on DE exposure has been found on those mines.DE exposure is believed likely for at least some of the cohort,and the latency period could have been over 30 years, from thelate 1940s to 1980. For the period 1950–1980 the SMR for lungcancer deaths was 70.0 for nonminers (43 deaths) and 77.6 forminers and ex-miners (191 deaths). The SMR for all deaths was99.0 for nonminers and 128 for miners and ex-miners. Thus,while information specific to DE is lacking, the study does notsuggest an increased risk of lung cancer.

An earlier study by Goldman, also in the IARC review,reported on the lung cancer deaths among miners and ex-minersemployed by the National Coal Board (England and Wales)in 1955 (Goldman, 1965). It is considered unlikely that manyof the miners and ex-miners would have had sufficient latencyfrom DE exposure, since rapid dieselization took place after1947. Regarding smoking, it was reported that there was “muchevidence that the cigarette consumption of miners at least equalsthat of men in other occupations.” The SMR for lung cancer was70.1 for underground miners (216 lung cancer deaths) and 91.5for surface miners (54 lung cancer deaths). The lung cancer risksfor miners in the studies of Atuhaire et al., (1985) and Goldman(1965) appear similar.

Consider another study of coal miners, this one in theNetherlands, reported by Swaen et al. (1995). As with theAtuhaire et al. cohort, this cohort was originally identifiedduring surveys of respiratory health during the 1950s. All 3790in the cohort were identified as having radiological signs ofrespiratory disease. All workers in the study were followed formortality through 1991. All members of the cohort had at least10 years underground (90.5% had 20 or more years) at thetime of their survey in the 1950s. Coal production remainedhigh in the Netherlands through the late 1960s and stopped by1975. DE exposure is judged likely for at least many in thecohort because: By 1936 diesel engines were used extensivelyin coal mines in Germany and Belgium; the coal mining regionin the Netherlands was near Germany and Belgium; and thereare pictures of diesel engines underground in the Netherlandsfrom the 1940s. Here again the latency for those exposed toDE is certainly sufficient, even though details on the exposureare lacking. The SMR for all causes is 127 (2941 deaths), withthe excess essentially due to nonmalignant respiratory disease

(NMRD). The SMR for lung cancer is 102, based on 272 lungcancer deaths.

Morfeld et al., reported on the mortality of German coalminers; this study was reported after the IARC review (Morfeldet al., 1997). The cohort of 4628 was originally recruited for apneumoconiosis study. All worked at least 5 years undergroundduring 1963–1977 and the cohort was followed for 12 years from1980 through 1991. DE exposure is considered very likely; theminers had an average of 29 years underground. The minimumlatency would have been 19 years at the end of the 1991 andranged from 5 to 59 during follow-up. Smoking was reported tobe higher among miners (50%) than the general male population(33%) in the Saar area. The SMR for all deaths was 63 (317deaths) and the SMR for lung cancer was 70 (41 deaths). Theauthors concluded there was “no indication of an increasedcancer or lung cancer risk in coal miners.” The power in thisstudy is modest and the authors noted the need for additionalfollow-up and analysis. Once again, the intent of the researcherswas to investigate the risk of lung cancer and coal mine dust, notDE. However, with the likelihood of DE exposure, the findingsare consistent with no increase in risk because of DE exposure.

Waxweiler et al. reported on a study of underground potashminers from 8 New Mexico mines (Waxweiler et al., 1973). Thecohort consisted of 2,743 men with 1 year or more undergroundand less than 1 year at surface between 1940 and 1967, and1143 men with 1 year or more at surface and less than 1year underground. There was dieselization in some mines inthe early 1950s, so for miners from those mines latency wouldrange from none to 17 years. Lung cancer SMRs were 112(10 deaths) and 108 (12 deaths) for surface and undergroundworkers, respectively. In this study the power is, of course, low.Also, there is a possibility of a healthy worker effect, since newminers were added to the cohort as they reached the threshold forinclusion. Nevertheless, with smoking rates among the minersreported to have been higher than for all U.S. males, the findingsare consistent with no increased risk.

The Institute of Occupational Medicine (IOM) conductedan evaluation of a cohort of 18,166 colliers (coal miners) whowere employed in British underground coal mines between theearly 1950s to the mid-1980s (Johnston et al., 1997). Acrossall collieries (coal mines), a weak association between DEexposure and lung cancer risk was found (relative risk [RR] =1.23, 95% confidence interval [CI] 1.00–1.50), but aftercorrection for overall differences in the collieries, the associationdiminished (RR = 1.16, 95% CI 0.90–1.49), and no associationwas found among men with different DE exposures working inthe same colliery. In other words, groups of workers withinthe same colliery that had different levels of DE exposurehad the same relative risks for lung cancer. Moreover, thecolliery with the highest lung-cancer mortality rate also hadhigher exposures to respirable quartz and low-level radiation.The authors concluded: (a) “It is entirely plausible that anysuggestion of a relationship between cancer death and dieselexhaust exposure can be explained by different practices and/or


environmental conditions among the ten collieries in this study”and (b) “The findings of the current study suggest that currenturban exposure concentrations for diesel exhaust particulate areunlikely to result in significantly elevated risks of lung cancer.”

These examples of studies of underground miners illustratethe broad range of factors such as likelihood of DE exposure,latency periods, study sizes, and smoking history that makea review of mining experience important to the investigationof DE health effects. The discussion here is not intended tobe complete, but simply to illustrate that underground miningstudies are potentially much more useful for risk assessmentof DE than studies of other occupational groups. Furthermore,while certainly not definitive, they provide no convincingevidence of a risk of lung cancer associated with DE, andgenerally are consistent with no risk. The studies discussedabove are included, along with a number of other studies, manyfrom the IARC review, in the Appendix, Tables A-2 and A-3.

Perusal of Table A-3 shows that almost all of the studiesreported empirical measures of lung cancer risk (e.g., SMRsand ORs) within or below the ranges of “none” and “weak”noted earlier. The only exception is the study by Saverin et al.,(1999). While other elevated RRs were given, the RR of 1.7was considered the principal finding by the authors. However,the numbers in this study are modest, and the broad range forthe confidence interval clearly shows the statistical uncertainty.As Saverin et al., cautioned, “the observed elevation is non-significant even at a 90% level.” Thus, as with the examplesdiscussed in more detail here, even with DE exposures that werean order of magnitude higher than those in either the truckingor railroad industries studies, the mining studies summarized inTable A-3 are, on balance, consistent with no detectable increasein risk.

Meta-Analyses of the Diesel Exhaust EpidemiologicDatabase

The epidemiologic database for DE has undergone two majormeta-analyses that were conducted to evaluate the relationshipbetween occupational exposure to DE and lung cancer incidence(Bhatia et al., 1998; Lipsett and Campleman, 1999). Bhatiaet al. (1998) evaluated 29 DE epidemiologic studies and selected23 that complied with their criteria for inclusion in theirmeta-analysis. They defined exposure to DE as work in anindustry in which diesel engines (vehicles or equipment) wereused. They included studies of truckers, railroad workers, busdrivers, other professional drivers, equipment operators, andmechanics. However, they excluded from their analysis studiesof miners, due to the potential for exposure to multiple airbornesubstances in this industry. Ten of the 23 studies controlledfor smoking, and 13 did not. The investigators chose 10 yearsas a minimum latency interval from first exposure to end offollow-up; if at least some of the workers in the study hadexperienced their first exposure 10 years or more prior tofollow-up, then the study was included. Bhatia et al. reporteda lung cancer relative risk of about 1.33 for all 29 studies

combined and for several subcategories of studies (e.g., studieswith adjustments for smoking vs. studies without adjustmentsfor smoking, case-control vs. cohort, internal referent groupvs. external referent group). Relative risks for individual jobcategories ranged from a low of 1.11 for equipment operatorsto a high of 1.49 for truck drivers. The investigators concludedthat their meta-analysis “supports a causal association betweenincreased risks for lung cancer and exposure to diesel exhaust.”

Lipsett and Campleman (1999) also conducted a meta-analysis of epidemiologic studies to investigate associationsbetween occupational DE exposure and lung cancer incidence.Their analysis included many of the same studies as thoseincluded in the Bhatia et al. analysis, and, like Bhatia et al.they excluded studies of miners. Lipsett and Campleman alsoreported increased relative risks for lung cancer of about 1.33when data for all studies were pooled or were grouped intovarious subcategories.

Both Bhatia et al. (1998) and Lipsett and Campleman (1999)concluded that their meta-analyses of the epidemiologic studiessupported a causal relationship between occupational exposureto DE and increased incidence in lung cancer. However, ameta-analysis is only as strong as the data on which it isbased. In the case of DE, the existing epidemiological databasehas important limitations, among which can be inadequate orabsent controls for tobacco smoking, inadequate latency forthe development of lung cancer among some or all of thestudy subjects, lack of direct quantitative data to confirm DEexposure, and lack of consistent evidence of a dose-responserelationship. Silverman (1998) notes three main concerns aboutthe epidemiologic evidence: The magnitude of effect in moststudies is low (reported RRs were generally under 1.5); of the30 studies that investigated associations between DE and lungcancer, only two (truckers and railroad workers) (Steenlandet al., 1998; Garshick et al., 2004) had quantitative data onwhich to base their estimates of historical exposure (Silverman,1998; and. In these studies, exposures for past time periods wereestimated from more contemporary data collected well after thestudy time periods.

Given the strong association between smoking and lungcancer, failure to control adequately for smoking can causesignificant confounding of the results in the DE epidemiologicstudies. For example, Stober et al. (1998) found that of the sevenepidemiologic studies of truckers cited in Bhatia et al. (1998);four made no adjustment for smoking, even though 78% of truckdrivers in the United States reportedly smoke (Stober and Abel,1996). Of the 29 studies included in the Bhatia analysis, theinvestigators listed 16 as having no adjustments for smoking.Of the 35 studies cited in the Bhatia paper (including 6 thatwere excluded from their meta-analysis), 17 did not control forsmoking (Silverman, 1998). Similarly, in the analysis by Lipsettand Campleman (1999); 19 of the 30 studies were listed as notcontrolling for smoking. Further, both of these meta-analysesrelied predominantly on studies in the trucking industry, inwhich latency periods were inadequate, that is, many or all


of the study subjects’ initial exposure to DE was less than 20years prior to the follow-up date (Raffle, 1957; Menck, 1976;Williams et al., 1977; Ahlberg et al., 1981; Howe et al., 1983;Rushton et al., 1983; Coggon et al., 1984; Buiatti et al., 1985;Gustafsson et al., 1986; Damber and Larsson 1987; Siemiatyckiet al., 1988; Swanson et al., 1993).

Another important item to note is the fact that 17 of the studiescited by Bhatia and 19 of the studies cited by Lipsett/Camplemaninvolved transportation workers (truck and bus drivers andmechanics). However, as discussed earlier in the present review,there was an increased relative risk of lung cancer among truckdrivers before there were diesel trucks (Table 9). A reanalysisof the Teamster studies data also demonstrated increased lungcancer incidence in truckers prior to dieselization (Crump, 2000)(see earlier discussion of Steenland et al., 1998). The cause ofthat pre-dieselization elevation in risk has never been identified;consequently, investigators have not been able to install controlsin the DE epidemiologic for this unidentified cause.

The lack of dose-response findings in the DE epidemiologicdatabase further suggests that the lung cancer relative risksderived by the Bhatia et al. and Lipsett/Campleman analysescould be related to lifestyle or other exposures of theseoccupational populations rather than to DE. Once again, it isimportant to return to the fact that all of the existing positiveepidemiological studies show a consistent, relatively weakincreased risk, while the estimated exposure levels of DE in thesestudies vary substantially for the different worker categories.There is a lack of dose-response even within occupations.Valberg and Watson compared reported lung cancer risks withestimated DPM exposures for a number of epidemiologicstudies, some of which were included in the Bhatia et al.(1998) meta-analyses (Valberg and Watson 2000). They foundthat estimates of exposures for these occupations fell into threeoverlapping groups:

Truck drivers, dock workers, train crews, 5–100 µg/m3.Bus garage workers, railroad shop workers, and railroad

hostlers, 50–700 µg/m3.Underground miners, 500–2000 µg/m3.

In their meta-analysis, Bhatia et al. (1998) found an overallrelative risk value of 1.33, with a range from 1.11 to 1.49 inthe subanalysis by occupation. Valberg and Watson pointedout that, if DE were causally increasing lung-cancer risk by50% for low-exposure occupations (e.g., truck drivers, RR =1.49), then the lung-cancer risk in a more heavily exposedpopulation (e.g., railroad shop workers) should be much higher.However, the shop workers experienced an RR of around 1.0(Crump, 1999; HEI, 1999). Similarly, the added lung-cancerrisk for bus garage workers (RR = 1.24) was half that of truckdrivers, but DPM concentrations were considerably higher forgarage workers (ACGIH, 2000). The occupations in the studiesanalyzed by Bhatia et al. (1998) encompassed approximatelytwo orders of magnitude difference in potential diesel-exhaustexposure, yet, the epidemiologic relative risks clustered in a

narrow range. Valberg and Watson concluded that such a lack ofconcordance between reported lung-cancer risk and estimatedexposure argues against a causal role for diesel exhaust in theepidemiologic associations; the interpretation of this lack ofconcordance remains uncertain because of the epidemiologicstudies lacked concurrent exposure data.

In regard to the epidemiologic studies on DE, Silvermanconcluded, “The repeated finding of small effects, coupledwith the absence of quantitative data on historical exposure,precludes a causal interpretation. To establish causality willrequire well designed epidemiologic studies that do not sufferfrom the weaknesses of previous studies.” Specifically, sherecommended large cohorts of heavily exposed workers withadequate latency for lung cancer and quantitative exposure data.She further concluded, “Underground miners may, in fact, be themost attractive group for study because their exposure to dieselexhaust is at least five times greater than that of previouslystudied occupational groups.”

Indeed, if the increased relative risks of lung cancer reportedfor truck drivers and train crews were caused by DE exposure,then the highest incidence of lung cancer should appear in anoccupation that has the potential for even higher DE exposures,that is, underground mining, which has not been demonstratedby the data to date. As discussed earlier, even though miners’estimated exposures can be as much as two orders of magnitudehigher than truck drivers or railroad workers, miners haveactually shown slightly lower lung cancer risks than these otheroccupations (Table A-3) (Valberg and Watson, 2000).

Notably, the meta-analyses do not take into account the factthat lung cancer rates are elevated in a number of non-DE-exposed occupations. For example, the analysis by Bruske-Hohlfeld et al. (2000) demonstrated that, even after adjustmentfor smoking and potential asbestos exposure, an elevatedodds ratio for lung cancer excess was statistically significantin a wide variety of occupations: farmers; forestry workers,fishermen, and livestock workers; miners and quarrymen;chemical processors; cabinetmakers and related woodworkers;metal producers and processors; bricklayers and carpenters;road construction workers, pipe layers, and well diggers;plasterers, insulators, and upholsterers; painters and lacquerers;stationary engine and heavy equipment operators; transportworkers and freight handlers; and service workers. Althoughsome of these occupations have the potential for DE exposure,the fact that a lung cancer elevation was found in such abroad range of occupations suggests that a common failing ofoccupational studies is incomplete adjustment for confoundingby cigarette smoking, as well as insufficient latency periods.As Bruske-Hohlfeld et al. point out, “Cohort studies usuallydo not provide information on smoking detailed enough toallow for accurate adjustment in the analysis.” This finding isvery similar to the HEI conclusion that confounding factors(e.g., lifestyle) are more likely responsible for the elevatedlung cancer odds ratios reported in the railroad worker studies,rather than DE exposure (HEI, 1999). In an earlier publication


(accepted for publication a month earlier, but published a yearearlier), Bruske-Hohlfeld et al. (1999) used the same pooledcase-control study to investigate only workers exposed to dieselmotor emissions. The odds ratio for workers exposed to DE,adjusted for smoking and asbestos exposure, was reported as1.43 in both papers. However, the earlier publication went intomore detail on occupations with exposure to DE. The authorsnoted “a weakness of the study lies in the limited exposureassessment available.”

In sum, meta-analyses are only as strong as the studies onwhich they are based. In the DE epidemiologic database, thecurrently available data do not constitute an adequate basis formeta-analyses in lieu of a detailed and critical review of theindividual studies on DE versus lung cancer incidence.

Evaluation of the Epidemiological Database Usingthe Hill Criteria

The Hill criteria constitute a systematic approach forevaluating causality when an association has been observed inepidemiologic studies. These criteria were originally identifiedby the noted British medical statistician, Austin Bradford Hill,in his landmark 1965 paper (Hill, 1965), and have since becomea basic tool of epidemiological research. The nine Hill Criteriaare listed and defined in Appendix 2 of this work.

In his comments on the U.S. EPA draft HAD for DE, Dr.Sverre Vedal (a member of the Clean Air Scientific AdvisoryCommittee, CASAC) found that the DE database satisfied fewof the Hill criteria (CASAC, 1999). A closer look at the firstsix of the criteria with regard to the DE database supports thisfinding.

1. The “temporality” criterion appears to be satisfied in theDE epidemiologic studies because DE exposures occurredprior to the onset of lung cancer. In most of the DE studies,the latency period is barely adequate or of questionableadequacy for the reliable detection of an increased risk,if such a risk exists. The latency period in the Teamsterstudies, for example, would be about 22 years if the date ofdieselization of the trucking fleet had been 1959 as assumedby the researchers; if the more likely date for dieselization of1970 is used, the latency period in this study would be only11 years, which is clearly insufficient.

2. The “strength of association” between diesel and lung canceris weak, given that the magnitude of the observed lung cancerincrease is relatively small. In the DE database, the relativerisks have been generally 1.2–1.4 with a few instances of2.0 (see tables in IARC, 1997, and U.S. EPA 2002). Theweak statistical associations, combined with the existenceof several negative as well as statistically nonsignificantstudies, and the potential for residual confounding fromcigarette smoking and other exposures, all undermine theoverall strength of the association.

3. The DE epidemiologic studies do not show a “dose-responserelationship” or “biological gradient,” in that similar lung

cancer increases were seen across many different populationswith a wide range of exposure levels. The estimated levelsto which the different types of workers were exposedvaried dramatically (Table A-3). For example, the estimatedexposures of truck drivers were an order of magnitude lowerthan those of railroad repair workers and train crews, and twoorders of magnitude lower than exposures of mine workers,yet similar relative lung cancer risk estimates have beenreported for all of these workers. Actually, miners haveshown slightly lower risks than truck drivers or railroadworkers. The fact that risk levels are not substantially higheramong miners, whose estimated exposures are more thantwo orders of magnitude higher than the truckers,’ does notsupport a finding of a biological gradient. Commenting on thenearly 100-fold range of DPM exposures among the variousoccupational categories, Valberg and Watson noted that “theepidemiologic relative risks cluster in a narrow range,” which“argues against a cause and effect relationship” (Valberg andWatson, 2000).

4. “Consistency”: In the DE epidemiologic database, studiesconducted in several industries and occupations have con-sistently reported the same effect, that is, a small elevationin lung cancer risk for those working in occupations withpotential DE exposure. However, in its Proposed Guidelinesfor Carcinogenic Risk Assessment, the U.S. EPA notes thatconsistency across study results is strong evidence for acausal interpretation “when the same bias or confoundingis not also duplicated across studies” (U.S. EPA 1996).As pointed out in previous sections of this article, residualconfounding from smoking very likely exists in many of theDE epidemiologic studies. Stober and Abel (1996) noted,“Occupations with a high exposure to diesel exhaust aremainly manual ones where smoking is highly prevalentamong the workers.” They reported that 78% of truckdrivers smoked, which was much higher than the rate in thegeneral population. Likewise, railroad workers have beenreported to have one of the highest rates of smoking ofany occupation, slightly over 80% (Morgan et al., 1997).Thus, the consistency among the studies is not strong (aweak or modest association reported only for some butnot all DE-exposed occupations), and possible residualconfounding from tobacco smoking further weakens the casefor consistency.

5. The case for the “biological plausibility” of a causalrelationship between DE exposure and lung cancer hasincluded the following: DE caused lung tumors in rats; DEcontains mutagenic compounds; and DE contains particulatematter consisting of a carbon core with surface layers oforganic compounds that include known mutagens. At thistime, the lung cancer in rats is viewed with caution, becausethis effect was observed consistently only in rats (not in miceor hamsters) and only with chronic exposure to extremelyhigh DE doses (orders of magnitude greater than humanexposures). The rat lung tumors are now generally accepted


to be a result of lung overload and a nonspecific inflammatoryparticle effect unique to rats and not relevant to humans.While diesel exhaust does contain compounds known tobe mutagenic and potentially carcinogenic (e.g., PAHs), itappears that those compounds are tightly adsorbed to thecarbon core. Negative mutagenicity data on whole diesel ex-haust particulate suggest that these compounds are not likelyto be bioavailable. (For more details on studies of animalsand cells, see previous sections in this article.) Moreover,the large body of negative animal studies (with the exceptionof rat data that involve a rat-specific threshold mechanism)undermines arguments for the biological plausibility of anassociation between DE and lung cancer.

6. The “specificity” of the cancers seen in these studies isnot a persuasive factor since no other outcomes (i.e., typesof cancers) were systematically evaluated. Lung cancer isa relatively common disease that can be caused by manypossible agents (not the least of which is smoking), makingit one of the least specific tumors in terms of attributingcausality. Thus, in the case of the DE database, the specificitycriterion does not provide any particular support for causality.

Overall, a hypothesis for a cause-and-effect relationshipbetween DE and lung cancer does not gain much support fromthe Hill criteria. The only Hill criterion that clearly is met by thediesel epidemiologic database is temporality, in that some, butnot all, of the positive studies include an adequate latency period.Evidence in support of biological plausibility and consistency isat best equivocal; only small risk ratios have been reported, andthus the current data suggest only a modest or weak association;no biological gradient has been demonstrated; and specificity isof little relevance in this case in that the effect (lung cancer) canresult from a number of different agents.

Conclusions on Epidemiologic StudiesA number of recent reevaluations of the DE epidemiologic

data have concluded that existing epidemiological studies areunable to predict potential human health effects from exposureto DE or to link DE to increases in lung cancer (Muscat andWynder, 1995; Stober and Abel, 1996; Cox, 1997; Morgan et al.,1997). There are several factors that lead to this conclusion:(1) Many, if not most, of the DE epidemiologic studies sufferfrom inadequate latency periods; (2) of the positive studies,only weak associations are seen and those could be attributableto residual confounding (particularly by smoking); (3) theepidemiologic database is inconsistent and inconclusive, witha few studies showing a weak association between DE exposureand lung cancer and other studies showing no association;(4) there is no exposure-response relationship in most studies,with some studies even showing negative dose response;(5) given the negative mutagenicity data on whole DE anda negative animal database for carcinogenicity, biologicalplausibility is questionable; and (6) the epidemiological studies

lack adequate exposure information regarding DE particulate,without which the relevance of the human studies is unknown.

CHANGES IN DIESEL EXHAUST COMPOSITIONThe existing epidemiologic and toxicologic databases on DE

address predominantly or only pre-1988 TDE. Over the past18 years, major changes have occurred in diesel technologywhich have resulted in very significant quantitative and qual-itative changes in engine emissions, noteworthy of which aremajor reductions in emitted DPM, nitrogen oxides, and othercomponents (Fig. 1–4). Thus, past research does not provideaccurate information for assessments of human health effectsthat might be associated with current and future exposures todiesel exhaust. The paragraphs that follow summarize the majoradvances in diesel technology over the past 18 years and theresultant dramatic changes in diesel exhaust composition. Asdiscussed next; the physical and chemical characteristics ofNTDE are closer to those of compressed natural gas (CNG)emissions than to TDE. Thus, NTDE should be evaluated forhuman health effects independently from TDE.

To comply with the 2007 emissions standards, the dieselindustry has developed NTD engines, which consist of an inte-grated system of advanced engine design, ultra-low-sulfur (<15ppm) fuel, specialized lubricants, and a catalyzed particulatetrap filter (International, 2002). New technology diesel has beensummarized elsewhere (Hesterberg et al., 2005). NTD engineshave been developed to be introduced into the marketplace by2007. Emissions from current diesel engines manufactured after1994 can be dramatically reduced by retrofitting the engineswith the new catalyzed particulate filters and running them onultra-low-sulfur fuel. Other than higher NOx levels, emissionsfrom these retrofitted engines are very close to NTDE. Severalthousand retrofitted diesel engines (e.g., school buses) have beenintroduced into limited markets where the fleets operate closeto a common fueling point and ultra-low-sulfur diesel fuel isavailable.

Advances in diesel technology by 2007 are far-reaching, tothe extent that NTDE does not resemble TDE, which werethe emissions evaluated in all published chronic inhalation andepidemiologic studies of DE. In fact, emissions from NTD are asclean as or cleaner than emissions from engines fueled by eithergasoline (Ahlvik, 2002) or CNG (Ullman et al., 2003) (Tables1 and 2). By 2010, U.S. heavy-duty diesel engine emissionstandards (on a per-mile basis) will have dropped 99% for bothoxides of nitrogen and particulate matter (Figs. 1 and 2) (U.S.EPA, 2002).

Changes in fuel composition and the introduction of exhaustafter-treatment filters have led to qualitative and quantitativechanges in the composition of diesel exhaust, as seen inFigs. 3 and 4. Compared to the emissions from a 2001transitional diesel engine, NTDE shows a large drop in thetotal quantity of both low and high molecular weight PAHs,as well as large differences in the proportions of each ofthe different PAHs—many of them are no longer detectable.


Mandated changes in California diesel fuel produced largedrops in the emissions of total polycyclic aromatic hy-drocarbons (PAH) as well as specific compounds, such asphenanthrene, methylphenanthrenes, methylanthracenes, and2,3,5-trimethylnaphthalene (Norbeck et al., 1998). Furthermore,ultra-low-sulfur (<15 ppm) and low-aromatic (4%) diesel fuelproduced additional decreases in PAHs (Lev-On et al., 2002a).These quantitative and qualitative changes in emissions wouldbe even greater if NTDE were compared with TDE.

Examples of qualitative and quantitative differences betweenNTDE and transitional diesel engine exhaust (from engines builtbetween 1988 and 2006) are striking, as seen here (see also Figs.3 and 4):

Low molecular weight (MW) PAHs in diesel exhaustNaphthalene

NTDE69 µg/mile

(∼ 90% of the low-MW PAHs)

Transitional DE730 µg/mile

(∼25% of the low-MW PAHs)

2-MethylnaphthaleneNTDE

3.1 µg/mile(4% of the low-MW PAHs)

Transitional DE1200 µg/mile

(43% of the low-MW PAHs)

High-molecular-weight (MW) PAHs in diesel exhaustBenzo[a]anthracene

NTDE0.08 µg/mile

(> 50% of high-MW PAHs)

Transitional DE1.1 µg/mile

(∼10% of high-MW PAHs)

ChryseneNTDE

0.00003 µg/mile(0.02% of high-MW PAHs)

Transitional DE2.4 µg/mile

(29% of high-MW PAHs)

Studies have shown that the combination of ultra-low-sulfurfuels with the new after treatment (used in NTD-type engines)systems produce diesel emissions that are much lower thantransitional diesel (1988–2006) and that compare very favorablywith emissions from CNG, typically considered to be “cleanburning” (Gragg, 1995b; Ayala et al., 2002; Lev-On et al., 2002a,2002b; Lanni et al., 2003; Ullman et al., 2003). Continuouslyregenerating traps with oxidation catalysts significantly reduceor eliminate particulate matter, carbon monoxide and volatilehydrocarbons to levels that are lower than those found with CNG(Table 1). Also total PAH and semivolatile PAH levels weremuch lower in diesels with traps (particulate-filtered diesel)compared to diesels without traps or to CNG emissions (Gragg,1995a, 1995b, 2001; Lev-On et al., 2002a; Okamoto et al., 2002,2006; Lanni et al., 2003; Ullman et al., 2003; Kado et al., 2005).

In fact, the PAH composition of particulate-filtered diesel ismore similar to CNG emissions than pre-1994 diesel emissions.Further, a study comparing the emissions of diesel-fueled schoolbuses to those fueled by CNG found that CNG exhaust hadhigher levels of six toxic air contaminants (TACs) listed by theCalifornia Air Resources Board than particulate-filtered diesel,and CNG did not have lower levels of any TAC (Table 2) (Ullmanet al., 2003).

A recent short-term inhalation study in mice illustratesthe differences between standard diesel technology and newdiesel emissions reduction technology (McDonald et al., 2004c).Although this study does not address carcinogenicity, it isincluded in this review because it demonstrates importantdifferences between the respective emissions of old and newdiesel technologies. McDonald et al. compared lung toxicityof emissions from two diesel engine configurations: (1) adiesel engine powered by standard diesel fuel and lackingafter treatment, and (2) the same diesel engine running onultra-low-sulfur fuel and fitted with a catalyzed particle trap.The studies were conducted serially using a small (0.65-L)diesel-powered generator (5500-W single cylinder). The enginewas operated identically in both cases, and the inhalationexposures were diluted at the same ratio of 1:620 exhaustto air. Particulate concentration in standard engine emissionswas 200 µg/m3. However, when the engine was fitted with atrap filter and run on ultra-low-sulfur fuel, particulate matteras well as most other emissions components (except nitrogenoxides, NOx) were near background levels. Mice (C57Bl/6)were exposed to emissions by inhalation for 6 h/d for 1week and then assessed for resistance to respiratory viralinfection, lung inflammation, and oxidative stress. Comparedto air controls, DE without emissions reduction technologyproduced statistically significant elevations in all three toxicityparameters in the mice. However, the use of ultra-low-sulfurfuel and a catalyzed particle trap either completely or nearlyeliminated the three effects. Thus, in this short-term inhalationstudy, diesel emissions reduction technology (ultra-low-sulfurfuel and catalyzed particle trap) was effective in mitigatingthese noncarcinogenic pulmonary effects in mice. This studydemonstrates the significant differences in biological impactbetween emissions from uncontrolled diesel engines versusdiesel engines with emissions reduction technology.

In summary, over the past several years, the compositionof DE has changed both quantitatively and qualitatively to theextent that NTDE hardly resembles TDE. NTDE is now morecomparable to CNG exhaust than to TDE. Given the dramaticchanges in diesel emissions composition, new toxicologic andepidemiologic research should focus more on NTDE exposures,to begin developing a health effects database upon which thisnew technology can be evaluated. Clearly, when evaluatingpossible health effects of engine emissions, it is importantto make a clear distinction between NTDE and TDE. In1989, IARC evaluated the evidence for the carcinogenicity ofTDE. The numerous studies conducted on this topic since that


evaluation suggest that it would be appropriate for IARCto consider reevaluating TDE. Furthermore, the dramaticdifferences in the physical/chemical composition of NTDEcompared to TDE, suggest that IARC should evaluate theemissions of this new technology independently from TDE.To apply the findings of the health studies conducted over thelast 30 years on TDE to NTDE would make as much senseas applying those health study results to gasoline or CNGexhaust, which are much closer in composition to NTDE than toTDE.

STUDIES UNDERWAY OR PLANNEDSeveral DE studies are either underway or planned that

will significantly improve our understanding of the effects ofpast, current and future exposures to DE. When evaluatingDE, it is important to account for the marked reductions inemissions from diesel engines over the last two decades and theadditional advances that will be made in order to meet upcomingemission regulatory requirements. New epidemiologic studiesare underway that address many of the shortcomings of earlierstudies, which are discussed throughout this article. These newstudies are designed to provide a better understanding of thepotential biological effects of exposure to TDE as well asNTDE. Further, there are recent toxicity studies that providea context for comparing current diesel emissions with othertypes of engine exhausts (summarized elsewhere; Hesterberget al., 2005).

A major research effort is underway in the United States tocharacterize the composition and potential toxicity of emissionsof diesel engines equipped with the latest emissions controltechnology. This 5-year, multi-million-dollar research programwill receive funding from the U.S. Environmental ProtectionAgency, the Engine Manufacturers Association, the U.S. De-partment of Energy, the California Air Resources Board, and theAmerican Petroleum Institute. Initially, the testing program willchemically and physically characterize the emissions of dieselengines that are equipped with NTD (i.e., engines that meet the2007 U.S. EPA emissions standards). The centerpiece of theprogram will be a chronic inhalation toxicity study of multipleexposure levels of NTDE in two species of animals, using theNational Toxicology Program protocol as a guideline. This studywill provide a safety assessment of NTDE to determine whetherthere are any unintended health risks associated with exposureto this new low-emitting technology.

Preliminary data provide important insights on the impact ofnew diesel technologies on the chemical and physical charac-teristics of NTDE. Elements of NTD (e.g., ultra-low-sulfur fuelwith catalyzed particulate filters) have already been studied.By itself, ultra-low-sulfur fuel with lower aromatic contentprovides a 10–30% reduction in particulate and polycyclicaromatic hydrocarbon (PAH) emissions (Ball et al., 2001;LeTavec et al., 2002). Moreover, the ultra-low sulfur enablesthe use of catalyzed particulate filters, which provide substantial

reductions (80–100%) in particulate mass and number (in all sizeranges), volatile hydrocarbons (including benzene, butadiene,and formaldehyde), and carbon monoxide and PAHs (Ayalaet al., 2002; Lev-On et al., 2002a, 2002b; Lanni et al., 2003;Ullman et al., 2003). Testing of engines that will be usedto meet the U.S. 2007–2010 emission requirements is in theplanning stages in the United States. Japan has also begun testingprototype engines that meet the new requirements (Shibataet al., 2003). Recent results from studies of ultra-low-sulfurfuel and catalyzed particulate filters clearly demonstrate thatemissions from diesels in the future will be quite different (bothquantitatively and qualitatively) from TDE.

There are three large epidemiologic studies underway thataddress many of the shortcomings of earlier studies. Findingsfrom these studies are expected within the next 3 to 5 years, andshould provide a better understanding of the effects of exposureto historical diesel.

Harvard University researchers are conducting an epidemio-logic study of particle exposures in the trucking industry, whichis being funded by the National Cancer Institute (Garshick et al.,2003). This large cohort, 54,319 unionized workers employedin 1985, included drivers, dock workers, hostlers, mechanics,and clerks from four large shipping companies in the UnitedStates. The study will assess lung cancer risk over a longperiod (through 2000, covering >20–30 years), will includelarge numbers of subjects with relevant exposure, and willaccurately characterize exposure by an extensive assessmentof representative samples. Preliminary results from this studyshowed that PM exposures were from mobile sources, includinggasoline exhaust, and not diesel exhaust alone (Garshick et al.,2006a).

Researchers at the National Institute of Occupational Safetyand Health (NIOSH) and the National Cancer Institute (NCI) areevaluating mortality from lung cancer and other diseases amongnonmetal miners in relation to quantitatively measured exposureto diesel exhaust, using a cohort and nested case-control study(Attfield, 2003). NIOSH researchers will characterize currentand past levels of surrogates of diesel exhaust with the aimof developing reliable estimates of cumulative exposure andassociated indices. These exposures will be used to investigatepotential exposure-response relationships in the two studies.NIOSH is expected to issue a final report on this study inapproximately 2 years.

Finally, in Australia, the Cancer Surveillance Project ismonitoring the rate of cancer in 24,139 New South Walesblack-coal miners (Kirby et al., 2000). As mentioned earlier,miners have the highest occupational exposure to diesel exhaust.This study, with results expected in about 5 years, will providefurther insight into the potential health effects of traditionaldiesel exhaust.

These extensive new data should prove invaluable to a con-temporary, comprehensive assessment of DE exposures—bothpast, present, and future—and any association withcarcinogenicity.


CONCLUSIONSA critical assessment of the currently available laboratory and

epidemiological data has not provided a convincing argumentfor a causal relationship between exposure to TDE and anincreased incidence of lung cancer. This historical databaseapplies primarily to TDE and has only limited relevance to ahealth assessment of NTDE. The data from laboratory studiesof TDE, both in vivo and in vitro, have only limited relevancein assessing the carcinogenic potential of TDE in humans.Laboratory rats exposed to very high levels of TDE (>2200µg/m3) developed an excess of lung tumors; however, the tumorincidence was consistent with that observed in rats exposed tothe same overload levels of other types of fine particles (TiO2,talc, and carbon black). Other species (mice and hamsters)exposed at similar, high DE levels did not show an excessof lung tumors, nor did rats exposed at lower DE levels. Inrats, high exposures to a variety of different particulates (DPMas well as inert TiO2, talc, and carbon black) resulted in lungoverload, lung inflammation, cell proliferation, and eventuallytumors. This mechanism is not DE specific and did not occur inthe rats at DPM exposure concentrations below 2000 µg/m3, aconcentration level that is 100-fold greater than DPM levels towhich railroad and trucking industry workers might be exposed.Thus, the tumorigenic effect of high levels of TDE PM in rats isnow considered to be a nonspecific particle effect that resultedfrom a species-specific overload mechanism. Such a mechanismhas little or no relevance to humans exposed either to lowlevels in occupational environments or to even lower ambientlevels.

Furthermore, mutagenicity studies in which cultures ofmammalian or bacterial cells were exposed to organic solventextracts of DPM are of limited utility for understanding thepotential carcinogenicity of whole DPM. Although organiccompounds can be extracted from DPM, and some of thesecompounds have been shown to cause mutations in vitro, suchmutagens become effectively available only after particles havebeen treated with organic solvents, agitation, and heat. WholeDPM itself has not been found to be mutagenic in most studies.The mutagens extractable from DPM dissolve either minimallyor not at all in aqueous based fluids, such as body fluids or cellculture medium. Thus, these adsorbed mutagens are generallynot considered to be bioavailable, which could explain why moststudies have not shown DPM to be a direct-acting mutagen.

The epidemiologic database for DE is comprised of studiesof the transportation industry and of the underground miningindustry. Epidemiologic studies of the transportation industry(trucking, busing, and railroad) generally show a low elevationin lung cancer incidence (RRs generally below 1.5), but doseresponse for DE exposure is lacking, and the studies are limitedby minimal or inadequate latency periods, a lack of quantitativeconcurrent exposure data, and inadequate or lack of controls fortobacco smoking. Furthermore, there were similar elevationsin lung cancer incidence in truck drivers prior to dieselization.And finally, in-cab PM exposures of truck drivers have been

shown to be comparable to ambient highway exposures; thus,at least on the road, long-haul truckers are not exposed to anyhigher DPM than the rest of the driving or highway-situatedpopulation. Taken together, these findings suggest that lifestyleor an unidentified occupational agent other than DE mightbe responsible for the low elevations in lung cancer reportedin the transportation studies. In contrast to the transporta-tion industries studies, epidemiologic studies of undergroundminers, many of whom are exposed to perhaps the highestknown human DPM exposures, are generally negative for lungcancer.

The existing epidemiologic studies were of occupational pop-ulations that were exposed to TDE. However, diesel technologyhas undergone significant changes over the past two decades,resulting in dramatic changes in exhaust emissions. Furthermarked reductions in diesel engine emissions will occur in 2007,as the new-technology diesel (NTD) engines enter the market.NTDE differs, both quantitatively and qualitatively, from TDE.In fact, the physical/chemical characteristics of NTDE aremore similar to compressed natural gas (CNG) emissions thanto TDE. Thus IARC and other regulatory agencies shouldevaluate the potential carcinogenicity of NTDE independentlyof TDE, just as CNG and gasoline exhaust are independentlyevaluated.

Understanding the potential health effects of DE is important,not only for the large populations that are occupationallyexposed but also for the general public, which is exposed atlower ambient levels. New studies are underway and othersare proposed that will investigate possible associations betweenexposure to DE and increases in lung cancer incidence (as wellas other possible health effects). These new studies will striveto eliminate the weaknesses and limitations of the past studies.Specifically, the new epidemiologic studies will measure healtheffects in a large cohort of heavily exposed miners with anadequate latency period for lung cancer and with quantitativehistorical exposure data. Furthermore, additional new laboratorystudies will evaluate the potential health effects of NTDEindependently from those studies that have historically focusedon TDE.

ACKNOWLEDGMENTSThis review was prepared by T.W. Hesterberg and W.B. Bunn

in the course of their employment by the International Truckand Engine Corporation and Gerald R. Chase, Peter A. Valberg,Thomas J. Slavin, Charles A. Lapin, and Georgia A. Hart asconsultants to International Truck and Engine Corporation.The proposed studies of the new-technology diesel exhaustemissions are part of a proposed program being developed bythe Health Effects Institute (HEI) and its stakeholders. Theproposed program outlined here represents the independentviews of the authors and does not necessarily imply acceptanceor endorsement by the HEI and its stakeholders.


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APPENDIX 1. DIESEL USE IN UNDERGROUND MININGIN THE UNITED STATES, CANADA, EUROPE, ANDAUSTRALIA

The United StatesAt the beginning of 1947 only four diesel mine locomotives

were used in underground mines in the United States, twoin metal mines and two in nonmetal mines. Adverse mininglaws and safety concerns prevented their widespread adoption.However, a 1947 Bureau of Mines report noted that othertypes of diesel-powered equipment in underground mineswere “somewhat common in the Central States: Diesel trucks,

shovels, Caterpillar tractors and loaders, and diesel-poweredportable compressors are used successfully in undergroundlimestone, clay, and lead-zinc mines of that area.” (Harringtonand East, 1947).

In the United States, diesel engines currently power a fullrange of mining equipment on the surface and underground.As shown in Table A-1, nearly all U.S. underground metal andnonmetal mines use diesel powered equipment. This is not truein underground coal mines in the United States, due in part tothe fact that several key underground coal states have for manyyears banned the use of diesel-powered equipment (MSHA,1998a). When the U.S. Bureau of Mines was established in1910, gasoline engines were being used in mines and tunnels,sometimes with fatal consequences. As a result, most statesdeveloped laws that prohibited use of gasoline or other volatilefuels in mines except in very limited and controlled quantities.After review by the Bureau of Mines in the 1940s, many statesbegan to permit diesel use in underground mines by specialexemption (Holtz, 1962).

Diesel equipment used in underground coal mines in theUnited States has been as follows: in 1976, 114 pieces in 22mines located in three districts, with a majority located inDistrict 9 (Colorado, Wyoming and Utah); in 1977, 162 piecesin 28 mines, with all of the increase in District 9 (Barrett, 1982);in 1987, 1100 pieces in 110 mines; in 1992, 1951 pieces in 152mines. Approximately 33% of the diesel engines were used tohaul coal, 45% were used to haul personnel and materials, and22% performed other duties, such as roof bolting, rock dusting,and road maintenance. Most mines using diesel equipment werelocated in Kentucky, Utah, Virginia, and Colorado (Watts et al.,1992).

Continental EuropeMines employ locomotives to haul coal or ore out of the mines

and typically also to transport personnel to the work area. Diesellocomotives were introduced into German underground coalmines in 1927, and by 1938 there were 602 diesel locomotivesused accounting for 16% of the mine locomotives in use. Thenational policy of not using imported materials, such as fuel oil,prevented a more rapid increase. (East, 1946)

Diesel engines are in widespread use throughout the miningindustry in Germany. In salt and potash mining they have beenthe most important production factor since their introductionin the early 1960s (Dahmann and Bauer, 1997). During 1969to 1970 the potash mines in the South Harz Mountains areaof Germany changed technology to the use of mobile diesel-powered vehicles. From that time until the mines were closed in1991 the underground workforce was exposed to diesel exhaust.The potash mines used the room and pillar method allowingspacious rooms for production and transportation. The mainsources of diesel exhaust were huge front-end loaders used toscoop and carry material after blasting. Drill carriages were asecondary source. The mining technology and type of machinery


TABLE A1Diesel equipment in U.S. mines in 1996

Mine typeNumber of

minesNumber of mines

with dieselPercent mines

with dieselNumber of

enginesNumber of

miners

Underground coal 971 173 18% 2950 50,577Small 426 15 4% 50 4371Large 545 158 29% 2900 46,206

Underground M/NM 261 203 78% 4100 17,786Small 130 82 63% 625 1103Large 131 121 92% 3475 16,683

Surface Coal 1673 1673 100% 22,000 40,567Small 1175 1175 100% 7000 7243Large 498 498 100% 15,000 33,324

Surface M/NM 10,474 10,474 100% 97,000 129,400

Note. Small = a mine with less than 20 miners. M/NM, metal/nonmetal. Source: MSHA (1998a, 1998b).

used did not change between 1970 and 1991 (Saverin et al.,1999).

The coal beds of Belgium are thinner and more broken byfaults than other European countries. They are also gassier,which limits the use of electric locomotives. After the successfulintroduction of diesel locomotives in German mines, theadoption in Belgium was rapid. By 1939, 114 diesel locomotiveswere in use in Belgian underground coal mines, accounting for62% of the locomotives used (East, 1946).

In 1935 the number of diesel locomotives used in under-ground French coal mines was 357, representing 49% of thetotal locomotives used in that country. By 1937 the number ofdiesel locomotives had grown to 380, with no increase for othertypes (electric or compressed air). Diesel locomotive use was58% in the top four producing districts, which accounted for81% of the coal (East, 1946).

A 1946 review of European underground diesel use foundthat while the coal deposits of Italy and Sardinia were relativelyunimportant, diesel locomotives were used exclusively for alltypes of underground service. Diesels were also used extensivelyin mercury and pyrite mines (East, 1946).

In 1977 there were about 1500 diesels in use in undergroundSwedish mines, more than half of which were in use by the ironore company LKAB in northern Sweden. Until 1959 the minewas mainly an open-pit mine, but in the late 1950s undergroundmining began and used diesels for subterranean transportation(Jorgensen, 1982).

Great BritainIn a May 1935 communication, Sir Henry Walker, H.M.

Chief Inspector of Mines of Great Britain, stated: “At thepresent time Diesel engines are in use successfully in onecoal mine and in about half a dozen metalliferous mines inGreat Britain” (Rice and Harris, 1936). In April 1946, 40flame-proof diesel locomotives were in service in mines in theBritish Isles (Harrington and East, 1947). The conversion to

diesel power was limited until nationalization of coal mining in1947. The use of diesel locomotives in Great Britain increasedrapidly from 37 pieces in 1945 to a peak of 874 in 1965 whenproduction efficiencies reduced the number of coal faces inuse, and improved belt conveyors replaced some diesel uses(Higginson, 1975).

During 1976–1977 the Great Britain National Coal Boardproduced 106 million tons of coal from 236 underground mineswith a payroll of 242,000 people. Use of diesel equipment islimited by the layouts of some mines, many over 100 yearsold, which do not make it easy for diesel use. Even in newermines, the coal formations do not allow large or wide openings.A typical 9-foot-high, 12-foot-wide roadway precludes the useof large vehicles. Ninety-five percent of underground coal ismined by longwall faces, with only two or three mines beingon stall-and-pillar methods that involve more extensive use ofdiesel equipment (Higginson, 1975).

About 17% of the payroll in underground mines are employedon transport duties. In addition, those at the coal face or intunneling work, some 50% of the total, spend on average 1.5hours out of a 7.25-hour shift traveling to and from their workassignment. Some travel is done on conveyor belt, but the mostcommon method is by rope haulage of vehicles on rails. In1976 there were 617 diesel locomotives in use and 337 electriclocomotives (Kibble, 1982).

AustraliaTechnical literature as far back as 1912 contains references

to the use of 7 diesel engines in Australian mines to drivepumps underground. In 1926 legislation was introduced in NewSouth Wales prohibiting the use of diesel engines underground.However, this rule was amended in 1941 to allow only dieselengines. At the same time, another rule was introduced requiringthe provision of underground human transport (Clark, 1982).The first diesel engine in this era, a 10-ton locomotive, wasintroduced into an Australian coal mine shortly after the rule


was amended. “The design largely followed the British practicewhere diesel locomotives had been in use for some years. Forpractical purposes Australian experience with diesel engines inunderground coal mines can therefore be regarded as from 1941.Diesel equipment in underground coal mines consisted only ofrail mounted locomotives ranging in sizes up to 25 tons and 204bhp, and were used for coal haulage as well as men and materialstransport” (Clark, 1982). Diesel locomotives were confined tomain intake roads where ventilation was provided. In 1966, inaddition to locomotives, diesel shuttle cars were introduced intoface areas, followed by other diesel equipment used for facehaulage, transport, roof drills, rock dusters, tractors and frontend loaders. As of December 1976 there were 599 pieces ofdiesel equipment used in underground coal mines in Australia(Clark, 1982).

CanadaIn Canada, diesel engines have been used in coal mines

since 1949 (Zorychta, 1975), but they have not been as popularin coal mines as they have in metal and non-metal mines.A 1975 survey indicated that 75% of underground mineralproduction was conducted by trackless methods, which, inCanada, is synonymous with diesel power. While the worldwidepopulation of diesels underground was estimated at 10,000 in1976, there were 3151 diesel units underground in Canada in1977, including 40 units in Canadian underground coal mines(Stewart et al., 1982).

APPENDIX 2. THE HILL CRITERIA (HILL, 1965)The nine Hill Criteria proposed by Hill, 1965, for evaluating

causality when an association has been observed in epidemio-logic studies are:

1. Temporality: Exposure to the suspected causative agent mustprecede the onset of the adverse effect. This is the only one ofthe Hill criteria that is absolutely essential; all others simplycontribute to the weight of the evidence.

2. Strength of the association: This criterion evaluates themagnitude of the association as measured using statisticaltests. The stronger the association, the more likely that

the relationship is causal. According to Morgan et al.(1997), when evaluating the strength of the association, an“association of greater than 3 is likely to be causal, while arisk of 1.5 to 3 is suggestive, [and] associations below 1.5are often weak and explicable by bias and other confoundingfactors.”

3. Dose-response relationship (biological gradient): Exposureto increasing amounts of the suspected causative agentcorresponds with increasing risk of the adverse effect.Presence of a dose-response relationship provides strongevidence of causality, but absence of a dose-responserelationship may not rule out causality, as there may be athreshold below which the suspected agent does not causethe adverse effect. Some epidemiologists have suggested a“supralinear” dose response, where the slope is steeper atlow exposures than at high exposures.

4. Consistency: The association between the suspected agentand presence of the adverse effect is consistent in a varietyof studies in a variety of locations, and using differentmethods.

5. Biological plausibility: The association can be explainedbased on current understanding of pathological processes.

6. Specificity: Considered by some to be the weakest ofthe criteria, specificity refers to a single suspected causeleading to a single suspected effect. With a disease suchas angiosarcoma, which is both rare and has few causalagents, the concurrent presence of the disease and the agentcontributes strongly to a finding of causality, but this criterionmay not be helpful with more commonly occurring diseases.

7. Consideration of alternate explanations: Has the researchertaken into account—and effectively ruled out—other possi-ble explanations?

8. Experiment: Can an experimental regime be devised wherebythe outcome is prevented (or lessened) by eliminating thepresence of the suspected causative agent?

9. Coherence: This criterion is related to biological plausibilityand refers to whether the association is consistent withexisting theory and knowledge (e.g., do we need to rejectwhat we currently believe to be true in order to accept thisassociation as true?).

TAB

LE

A2

Exp

osur

esto

dies

elex

haus

tin

vari

ous

occu

patio

ns

DPM

surr

ogat

e(µ

g/m

3)

Exp

osur

ety

pePa

ram

eter

EC

aT

Cb

DPM

cA

RPM

dR

CD

eR

PMf

Ref

eren

ce

Am

bien

tR

esid

entia

ln=

23M

ean

1.4

(Zae

bste

tal.,

1991

)H

ighw

aybk

dn

=21

Mea

n3.

4(Z

aebs

teta

l.,19

91)

Bac

kgro

und

atel

ectr

icut

ility

wor

ksi

tes

(U.S

.)n

=18

Mea

n2

18(W

hitta

ker

etal

.,19

99)

28U

.S.n

onra

ilroa

dlo

catio

nsM

ean

2.6

29.5

(Liu

kone

net

al.,

2002

)T

ruck

ers

Ele

ctri

cut

ility

wor

kers

(US)

(Whi

ttake

ret

al.,

1999

)T

ruck

bay

n=

64M

ean

611

5L

inem

ann

=90

Mea

n3

61W

inch

truc

kop

er.n

=30

Mea

n4

69T

ruck

repa

ir(C

anad

a)n

=40

Mea

n9.

9(S

esha

giri

and

Bur

ton,

2003

)D

ock

wor

kers

and

mec

hani

cs(U

.S.)

n=

155

Mea

n25

(Zae

bste

tal.,

1991

)D

rive

rs(U

.S.)

n=

128

Mea

n5.

2(Z

aebs

teta

l.,19

91)

Det

roit

inw

inte

rn

=10

3M

ean

2.2

21.9

32.6

h(L

eeet

al.,

2005

)Sh

op17

.472

84Pi

ckup

and

deliv

ery

1.8

3041

Lon

g-ha

ul0.

619

27Y

ard

and

dock

0.4–

1.1

6–13

19–3

7O

ffice

0.3

1515

Min

neso

tatr

ansp

orta

tion

(Ram

acha

ndra

net

al.,

2005

)B

usdr

iver

sn

=39

Mea

n2.

0R

amp

atte

ndan

tsn

=34

Mea

n1.

1G

arag

em

echa

nics

n=

35M

ean

3.9

Rai

lroa

dw

orke

rsFo

urra

ilroa

ds(U

S)N

=399

Mea

n10

314

3(H

amm

ond

etal

.,19

88)

Can

ada

(N=1

77A

)R

ange

<0.

9–60

.1(V

erm

aet

al.,

2003

)M

edia

n3.

6L

ead

loco

mot

ive

Mea

nl2.

9T

raili

nglo

com

otiv

eM

eanl

7.9

Bot

hle

adan

dtr

ailin

gM

eanl

2.5

Cab

oose

Mea

nl3.

6T

urna

roun

d/fu

elpl

ant

Mea

nl4.

9H

eavy

repa

ir/b

acks

hop

Mea

nl3.

6O

ffice

sM

eanl

<2.

2T

rack

equi

pmen

teng

inee

ring

Mea

nl2.

7

770

Can

ada

(n=

101

P)R

ange

<0.

9–18

.8(V

erm

aet

al.,

2003

)M

edia

n4.

0E

ngin

eers

Mea

nl2.

9C

ondu

ctor

sM

eanl

3.5

Mac

hini

sts/

mec

hani

csM

eanl

4.6

Lab

orer

s/en

gine

atte

ndan

tsM

eanl

4.3

Hos

tlers

/labo

rers

mov

ing

units

Mea

nl3.

5E

lect

rici

ans

Mea

nl7.

2Pi

pefit

ters

Mea

nl<

2.7

Stor

ecl

erks

Mea

nl<

1.6

Supe

rvis

ors

Mea

nl4.

0E

ngin

eers

/equ

ipm

ento

pera

tors

Mea

nl7.

3C

anad

an

=57

Mea

n8

(Ver

ma

etal

.,19

99)

Can

ada

n=

62M

ean

157

166

Can

ada

n=

40M

ean

3.7

(Ses

hagi

rian

dB

urto

n,20

03)

Can

ada

(Ses

hagi

ri,2

003)

On

boar

dle

adlo

com

otiv

esn

=23

1M

ean

<2

On

boar

dtr

ailin

glo

com

otiv

esn

=47

Mea

n10

.1R

ailr

oad

trai

ncr

ews

(U.S

.)n

=49

GM

3.7

40(L

iuko

nen

etal

.,20

02)

Min

ing—

Uni

ted

Stat

es11

U.S

.sur

face

min

esn

=45

Mea

n88

(MSH

A,1

998a

)12

US

Und

ergr

ound

coal

min

esn

=22

6M

ean

640

(MSH

A,1

998a

)25

US

Und

ergr

ound

met

al/m

iner

alm

ines

n=

331

Mea

n83

0g(M

SHA

,199

8a)

31U

.S.u

nder

grou

ndm

etal

and

nonm

etal

min

esn

=11

94M

ean

i196

j29

3k 366

(MSH

A,2

005)

Met

aln

=28

4M

ean

274

370

463

Ston

en

=68

9M

ean

182

282

353

Oth

erno

nmet

aln

=19

6M

ean

149

238

298

Tro

nan

=25

Mea

n81

140

175

Seve

nno

n-m

etal

min

es(U

.S.)

(Coh

enet

al.,

2002

)U

nder

grou

ndw

orke

rsn

=61

2M

ean

177

290

Surf

ace

wor

kers

n=

164

Mea

n13

80Z

inc

Min

e(U

.S.)

n=

19R

ange

140–

260

(Han

eyan

dFi

elds

,199

6)M

edia

n20

0Po

tash

min

e(U

.S.)

n=

30R

ange

150–

450

(Han

eyan

dFi

elds

,199

6)M

edia

n42

0(C

onti

nued

onne

xtpa

ge)

771

TAB

LE

A2

Exp

osur

esto

dies

elex

haus

tin

vari

ous

occu

patio

ns(C

onti

nued

)

DPM

surr

ogat

e(µ

g/m

3)

Exp

osur

ety

pePa

ram

eter

EC

aT

Cb

DPM

cA

RPM

dR

CD

eR

PMf

Ref

eren

ce

Pota

shm

ine—

surf

ace

(U.S

.)n

=25

Mea

n24

(Sta

nevi

chet

al.,

1997

)Po

tash

min

e-un

derg

roun

d(U

.S.)

n=

43M

ean

190

(Sta

nevi

chet

al.,

1997

)U

nder

grou

ndm

inin

g(U

.S.)

n=

193

Mea

n11

12(C

antr

ella

ndW

atts

,19

97)

Four

unde

rgro

und

coal

min

es(T

omb

and

Ran

ey,1

995)

No

afte

rtre

atm

ent

Mea

ns90

0–12

00W

ithdi

esel

exha

ustfi

lter

Mea

ns10

0–20

0W

ithw

ire

mes

hfil

ter

(U.S

.)M

ean

1200

Ten

met

al/n

onm

etal

unde

rgro

und

min

es(U

.S.)

Mea

n70

0(T

omb

and

Ran

ey,1

995)

Six

unde

rgro

und

coal

min

es(U

S)n

=78

Mea

n14

83(R

eger

etal

.,19

82)

Und

ergr

ound

gold

min

e(U

.S.)

374

496

656h

(McD

onal

det

al.,

2003

)M

inin

g—ou

tsid

eU

nite

dSt

ates

Und

ergr

ound

salt

and

pota

shm

ines

(Ger

man

y)n

=28

5M

edia

ndi

stri

butio

n10

0–15

0(D

ahm

ann

and

Bau

er,

1997

)U

nder

grou

ndsa

lt,po

tash

and

met

alm

ines

(Ger

man

y)n

=62

2M

edia

ndi

stri

butio

n30

0–40

0(D

ahm

ann

etal

.,19

96)

Und

ergr

ound

min

ing

(Aus

tral

ia)

n=

134

Ran

ge30

–165

0(P

ratt

etal

.,19

97)

Und

ergr

ound

pota

shm

inin

g(G

erm

any)

(Sav

erin

etal

.,19

99)

Wor

ksho

pn

=37

Mea

n12

0M

aint

enan

cen

=18

Mea

n23

0Pr

oduc

tion

n=

200

Mea

n39

0U

nder

grou

ndm

inin

g(C

anad

a)n

=90

Mea

n14

826

4(R

amac

hand

ran

and

Wat

ts,2

003)

n=

79M

ean

421

n=

73M

ean

398

aE

C,e

lem

enta

lcar

bon.

bT

C,t

otal

carb

on.

cD

PM,d

iese

lpar

ticul

ate

mat

ter,

allp

artic

ulat

em

atte

r<

0.8

µm

diam

eter

.MSH

A(1

998)

estim

ates

that

400

µg/

m3

tota

lcar

bon

corr

espo

nds

to∼5

00µ

g/m

3D

PM.

dA

RPM

,adj

uste

dre

spir

able

part

icul

ate

mat

ter=

resp

irab

lepa

rtic

ulat

em

inus

aver

age

estim

ated

cont

ribu

tion

ofto

bacc

osm

oke

for

this

job

cate

gory

.e

RC

D,r

espi

rabl

eco

mbu

stib

ledu

st.

fR

PM,r

espi

rabl

epa

rtic

ulat

em

atte

r.g

Sam

ples

attw

oof

the

25m

etal

/min

eral

min

esw

ere

colle

cted

usin

gth

esu

bmic

rom

eter

impa

ctor

.h

Part

icul

ate

mat

ter<

2.5

µm

.iB

ack

calc

ulat

edfr

omso

urce

tabl

e.jT

C=

EC

+OC

(org

anic

carb

on).

kM

SHA

calc

ulat

esth

atD

PM=

TC

×1.

3(M

SHA

2005

).lno

n-de

tect

able

valu

esca

lcul

ated

usin

gde

tect

ion

limit.

772

TAB

LE

A3

Stud

ies

oflu

ngca

ncer

inm

iner

sgr

oupe

dby

coun

try

and

conf

ound

ers

Cou

ntry

(ref

eren

ce)

Stud

yba

se/f

ollo

w-u

pFo

llow

-up

Subg

roup

Lun

gca

ncer

risk

Cas

es95

%C

ID

Eex

posu

reL

aten

cyd

Coa

lMin

ers

W.V

irgi

nia,

USA

(Ent

erlin

e,19

72)

553

WV

mal

eco

alm

iner

sin

1937

1938

–66

Res

pira

tory

canc

erSM

R1.

114

0.3–

2.85

Unl

ikel

yN

/A

USA

(Cos

tello

etal

.,19

74)

2549

empl

oyed

min

ers,

1962

–63,

1177

ex-m

iner

sfr

omA

ppal

achi

a.U

.S.P

HS

stud

y.

1962

–63

to19

72V

olun

teer

sam

ong

4134

rand

omly

sele

cted

SMR

0.67

240.

43–0

.99

Unl

ikel

yN

/A

USA

(Roc

kette

,19

77)

23,2

32co

alm

iner

sco

vere

dby

the

Uni

ted

Min

eW

orke

rsH

ealth

and

Ret

irem

entF

unds

in19

59

1959

–71

Lun

gca

ncer

SMR

1.13

352

1.02

–1.2

6L

imite

dto

afe

wN

/A

USA

(Am

eset

al.,

1983

)Tw

oca

se-c

ontr

olst

udie

sba

sed

onlu

ngca

ncer

deat

hsam

ong

coal

min

ers

from

4N

IOSH

coho

rts;

mat

ched

for

age;

with

and

with

outs

mok

ing

stat

us;d

ecea

sed

and

livin

gco

ntro

ls(O

Rfo

r25

+vs

<25

yrun

derg

roun

d)

1959

–75

Dec

ease

dco

ntro

ls1:

1w

/osm

okin

g2:

1w

ithsm

okin

gL

ivin

gco

ntro

ls1:

1w

/osm

okin

g2:

1w

ithsm

okin

g

OR

1.18

0.89

0.87

0.80

317

137

0.86

–1.6

20.

66–1

.20

0.52

–1.4

50.

48–1

.32L

imite

dto

afe

wU

nlik

ely

>20

yr

USA

(Am

esan

dG

ambl

e,19

83)

Four

coho

rts

com

pose

dof

appr

oxim

atel

y20

,000

coal

min

ers

prov

ided

case

sof

lung

and

stom

ach

canc

er

Not

give

nL

ung

canc

er(u

nder

grou

nd>

25yr

)an

dde

ceas

edco

ntro

ls.

OR

1.42

460.

70–2

.89

Unl

ikel

yfo

rm

any

Unl

ikel

y>

15yr

USA

(Kue

mpe

let

al.,

1995

)88

78co

alm

iner

sm

edic

ally

exam

ined

1969

–71

from

31m

ines

(Pen

nsyl

vani

a,E

.A

ppal

achi

a,W

.App

alac

hia,

Mid

wes

t,W

est)

1969

–71

thro

ugh

1979

SMR

RSM

R0.

770.

9165

0.60

–0.9

Lim

ited

toa

few

(Wes

tan

dM

idw

est)

>10

yr.

Lik

ely

for

som

e

Can

ada

(Sie

mia

tyck

i,19

91)

3,73

0m

ale

canc

erpa

tient

sre

side

ntin

Mon

trea

l,ag

ed35

–70;

6%ex

pose

dto

coal

dust

Any

expo

sure

Subs

tant

ial

expo

sure

OR

1.3

1.1

63 271.

0–1.

90.

7–1.

7L

ikel

yfo

rso

me

Lik

ely

>20

yr

Uni

ted

Kin

gdom

(Gol

dman

,196

5)M

iner

sem

ploy

edby

Nat

iona

lCoa

lB

oard

,age

d20

–65

in19

5550

96m

ale

coal

min

ers≥

35ye

ars

inG

lam

orga

n

1955

1955

1951

–56

Und

ergr

ound

wor

kers

Surf

ace

wor

kers

Min

ers

and

ex-m

iner

s

SMR

0.70

0.92

0.81

216

54 30

0.61

–0.8

00.

69–1

.19

0.55

–1.1

6Lik

ely

for

man

yL

imite

d

Uni

ted

Kin

gdom

(Boy

det

al.,

1970

)

Coa

lmin

ers

inC

umbe

rlan

d,E

ngla

nd,a

ged

≥15

.19

48–6

7U

nder

grou

ndw

orke

rsSu

rfac

ew

orke

rs

PMR

0.79

0.99

28 110.

53–1

.15

0.49

–1.7

7Lik

ely

for

man

yL

imite

d

Uni

ted

Kin

gdom

(Roo

keet

al.,

1979

)

1003

deat

hsin

coal

min

ers

inN

WE

ngla

nd;i

nclu

des

lung

canc

ers

diag

nose

dat

auto

psy

1974

–76

Onl

yth

ose

repo

rted

toth

eco

rone

ror

pneu

moc

onio

sis

pane

l

PMR

1.17

114

0.96

–1.4

1L

ikel

yfo

rm

any

Lik

ely

>20

yrfo

rm

any

(Con

tinu

edon

next

page

)

773

TAB

LE

A3

Stud

ies

oflu

ngca

ncer

inm

iner

sgr

oupe

dby

coun

try

and

Foun

ders

(Con

tinu

ed)

Cou

ntry

(ref

eren

ce)

Stud

yba

se/f

ollo

w-u

pFo

llow

-up

Subg

roup

Lun

gca

ncer

risk

Cas

es95

%C

ID

Eex

posu

reL

aten

cyd

Uni

ted

Kin

gdom

(Lid

dell,

1973

)32

39de

aths

amon

gco

alm

iner

sag

ed20

–64

iden

tified

byth

eN

atio

nalC

oalB

oard

1961

Face

wor

kers

Und

ergr

ound

wor

kers

Surf

ace

wor

kers

SMR

0.49

0.53

0.82

n.d.

n.d.

Lik

ely

for

man

yL

imite

d

Wal

es,U

K(C

ochr

ane

etal

.,19

79)

6212

min

ers

and

ex-m

iner

s,ex

amin

edfo

rpn

eum

ocon

iosi

sin

1950

–51.

2138

nonm

iner

sag

ed≥2

0ye

ars

1950

–70

Non

min

ers

Min

ers—

all

radi

ogra

phic

cate

gori

es

SMR

0.66

0.70

21 570.

41–1

.00

0.53

–0.9

1L

ikel

yfo

rm

any

Unl

ikel

y>

20yr

for

mos

t

Uni

ted

Kin

gdom

(Joh

nsto

net

al.,

1997

)

18,1

66un

derg

roun

dco

alm

iner

sfr

om10

unde

rgro

und

coal

min

es(6

used

dies

ello

com

otiv

es

1958

–78

thro

ugh

1992

Cox

regr

essi

onw

ithou

gpi

tadj

.Cox

reg.

with

pita

dj.

RR

1.23

c

1.16

c63

263

21.

00–1

.50

0.90

–1.4

9Y

esfo

rm

iner

sfr

om6

min

es.

>20

yrfo

rm

any

UK

,Wal

es(A

tuha

ire

etal

.198

5)E

xten

ded

follo

w-u

pof

Coc

hran

eet

al.(

1979

).19

50–1

980

Non

-min

ers

Min

ers

SMR

0.70

0.77

43 100

0.51

–0.9

40.

63–0

.94

Lik

ely

for

man

y>

20yr

for

som

e

W.A

ustr

alia

(Arm

stro

nget

al.,

1979

)

213

mal

eco

alm

iner

s(2

05un

derg

roun

d)19

61–7

5R

espi

rato

ryca

ncer

SMR

0.2

10.

01–1

.1L

ikel

yfo

ral

lL

ikel

y>

20yr

.fo

rso

me

Aus

tral

ia∗

(Kir

byet

al.,

2000

)24

,139

min

ers

join

ed1/

1/73

–12/

31/9

719

73–9

7SI

R0.

6549

0.48

–0.8

6L

ikel

yfo

ral

lL

ikel

y>

20yr

for

som

eT

heN

ethe

rlan

ds(M

eije

rset

al.,

1991

)

334

unde

rgro

und

coal

min

ers

with

pneu

moc

onio

sis

diag

nose

dbe

twee

n19

56an

d19

60.

1956

–60

thro

ugh

1983

Und

ergr

ound

SMR

1.31

190.

79–2

.05

Lik

ely

for

mos

t>

15yr

?

The

Net

herl

ands

(Sw

aen

etal

.,19

95)

3790

coal

min

ers

with

abno

rmal

ches

tx-r

ays

in19

50s

1950

s–19

91un

derg

roun

dSM

R1.

0227

20.

90–1

.15

Lik

ely

for

mos

tL

ikel

y>

20yr

for

man

y

Ger

man

y(M

orfe

ldet

al.1

997)

∗45

78m

iner

sw

how

orke

dat

leas

t5yr

.196

3–79

(ave

rage

time

sinc

e1s

texp

osur

e36

.3yr

)

1980

–91

Und

ergr

ound

min

ers

SMR

RS

0.70

a

1.11

a41

410.

50–0

.95

0.80

–1.5

1L

ikel

yfo

rm

ost

Lik

ely

>20

yrfo

rm

any

Pola

nd∗(

Star

zyns

kiet

al.,

1996

)70

65m

iner

sdi

agno

sed

with

coal

-wor

ker

pneu

moc

onio

sis

1970

–85.

1970

–91

SMR

1.04

b15

30.

88–1

.22

Lik

ely

for

mos

tsa

me

Pota

shM

iner

sG

erm

any

(Sav

erin

etal

.,19

99)

5536

min

ers

follo

wed

from

1970

–94;

Cox

regr

essi

on(c

onsi

dere

dth

epr

inci

palfi

ndin

gby

the

auth

ors)

base

don

subc

ohor

t.

1970

–94

SMR

Eas

tGer

man

y20

yrD

Eex

p.(C

oxre

gres

sion

)

SMR

RR

0.78

1.7

380.

55–1

.07

0.5–

5.8

120–

390

µg/

m3

TC

>20

yrfo

rso

me

US

(Wax

wei

ler

etal

.,19

73)

1143

surf

ace

wor

kers

(>1

yrbe

twee

n19

40–6

7)19

40–6

7Su

rfac

em

iner

sSM

R1.

1210

0.41

–1.8

3L

ikel

yfo

rm

any

Unk

now

n

2743

unde

rgro

und

wor

kers

(>1

yr.

betw

een

1940

–67)

,9m

ines

;2w

ithdi

esel

1940

–67

Und

ergr

ound

min

ers

SMR

1.08

120.

46–1

.72

of9

min

es:1

sinc

e19

49;1

sinc

e19

57

<20

yr.f

oral

l

774

TAB

LE

A3

Stud

ies

oflu

ngca

ncer

inm

iner

sgr

oupe

dby

coun

try

and

Foun

ders

(Con

tinu

ed)

Cou

ntry

(ref

eren

ce)

Smok

ing

disc

usse

d/m

entio

ned

rest

udy

Det

aile

din

form

atio

nav

aila

ble

for

stud

yA

djus

tmen

tsin

anal

yses

Oth

erco

nfou

nder

se

Coa

lMin

ers

WV

irgi

nia,

USA

(Ent

erlin

e,19

72)

No

Non

eN

one

Non

eU

SA(C

oste

lloet

al.1

974)

Yes

Pack

year

san

dsm

okin

gst

atus

atst

arto

ffo

llow

-up

Non

eN

one

USA

(Roc

kette

,197

7)C

omm

ento

nly

Non

eN

one

Non

eU

SA(A

mes

etal

.,19

83)

Yes

Smok

ing

hist

orie

sC

ase-

cont

rols

:mat

ched

and

unm

atec

hed

for

smok

ing

Non

e

USA

(Am

eset

al.,

1983

)Y

esSm

okin

ghi

stor

ies

Smok

ing

incl

uded

inan

alys

esN

one

USA

(Kue

mpe

leta

l.,19

95)

Yes

Pack

year

san

dsm

okin

gst

atus

atst

arto

ffo

llow

upY

es,i

nclu

ded

inpr

opor

tiona

lha

zard

sm

odel

Non

e

Can

ada

(Sie

mia

tyck

i,19

91)

Yes

Smok

ing

stat

usY

es,i

nM

ante

l-H

anze

land

logi

stic

anal

yses

Yes

,inc

ludi

ngas

best

osan

dot

hers

Uni

ted

Kin

gdom

(Gol

dman

,196

5)Y

esSm

okin

ghi

stor

ies

amon

gm

iner

san

dge

nera

lpo

pula

tion

Dis

cuss

ion

ofpo

tent

ial

impa

ctU

rban

diff

eren

ces

disc

usse

d

Uni

ted

Kin

gdom

(Boy

det

al.,

1970

)Y

esN

one

Non

eR

adon

men

tione

dre

iron

ore

min

ing,

butn

otfo

rco

alU

nite

dK

ingd

om(R

ooke

etal

.,19

79)

Yes

His

tori

esav

aila

ble

for

som

eD

iscu

ssio

nof

pote

ntia

lim

pact

Non

e

Uni

ted

Kin

gdom

(Lid

dell,

1973

)N

oN

one

Non

eN

one

Wal

es,U

K(C

ochr

ane

etal

.,19

79)

No

Non

eN

one

Non

eU

nite

dK

ingd

om(J

ohns

ton

etal

.,19

97)

Yes

Stat

usan

dam

ount

smok

edat

time

ofen

try

into

stud

yY

es,C

oxre

gres

sion

mod

els

Non

e

UK

,Wal

es(A

tuha

ire

etal

.,19

85)

No

Non

eN

one

Non

eW

.Aus

tral

ia(A

rmst

rong

etal

.,19

79)

Yes

Smok

ing

hist

orie

sam

ong

attim

eof

orig

inal

surv

eyN

one

Non

e

Aus

tral

ia(K

irby

etal

.,20

00)

No

Non

eN

one

Non

eT

heN

ethe

rlan

ds(M

eije

rset

al.,

1991

)Y

esR

ates

inpo

pula

tion

atst

arto

fst

udy

Non

e,bu

tpot

entia

lim

pact

disc

usse

dA

lcoh

olm

entio

ned

(Con

tinu

edon

next

page

)

775

TAB

LE

A3

Stud

ies

oflu

ngca

ncer

inm

iner

sgr

oupe

dby

coun

try

and

Foun

ders

(Con

tinu

ed)

Cou

ntry

(ref

eren

ce)

Smok

ing

disc

usse

d/m

entio

ned

rest

udy

Det

aile

din

form

atio

nav

aila

ble

for

stud

yA

djus

tmen

tsin

anal

yses

Oth

erco

nfou

nder

se

The

Net

herl

ands

(Sw

aen

etal

.,19

95)

No

Non

eN

one

Som

e(e

.g.,

silic

a,tr

ace

met

als)

men

tione

dG

erm

any

(Mor

feld

etal

.,19

97)

Yes

Rat

esam

ong

unde

rgro

und

coal

min

ers

and

gene

ral

popu

latio

n

Axe

lson

met

hod

Qua

rtz

men

tione

d

Pola

nd(S

tarz

ynsk

ieta

l.,19

96)

Yes

Smok

ing

stat

usan

dhi

stor

yfr

oma

sam

ple

surv

eyof

coho

rt;p

opul

atio

nra

tes

(sta

tus)

avai

labl

e

Axe

lson

met

hod

for

nonm

inin

gsu

bcoh

ort

Rad

onm

entio

ned

Pota

shM

iner

sG

erm

any

(Sav

erin

etal

.,19

99)

Yes

His

tori

es(f

orm

ost)

from

med

ical

reco

rds

&vo

lunt

eer

subg

roup

Con

clud

edsm

okin

gno

taco

nfou

nder

Asb

esto

sm

entio

ned

for

subc

ohor

t

U.S

.(W

axw

eile

ret

al.,

1973

)Y

esR

ates

avai

labl

efr

omsa

mpl

eof

wor

kers

;U.S

.rat

esal

soci

ted

Pote

ntia

lim

pact

disc

usse

dR

adon

men

tione

das

abse

ntor

only

trac

eam

ount

s

Not

e.A

dapt

edfr

omIA

RC

Mon

ogra

phV

ol.4

6(1

997)

and

upda

ted

with

seve

rala

dditi

onal

stud

ies.

Add

ition

alre

fere

nces

notc

ited

inIA

RC

1997

have

been

adde

dto

this

tabl

ean

dar

ein

dica

ted

with

anas

teri

sk.

PMR

,pro

port

iona

tem

orta

lity

ratio

;SM

R,s

tand

ardi

zed

mor

talit

yra

tio;O

R,o

dds

ratio

;CI,

confi

denc

ein

terv

al;R

SMR

,rel

ativ

eSM

R;S

IR,s

tand

ardi

zed

inci

denc

era

tio.

USP

HS;

U.S

.Pub

licH

ealth

Serv

ices

.aU

nadj

uste

dfo

rsm

okin

g.W

hen

adju

sted

for

smok

ing

(Axe

lson

tech

niqu

e),R

SMR

<1.

bD

idno

tinc

lude

deat

hsov

er80

.Una

djus

ted

for

smok

ing

(85%

ever

smok

ers)

.c T

heun

itcu

mul

ativ

eex

posu

reof

1g-

hour

s-m

−3fo

rth

eR

Rw

asgr

eate

rth

anth

em

ean

and

med

ian

cum

ulat

ive

expo

sure

for

the

coho

rtan

dw

asex

ceed

edby

only

asm

all

perc

enta

geof

the

coho

rtdB

estj

udgm

ento

fth

epr

esen

taut

hors

,bas

edon

the

info

rmat

ion

inth

eci

ted

stud

ies.

e Som

eau

thor

s(e

.g.,

John

ston

etal

.,19

97)

use

the

term

“con

foun

der”

tode

scri

befa

ctor

sth

atot

hers

refe

rto

as“e

ffec

tmod

ifier

”(e

.g.,

age)

.Mos

tsuc

h“c

onfo

unde

rs”

are

notl

iste

dhe

re.

776

Documents

A Critical Assessment of Studies on the Carcinogenic Potential of Diesel Exhaust