Accuracy of two geocoding methods for geographic information system-based exposure assessment in epidemiological studies

Multi-pollutant exposure profiles associated with breast cancer risk: A Bayesian profile regression analysis in the French E3N cohort

BACKGROUND

Human exposure to air pollution involves complex mixtures of multiple correlated air pollutants. To date, very few studies have assessed the combined effects of exposure to multiple air pollutants on breast cancer (BC) risk.

OBJECTIVES

We aimed to assess the association between combined exposures to multiple air pollutants and breast cancer risk.

METHODS

The study was based on a case-control study nested within the French E3N cohort (5222 incident BC cases/5222 matched controls). For each woman, the average of the mean annual exposure to eight pollutants (benzo(a)oyrene, cadmium, dioxins, polychlorinated biphenyls (PCB153), nitrogen dioxide (NO2), ozone, particulate matter and fine particles (PMs)) was estimated from cohort inclusion in 1990 to the index date. We used the Bayesian Profile Regression (BPR) model, which groups individuals according to their exposure and risk levels, and assigns a risk to each cluster identified. The model was adjusted on a combination of matching variables and confounders to better consider the design of the nested case-control study. Odds ratios (OR) and their 95 % credible intervals (CrI) were estimated.

RESULTS

Among the 21 clusters identified, the cluster characterised by low exposures to all pollutants, except ozone, was taken as reference. A consistent increase in BC risk compared to the reference cluster was observed for 3 clusters: cluster 9 (OR=1.61; CrI=1.13,2.26), cluster 16 (OR=1.59; CrI=1.10,2.30) and cluster 15 (OR=1.38; CrI=1.00,1.88) characterised by high levels of NO2, PMs and PCB153. The other clusters showed no consistent association with BC.

DISCUSSION

This is the first study assessing the effect of exposure to a mixture of eight air pollutants on BC risk, using the BPR approach. Overall, results showed evidence of a positive joint effect of exposure to high levels to most pollutants, particularly high for NO2, PMs and PCB153, on the risk of BC.

Multiple xenoestrogen air pollutants and breast cancer risk: Statistical approaches to investigate combined exposures effect

Studies suggested that exposure to air pollutants, with endocrine disrupting (ED) properties, have a key role in breast cancer (BC) development. Although the population is exposed simultaneously to a mixture of multiple pollutants and ED pollutants may act via common biological mechanisms leading to synergic effects, epidemiological studies generally evaluate the effect of each pollutant separately. We aimed to assess the complex effect of exposure to a mixture of four xenoestrogen air pollutants (benzo-[a]-pyrene (BaP), cadmium, dioxin (2,3,7,8-Tétrachlorodibenzo-p-dioxin TCDD)), and polychlorinated biphenyl 153 (PCB153)) on the risk of BC, using three recent statistical methods, namely weighted quantile sum (WQS), quantile g-computation (QGC) and Bayesian kernel machine regression (BKMR). The study was conducted on 5222 cases and 5222 matched controls nested within the French prospective E3N cohort initiated in 1990. Annual average exposure estimates to the pollutants were assessed using a chemistry transport model, at the participants' residence address between 1990 and 2011. We found a positive association between the WQS index of the joint effect and the risk of overall BC (adjusted odds ratio (OR) = 1.10, 95% confidence intervals (CI): 1.03-1.19). Similar results were found for QGC (OR = 1.11, 95%CI: 1.03-1.19). Despite the association did not reach statistical significance in the BKMR model, we observed an increasing trend between the joint effect of the four pollutants and the risk of BC, when fixing other chemicals at their median concentrations. BaP, cadmium and PCB153 also showed positive trends in the multi-pollutant mixture, while dioxin showed a modest inverse trend. Despite we found a clear evidence of a positive association between the joint exposure to pollutants and BC risk only from WQS and QGC regression, we observed a similar suggestive trend using BKMR. This study makes a major contribution to the understanding of the joint effects of air pollution.

Association between cumulative airborne dioxin exposure and non-Hodgkin's lymphoma risk in a nested case-control study within the French E3N cohort

BACKGROUND

Dioxins are a family of chemical molecules that are chlorinated, lipophilic, and bio-accumulative. They are thought to enhance the risk of non-lymphoma Hodgkin's due to their known carcinogenic properties (NHL). This is the first epidemiological research to investigate the relationship between repeated emissions of airborne dioxin exposure and the risk of NHL.

OBJECTIVE

A case-control study nested within the French E3N cohort of 98,995 women covered by the health insurance provider of the national education system evaluated the association between cumulative airborne dioxin exposure and NHL risk.

MATERIALS AND METHODS

NHL incident cases (368) and controls (368) were compared. Over the duration of the study, participants' residential histories and the locations of industrial sites were gathered (1990-2008). Using a Geographic Information System (GIS)-based exposure index, the cumulative exposure to airborne dioxins for each participant was calculated at the individual address level. The odds ratios (OR) and 95 % confidence intervals (CI) were calculated using multivariable conditional logistic regression models (CI).

RESULTS

The log-transformed continuous cumulative dioxin exposure index was substantially correlated with the risk of NHL (OR1.2 (95 % CI 1.0,1.4) for an increase in log-TEQ/m2 of 4.4, or one standard deviation). The combined chronic lymphocytic leukemia (CLL) and small lymphocytic lymphoma (SLL) subtype was significantly associated with NHL histological subtypes (OR 1.6 (95 % CI 1.1,2.3)).

CONCLUSION

The findings of this study demonstrate a significant positive correlation between cumulative airborne dioxin exposure and the risk of NHL in women, and more specifically, a significant positive association for the CLL & SLL subtype. These results help to support the attempts to reduce the exposure to dioxins in the air.

Enrichment of a Data Lake to Support Population Health Outcomes Studies Using Social Determinants Linked EHR Data

The integration of electronic health records (EHRs) with social determinants of health (SDoH) is crucial for population health outcome research, but it requires the collection of identifiable information and poses security risks. This study presents a framework for facilitating de-identified clinical data with privacy-preserved geocoded linked SDoH data in a Data Lake. A reidentification risk detection algorithm was also developed to evaluate the transmission risk of the data. The utility of this framework was demonstrated through one population health outcomes research analyzing the correlation between socioeconomic status and the risk of having chronic conditions. The results of this study inform the development of evidence-based interventions and support the use of this framework in understanding the complex relationships between SDoH and health outcomes. This framework reduces computational and administrative workload and security risks for researchers and preserves data privacy and enables rapid and reliable research on SDoH-connected clinical data for research institutes.

Long-term exposure to nitrogen dioxide air pollution and breast cancer risk: A nested case-control within the French E3N cohort study

Nitrogen dioxide (NO₂) is an important air pollutant due to its adverse effects on human health. Yet, current evidence on the association between NO₂ and the risk of breast cancer lacks consistency. In this study, we investigated the association between long-term exposure to NO₂ and breast cancer risk in the French E3N cohort study. Association of breast cancer risk with NO₂ exposure was assessed in a nested case-control study within the French E3N cohort including 5222 breast cancer cases identified over the 1990-2011 follow-up period and 5222 matched controls. Annual mean concentrations of NO₂ at participants' residential addresses for each year from recruitment 1990 through 2011, were estimated using a land use regression (LUR) model. Multivariable conditional logistic regression models were used to compute odds ratios (ORs) and their 95% confidence intervals (CIs). Additional analyses were performed using NO₂ concentrations estimated by CHIMERE, a chemistry transport model. Overall, the mean NO₂ exposure was associated with an increased risk of breast cancer. In all women, for each interquartile range (IQR) increase in NO₂ levels (LUR: 17.8 μg/m³), the OR of the model adjusted for confounders was 1.09 (95% CI: 1.01-1.18). The corresponding OR in the fully adjusted model (additionally adjusted for established breast cancer risk factors) was 1.07 (95% CI: 0.98-1.15). By menopausal status, results for postmenopausal women were comparable to those for all women, while no association was observed among premenopausal women. By hormone receptor status, the OR of estrogen receptor positive breast cancer = 1.07 (95% CI: 0.97-1.19) in the fully adjusted model. Additional analyses using the CHIMERE model showed slight differences in ORs estimates. The results of this study indicate an increased risk of breast cancer associated with long-term exposure to NO₂ air pollution. Observing comparable effects of NO₂ exposure estimated by two different models, reinforces these findings.

Quality of automatic geocoding tools: a study using addresses from hospital record files in Temuco, Chile

Abstract: Automatic geocoding methods have become popular in recent years, facilitating the study of the association between health outcomes and the place of living. However, rather few studies have evaluated geocoding quality, with most of them being performed in the US and Europe. This article aims to compare the quality of three automatic online geocoding tools against a reference method. A subsample of 300 handwritten addresses from hospital records was geocoded using Bing, Google Earth, and Google Maps. Match rates were higher (> 80%) for Google Maps and Google Earth compared with Bing. However, the accuracy of the addresses was better for Bing with a larger proportion (> 70%) of addresses with positional errors below 20m. Generally, performance did not vary for each method for different socioeconomic status. Overall, the methods showed an acceptable, but heterogeneous performance, which may be a warning against the use of automatic methods without assessing quality in other municipalities, particularly in Chile and Latin America.

Individual mobility pattern in Malaysia during COVID-19 Recovery Movement Control Order partial lockdown

Malaysia Recovery Movement Control Order (RMCO) aims to bring the business, education, tourism and other industry sectors back into operation. Due to movement constraints that result in local economic patterns, individual mobility patterns are expected to occur. However, this matter needs further investigation from people's spatial behaviour during the RMCO. Therefore, this research proposed a new technique for analysing people's spatial behaviour patterns via geo-tagged data. The data from social media users are gathered using data mining techniques. Geographical Information System (GIS) is used to show the geolocation of social media users and analyse their spatial behaviour. The finding of this analysis shows higher people's movement recorded when the RMCO was enforced; a distinctive pattern where spatial trajectory length is high but spatial area coverage is low. It is noticed that the focal points are concentrated in urban areas and tourism attractions.

Exposure to airborne cadmium and breast cancer stage, grade and histology at diagnosis: findings from the E3N cohort study

Molecular studies suggest that cadmium due to its estrogenic properties, might play a role in breast cancer (BC) progression. However epidemiological evidence is limited. This study explored the association between long-term exposure to airborne cadmium and risk of BC by stage, grade of differentiation, and histological types at diagnosis. A nested case-control study of 4401 cases and 4401 matched controls was conducted within the French E3N cohort. A Geographic Information System (GIS)-based metric demonstrated to reliably characterize long-term environmental exposures was employed to evaluate airborne exposure to cadmium. Multivariable adjusted odds ratios (OR) and 95% confidence intervals (CI) were estimated using conditional logistic regression models. There was no relationship between cadmium exposure and stage of BC. Also, no association between cadmium exposure and grade of differentiation of BC was observed. However, further analyses by histological type suggested a positive association between cadmium and risk of invasive tubular carcinoma (ITC) BC [OR_{Q5 vs Q1} = 3.4 (95% CI 1.1-10.7)]. The restricted cubic spline assessment suggested a dose-response relationship between cadmium and ITC BC subtype. Our results do not support the hypothesis that airborne cadmium exposure may play a role in advanced BC risk, but suggest that cadmium may be associated with an increased risk of ITC.

Uncertainty in geospatial health: challenges and opportunities ahead

PURPOSE

Uncertainty is not always well captured, understood, or modeled properly, and can bias the robustness of complex relationships, such as the association between the environment and public health through exposure, estimates of geographic accessibility and cluster detection, to name a few.

METHODS

We review current challenges and future opportunities as geospatial data and analyses are applied to the field of public health. We are particularly interested in the sources of uncertainty in geospatial data and how this uncertainty may propagate in spatial analysis.

RESULTS

We present opportunities to reduce the magnitude and impact of uncertainty. Specifically, we focus on (1) the use of multiple reference data sources to reduce geocoding errors, (2) the validity of online geocoders and how confidentiality (e.g., HIPAA) may be breached, (3) use of multiple reference data sources to reduce geocoding errors, (4) the impact of geoimputation techniques on travel estimates, (5) residential mobility and how it affects accessibility metrics and clustering, and (6) modeling errors in the American Community Survey. Our paper discusses how to communicate spatial and spatiotemporal uncertainty, and high-performance computing to conduct large amounts of simulations to ultimately increase statistical robustness for studies in public health.

CONCLUSIONS

Our paper contributes to recent efforts to fill in knowledge gaps at the intersection of spatial uncertainty and public health.

The impact of left truncation of exposure in environmental case-control studies: evidence from breast cancer risk associated with airborne dioxin

In epidemiology, left-truncated data may bias exposure effect estimates. We analyzed the bias induced by left truncation in estimating breast cancer risk associated with exposure to airborne dioxins. Simulations were run with exposure estimates from a Geographic Information System (GIS)-based metric and considered two hypotheses for historical exposure, three scenarios for intra-individual correlation of annual exposures, and three exposure-effect models. For each correlation/model combination, 500 nested matched case-control studies were simulated and data fitted using a conditional logistic regression model. Bias magnitude was assessed by estimated odds-ratios (ORs) versus theoretical relative risks (TRRs) comparisons. With strong intra-individual correlation and continuous exposure, left truncation overestimated the Beta parameter associated with cumulative dioxin exposure. Versus a theoretical Beta of 4.17, the estimated mean Beta (5%; 95%) was 73.2 (67.7; 78.8) with left-truncated exposure and 4.37 (4.05; 4.66) with lifetime exposure. With exposure categorized in quintiles, the TRR was 2.0, the estimated OR_{Q5 vs. Q1} 2.19 (2.04; 2.33) with truncated exposure versus 2.17 (2.02; 2.32) with lifetime exposure. However, the difference in exposure between Q5 and Q1 was 18× smaller with truncated data, indicating an important overestimation of the dose effect. No intra-individual correlation resulted in effect dilution and statistical power loss. Left truncation induced substantial bias in estimating breast cancer risk associated with exposure with continuous and categorical models. With strong intra-individual exposure correlation, both models detected associations, but categorical models provided better estimates of effect trends. This calls for careful consideration of left truncation-induced bias in interpreting environmental epidemiological data.

Population-Based Geospatial and Molecular Epidemiologic Study of Tuberculosis Transmission Dynamics, Botswana, 2012-2016

Tuberculosis (TB) elimination requires interrupting transmission of Mycobacterium tuberculosis. We used a multidisciplinary approach to describe TB transmission in 2 sociodemographically distinct districts in Botswana (Kopanyo Study). During August 2012-March 2016, all patients who had TB were enrolled, their sputum samples were cultured, and M. tuberculosis isolates were genotyped by using 24-locus mycobacterial interspersed repetitive units-variable number of tandem repeats. Of 5,515 TB patients, 4,331 (79%) were enrolled. Annualized TB incidence varied by geography (range 66-1,140 TB patients/100,000 persons). A total of 1,796 patient isolates had valid genotyping results and residential geocoordinates; 780 (41%) patients were involved in a localized TB transmission event. Residence in areas with a high burden of TB, age <24 years, being a current smoker, and unemployment were factors associated with localized transmission events. Patients with known HIV-positive status had lower odds of being involved in localized transmission.

How to improve automated external defibrillator placement for out-of-hospital cardiac arrests: A case study

Introduction

In out-of-hospital cardiac arrests (OHCAs), the use of an automatic external defibrillator (AED) by a bystander remains low, as AEDs may be misplaced with respect to the locations of OHCAs. As the distribution of historical OHCAs is potentially predictive of future OHCA locations, the purpose of this study is to assess AED positioning with regard to past locations of OHCAs, in order to improve the efficiency of public access defibrillation programs.

Methods

This is a retrospective observational study from 2014 to 2018. The locations of historical OHCAs and AEDs were loaded into a geodata processing tool. Median distances between AEDs were collected, as well as the number and rates of OHCAs covered (distance of <100 meters from the nearest AED). Areas with high densities of uncovered OHCAs (hotspots) were identified in order to propose the placement of additional AEDs. Areas over-covered by AEDs (overlays) were also identified in order to propose the relocation of overlapping AEDs.

Results

There were 2,971 OHCA, 79.3% of which occurred at home, and 633 AEDs included in the study. The global coverage rate was 7.5%. OHCAs occurring at home had a coverage rate of 4.5%. Forty hotspots were identified, requiring the same number of additional AEDs. The addition of these would increase the coverage from 7.5% to 17.6%. Regarding AED overlays, 17 AEDs were found to be relocatable without reducing the AED coverage of historical OHCAs.

Discussion

This study confirms that geodata tools can assess AED locations and increase the efficiency of their placement. Historical hotspots and AED overlays should be considered, with the aim of efficiently relocating or adding AEDs. At-home OHCAs should become a priority target for future public access defibrillation programs as they represent the majority of OHCAs but have the lowest AED coverage rates.

Risk of breast cancer associated with long-term exposure to benzo[a]pyrene (BaP) air pollution: Evidence from the French E3N cohort study

BACKGROUND

Benzo[a]pyrene (BaP) is an endocrine-disrupting pollutant formed during incomplete combustion of organic materials. It has been recognized as a reproductive and developmental toxicant, however epidemiological evidence of the long-term effect of ambient air BaP on breast cancer (BC) is limited. Thus we evaluated associations between ambient air BaP exposure and risk of BC, overall and according to menopausal status and molecular subtypes (estrogen receptor negative/positive (ER-/ER+) and progesterone receptor negative/positive (PR-/PR+)), stage and grade of differentiation of BC in the French E3N cohort study.

METHODS

Within a nested case-control study of 5222 incident BC cases and 5222 matched controls, annual BaP exposure was estimated using a chemistry-transport model (CHIMERE) and was assigned to the geocoded residential addresses of participants for each year during the 1990-2011 follow-up period. Multivariable conditional logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

Overall, cumulative airborne BaP exposure was significantly associated with the overall risk of BC, for each 1 interquartile range (IQR) increase in the concentration levels of BaP (1.42 ng/m³), the OR = 1.15 (95% CI: 1.04-1.27). However, by menopausal status, the significant positive association remained only in women who underwent menopausal transition (i.e. premenopausal women at inclusion who became postmenopausal at diagnosis), OR per 1 IQR = 1.20 (95% CI: 1.03-1.40). By hormone receptor status, positive associations were observed for ER+, PR + and ER + PR + BC, with ORs = 1.17 (95% CI: 1.04-1.32), 1.16 (95% CI: 1.01-1.33), and 1.17 (95% CI: 1.01-1.36) per 1 IQR, respectively. There was also a borderline positive association between BaP and grade 3 BC (OR per 1 IQR = 1.15 (95% CI: 0.99-1.34).

CONCLUSIONS

We provide evidence of increased risk of BC associated with cumulative BaP exposure, which varied according to menopausal status, hormone receptor status, and grade of differentiation of BC. Our results add further epidemiological evidence to the previous experimental studies suggesting the adverse effects of BaP.

Spatial Heterogeneity in Positional Errors: A Comparison of Two Residential Geocoding Efforts in the Agricultural Health Study

Geocoding is a powerful tool for environmental exposure assessments that rely on spatial databases. Geocoding processes, locators, and reference datasets have improved over time; however, improvements have not been well-characterized. Enrollment addresses for the Agricultural Health Study, a cohort of pesticide applicators and their spouses in Iowa (IA) and North Carolina (NC), were geocoded in 2012–2016 and then again in 2019. We calculated distances between geocodes in the two periods. For a subset, we computed positional errors using “gold standard” rooftop coordinates (IA; N = 3566) or Global Positioning Systems (GPS) (IA and NC; N = 1258) and compared errors between periods. We used linear regression to model the change in positional error between time periods (improvement) by rural status and population density, and we used spatial relative risk functions to identify areas with significant improvement. Median improvement between time periods in IA was 41 m (interquartile range, IQR: −2 to 168) and 9 m (IQR: −80 to 133) based on rooftop coordinates and GPS, respectively. Median improvement in NC was 42 m (IQR: −1 to 109 m) based on GPS. Positional error was greater in rural and low-density areas compared to in towns and more densely populated areas. Areas of significant improvement in accuracy were identified and mapped across both states. Our findings underscore the importance of evaluating determinants and spatial distributions of errors in geocodes used in environmental epidemiology studies.

Chronic Low-Dose Exposure to Xenoestrogen Ambient Air Pollutants and Breast Cancer Risk: XENAIR Protocol for a Case-Control Study Nested Within the French E3N Cohort

Background

Breast cancer is the most frequent cancer in women in industrialized countries. Lifestyle and environmental factors, particularly endocrine-disrupting pollutants, have been suggested to play a role in breast cancer risk. Current epidemiological studies, although not fully consistent, suggest a positive association of breast cancer risk with exposure to several International Agency for Research on Cancer Group 1 air-pollutant carcinogens, such as particulate matter, polychlorinated biphenyls (PCB), dioxins, Benzo[a]pyrene (BaP), and cadmium. However, epidemiological studies remain scarce and inconsistent. It has been proposed that the menopausal status could modify the relationship between pollutants and breast cancer and that the association varies with hormone receptor status.

Objective

The XENAIR project will investigate the association of breast cancer risk (overall and by hormone receptor status) with chronic exposure to selected air pollutants, including particulate matter, nitrogen dioxide (NO2), ozone (O3), BaP, dioxins, PCB-153, and cadmium.

Methods

Our research is based on a case-control study nested within the French national E3N cohort of 5222 invasive breast cancer cases identified during follow-up from 1990 to 2011, and 5222 matched controls. A questionnaire was sent to all participants to collect their lifetime residential addresses and information on indoor pollution. We will assess these exposures using complementary models of land-use regression, atmospheric dispersion, and regional chemistry-transport (CHIMERE) models, via a Geographic Information System. Associations with breast cancer risk will be modeled using conditional logistic regression models. We will also study the impact of exposure on DNA methylation and interactions with genetic polymorphisms. Appropriate statistical methods, including Bayesian modeling, principal component analysis, and cluster analysis, will be used to assess the impact of multipollutant exposure. The fraction of breast cancer cases attributable to air pollution will be estimated.

Results

The XENAIR project will contribute to current knowledge on the health effects of air pollution and identify and understand environmental modifiable risk factors related to breast cancer risk.

Conclusions

The results will provide relevant evidence to governments and policy-makers to improve effective public health prevention strategies on air pollution. The XENAIR dataset can be used in future efforts to study the effects of exposure to air pollution associated with other chronic conditions.

International Registered Report Identifier (IRRID)

DERR1-10.2196/15167

Validation of a province-wide commercial food store dataset in a heterogeneous predominantly rural food environment

OBJECTIVE

Commercially available business (CAB) datasets for food environments have been investigated for error in large urban contexts and some rural areas, but there is a relative dearth of literature that reports error across regions of variable rurality. The objective of the current study was to assess the validity of a CAB dataset using a government dataset at the provincial scale.

DESIGN

A ground-truthed dataset provided by the government of Newfoundland and Labrador (NL) was used to assess a popular commercial dataset. Concordance, sensitivity, positive-predictive value (PPV) and geocoding errors were calculated. Measures were stratified by store types and rurality to investigate any association between these variables and database accuracy.

SETTING

NL, Canada.

PARTICIPANTS

The current analysis used store-level (ecological) data.

RESULTS

Of 1125 stores, there were 380 stores that existed in both datasets and were considered true-positive stores. The mean positional error between a ground-truthed and test point was 17·72 km. When compared with the provincial dataset of businesses, grocery stores had the greatest agreement, sensitivity = 0·64, PPV = 0·60 and concordance = 0·45. Gas stations had the least agreement, sensitivity = 0·26, PPV = 0·32 and concordance = 0·17. Only 4 % of commercial data points in rural areas matched every criterion examined.

CONCLUSIONS

The commercial dataset exhibits a low level of agreement with the ground-truthed provincial data. Particularly retailers in rural areas or belonging to the gas station category suffered from misclassification and/or geocoding errors. Taken together, the commercial dataset is differentially representative of the ground-truthed reality based on store-type and rurality/urbanity.

Beyond Smoking: Environmental Determinants of Asthma Prevalence in Western Nepal

BACKGROUND

Asthma is widely prevalent in Nepal, but the causes are not well known aside from some general associations with ambient air pollution and microbial exposures. Information on the wide-ranging determinants of asthma prevalence among the population at risk can help policy makers to reduce risk.

OBJECTIVE

The present study is a preliminary investigation of the environmental, socioeconomic and behavioral determinants of asthma prevalence in western Nepal.

METHODS

A survey was conducted among 420 randomly selected households in western Nepal. A cross-sectional analytical study design was employed with the primary data using econometric tools of probit and logistic regression.

RESULTS

Environmental variables such as extreme cold winter, deteriorating river water quality and air pollution were associated with an increase in asthma prevalence. However, individual or household characteristics such as advancing age of household head, use of pesticides in the home for the control of pests, piped drinking water with old pipes and lack of participation in awareness programs were associated with an increase in asthma prevalence.

DISCUSSION

Among environmental factors, decreasing river water quality, increasing air pollution, and extremely cold winters are more likely to contribute to asthma prevalence. In light of the effects of environmental factors on the prevalence of asthma in Nepal, the high public and private costs of asthma could further impoverish the rural poor.

CONCLUSIONS

Environmental health policy makers should design adaptation strategies along with additional community programs addressing asthma-instigating factors. Programs to reduce environmental pollution can reduce morbidity due to asthma.

PARTICIPANT CONSENT

Obtained.

ETHICS APPROVAL

This study was approved by the Ethical Committee of the Nepal Health Research Council.

COMPETING INTERESTS

The authors declare no competing financial interests.

Chronic long-term exposure to cadmium air pollution and breast cancer risk in the French E3N cohort

Cadmium, due to its estrogen-like activity, has been suspected to increase the risk of breast cancer; however, epidemiological studies have reported inconsistent findings. We conducted a case-control study (4,059 cases and 4,059 matched controls) nested within the E3N French cohort study to estimate the risk of breast cancer associated with long-term exposure to airborne cadmium pollution, and its effect according to molecular subtype of breast cancer (estrogen receptor negative/positive [ER-/ER+] and progesterone receptor negative/positive [PR-/PR+]). Atmospheric exposure to cadmium was assessed using a Geographic Information System-based metric, which included subject's residence-to-cadmium source distance, wind direction, exposure duration and stack height. Adjusted odds ratios (OR) and 95% confidence intervals (CI) were estimated using conditional logistic regression. Overall, there was no significant association between cumulative dose of airborne cadmium exposure and the risk of overall, premenopausal and postmenopausal breast cancer. However, by ER and PR status, inverse associations were observed for ER- (ORQ5 vs. Q1  = 0.63; 95% CI: 0.41-0.95, ptrend  = 0.043) and for ER-/PR- breast tumors (ORQ4 vs. Q1  = 0.62; 95% CI: 0.40-0.95, ORQ5 vs. Q1  = 0.68; 95% CI: 0.42-1.07, ptrend  = 0.088). Our study provides no evidence of an association between exposure to cadmium and risk of breast cancer overall but suggests that cadmium might be related to a decreased risk of ER- and ER-/PR- breast tumors. These observations and other possible effects linked to hormone receptor status warrant further investigations.

Verifying locations of sources of historical environmental releases of dioxin-like compounds in the U.S.: implications for exposure assessment and epidemiologic inference

Polychlorinated dibenzo-p-dioxin and dibenzofuran (PCDD/F) emissions from industrial sources contaminate the surrounding environment. Proximity-based exposure surrogates assume accuracy in the location of PCDD/F sources, but locations are not often verified. We manually reviewed locations (i.e., smokestack geo-coordinates) in a historical database of 4478 PCDD/F-emitting facilities in 2009 and 2016. Given potential changes in imagery and other resources over this period, we re-reviewed a random sample of 5% of facilities (n = 240) in 2016. Comparing the original and re-review of this sample, we evaluated agreement in verification (location confirmed or not) and distances between verified locations (verification error), overall and by facility type. Using the verified location from re-review as a gold standard, we estimated the accuracy of proximity-based exposure metrics and epidemiologic bias. Overall agreement in verification was high (>84%), and verification errors were small (median = 84 m) but varied by facility type. Accuracy of exposure classification (≥1 facility within 5 km) for a hypothetical study population also varied by facility type (sensitivity: 69-96%; specificity: 95-98%). Odds ratios were attenuated 11-69%, with the largest bias for rare facility types. We found good agreement between reviews of PCDD/F source locations, and that exposure prevalence and facility type may influence associations with exposures derived from this database. Our findings highlight the need to consider location error and other contextual factors when using proximity-based exposure metrics.

Chronic Kidney Disease in Agricultural Communities

Patients residing in agricultural communities have a high risk of developing chronic kidney disease. In the Great Plains, geo-environmental risk factors (eg, variable climate, temperature, air quality, water quality, and drought) combine with agro-environmental risk factors (eg, exposure to fertilizers, soil conditioners, herbicides, fungicides, and pesticides) to increase risk for toxic nephropathy. However, research defining the specific influence of agricultural chemicals on the progression of kidney disease in rural communities has been somewhat limited. By linking retrospective clinical data within electronic medical records to environmental data from sources like US Environmental Protection Agency, analytical models are beginning to provide insight into the impact of agricultural practices on the rate of progression for kidney disease in rural communities.

Residential mobility in early childhood and the impact on misclassification in pesticide exposures

Studies of environmental exposures and childhood cancers that rely on records often only use maternal address at birth or address at cancer diagnosis to assess exposures in early childhood, possibly leading to exposure misclassification and questionable validity due to residential mobility during early childhood. Our objective was to assess patterns and identify factors that may predict residential mobility in early childhood, and examine the impact of mobility on early childhood exposure assessment for agriculturally applied pesticides and childhood cancers in California. We obtained the addresses at diagnosis of all childhood cancer cases born in 1998-2011 and diagnosed at 0-5 years of age (n = 6478) from the California Cancer Registry (CCR), and their birth addresses from linked birth certificates. Controls were randomly selected from California birth records and frequency matched (20:1) to all cases by year of birth. We obtained residential histories from a public-record database LexisNexis for both case (n = 3877 with age at diagnosis 1-5 years) and control (n = 99,262) families. Logistic regression analyses were conducted to assess the socio-demographic factors in relation to residential mobility in early childhood. We employed a Geographic Information System (GIS)-based system to estimate children's first year of life exposures to agriculturally applied pesticides based on birth vs diagnosis address or residential histories based upon Lexis-Nexis Public Records and assessed agreement between exposure measures using Spearman correlations and kappa statistics. Over 20% of case and control children moved in their first year of life, and 55% of children with cancer moved between birth and diagnosis. Older age at diagnosis, younger maternal age, lower maternal education, not having a Hispanic ethnic background, use of public health insurance, and non-metropolitan residence at birth were predictors of higher residential mobility. There was moderate to strong correlation (Spearman correlation = 0.76-0.83) and good agreement (kappa = 0.75-0.81) between the first year of life exposure estimates for agricultural pesticides applied within 2 km of a residence relying on an address at birth or at diagnosis or LexisNexis addresses; this did not differ by outcome status, but agreement decreased with decreasing buffer size, and increasing distance moved or age at diagnosis. These findings suggest that residential addresses collected at one point in time may represent residential history in early childhood to a reasonable extent; nevertheless, they exposure misclassification in the first year of life remains an issue. Also, the highest proportion of women not captured by LexisNexis were Hispanic women born in Mexico and those living in the lowest SES neighborhoods, i.e. possibly those with the higher environmental exposures, as well as younger women and those with less than high school education. Though LexisNexis only captures a sub-population, its data may be useful for augmenting address information and assessing the extent of exposure misclassification when estimating environmental exposures in large record linkage studies. Future research should investigate how to correct for exposure misclassification introduced by residential mobility that is not being captured by records.

Long-term airborne dioxin exposure and breast cancer risk in a case-control study nested within the French E3N prospective cohort

BACKGROUND

Dioxins, Group 1 carcinogens, are emitted by industrial chlorinated combustion processes and suspected to increase breast cancer risk through receptor-mediated pathways.

OBJECTIVES

We estimated breast cancer risk associated with airborne dioxin exposure, using geographic information system (GIS) methods and historical exposure data.

METHODS

We designed a case-control study (429 breast cancer cases diagnosed between 1990 and 2008, matched to 716 controls) nested within the E3N (Etude Epidémiologique auprès de femmes de la Mutuelle Générale de l'Education Nationale) cohort. Airborne dioxin exposure was assessed using a GIS-based metric including participants' residential history, technical characteristics of 222 dioxin sources, residential proximity to dioxin sources, exposure duration and wind direction. Odds ratios (OR) and 95% confidence intervals (CI) associated with quintiles of cumulative exposure were estimated using multivariate logistic regression models.

RESULTS

We observed no increased risk of breast cancer for higher dioxin exposure levels overall and according to hormone-receptor status. We however observed a statistically significant OR for Q2 versus Q1 overall (1.612, 95% CI: 1.042-2.493) and for estrogen-receptor (ER) positive breast cancer (1.843, 95% CI: 1.033-3.292).

CONCLUSIONS

Overall, as well as according to hormone-receptor status, no increased risk was observed for higher airborne dioxin exposure. The increased risk for low exposure levels might be compatible with non-monotonic dose-response relationship. Confirmation of our findings is required. Our GIS-based metric may provide an alternative in absence of ambient dioxin monitoring and may allow assessing exposure to other pollutants.

Development and performance evaluation of a GIS-based metric to assess exposure to airborne pollutant emissions from industrial sources

BACKGROUND

Dioxins are environmental and persistent organic carcinogens with endocrine disrupting properties. A positive association with several cancers, including risk of breast cancer has been suggested.

OBJECTIVES

This study aimed to develop and assess performances of an exposure metric based on a Geographic Information System (GIS) through comparison with a validated dispersion model to estimate historical industrial dioxin exposure for its use in a case-control study nested within a prospective cohort.

METHODS

Industrial dioxin sources were inventoried over the whole French territory (n > 2500) and annual average releases were estimated between 1990 and 2008. In three selected areas (rural, urban and urban-costal), dioxin dispersion was modelled using SIRANE, an urban Gaussian model and exposure of the French E3N cohort participants was estimated. The GIS-based metric was developed, calibrated and compared to SIRANE results using a set of parameters (local meteorological data, characteristics of industrial sources, e.g. emission intensity and stack height), by calculating weighted kappa statistics (wκ) and coefficient of determination (R2). Furthermore, as performance evaluation, the final GIS-based metric was tested to assess atmospheric exposure to cadmium.

RESULTS

The concordance between the GIS-based metric and the dispersion model for dioxin exposure estimate was strong (wκ median = 0.78 (1st quintile = 0.72, 3rd quintile =0.82) and R2 median = 0.82 (1st quintile = 0.71, 3rd quintile = 0.87)). We observed similar performance for cadmium.

CONCLUSIONS

Our study demonstrated the ability of the GIS-based metric to reliably characterize long-term environmental dioxin and cadmium exposures as well as the pertinence of using dispersion modelling to construct and calibrate the GIS-based metric.

Prediction of Lime Tolerance in Rhododendron Based on Herbarium Specimen and Geochemical Data

Rhododendrons are typically known to be calcifuges that cannot grow well in lime soils. Data on lime tolerance of different taxa in Rhododendron are scarce. Habitats of naturally distributed specimens of genus Rhododendron were compiled as Chinese text-based locations from the Chinese Virtual Herbarium. The locations were then geocoded into latitude/longitude pairs and subsequently connected to soil characteristics including pH and CaCO₃ from the Harmonized World Soil Database (HWSD). Using the upper quartile values of pH > 7.2 and CaCO₃ > 2% weight in topsoil as threshold, we predicted the lime tolerant taxa. A dataset of 31,146 Rhododendron specimens including the information on taxonomy, GPS locations and soil parameters for both top- and subsoil was built. The majority of the specimens were distributed in soils with moderately acidic pH and without presence of CaCO₃. 76 taxa with potential lime tolerance were predicted out of 525 taxa. The large scale data analysis based on combined data of geocoded herbarium specimens and HWSD allows identification of valuable Rhododendron species, subspecies or botanical varieties with potential tolerance to lime soils with higher pH. The predicted tolerant taxa are valuable resources for an in-depth evaluation of lime tolerance or for further use in horticulture and breeding.

The association between objective measures of residence and worksite neighborhood environment, and self-reported leisure-time physical activities: The Aichi Workers' Cohort Study

The possible effects of a neighborhood's built environment on physical activity have not been studied in Asian countries as much as in Western countries. The present study cross-sectionally examined the relationship between geographic information system (GIS) measured residence and worksite neighborhood walkability, and the number of parks/green spaces and sports facilities within a 1 km radius of home and workplace, with self-reported leisure-time habitual (3–4 times per week or more) walking and moderate-to-vigorous intensity habitual exercise among local government workers aged 18 to 64 years living in an urban-suburban area of Aichi, Japan in 2013. A single-level binomial regression model was used to estimate the multivariable odds ratios (ORs) and 95% confidence intervals (95% CIs). Of the 1959 male and 884 female participants, 288 (15%) and 141 (16%) reported habitual walking, respectively, and 18% and 17% reported habitual exercise, respectively. Compared with women who resided in neighborhood with a walkability index of 4–30, those living in an area with that of 35–40 were significantly more likely to engage in leisure-time habitual exercise (multivariable OR: 1.70, 95% CI: 1.08–2.68). Marginally significant positive associations were found between leisure-time habitual exercise and the residential neighborhood's number of parks/green spaces among women, as well as the number of sports facilities among men. In conclusion, a residential neighborhood environment characterized by higher walkability may contribute to the initiation or maintenance of moderate-to-vigorous intensity leisure-time exercise among working women living in an urban-suburban area of Japan.

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Residential neighborhood walkability was associated with exercise habits of women.

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No features of residential neighborhood were related to walking habits in both sexes.

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No association was found for worksite neighborhood environmental features.

Assessment of long-term exposure to airborne dioxin and cadmium concentrations in the Lyon metropolitan area (France)

Identifying the long-term effects of airborne pollutants requires the computation of the spatial and temporal variability of their concentration in air to estimate the exposure of the population. To estimate exposure levels of individuals in a breast cancer case control study nested in a national prospective cohort, we determine here the differential impact of a variety of cadmium and dioxin sources on urban air over a large urban area and over a period of almost 20years. To that end, we couple an emission model, to estimate dioxin and cadmium atmospheric annual releases, with an urban dispersion model in order to compute pollutant concentration fields at a fine temporal (1h) and spatial (25m) resolution. The reliability of the modelling chain is compared to two types of measurement: i) localized industrial emissions and ii) dioxin and cadmium air monitoring data (from 2007 to 2008), collected at a fixed station, placed in the city centre, as well as at three mobile short-term dioxin monitoring stations, located in the suburbs (the latter providing dioxin data, only). Comparisons between measured and estimated emissions show non-negligible difference, with a correlations for dioxin (r_s=0.42) and cadmium (r_s=0.41). Despite this, mean values between estimated emissions and emission measurements are close to each other, in particular for cadmium. Weekly average modelled concentrations show an overall good agreement with weekly average measured concentrations in spring and summer but are generally lower than monitored data in winter due to peak concentrations from diffuse sources representing an important proportion of emissions in 2007/2008. The model provides better results for cadmium than for dioxin. Despite the relevant errors in the model predictions, the model meets the validation criteria, defined by Chang and Hanna for an urban dispersion model. Simulation scenarios of air pollutant concentrations, reconstructed over the last 20years, show the effects of the variability of the pollutant sources over time with decreasing levels of dioxin and cadmium concentrations in air. This is primarily due to the reduction in localized industrial releases, which results in a general trend of homogenization of the exposure of the population. The model further allows us to dissociate the contribution of different types of pollutant sources on the population exposure. The impact on local concentrations due to industrial emissions, which were originally responsible for the major impact on air quality, is shown to drop over the years by 99% and 92% for dioxin and cadmium, respectively. Today, the major contributions are due to diffuse miscellaneous sources in the case of dioxin and to traffic-related emissions for cadmium. Average modelled concentrations at the study subjects' residential locations range from 10.2 to 82.1fg-TEQ/m³ for dioxin and 0.10 to 1.6ng/m³ for cadmium and are comparable with data from the literature. The study results will be essential to increase the accuracy of the assessment of long-term airborne dioxin and cadmium exposure and improve the results of epidemiological studies.