Person:

Schwartz, Joel

Results from air pollution exposure assessment studies suggest that ambient fine particles [particulate matter with aerodynamic diameter ≤ 2.5 μg (PM2.5)], but not ambient gases, are strong proxies of corresponding personal exposures. For particles, the strength of the personal–ambient association can differ by particle component and level of home ventilation. For gases, however, such as ozone (O3), nitrogen dioxide (NO2), and sulfur dioxide (SO2), the impact of home ventilation on personal–ambient associations is untested. We measured 24-hr personal exposures and corresponding ambient concentrations to PM2.5, sulfate (SO42−), elemental carbon, O3, NO2, and SO2 for 10 nonsmoking older adults in Steubenville, Ohio. We found strong associations between ambient particle concentrations and corresponding personal exposures. In contrast, although significant, most associations between ambient gases and their corresponding exposures had low slopes and R2 values; the personal–ambient NO2 association in the fall season was moderate. For both particles and gases, personal–ambient associations were highest for individuals spending most of their time in high- compared with low-ventilated environments. Cross-pollutant models indicated that ambient particle concentrations were much better surrogates for exposure to particles than to gases. With the exception of ambient NO2 in the fall, which showed moderate associations with personal exposures, ambient gases were poor proxies for both gas and particle exposures. In combination, our results suggest that a) ventilation may be an important modifier of the magnitude of effect in time-series health studies, and b) results from time-series health studies based on 24-hr ambient concentrations are more readily interpretable for particles than for gases.

Background: Extremes of temperature are associated with short-term increases in daily mortality. Objectives: We set out to identify subpopulations and mortality causes with increased susceptibility to temperature extremes. Methods: We conducted a case-only analysis using daily mortality and hourly weather data from 50 U.S. cities for the period 1989–2000, covering a total of 7,789,655 deaths. We used distributions of daily minimum and maximum temperature in each city to define extremely hot days (≥ 99th percentile) and extremely cold days (≤ 1st percentile), respectively. For each (hypothesized) effect modifier, a city-specific logistic regression model was fitted and an overall estimate calculated in a subsequent meta-analysis. Results: Older subjects [odds ratio (OR) = 1.020; 95% confidence interval (CI), 1.005–1.034], diabetics (OR = 1.035; 95% CI, 1.010–1.062), blacks (OR = 1.037; 95% CI, 1.016–1.059), and those dying outside a hospital (OR = 1.066; 95% CI, 1.036–1.098) were more susceptible to extreme heat, with some differences observed between those dying from a cardiovascular disease and other decedents. Cardiovascular deaths (OR = 1.053; 95% CI, 1.036–1.070), and especially cardiac arrest deaths (OR =1.137; 95% CI, 1.051–1.230), showed a greater relative increase on extremely cold days, whereas the increase in heat-related mortality was marginally higher for those with coexisting atrial fibrillation (OR = 1.059; 95% CI, 0.996–1.125). Conclusions: In this study we identified several subpopulations and mortality causes particularly susceptible to temperature extremes. This knowledge may contribute to establishing health programs that would better protect the vulnerable.

Several studies have reported significant health effects of air pollution even at low levels of air pollutants, but in most of theses studies linear nonthreshold relations were assumed. We investigated the exposure–response association between ambient particles and mortality in the 22 European cities participating in the APHEA (Air Pollution and Health—A European Approach) project, which is the largest available European database. We estimated the exposure–response curves using regression spline models with two knots and then combined the individual city estimates of the spline to get an overall exposure–response relationship. To further explore the heterogeneity in the observed city-specific exposure–response associations, we investigated several city descriptive variables as potential effect modifiers that could alter the shape of the curve. We conclude that the association between ambient particles and mortality in the cities included in the present analysis, and in the range of the pollutant common in all analyzed cities, could be adequately estimated using the linear model. Our results confirm those previously reported in Europe and the United States. The heterogeneity found in the different city-specific relations reflects real effect modification, which can be explained partly by factors characterizing the air pollution mix, climate, and the health of the population.

Bioaerosol concentrations in office environments and their roles in causing building-related symptoms have drawn much attention in recent years. Most bioaerosol studies have been cross-sectional. We conducted a longitudinal study to examine the characteristics of airborne fungal populations and correlations with other environmental parameters in office environments. We investigated four office buildings in Boston, Massachusetts, during 1 year beginning May 1997, recruiting 21 offices with open workstations. We conducted intensive bioaerosol sampling every 6 weeks resulting in 10 sets of measurement events at each workstation, and recorded relative humidity, temperature, and CO2 concentrations continuously. We used principal component analysis (PCA) to identify groups of culturable fungal taxa that covaried in air. Four major groupings (PCA factors) were derived where the fungal taxa in the same groupings shared similar ecological requirements. Total airborne fungal concentrations varied significantly by season (highest in summer, lowest in winter) and were positively correlated with relative humidity and negatively related to CO2 concentrations. The first and second PCA factors had similar correlations with environmental variables compared with total fungi. The results of this study provide essential information on the variability within airborne fungal populations in office environments over time. These data also provide background against which cross-sectional data can be compared to facilitate interpretation. More studies are needed to correlate airborne fungi and occupants' health, controlling for seasonal effects and other important environmental factors.

Background: Given the association between iron deficiency and lead absorption, we hypothesized that variants in iron metabolism genes would predict higher blood lead levels in young children. Objective: We examined the association between common missense variants in the hemochromatosis (HFE) and transferrin (TF) genes and blood lead levels in 422 Mexican children. Methods: Archived umbilical cord blood samples were genotyped for HFE (H63D and C282Y) and TF (P570S) variants. Blood lead was measured at 24, 30, 36, 42, and 48 months of age. A total of 341 subjects had at least one follow-up blood lead level available and data available on covariates of interest for inclusion in the longitudinal analyses. We used random-effects models to examine the associations between genotype (HFE, TF, and combined HFE + TF) and repeated measures of blood lead, adjusting for maternal blood lead at delivery and child’s concurrent anemia status. Results: Of 422 children genotyped, 17.7, 3.3, and 18.9% carried the HFE H63D, HFE C282Y, and TF P570S variants, respectively. One percent of children carried both the HFE C282Y and TF P570S variants, and 3% of children carried both the HFE H63D and TF P570S variants. On average, carriers of either the HFE (β = 0.11, p = 0.04) or TF (β = 0.10, p = 0.08) variant had blood lead levels that were 11% and 10% higher, respectively, than wild-type subjects. In models examining the dose effect, subjects carrying both variants (β = 0.41, p = 0.006) had blood lead 50% higher than wild-type subjects and a significantly higher odds of having a blood lead level > 10 μg/dL (odds ratio = 18.3; 95% confidence interval, 1.9–177.1). Conclusions: Iron metabolism gene variants modify lead metabolism such that HFE variants are associated with increased blood lead levels in young children. The joint presence of variant alleles in the HFE and TF genes showed the greatest effect, suggesting a gene-by-gene-by-environment interaction.

Nursing infants may be exposed to lead from breast milk, but relatively few data exist with which to evaluate and quantify this relationship. This route of exposure constitutes a potential infant hazard from mothers with current ongoing exposure to lead as well as from mothers who have been exposed previously due to the redistribution of cumulative maternal bone lead stores. We studied the relationship between maternal breast milk lead and infant blood lead levels among 255 mother–infant pairs exclusively or partially breast-feeding through 1 month of age in Mexico City. A rigorous, well-validated technique was used to collect, prepare, and analyze the samples of breast milk to minimize the potential for environmental contamination and maximize the percent recovery of lead. Umbilical cord and maternal blood lead were measured at delivery; 1 month after delivery (± 5 days) maternal blood, bone, and breast milk and infant blood lead levels were obtained. Levels of lead at 1 month postpartum were, for breast milk, 0.3–8.0 μg/L (mean ± SD, 1.5 ± 1.2); maternal blood lead, 2.9–29.9 μg/dL (mean ± SD, 9.4 ± 4.5); and infant blood lead, 1.0–23.1 μg/dL (mean ± SD, 5.5 ± 3.0). Infant blood lead at 1 month postpartum was significantly correlated with umbilical cord (Spearman correlation coefficient rS = 0.40, p < 0.0001) and maternal (rS = 0.42, p < 0.0001) blood lead at delivery and with maternal blood (rS = 0.67, p < 0.0001), patella (rS = 0.19, p = 0.004), and breast milk (rS = 0.32, p < 0.0001) lead at 1 month postpartum. Adjusting for cord blood lead, infant weight change, and reported breast-feeding status, a difference of approximately 2 μg/L (ppb; from the midpoint of the lowest quartile to the midpoint of the highest quartile) breast milk lead was associated with a 0.82 μg/dL increase in blood lead for breast-feeding infants at 1 month of age. Breast milk lead accounted for 12% of the variance of infant blood lead levels, whereas maternal blood lead accounted for 30%. Although these levels of lead in breast milk were low, they clearly have a strong influence on infant blood lead levels over and above the influence of maternal blood lead. Additional information on the lead content of dietary alternatives and interactions with other nutritional factors should be considered. However, because human milk is the best and most complete nutritional source for young infants, breast-feeding should be encouraged because the absolute values of the effects are small within this range of lead concentrations.

Background: Cumulative exposure to lead has been shown to be associated with depression of electrocardiographic conduction, such as QT interval (time from start of the Q wave to end of the T wave). Because iron can enhance the oxidative effects of lead, we examined whether polymorphisms in iron metabolism genes [hemochromatosis ((HFE)), transferrin ((TF)) C2, and heme oxygenase-1 ((HMOX-1))] increase susceptibility to the effects of lead on QT interval in 613 community-dwelling older men. Methods: We used standard 12-lead electrocardiograms, K-shell X-ray fluorescence, and graphite furnace atomic absorption spectrometry to measure QT interval, bone lead, and blood lead levels, respectively. Results: A one-interquartile-range increase in tibia lead level (13 μg/g) was associated with a 11.35-msec [95% confidence interval (CI), 4.05–18.65 msec] and a 6.81-msec (95% CI, 1.67–11.95 msec) increase in the heart-rate–corrected QT interval among persons carrying long (HMOX-1) alleles and at least one copy of an (HFE) variant, respectively, but had no effect in persons with short and middle (HMOX-1) alleles and the wild-type HFE genotype. The lengthening of the heart-rate–corrected QT interval with higher tibia lead and blood lead became more pronounced as the total number (0 vs. 1 vs. ≥2) of gene variants increased (tibia, (p)-trend = 0.01; blood, (p)-trend = 0.04). This synergy seems to be driven by a joint effect between (HFE) variant and (HMOX-1) L alleles. Conclusion: We found evidence that gene variants related to iron metabolism increase the impacts of low-level lead exposure on the prolonged QT interval. This is the first such report, so these results should be interpreted cautiously and need to be independently verified.

Background and Objectives: We have previously shown that reduced defenses against oxidative stress due to glutathione S-transferase M1 (GSTM1) deletion modify the effects of PM[2.5] (fine-particulate air pollution of < 2.5 μm in aerodynamic diameter) on heart rate variability (HRV) in a cross-sectional analysis of the Normative Aging Study, an elderly cohort. We have extended this to include a longitudinal analysis with more subjects and examination of the GT short tandem repeat polymorphism in the heme oxygenase-1 (HMOX-1) promoter. Methods: HRV measurements were taken on 539 subjects. Linear mixed effects models were fit for the logarithm of HRV metrics—including standard deviation of normal-to-normal intervals (SDNN), high frequency (HF), and low frequency (LF)—and PM2.5 concentrations in the 48 hr preceding HRV measurement, controlling for confounders and a random subject effect. Results: PM2.5 was significantly associated with SDNN (p = 0.04) and HF (p = 0.03) in all subjects. There was no association in subjects with GSTM1, whereas there was a significant association with SDNN, HF, and LF in subjects with the deletion. Similarly, there was no association with any HRV measure in subjects with the short repeat variant of HMOX-1, and significant associations in subjects with any long repeat. We found a significant three-way interaction of PM[2.5] with GSTM1 and HMOX-1 determining SDNN (p = 0.008), HF (p = 0.01) and LF (p = 0.04). In subjects with the GSTM1 deletion and the HMOX-1 long repeat, SDNN decreased by 13% [95% confidence interval (CI), −21% to −4%], HF decreased by 28% (95% CI, −43% to −9%), and LF decreased by 20% (95% CI, −35% to −3%) per 10 μg/m3 increase in PM. Conclusions: Oxidative stress is an important pathway for the autonomic effects of particles.

Background: Altered patterns of gene expression mediate the effects of particulate matter (PM) on human health, but mechanisms through which PM modifies gene expression are largely undetermined.Objectives We aimed at identifying short- and long-term effects of PM exposure on DNA methylation, a major genomic mechanism of gene expression control, in workers in an electric furnace steel plant with well-characterized exposure to PM with aerodynamic diameters < 10 μm (PM10). Methods: We measured global genomic DNA methylation content estimated in Alu and long interspersed nuclear element-1 (LINE-1) repeated elements, and promoter DNA methylation of iNOS (inducible nitric oxide synthase), a gene suppressed by DNA methylation and induced by PM exposure in blood leukocytes. Quantitative DNA methylation analysis was performed through bisulfite PCR pyrosequencing on blood DNA obtained from 63 workers on the first day of a work week (baseline, after 2 days off work) and after 3 days of work (postexposure). Individual PM10 exposure was between 73.4 and 1,220 μg/m3. Results: Global methylation content estimated in Alu and LINE-1 repeated elements did not show changes in postexposure measures compared with baseline. PM10 exposure levels were negatively associated with methylation in both Alu [β = −0.19 %5-methylcytosine (%5mC); p = 0.04] and LINE-1 [β = −0.34 %5mC; p = 0.04], likely reflecting long-term PM10 effects. iNOS promoter DNA methylation was significantly lower in postexposure blood samples compared with baseline (difference = −0.61 %5mC; p = 0.02). Conclusions: We observed changes in global and gene specific methylation that should be further characterized in future investigations on the effects of PM.

Background: Although studies have documented the association between heart rate variability (HRV) and ambient particulate exposures, the association between HRV, especially at night, and metal-rich, occupational particulate exposures remains unclear. Objective: Our goal in this study was to investigate the association between long-duration HRV, including nighttime HRV, and occupational PM2.5 exposures. Methods: We used 24-hr ambulatory electrocardiograms (ECGs) to monitor 36 male boilermaker welders (mean age of 41 years) over a workday and nonworkday. ECGs were analyzed for HRV in the time domain; rMSSD (square root of the mean squared differences of successive intervals), SDNN (SD of normal-to-normal intervals over entire recording), and SDNNi (SDNN for all 5-min segments) were summarized over 24-hr, day (0730–2130 hours), and night (0000–0700 hours) periods. PM2.5 (particulate matter with an aerodynamic diameter ≤ 2.5 μm) exposures were monitored over the workday, and 8-hr time-weighted average concentrations were calculated. We used linear regression to assess the associations between HRV and workday particulate exposures. Matched measurements from a nonworkday were used to control for individual cardiac risk factors. Results: Mean (± SD) PM2.5 exposure was 0.73 ± 0.50 mg/m3 and ranged from 0.04 to 2.70 mg/m3. We observed a consistent inverse exposure–response relationship, with a decrease in all HRV measures with increased PM2.5 exposure. However, the decrease was most pronounced at night, where a 1-mg/m3 increase in PM2.5 was associated with a change of −8.32 [95% confidence interval (CI), −16.29 to −0.35] msec nighttime rMSSD, −14.77 (95% CI, −31.52 to 1.97) msec nighttime SDNN, and −8.37 (95% CI, −17.93 to 1.20) msec nighttime SDNNi, after adjusting for nonworking nighttime HRV, age, and smoking. Conclusion: Metal-rich particulate exposures were associated with decreased long-duration HRV, especially at night. Further research is needed to elucidate which particulate metal constituent is responsible for decreased HRV.