P-0111 - Metals and breast cancer risk: a prospective study using toenail metal biomarkers
Abstract Control Number
1510
Abstract Body
Background: Certain metals are known or suspected carcinogens and have been found in breast tissue samples. Toenails are a stable matrix that reflect exposure 6-12 months before collection and measurements correlate well over time. We prospectively examined a large panel of toenail metals in relation to breast cancer risk and were the first to consider whether multiple metal biomarkers jointly influence risk. Methods: The Sister Study is prospective cohort of 50,884 women who enrolled between 2003-2009 with follow-up for breast cancer through September 2016. We measured 15 metals in toenails collected at enrollment using a case-cohort design of 1,495 cases and a randomly-selected sub-cohort of 1,605 women. For individual metals, multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox regression with robust variance. We examined associations overall and stratified by race, estrogen receptor (ER), and menopausal status. Quantile g-computation was used to examine joint associations between multiple metals and breast cancer risk. Results: In individual metal models, arsenic was associated with a non-linear increase in breast cancer risk (2nd vs. 1st tertile, HR=1.22; 95% CI: 1.01-1.49). This association was stronger for ER+ breast cancer (HR=1.31; 95% CI: 1.06-1.62). In non-Hispanic Blacks, zinc was associated with an elevated risk (3rd vs. 1st tertile, HR=1.40; 95% CI: 0.97-2.02). Molybdenum was inversely associated with breast cancer overall (3rd vs. 1st tertile, HR=0.83; 95% CI: 0.68-1.00) and particularly for ER- breast cancer (3rd vs. 1st tertile, HR=0.57; 95% CI: 0.37-0.87). A simultaneous increase in multiple metals was not associated with breast cancer risk. Conclusions: In this prospective study considering multiple toenail metals in relation to breast cancer, we found that individual metals and metal mixtures were not consistently associated with a higher risk. However, a few metals appeared to be related to breast cancer risk in certain subgroups.
P-0040 - Comparison of PM2.5 exposure estimates in the REGARDS cohort: understanding differences by community type and exposure assignment choices
Abstract Control Number
1248
Abstract Body
Background: There is biologic rationale for associations between ambient PM2.5 exposure and type 2 diabetes. However, studies of these associations demonstrate mixed results, potentially due to differences in: PM2.5 estimation by community types and regions; PM2.5 estimation methods that optimize temporal vs. spatial variability; and exposure lags and durations assigned to individuals for evaluation with diabetes outcomes. Methods: We evaluated several PM2.5 data sources and exposure assignment choices for 10,332 participants free of diabetes at baseline (2003-2007) and with follow-up data on diabetes in the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort. We calculated exposure durations of 2-weeks, 30-days, and 1-year; lagged 1-day, 6-months, and 1-year prior to baseline, and evaluated these by: US region (Northeast, South, Midwest, and West); community type (high density urban, low density urban, suburban and small town, and rural); and year for two sources of PM2.5: CDC EPA Downscaler model and CDC Wonder data modeled from NASA satellite observations and EPA monitor data. Results: Participants in the analysis had a mean (SD) age of 63.0 (8.5) years, were 55.8% female; 32.4% black. The mean (SD) PM2.5 estimates from CDC Wonder were 13.5 (4.2) µg/m3, 13.5 (3.6) µg/m3, and 13.3 (2.0) µg/m3, for 2-week, 30-day, and 1-year exposure periods, respectively. One-way analysis of variance (ANOVA) of PM2.5 exposure estimates of all durations showed significant differences (p ≤ 0.01) by community type, region, and year. Differences by region and community type became more pronounced with longer exposure durations. Analysis of additional exposure lags and durations is in progress. Conclusions: These results suggest that exposure assignment choices can either exacerbate or mitigate underlying spatial differences in this cohort, which can lead to differential associations between PM2.5 and diabetes. Future work should focus on better exposure classification in order to more clearly estimate this association.
P-1046 - Exposure assessment of PM2.5 for entire population in the region of interest using sensor-based air monitoring system and similar time-activity groups
Abstract Control Number
3261
Abstract Body
PM2.5 is an air pollutant that can cause various adverse health effects. Although the fixed ambient air monitoring stations provides ambient PM2.5 concentration within a community, it is still weak to assess actual exposure of population account for time-activity patterns. However, the exposure of the entire population in a region of interest may be estimated by classifying the population according to time-activity pattern and modeling their exposure. In this study, we tried to suggest the methodology to assess exposure to PM2.5 of entire population in a region of interest. The five field technicians representing similar time-activity groups (STG) of preschool children, students, housewives, office workers, and the elderly conducted exposure simulation with PM2.5 personal exposure monitor in Guro-gu, Seoul, Korea. The PM2.5 exposure concentrations (cs) were modeled by interpolation (point in polygon, inverse distance weighted and ordinary kriging) and regression model using GPS data and sensor-based air monitoring instruments network and compared with MicroPEM data (cm). The exposure of the entire population to PM2.5 was estimated by population-weighted average through Monte-Carlo simulation. The elderly had the highest average cm follows by office workers, housewives, preschool children, and students. The correlation between c¬m and cs was good in order of ordinary kriging (R2=0.822), inverse distance weighted (R2=0.747), and point in polygon method (R2=0.721). The 33.8% of the entire population exposed to PM2.5 higher than Atmospheric Environmental Standard of PM2.5 for 24-hour average. In this study, the possibility of assessing the exposure of the entire population for real-time and long-term cumulative exposure was suggested by applying this methodology, and it is expected that the exposure surveillance system can be developed based on these results.
P-1044 - Characterization of particulate matter (PM) species in an area impacted by aggregate mining north of San Antonio, TX
Abstract Control Number
2906
Abstract Body
Background: Aggregate and limestone mining in counties - especially Bexar and Comal, north of the city of San Antonio have been a cause of health concern recently. Aggregate mining particularly in residential areas can be problematic due to heavy truck traffic transporting the material resulting in vehicular air pollution as well.
Methods: PM species were sampled at four locations north of San Antonio. The data was collected using a TSI Air Quality Sampler that sampled PM1, PM2.5, PM10, wind speed, wind direction, temperature, and relative humidity. Continuous data (1 minute averages) was recorded for the entire study period. The instrument was stationed at every location for a period of 7 days. The four locations were a ranch, open field, residential compound, and an elementary school. The sampling was conducted in August and September 2019.
Results: The PM1 and PM2.5 levels were low at all the four sites in contrast to the PM10 levels. This suggests that the PM in Bexar and Comal Counties are impacted by mining activities primarily. For example, the seven day average for PM2.5 was about 8.6 ug/m3 at the ranch and PM10 values were around 15.8 ug/m3. PM species were highest at the residential compound due to the close proximity to an active mining area.
Conclusions: Mining activities for limestone and aggregates should be limited in areas that are away from residential locations to minimize the respiratory exposure burden of the local population. More sampling needs to be done in other seasons as well.
Methods: PM species were sampled at four locations north of San Antonio. The data was collected using a TSI Air Quality Sampler that sampled PM1, PM2.5, PM10, wind speed, wind direction, temperature, and relative humidity. Continuous data (1 minute averages) was recorded for the entire study period. The instrument was stationed at every location for a period of 7 days. The four locations were a ranch, open field, residential compound, and an elementary school. The sampling was conducted in August and September 2019.
Results: The PM1 and PM2.5 levels were low at all the four sites in contrast to the PM10 levels. This suggests that the PM in Bexar and Comal Counties are impacted by mining activities primarily. For example, the seven day average for PM2.5 was about 8.6 ug/m3 at the ranch and PM10 values were around 15.8 ug/m3. PM species were highest at the residential compound due to the close proximity to an active mining area.
Conclusions: Mining activities for limestone and aggregates should be limited in areas that are away from residential locations to minimize the respiratory exposure burden of the local population. More sampling needs to be done in other seasons as well.
P-0033 - Lower placental iodine concentrations are linked with higher concentrations of ambient PM2.5 exposure during the last trimester of pregnancy.
Abstract Control Number
2790
Abstract Body
Background - The essential trace element iodine is needed for an optimal (neuro)-development of the fetus via the production of thyroid hormones. Recent findings indicate that exposure to ambient air pollution was linked with mild thyroid dysfunction during pregnancy. We hypothesize that air pollution might alter the placental iodine concentrations during gestation. Methods -We determined the placental iodine concentrations in 470 mother newborn pairs included in the ENVIRONAGE birth cohort. Maternal residential PM2.5 (particulate matter with a diameter < 2.5 µm), NO2, and black carbon concentrations were determined during the pregnancy using a high-resolution air pollution model. Using distributed lag nonlinear models (DLNM), we modeled the gestational week-specific association between placental iodine concentrations and air pollutants. Results - Significant inverse associations were observed between gestational exposure to PM2.5 at weeks 28 to 35 and placental iodine concentrations. Cumulative estimates over the trimesters of pregnancy showed that in the third trimester of pregnancy (week 27 until delivery) an increase of 5 µg/m³ in PM2.5 exposure was associated with a decrease of 0.85 µg/kg in placental iodine concentration (95%CI: -1.56 to -0.14). These associations were adjusted for maternal pre-pregnancy BMI, gestational weight gain, household smoking behavior, maternal alcohol consumption, maternal education, maternal age, vitamin use, gestational age, date and season at delivery, and newborns’ sex. No significance was found between placental iodine load and the ambient NO2 or black carbon exposure.Conclusions- Gestational exposure to PM2.5 is linked with a lower placental iodine concentration. This decrease indicates that ambient air pollution might interfere with the normal uptake mechanisms of iodine, which could results in worse neurocognitive health outcomes later in life.
P-0760 - Linkage of occupational history records and medical screening examinations as a tool for assessing the long-term health impacts of wildland firefighting
Abstract Control Number
2237
Abstract Body
Background. Wildland firefighters (WFFs) work under intense and demanding conditions in the protection of human health, life, and property. Air pollutant exposures, heat, noise, disrupted sleep, emotional and psychological stress, and extreme physical exertion each may have short-term consequences for WFFs. Although countless population-based studies have established the long-term consequences of these exposures individually, to date little research has been devoted to their chronic effects in WFFs. The health and fitness of WFFs and the duration and intensity of their varied exposures combined with their limited use of personal protective equipment make WFFs a unique population in need of study. Methods. Occupational history as a WFF was assessed using Incident Qualification and Certification System (IQCS) responder records. These records contain information on specific fires to which a WFF was assigned, the duration of the assignment, and jobs for which a WFF is qualified and the number of times those jobs were performed. IQCS records were linked to Department of the Interior Wildland Fire Medical Standards Program medical screening examinations performed between 2014 and 2017. Results. Between 2014 and 2017, over 10,000 prospective and current WFFs completed comprehensive medical screening examinations to determine fitness for arduous duty firefighting. The median age was 33 years, and 85% of participants were male. Measured median systolic and diastolic blood pressures were 122 and 78 mm Hg, respectively, and 13% had an abnormal resting electrocardiogram. Forty-one percent of participants had available IQCS occupational history records.Conclusions. Preliminary analyses emphasized cardiovascular health among WFFs, and future work will investigate other health measures and their association with occupational history. The project establishes a framework for expanded studies of the occupational health risks linked to wildland firefighting, and findings have the potential to guide future screening and surveillance programs.
P-0074 - Gene-Environment Interaction of Residential Greenness and FOXO on Mortality among Older Adults
Abstract Control Number
2108
Abstract Body
Background The Forkhead box O (FOXO) gene is a candidate longevity gene. Residential greenness is an important built environment factor strongly associated with mortality. There was no previous study on the interaction between FOXO and residential greenness based on our knowledge. Methods We studied 3,179 participants aged 65 and older from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). We measured residential greenness by satellite derived Normalized Difference Vegetation Index (NDVI) using a 500-m radius around each residential address. We calculated contemporaneous NDVI, cumulative NDVI and changes in NDVI over time. We used adjusted Cox-proportional hazard regression models to assess main effects and interaction of FOXO SNPs and residential greenness on mortality risk. Results We found participants with two minor allele copies of FOXO3A SNPs had lower mortality risk than those with zero copy (HR: 0.803 95% CI: 0.654, 0.987 for rs4946936, HR: 0.807 95% CI: 0.669, 0.974 for rs2802292, HR: 0.803 95%CI: 0.666, 0.968 for rs2253310). We found no mortality difference among different genotypes for FOXO1A SNPs rs17630266, rs2755209 and rs2755213. Higher contemporaneous NDVI was associated with lower mortality risk (HR: 0.887 95% CI: 0.863, 0.911 for 0.1 unit of NDVI). The protective effect of NDVI was stronger among participants with two minor allele copies of rs2802292 SNP compared with the ones with zero copy (Interaction term P<0.05), while not different between participants with one copy and zero copy.Conclusions We found gene-environment interaction between FOXO and residential greenness on mortality in this population study. A higher level of greenness may interact with FOXO pathways.
P-0897 - Short-term PM2.5 exposure and acute incidence of myocardial infarction a time-stratified case-crossover study in China
Abstract Control Number
1997
Abstract Body
Background Myocardial infarction (MI) and ambient fine particulate matter (PM2.5) pollution are two global public health concerns. Evidence investigating the association between PM2.5 and acute incidence of MI in developing countries is limited. Methods A multicenter study based on a time-stratified case-crossover design including 36,679 cases from MI incidence registry data and PM2.5 site monitoring data was conducted. Results With a 10 μg/m3 increase in PM2.5 concentration, there was an increase of 0.98% (0.40%, 1.57%) in acute incidence risk of MI on day lag02. The corresponding values for males and individuals aged over 74 years were 1.58% (95% CI: 0.82%, 2.35%) and 1.19% (95% CI: 0.35%, 2.05%) respectively, indicating higher risks than other groups. The non-linear concentration-response curve indicated a steeper slope under daily PM2.5 below 50μg/m3 and the marginal avoided premature morbidity attributed to per 10μg/m3 reduction became larger under the current air quality standard.Conclusion This study is the first multicenter study to examine the association between the acute incidence of MI and short-term exposure to PM2.5 in China. We provide solid evidence that PM2.5 is a risk factor for accelerating MI incidence. A susceptible population was identified. The robust findings from this study may suggest the necessity for a continuous reduction of PM2.5 concentration from the perspectives of public health.
P-0171 - Neighborhood Socioeconomic Status, Long-Term Exposure to Particulate Matter, and Risk of Cardiovascular Disease and Mortality in the Nurses’ Health Study
Abstract Control Number
1878
Abstract Body
Background: Although associations between particulate matter <2.5 microns (PM2.5) and cardiovascular disease (CVD) and mortality are well-established, less is known regarding the joint impact of PM2.5 and neighborhood socioeconomic status (nSES). Our objective was to investigate this interaction in a nationwide cohort of U.S. women. Methods: We used time-varying Cox proportional hazards models, conditioned on age and calendar time, to assess main and interaction effects of PM2.5 and nSES on risk of CVD (stroke, myocardial infarction) and mortality among 100,257 women in the Nurses’ Health Study between 1986 and 2008. Incident CVD (n=6,445) and mortality (n=10,186) cases were ascertained from medical or death record reviews. We created Census tract-level nSES scores by summing z-scores (where increasing scores were associated with affluence) of selected nSES metrics (e.g., race, education, income, home value, nativity, unemployment), and calculated time-varying 24-month average PM2.5 exposure using residential address history. Models were adjusted for time-varying demographic, lifestyle (e.g., diet, physical activity, smoking), and individual-level SES factors. Results: In multivariable adjusted models, increases in nSES (Hazard Ratio [HR]CVD: 0.98, 95% Confidence Interval [CI]: 0.97, 0.99; HRmortality: 0.99, 95% CI: 0.99, 1.00, per 1 unit increase) and PM2.5 (HRCVD: 1.03, 95% CI: 0.95, 1.12; HRmortality: 1.04, 95% CI: 0.97, 1.11, per 10 µg/m3 increase) were associated with incident CVD and mortality rates, although the associations with PM2.5 did not reach statistical significance. The interaction between PM2.5 and nSES was statistically significant for CVD risk (p<0.001) and mortality (p<0.013); associations with mortality were strongest among the least affluent neighborhoods, while associations with CVD were weakest in areas of least and greatest affluence. Conclusions: Our results suggest that PM2.5 and nSES exposures are associated with small changes in rates of mortality and CVD incidence. These exposures interact in a complex fashion, even within a relatively demographically homogeneous cohort of women.
P-0652 - Effects of personal air pollution exposure on inflammatory responses: potential mediation by endogenous melatonin
Abstract Control Number
2689
Abstract Body
Background/Aim: Melatonin is a free radical scavenger and an anti-inflammatory molecule. Air pollution exposure has been associated with increased inflammatory responses. We hypothesize that endogenous melatonin plays a role in inflammatory responses to air pollution exposure. Methods: We tested this hypothesis in a cohort of 53 healthy adults (22-52 years old, 16 women), none of whom were on melatonin supplementation. Early morning urine and blood were collected from each participant for up to three times. We analyzed urinary 6-sulfatoxymelatonin (aMT6s), as a surrogate of circulating melatonin, and pro- and anti-inflammatory cytokines in plasma. Indoor and outdoor air pollutants were measured and combined with participants’ time-activity pattern to calculate personal exposure to O3, PM2.5, NO2, and SO2 averaged over 12-hour, 24-hour, 1-week, and 2-week prior to biospecimen collection, respectively. Linear mixed effects models were used to examine the relationships of urinary aMT6s with personal pollution exposure and plasma cytokines controlling for covariates including temperature, humidity, sex, age, and respiratory infection & smoking status. Mediation analysis was conducted to test whether aMT6s is a mediator for the relationships between pollution exposure and inflammatory cytokines. Results: A one interquartile range (4.2 ppb) increase in 2-week O3 exposure was associated with a -29.4% (95% CI: -50.0%, -0.50%) decrease in aMT6s, while the relationships of aMT6s with other pollutant exposures were nonsignificant. Within the range of endogenous aMT6s concentration (0.5-53.0 ng/ng creatinine), increasing aMT6s level was associated with decreasing levels of pro-inflammatory cytokines, including IL-1β, IL-6, IL-8, IL-17A, IFN-γ, and TNF-α. The mediation analysis showed that 5.2%, 7.7%, 8.2%, 10.5%, 16.1%, and 8.3% of the total effects of 2-week O3 exposure on IL-1β, IL-6, IL-8, IL-17A, IFN-γ, and TNF-α were mediated by urinary aMT6s, respectively. Conclusions: Our findings suggest that air pollution exposure may decrease endogenous melatonin, which may further contribute to enhanced pro-inflammatory responses.
P-0185 - The Long-term Effect of Exposure to Air Pollutants on Mortality among Medicare Participants: A National Study Using an Additive Hazards Model
Abstract Control Number
2576
Abstract Body
Background/Aims: Our goal is to look at the relationship between long-term exposure to multiple air pollutants and mortality among Medicare participants in the United States on an additive hazard scale using a doubly robust model. Methods: We used a doubly robust additive hazard model (DRAHM) to assess the effect of long-term exposure to PM2.5, NO2, and ozone on mortality among Medicare participants across the contiguous United States from 2000 to 2016. This effect estimates from this model are unbiased if either the inverse probability weight (IPW) model for exposure or the outcome regression model are correctly specified. Furthermore, unlike the Cox proportional hazards model, it does not require a proportional hazards assumption. PM2.5, NO2, and ozone levels were obtained from a previously validated high-resolution prediction models which utilized machine learning algorithms. These predictions were averaged spatio-temporally to obtain annual exposure on a zip code level. Mortality information was derived from the Medicare denominator file. Covariates included demographic and socioeconomic variables. Effect measure modification was assessed for sex, age, race, and Medicaid eligibility. We then repeated the analyses among observations that were less than the international annual standard of 10 mcg/m3 for PM2.5 and 20 ppb for NO2. For the ozone subgroup analysis, we looked at individuals in whom all years of observation had levels below 50 ppb. Results: Our preliminary results indicate that exposure to PM2.5 led to a 0.00248% (95% CI: -0.000252% to 0.00521%) per 1 µg/m3 increase in the hazard of death among the study population after adjustment for individual demographic factors and zip code-level socioeconomic and air pollution factors. Further results are pending. Conclusions: Long-term exposure to fine particulate matter does not significantly increase the hazard of mortality in the elderly Medicare population on an additive scale.
P-0400 - How the impact of heat and cold on mortality has changed in Switzerland during the last 50 years: a nationwide analysis.
Abstract Control Number
2454
Abstract Body
Background: Although previous studies quantified the effect of non-optimal ambient temperatures on mortality, many were limited to urban areas and short periods of time. By applying state-of-the-art methodologies and high-resolution nationwide data available in Switzerland, we aimed to assess trends in mortality attributable to heat and cold during the last five decades across the full Swiss geography. Methods: We collected daily mortality and derived population-weighted daily mean temperature from 2.2km-grid maps for each Swiss municipality between 1969 and 2017. We performed separate time series analyses with conditional quasi-Poisson regression and distributed lag non-linear models to obtain the corresponding temperature-mortality associations for each Canton and decade. We then pooled them through multivariate longitudinal meta-regression and calculated the corresponding excess mortality attributable to non-optimal temperatures. The analysis was repeated across categories of sex, age and main causes. Results: Between 1969 and 2017, overall all-cause excess mortality associated to non-optimal temperatures was 6.24%(95%CI,5.58-6.78) which translates into 3,714 annual excess deaths. Cold-related mortality represented a larger fraction compared to heat (5.89%(95%CI,5.26-6.42), versus 0.36%(95%CI,0.30-0.40)), amounting to 3,588 and 218 annual deaths, respectively. Cold-related mortality increased over the last five decades (5.17% to 6.43%) while for heat an increasing trend was observed until 1998 (0.23% to 0.40%), when it reached a plateau to present years. Similar trends were observed for sex, age and main causes. Conclusion: This first Swiss-wide study found a substantial mortality burden attributed to non-optimal temperatures. Despite the progressive warming of climate, our findings suggest that heat-related mortality remained constant during the last two decades possibly due to the recent implementation of public health measures, while cold-related mortality, which represents a larger burden, increased during the last 50 years. Future analyses will seek to identify potential vulnerability factors and adaptive mechanisms to non-optimal temperatures in Switzerland.