False Indications of Dose-Response Nonlinearity in Large Epidemiologic Cancer Radiation Cohort Studies; A Simulation Exercise.

This study explores the likely prevalence of false indications of dose-response nonlinearity in large epidemiologic cancer radiation cohort studies (A-bomb survivors, INWORKS, Techa River). Reasons: Increasing numbers of tests of nonlinearity are being made in studies. Hypothesized nonlinear dose-response models have been justified to policy makers by analyses that rely in part on isolated findings that could be statistical fluctuations. After removing dose nonlinearity (linearization) by adjusting person-years of observation at each dose category, indications of nonlinearity, necessarily false, were counted in 5,000 randomized replications of six datasets. The average frequency of any false positive for five indicators of nonlinearity tested against a linear null was roughly 25% in Monte Carlo simulations per study, consistent with binomial calculations, increasing to ∼50% within 6 studies assessed. Comparable frequencies were found using Akaike's information criterion (AIC) for model selection or multi-model averaging. False above-zero threshold doses were found more than 50% of the time, averaging to 0.05 Gy, consistent with findings in the 6 studies. Such bias, uncorrected, could distort meta-analyses of multiple studies, because meta-analyses can incorporate high P value findings. AIC-based correction for the extra threshold parameter lowered these false occurrences to 8 to 19%. Given the simulation rates, the possibility of false positives might be noted when isolated findings of nonlinearity are discussed in a regulatory context. When reporting a threshold dose with a P value > 0.05, it would be informative to note the expected high false prevalence rate due to bias.

Implications of Recent Epidemiological Studies for Compensation of Veterans Exposed to Plutonium.

ABSTRACT: The objective of this paper is to compare post-2007 epidemiological results for plutonium workers to risk predicted by the software program NIOSH-IREP (IREP for short), which is used to determine the lowest dose for a US veteran to obtain cancer compensation. IREP output and methodology were used to predict excess relative risk per Gy (ERR Gy -1 ) for lung cancer at the 99 th credibility percentile, which is used for compensation decisions. Also estimated were relative biological effectiveness factors (RBE) predicted for workers using IREP methodology. IREP predictions were compared to results for Mayak and Sellafield plutonium workers, separately and pooled. Indications that IREP might underpredict 99 th -percentile lung cancer plutonium risk came from (1) comparison of worker RBEs and (2) from comparison of Sellafield results separately. When Sellafield and Mayak data were pooled, ERR Gy -1 comparisons at the 99 th percentile roughly matched epidemiological data with regression dose range restricted to < 0.05 Gy, the most relevant region to veterans, but overpredicted for the full dose range. When four plausible distributions for lung cancer risk, including both new and old data, were combined using illustrative weighting factors, compensation cutoff dose for lung cancer matched current IREP values unless regression results below 0.05 were chosen for Sellafield, producing a two-fold reduction. A 1997 claim of a dose threshold in lung cancer dose response was not confirmed in later literature. The benefit of the doubt is given to claimants when the science is unclear. The challenge for NIOSH-IREP custodians is dealing with the Sellafield results, which might best match US claimants.

History of Dose, Risk, and Compensation Assessments for US Veterans of the 1966 Plutonium Cleanup in Palomares, Spain.

In 1966, about 1,600 US military men-mostly Air Force-participated in a cleanup of plutonium dispersed from two nuclear bombs in Palomares, Spain. As a base for future analyses, we provide a history of the Palomares incident, including the dosimetry and risk analyses carried out to date and the compensation assessments made for veterans. By law, compensation for illnesses attributed to ionizing radiation is based on maximum estimated doses and standard risk coefficients, with considerable benefit of the doubt given to claimants when there is uncertainty. In the Palomares case, alpha activity in urine fell far faster than predicted by plutonium biokinetic excretion models used at the time. Most of the measurements were taken on-site but were disqualified on the grounds that they were "unreasonably high" and because there was a possibility of environmental contamination. Until the end of 2013, the Air Force used low dose estimates derived from environmental measurements carried out well after the cleanup. After these estimates were questioned by Congress, the Air Force adopted higher dose estimates based on plutonium concentration measurements in urine samples collected from 26 veterans after they left Palomares. The Air Force assumed that all other cleanup veterans received lower doses and therefore assigned to them maximum organ doses based on the individual among the 26 with the lowest urine measurements. These resulting maximum organ doses appear to be sufficient to justify compensation to all Palomares veterans with lung and bone cancer and early-onset liver cancer and leukemia but not other radiogenic cancers.

Lifetime exposure to ambient air pollution and methylation of tumor suppressor genes in breast tumors.

BACKGROUND: We previously reported increased risk of breast cancer associated with early life exposure to two measures of air pollution exposure, total suspended particulates (TSP) and traffic emissions (TE), possible proxies for exposure to polycyclic aromatic hydrocarbons (PAHs). Exposure to PAHs has been shown to be associated with aberrant patterns of DNA methylation in peripheral blood of healthy individuals. Exposure to PAHs and methylation in breast tumor tissue has received little attention. We examined the association of early life exposure to TSP and TE with patterns of DNA methylation in breast tumors. METHODS: We conducted a study of women enrolled in the Western New York Exposures and Breast Cancer (WEB) Study. Methylation of nine genes (SFN, SCGB3A1, RARB, GSTP1, CDKN2A CCND2, BRCA1, FHIT, and SYK) was assessed using bisulfite-based pyrosequencing. TSP exposure at each woman's home address at birth, menarche, and when she had her first child was estimated. TE exposure was modeled for each woman's residence at menarche, her first birth, and twenty and ten years prior to diagnosis. Unconditional logistic regression was employed to estimate odds ratios (OR) of having methylation greater than the median value, adjusting for age, secondhand smoke exposure before age 20, current smoking status, and estrogen receptor status. RESULTS: Exposure to higher TSP at a woman's first birth was associated with lower methylation of SCGB3A1 (OR = 0.48, 95% CI: 0.23-0.99) and higher methylation of SYK (OR = 1.86, 95% CI: 1.03-3.35). TE at menarche was associated with increased methylation of SYK (OR = 2.37, 95% CI: 1.05-5.33). TE at first birth and ten years prior to diagnosis was associated with decreased methylation of CCND2 (OR ten years prior to diagnosis=0.48, 95% CI: 0.26-0.89). Although these associations were nominally significant, none were significant after adjustment for multiple comparisons (p < 0.01). CONCLUSIONS: We observed suggestive evidence that exposure to ambient air pollution throughout life, measured as TSP and TE, may be associated with DNA methylation of some tumor suppressor genes in breast tumor tissue. Future studies with a larger sample size that assess methylation of more sites are warranted.

Lessons to be learned from a contentious challenge to mainstream radiobiological science (the linear no-threshold theory of genetic mutations).

There are both statistically valid and invalid reasons why scientists with differing default hypotheses can disagree in high-profile situations. Examples can be found in recent correspondence in this journal, which may offer lessons for resolving challenges to mainstream science, particularly when adherents of a minority view attempt to elevate the status of outlier studies and/or claim that self-interest explains the acceptance of the dominant theory. Edward J. Calabrese and I have been debating the historical origins of the linear no-threshold theory (LNT) of carcinogenesis and its use in the regulation of ionizing radiation. Professor Calabrese, a supporter of hormesis, has charged a committee of scientists with misconduct in their preparation of a 1956 report on the genetic effects of atomic radiation. Specifically he argues that the report mischaracterized the LNT research record and suppressed calculations of some committee members. After reviewing the available scientific literature, I found that the contemporaneous evidence overwhelmingly favored a (genetics) LNT and that no calculations were suppressed. Calabrese's claims about the scientific record do not hold up primarily because of lack of attention to statistical analysis. Ironically, outlier studies were more likely to favor supra-linearity, not sub-linearity. Finally, the claim of investigator bias, which underlies Calabrese's accusations about key studies, is based on misreading of text. Attention to ethics charges, early on, may help seed a counter narrative explaining the community's adoption of a default hypothesis and may help focus attention on valid evidence and any real weaknesses in the dominant paradigm.

Polycyclic aromatic hydrocarbons and postmenopausal breast cancer: An evaluation of effect measure modification by body mass index and weight change.

BACKGROUND: Polycyclic aromatic hydrocarbons (PAHs) have been linked to breast cancer in many, but not all, previous studies. PAHs are lipophilic and stored in fat tissue, which we hypothesized may result in constant low-dose exposure to these carcinogens. No previous studies have evaluated whether obesity modifies associations between multiple measures of PAHs and breast cancer incidence. METHODS: This population-based study included 1,006 postmenopausal women with first primary in situ or invasive breast cancer and 990 age-frequency matched controls. To evaluate effect modification by obesity (adult body mass index (BMI, kg/m2) and weight change) on multiple PAH measures (the biomarker PAH-DNA adducts, and long-term sources active cigarette smoking, living with a smoking spouse, grilled/smoked meat intake, residential synthetic log burning, and vehicular traffic), interaction contrast ratios (ICRs) for the additive scale, and ratio of odds ratios (RORs) with log-likelihood ratio tests (LRT) for the multiplicative scale, were determined using unconditional logistic regression. RESULTS: BMI modified the PAH-DNA adduct and postmenopausal breast cancer association on the additive (ICR: 0.49; 95% CI: 0.01, 0.96) and multiplicative (ROR: 1.56; 95% CI: 0.91, 2.68) scales. The odds ratio for detectable vs. non-detectable adducts was increased among women with BMI ≥25 (OR=1.34; 95% CI: 0.94, 1.92), but not in those with BMI <25 (OR=0.86; 95% CI: 0.57, 1.28) (LRT p=0.1). For most other PAH measures, the pattern of modification by BMI/weight gain was similar, but estimates were imprecise. CONCLUSIONS: The association between PAH-DNA adducts and breast cancer incidence may be elevated among overweight/obese women.

Response to, "On the origins of the linear no-threshold (LNT) dogma by means of untruths, artful dodges and blind faith.".

It is not true that successive groups of researchers from academia and research institutions-scientists who served on panels of the US National Academy of Sciences (NAS)-were duped into supporting a linear no-threshold model (LNT) by the opinions expressed in the genetic panel section of the 1956 "BEAR I" report. Successor reports had their own views of the LNT model, relying on mouse and human data, not fruit fly data. Nor was the 1956 report biased and corrupted, as has been charged in an article by Edward J. Calabrese in this journal. With or without BEAR I, the LNT model would likely have been accepted in the US for radiation protection purposes in the 1950's.

Polymorphisms in DNA repair genes, traffic-related polycyclic aromatic hydrocarbon exposure and breast cancer incidence.

Vehicular traffic polycyclic aromatic hydrocarbons (PAHs) have been associated with breast cancer incidence in epidemiologic studies, including our own. Because PAHs damage DNA by forming adducts and oxidative lesions, genetic polymorphisms that alter DNA repair capacity may modify associations between PAH-related exposures and breast cancer risk. Our goal was to examine the association between vehicular traffic exposure and breast cancer incidence within strata of a panel of nine biologically plausible nucleotide excision repair (NER) and base excision repair (BER) genotypes. Residential histories of 1,508 cases and 1,556 controls were assessed in the Long Island Breast Cancer Study Project between 1996 and 1997 and used to reconstruct residential traffic exposures to benzo[a]pyrene, as a proxy for traffic-related PAHs. Likelihood ratio tests from adjusted unconditional logistic regression models were used to assess multiplicative interactions. A gene-traffic interaction was evident (p = 0.04) for ERCC2 (Lys751); when comparing the upper and lower tertiles of 1995 traffic exposure estimates, the odds ratio (95% confidence interval) was 2.09 (1.13, 3.90) among women with homozygous variant alleles. Corresponding odds ratios for 1960-1990 traffic were also elevated nearly 2-3-fold for XRCC1(Arg194Trp), XRCC1(Arg399Gln) and OGG1(Ser326Cys), but formal multiplicative interaction was not evident. When DNA repair variants for ERCC2, XRCC1 and OGG1 were combined, among women with 4-6 variants, the odds ratios were 2.32 (1.22, 4.49) for 1995 traffic and 2.96 (1.06, 8.21) for 1960-1990 traffic. Our study is first to report positive associations between traffic-related PAH exposure and breast cancer incidence among women with select biologically plausible DNA repair genotypes.

Exposure to multiple sources of polycyclic aromatic hydrocarbons and breast cancer incidence.

BACKGROUND: Despite studies having consistently linked exposure to single-source polycyclic aromatic hydrocarbons (PAHs) to breast cancer, it is unclear whether single sources or specific groups of PAH sources should be targeted for breast cancer risk reduction. OBJECTIVES: This study considers the impact on breast cancer incidence from multiple PAH exposure sources in a single model, which better reflects exposure to these complex mixtures. METHODS: In a population-based case-control study conducted on Long Island, New York (N=1508 breast cancer cases/1556 controls), a Bayesian hierarchical regression approach was used to estimate adjusted posterior means and credible intervals (CrI) for the adjusted odds ratios (ORs) for PAH exposure sources, considered singly and as groups: active smoking; residential environmental tobacco smoke (ETS); indoor and outdoor air pollution; and grilled/smoked meat intake. RESULTS: Most women were exposed to PAHs from multiple sources, and the most common included active/passive smoking and grilled/smoked food intake. In multiple-PAH source models, breast cancer incidence was associated with residential ETS from a spouse (OR=1.20, 95%CrI=1.03, 1.40) and synthetic firelog burning (OR=1.29, 95%CrI=1.06, 1.57); these estimates are similar, but slightly attenuated, to those from single-source models. Additionally when we considered PAH exposure groups, the most pronounced significant associations included total indoor sources (active smoking, ETS from spouse, grilled/smoked meat intake, stove/fireplace use, OR=1.45, 95%CrI=1.02, 2.04). CONCLUSIONS: Groups of PAH sources, particularly indoor sources, were associated with a 30-50% increase in breast cancer incidence. PAH exposure is ubiquitous and a potentially modifiable breast cancer risk factor.

Vehicular Traffic-Related Polycyclic Aromatic Hydrocarbon Exposure and Breast Cancer Incidence: The Long Island Breast Cancer Study Project (LIBCSP).

BACKGROUND: Polycyclic aromatic hydrocarbons (PAHs) are widespread environmental pollutants, known human lung carcinogens, and potent mammary carcinogens in laboratory animals. However, the association between PAHs and breast cancer in women is unclear. Vehicular traffic is a major ambient source of PAH exposure. OBJECTIVES: Our study aim was to evaluate the association between residential exposure to vehicular traffic and breast cancer incidence. METHODS: Residential histories of 1,508 participants with breast cancer (case participants) and 1,556 particpants with no breast cancer (control participants) were assessed in a population-based investigation conducted in 1996-1997. Traffic exposure estimates of benzo[a]pyrene (B[a]P), as a proxy for traffic-related PAHs, for the years 1960-1995 were reconstructed using a model previously shown to generate estimates consistent with measured soil PAHs, PAH-DNA adducts, and CO readings. Associations between vehicular traffic exposure estimates and breast cancer incidence were evaluated using unconditional logistic regression. RESULTS: The odds ratio (95% CI) was modestly elevated by 1.44 (0.78, 2.68) for the association between breast cancer and long-term 1960-1990 vehicular traffic estimates in the top 5%, compared with below the median. The association with recent 1995 traffic exposure was elevated by 1.14 (0.80, 1.64) for the top 5%, compared with below the median, which was stronger among women with low fruit/vegetable intake [1.46 (0.89, 2.40)], but not among those with high fruit/vegetable intake [0.92 (0.53, 1.60)]. Among the subset of women with information regarding traffic exposure and tumor hormone receptor subtype, the traffic-breast cancer association was higher for those with estrogen/progesterone-negative tumors [1.67 (0.91, 3.05) relative to control participants], but lower among all other tumor subtypes [0.80 (0.50, 1.27) compared with control participants]. CONCLUSIONS: In our population-based study, we observed positive associations between vehicular traffic-related B[a]P exposure and breast cancer incidence among women with comparatively high long-term traffic B[a]P exposures, although effect estimates were imprecise. CITATION: Mordukhovich I, Beyea J, Herring AH, Hatch M, Stellman SD, Teitelbaum SL, Richardson DB, Millikan RC, Engel LS, Shantakumar S, Steck SE, Neugut AI, Rossner P Jr., Santella RM, Gammon MD. 2016. Vehicular traffic-related polycyclic aromatic hydrocarbon exposure and breast cancer incidence: the Long Island Breast Cancer Study Project (LIBCSP). Environ Health Perspect 124:30-38; http://dx.doi.org/10.1289/ehp.1307736.

Sources of polycyclic aromatic hydrocarbons are associated with gene-specific promoter methylation in women with breast cancer.

BACKGROUND: Tobacco smoke, diet and indoor/outdoor air pollution, all major sources of polycyclic aromatic hydrocarbons (PAHs), have been associated with breast cancer. Aberrant methylation may be an early event in carcinogenesis, but whether PAHs influence the epigenome is unclear, particularly in breast tissue where methylation may be most relevant. We aimed to evaluate the role of methylation in the association between PAHs and breast cancer. METHODS: In a population-based case-control study, we measured promoter methylation of 13 breast cancer-related genes in breast tumor tissue (n=765-851 cases) and global methylation in peripheral blood (1055 cases/1101 controls). PAH sources (current active smoking, residential environmental tobacco smoke (ETS), vehicular traffic, synthetic log burning, and grilled/smoked meat intake) were evaluated separately. Logistic regression was used to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: When comparing methylated versus unmethylated genes, synthetic log use was associated with increased ORs for CDH1 (OR=2.26, 95%CI=1.06-4.79), HIN1 (OR=2.14, 95%CI=1.34-3.42) and RARß (OR=1.80, 95%CI=1.16-2.78) and decreased ORs for BRCA1 (OR=0.44, 95%CI=0.30-0.66). Residential ETS was associated with decreased ORs for ESR1 (OR=0.74, 95%CI=0.56-0.99) and CCND2 methylation (OR=0.65, 95%CI=0.44-0.96). Current smoking and vehicular traffic were associated with decreased ORs for DAPK (OR=0.53, 95%CI=0.28-0.99) and increased ORs for TWIST1 methylation (OR=2.79, 95%CI=1.24-6.30), respectively. In controls, synthetic log use was inversely associated with LINE-1 (OR=0.59, 95%CI=0.41-0.86). DISCUSSION: PAH sources were associated with hypo- and hypermethylation at multiple promoter regions in breast tumors and LINE-1 hypomethylation in blood of controls. Methylation may be a potential biologic mechanism for the associations between PAHs and breast cancer incidence.

Indoor air pollution exposure from use of indoor stoves and fireplaces in association with breast cancer: a case-control study.

BACKGROUND: Previous studies suggest that polycyclic aromatic hydrocarbons (PAHs) may adversely affect breast cancer risk. Indoor air pollution from use of indoor stoves and/or fireplaces is an important source of ambient PAH exposure. However, the association between indoor stove/fireplace use and breast cancer risk is unknown. We hypothesized that indoor stove/fireplace use in a Long Island, New York study population would be positively associated with breast cancer and differ by material burned, and the duration and timing of exposure. We also hypothesized that the association would vary by breast cancer subtype defined by p53 mutation status, and interact with glutathione S-transferases GSTM1, T1, A1 and P1 polymorphisms. METHODS: Population-based, case-control resources (1,508 cases/1,556 controls) were used to conduct unconditional logistic regression to estimate adjusted odds ratios (OR) and 95% confidence intervals (CI). RESULTS: Breast cancer risk was increased among women reporting ever burning synthetic logs (which may also contain wood) in their homes (OR = 1.42, 95% CI 1.11, 1.84), but not for ever burning wood alone (OR = 0.93, 95% CI 0.77, 1.12). For synthetic log use, longer duration >7 years, older age at exposure (>20 years; OR = 1.65, 95% CI 1.02, 2.67) and 2 or more variants in GSTM1, T1, A1 or P1 (OR = 1.71, 95% CI 1.09, 2.69) were associated with increased risk. CONCLUSIONS: Burning wood or synthetic logs are both indoor PAH exposure sources; however, positive associations were only observed for burning synthetic logs, which was stronger for longer exposures, adult exposures, and those with multiple GST variant genotypes. Therefore, our results should be interpreted with care and require replication.

Imputation method for lifetime exposure assessment in air pollution epidemiologic studies.

BACKGROUND: Environmental epidemiology, when focused on the life course of exposure to a specific pollutant, requires historical exposure estimates that are difficult to obtain for the full time period due to gaps in the historical record, especially in earlier years. We show that these gaps can be filled by applying multiple imputation methods to a formal risk equation that incorporates lifetime exposure. We also address challenges that arise, including choice of imputation method, potential bias in regression coefficients, and uncertainty in age-at-exposure sensitivities. METHODS: During time periods when parameters needed in the risk equation are missing for an individual, the parameters are filled by an imputation model using group level information or interpolation. A random component is added to match the variance found in the estimates for study subjects not needing imputation. The process is repeated to obtain multiple data sets, whose regressions against health data can be combined statistically to develop confidence limits using Rubin's rules to account for the uncertainty introduced by the imputations. To test for possible recall bias between cases and controls, which can occur when historical residence location is obtained by interview, and which can lead to misclassification of imputed exposure by disease status, we introduce an "incompleteness index," equal to the percentage of dose imputed (PDI) for a subject. "Effective doses" can be computed using different functional dependencies of relative risk on age of exposure, allowing intercomparison of different risk models. To illustrate our approach, we quantify lifetime exposure (dose) from traffic air pollution in an established case-control study on Long Island, New York, where considerable in-migration occurred over a period of many decades. RESULTS: The major result is the described approach to imputation. The illustrative example revealed potential recall bias, suggesting that regressions against health data should be done as a function of PDI to check for consistency of results. The 1% of study subjects who lived for long durations near heavily trafficked intersections, had very high cumulative exposures. Thus, imputation methods must be designed to reproduce non-standard distributions. CONCLUSIONS: Our approach meets a number of methodological challenges to extending historical exposure reconstruction over a lifetime and shows promise for environmental epidemiology. Application to assessment of breast cancer risks will be reported in a subsequent manuscript.

Confidence intervals after multiple imputation: combining profile likelihood information from logistic regressions.

In the logistic regression analysis of a small-sized, case-control study on Alzheimer's disease, some of the risk factors exhibited missing values, motivating the use of multiple imputation. Usually, Rubin's rules (RR) for combining point estimates and variances would then be used to estimate (symmetric) confidence intervals (CIs), on the assumption that the regression coefficients were distributed normally. Yet, rarely is this assumption tested, with or without transformation. In analyses of small, sparse, or nearly separated data sets, such symmetric CI may not be reliable. Thus, RR alternatives have been considered, for example, Bayesian sampling methods, but not yet those that combine profile likelihoods, particularly penalized profile likelihoods, which can remove first order biases and guarantee convergence of parameter estimation. To fill the gap, we consider the combination of penalized likelihood profiles (CLIP) by expressing them as posterior cumulative distribution functions (CDFs) obtained via a chi-squared approximation to the penalized likelihood ratio statistic. CDFs from multiple imputations can then easily be averaged into a combined CDF c , allowing confidence limits for a parameter ß at level 1 - α to be identified as those ß* and ß** that satisfy CDF c (ß*) = α ∕ 2 and CDF c (ß**) = 1 - α ∕ 2. We demonstrate that the CLIP method outperforms RR in analyzing both simulated data and data from our motivating example. CLIP can also be useful as a confirmatory tool, should it show that the simpler RR are adequate for extended analysis. We also compare the performance of CLIP to Bayesian sampling methods using Markov chain Monte Carlo. CLIP is available in the R package logistf.

Exposure to traffic emissions: associations with biomarkers of antioxidant status and oxidative damage.

BACKGROUND: Oxidative stress has been implicated as a possible mechanism for adverse health effects associated with traffic emissions. We examined the association of an estimate of traffic emissions with blood biomarkers of antioxidant capacity (glutathione, glutathione peroxidase, trolox-equivalent antioxidant capacity) and oxidative damage (thiobarbituric acid-reactive substances (TBARS)) among 1810 healthy women, randomly selected from Erie and Niagara Counties in Western New York. METHODS: A geographic traffic emission and meteorological dispersion model was used to estimate annual polycyclic aromatic hydrocarbon (PAH) exposure from traffic emissions for each woman based on her residence at the time of study. Associations of traffic-related PAH exposure with measures of oxidative stress and antioxidant capacity were examined in multiple regression analyses with adjustment for potential confounders. RESULTS: Higher traffic-related PAH exposure was associated with decreased glutathione and increased glutathione peroxidase. Stronger associations between traffic-related PAH exposure and levels of glutathione and glutathione peroxidase were suggested among nonsmoking women without secondhand smoke exposure, especially among premenopausal nonsmoking women. Associations were also stronger for measurements made in warmer months. CONCLUSIONS: These findings suggest that PAHs or other components of traffic emissions may impact anti-oxidative capacity among healthy women, particularly premenopausal non-smokers without secondhand smoke exposure.