104 research outputs found

    Spatial-temporal analysis of breast cancer in upper Cape Cod, Massachusetts

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    INTRODUCTION. The reasons for elevated breast cancer rates in the upper Cape Cod area of Massachusetts remain unknown despite several epidemiological studies that investigated possible environmental risk factors. Data from two of these population-based case-control studies provide geocoded residential histories and information on confounders, creating an invaluable dataset for spatial-temporal analysis of participants' residency over five decades. METHODS. The combination of statistical modeling and mapping is a powerful tool for visualizing disease risk in a spatial-temporal analysis. Advances in geographic information systems (GIS) enable spatial analytic techniques in public health studies previously not feasible. Generalized additive models (GAMs) are an effective approach for modeling spatial and temporal distributions of data, combining a number of desirable features including smoothing of geographical location, residency duration, or calendar years; the ability to estimate odds ratios (ORs) while adjusting for confounders; selection of optimum degree of smoothing (span size); hypothesis testing; and use of standard software. We conducted a spatial-temporal analysis of breast cancer case-control data using GAMs and GIS to determine the association between participants' residential history during 1947–1993 and the risk of breast cancer diagnosis during 1983–1993. We considered geographic location alone in a two-dimensional space-only analysis. Calendar year, represented by the earliest year a participant lived in the study area, and residency duration in the study area were modeled individually in one-dimensional time-only analyses, and together in a two-dimensional time-only analysis. We also analyzed space and time together by applying a two-dimensional GAM for location to datasets of overlapping calendar years. The resulting series of maps created a movie which allowed us to visualize changes in magnitude, geographic size, and location of elevated breast cancer risk for the 40 years of residential history that was smoothed over space and time. RESULTS. The space-only analysis showed statistically significant increased areas of breast cancer risk in the northern part of upper Cape Cod and decreased areas of breast cancer risk in the southern part (p-value = 0.04; ORs: 0.90–1.40). There was also a significant association between breast cancer risk and calendar year (p-value = 0.05; ORs: 0.53–1.38), with earlier calendar years resulting in higher risk. The results of the one-dimensional analysis of residency duration and the two-dimensional analysis of calendar year and duration showed that the risk of breast cancer increased with increasing residency duration, but results were not statistically significant. When we considered space and time together, the maps showed a large area of statistically significant elevated risk for breast cancer near the Massachusetts Military Reservation (p-value range:0.02–0.05; ORs range: 0.25–2.5). This increased risk began with residences in the late 1940s and remained consistent in size and location through the late 1950s. CONCLUSION. Spatial-temporal analysis of the breast cancer data may help identify new exposure hypotheses that warrant future epidemiologic investigations with detailed exposure models. Our methods allow us to visualize breast cancer risk, adjust for known confounders including age at diagnosis or index year, family history of breast cancer, parity and age at first live- or stillbirth, and test for the statistical significance of location and time. Despite the advantages of GAMs, analyses are for exploratory purposes and there are still methodological issues that warrant further research. This paper illustrates that GAM methods are a suitable alternative to widely-used cluster detection methods and may be preferable when residential histories from existing epidemiological studies are available.National Cancer Institute (5R03CA119703-02); National Institute of Enviornmental Health (5P42ES007381

    Retrospective Exposure Estimation and Predicted versus Observed Serum Perfluorooctanoic Acid Concentrations for Participants in the C8 Health Project

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    Background: People living or working in eastern Ohio and western West Virginia have been exposed to perfluorooctanoic acid (PFOA) released by DuPont Washington Works facilities

    Spatial analysis of learning and developmental disorders in upper Cape Cod, Massachusetts using generalized additive models

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    The spatial variability of three indicators of learning and developmental disability (LDD) was assessed for Cape Cod, Massachusetts. Maternal reports of receiving special education services, attention deficit hyperactivity disorder, and educational attainment were available for a birth cohort from 1969-1983. Using generalized additive models and residential history, maps of the odds of LDD were produced that also controlled for known risk factors. While results were not statistically significant, they suggest that children living in certain parts of Cape Cod were more likely to have a LDD. The spatial variation may be due to variation in the physical and social environment

    Using Residential History and Groundwater Modeling to Examine Drinking Water Exposure and Breast Cancer

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    BACKGROUND. Spatial analyses of case-control data have suggested a possible link between breast cancer and groundwater plumes in upper Cape Cod, Massachusetts. OBJECTIVE. We integrated residential histories, public water distribution systems, and groundwater modeling within geographic information systems (GIS) to examine the association between exposure to drinking water that has been contaminated by wastewater effluent and breast cancer. METHODS. Exposure was assessed from 1947 to 1993 for 638 breast cancer cases who were diagnosed from 1983 to 1993 and 842 controls; we took into account residential mobility and drinking water source. To estimate the historical impact of effluent on drinking water wells, we modified a modular three-dimensional finite-difference groundwater model (MODFLOW) from the U.S. Geological Survey. The analyses included latency and exposure duration. RESULTS. Wastewater effluent impacted the drinking water wells of study participants as early as 1966. For > 0-5 years of exposure (versus no exposure), associations were generally null. Adjusted odds ratios (AORs) for > 10 years of exposure were slightly increased, assuming latency periods of 0 or 10 years [AOR = 1.3; 95% confidence interval (CI), 0.9-1.9 and AOR = 1.6; 95% CI, 0.8-3.2, respectively]. Statistically significant associations were estimated for ever-exposed versus never-exposed women when a 20-year latency period was assumed (AOR = 1.9; 95% CI, 1.0-3.4). A sensitivity analysis that classified exposures assuming lower well-pumping rates showed similar results. CONCLUSION. We investigated the hypothesis generated by earlier spatial analyses that exposure to drinking water contaminated by wastewater effluent may be associated with breast cancer. Using a detailed exposure assessment, we found an association with breast cancer that increased with longer latency and greater exposure duration.National Cancer Institute (5R03CA119703-02); National Institute of Environmental Health Sciences (5P42 ES007381

    Private Drinking Water Wells as a Source of Exposure to Perfluorooctanoic Acid (PFOA) in Communities Surrounding a Fluoropolymer Production Facility

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    BACKGROUND: The C8 Health Project was established in 2005 to collect data on perfluorooctanoic acid (PFOA, or C8) and human health in Ohio and West Virginia communities contaminated by a fluoropolymer production facility. OBJECTIVE: We assessed PFOA exposure via contaminated drinking water in a subset of C8 Health Project participants who drank water from private wells. METHODS: Participants provided demographic information and residential, occupational, and medical histories. Laboratory analyses were conducted to determine serum-PFOA concentrations. PFOA data were collected from 2001 through 2005 from 62 private drinking water wells. We examined the relationship between drinking water and PFOA levels in serum using robust regression methods. As a comparison with regression models, we used a first-order, single-compartment pharmacokinetic model to estimate the serum:drinking-water concentration ratio at steady state. RESULTS: The median serum PFOA concentration in 108 study participants who used private wells was 75.7 μg/L, approximately 20 times greater than the levels in the U.S. general population but similar to those of local residents who drank public water. Each 1 μg/L increase in PFOA levels in drinking water was associated with an increase in serum concentrations of 141.5 μg/L (95% confidence interval, 134.9-148.1). The serum:drinking-water concentration ratio for the steady-state pharmacokinetic model was 114. CONCLUSIONS: PFOA-contaminated drinking water is a significant contributor to PFOA levels in serum in the study population. Regression methods and pharmacokinetic modeling produced similar estimates of the relationship

    Using zebrafish embryo bioassays combined with high-resolution mass spectrometry screening to assess ecotoxicological water bodies quality status: A case study in Panama rivers

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    Several studies show that many water bodies in developing countries are increasingly affected by anthropogenic pressure, such as agricultural activities, domestic and industrial wastewater. However, data is scarce in several of such countries, including Panama. Thus, in this work, the ecotoxicological status of selected rivers in Panama with distinct input sources were evaluated using the zebrafish (Danio rerio) embryo bioassays combined with a liquid chromatography-high resolution mass spectrometry screening of contaminants of emerging concern (CECs), using a library of over 3200 chemicals. A total of 68 CECs, including pharmaceuticals and metabolites, pesticides and several industrial chemicals, could be tentatively identified. Additionally, the zebrafish embryo bioassays showed a significant increase (p < 0.05) in embryo mortality/abnormalities when incubated with water samples from two rivers, Matasnillo and Curundú (47.5% and 32%, respectively). Importantly, a positive correlation between ecotoxicological endpoints and some of the detected CECs was observed. The findings demonstrate that both rivers are under strong anthropogenic pressure, and therefore, management actions are urgently needed to decrease their level of contamination. Overall, this study further supports the use of the zebrafish embryo bioassay as a fast, high throughput approach for screening the toxicity of water samples, and highlights the advantages of combining ecotoxicological assays with high-resolution mass spectrometry to an expedite assessment of the ecotoxicological status of water bodies.This work was supported by the Portuguese Foundation for Science and Technology (FCT) (PTDC|CTA-AMB|31554|2017; UIDB/04423/2020; UIDP/04423/2020), the Spanish Agencia Estatal de Investigación (ref. CTM2017-84763-C3-2-R), the Galician Council of Culture, Education and Universities (ref. ED431C2017/36 and Verónica Castro predoctoral contract, ref. ED481A-2017/156), co-funded by the European Regional Development Fund (ERDF/FEDER).2023-02-02S

    Association between Residences in U.S. Northern Latitudes and Rheumatoid Arthritis: A Spatial Analysis of the Nurses’ Health Study

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    Background: The etiology of rheumatoid arthritis (RA) remains largely unknown, although epidemiologic studies suggest genetic and environmental factors may play a role. Geographic variation in incident RA has been observed at the regional level. Objective: Spatial analyses are a useful tool for confirming existing exposure hypotheses or generating new ones. To further explore the association between location and RA risk, we analyzed individual-level data from U.S. women in the Nurses’ Health Study, a nationwide cohort study. Methods: Participants included 461 incident RA cases and 9,220 controls with geocoded addresses; participants were followed from 1988 to 2002. We examined spatial variation using addresses at baseline in 1988 and at the time of case diagnosis or the censoring of controls. Generalized additive models (GAMs) were used to predict a continuous risk surface by smoothing on longitude and latitude while adjusting for known risk factors. Permutation tests were conducted to evaluate the overall importance of location and to identify, within the entire study area, those locations of statistically significant risk. Results: A statistically significant area of increased RA risk was identified in the northeast United States (p-value = 0.034). Risk was generally higher at northern latitudes, and it increased slightly when we used the nurses’ 1988 locations compared with those at the time of diagnosis or censoring. Crude and adjusted models produced similar results. Conclusions: Spatial analyses suggest women living in higher latitudes may be at greater risk for RA. Further, RA risk may be greater for locations that occur earlier in residential histories. These results illustrate the usefulness of GAM methods in generating hypotheses for future investigation and supporting existing hypotheses

    Surveying the woody flora of green spaces in Esperanza city (Santa Fe, Argentina): Some suggestions for its management

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    La ciudad de Esperanza (Provincia de Santa Fe, Argentina) posee espacios verdes tales como parques, plazas y plazoletas que constituyen áreas de esparcimiento y garantizan el desarrollo humano en equilibrio con la naturaleza. Para el conocimiento de estos espacios verdes es fundamental conocer la superficie que ocupan, las especies vegetales, el estado de conservación de las plantas y el manejo que reciben, especialmente las leñosas.Considerando la importancia que el arbolado urbano tiene en esta ciudad se realizó un censo con el objetivo de evaluar las principales características de la flora leñosa de los espacios verdes. Se tomaron datos de las especies existentes, estado sanitario e intervenciones silviculturales. A partir de esta información se propusieron intervenciones silviculturales apropiadas. Finalmente se evaluó la disponibilidad de espacios verdes por habitante y la cantidad de habitantes por árbol.El 74 % de los árboles correspondió a especies exóticas, el estado sanitario en general resultó bueno y el 57 % de los árboles no tuvo ningún tipo de intervención silvicultural evidente. Cada habitante dispone en promedio de 7,64 m2 de espacio verde y la cantidad de habitantes por árbol fue 18,8.Los datos obtenidos constituyen el primer censo de especies leñosas de la infraestructura verde de Esperanza. Se propone aumentar la superficie de espacios verdes y promover la plantación, especialmente con especies nativas.Esperanza City (Santa Fe, Argentina) has green spaces such as parks, squares and small squares devoted to recreational areas and guarantee human development in balance with nature. To fully understand these green spaces, it is essential to know the area they occupy, the plant species included as well as their health condition and the management they receive, particularly the woody ones. Due to the importance given to urban trees in this city, a census was carried out to evaluate the main features of the woody flora int these green spaces. The data collected include: existing species, their health status and silvicultural interventions. Based upon this information, suitable silvicultural interventions were proposed. Finally, the availability of green spaces per inhabitant and the number of inhabitants per tree were evaluated. The results showed that 74 % of the trees corresponded to exotic species with a good general health status and 57 % of the trees showed nom evident silvicultural intervention. There exists an average of 7.64 m2 of green space per inhabitant and 18.8 inhabitants per tree. The data obtained become the first census of woody species of the Esperanza City green infrastructure. It is proposed to increase green space areas and promote planting, especially using native species.Fil: Bender, Adrian Gabriel. Universidad Nacional del Litoral. Facultad de Ciencias Agrarias; ArgentinaFil: Ruiz, Verónica Eugenia. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Ciencias Agropecuarias del Litoral. - Universidad Nacional del Litoral. Instituto de Ciencias Agropecuarias del Litoral.; ArgentinaFil: Gonzalez, M.. Universidad Nacional del Litoral. Facultad de Ciencias Agrarias; ArgentinaFil: Perreta, Mariel Gladis. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Ciencias Agropecuarias del Litoral. - Universidad Nacional del Litoral. Instituto de Ciencias Agropecuarias del Litoral.; ArgentinaFil: Spizzamiglio, S.. Universidad Nacional del Litoral. Facultad de Ciencias Agrarias; ArgentinaFil: Araujo Vieira de Souza, Jonicelia Cristina. Universidad Nacional del Litoral. Facultad de Ciencias Agrarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentin
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