Biomedical subjects

John R Nuckols

Publications and source records attributed to John R Nuckols.

9 recordsLinked to original sources

PubMed2006

Modeling the probability of arsenic in groundwater in New England as a tool for exposure assessment.

We developed a process-based model to predict the probability of arsenic exceeding 5 microg/L in drinking water wells in New England bedrock aquifers. The model is being used for exposure assessment in an epidemiologic study of bladder cancer. One important study hypothesis that may explain increased bladder cancer risk is elevated concentrations of inorganic arsenic in drinking water. In eastern New England, 20-30% of private wells exceed the arsenic drinking water standard of 10 micrograms per liter. Our predictive model significantly improves the understanding of factors associated with arsenic contamination in New England. Specific rock types, high arsenic concentrations in stream sediments, geochemical factors related to areas of Pleistocene marine inundation and proximity to intrusive granitic plutons, and hydrologic and landscape variables relating to groundwater residence time increase the probability of arsenic occurrence in groundwater. Previous studies suggest that arsenic in bedrock groundwater may be partly from past arsenical pesticide use. Variables representing historic agricultural inputs do not improve the model, indicating that this source does not significantly contribute to current arsenic concentrations. Due to the complexity of the fractured bedrock aquifers in the region, well depth and related variables also are not significant predictors.

Arsenic↗

PubMed2006

Geographically based investigation of prostate cancer mortality in four U.S. Northern Plain states.

BACKGROUND: Historically, prostate cancer mortality rates have been elevated in the U.S. Northern Plains states. The purpose of this study was to investigate possible contributing factors, especially whether there was any association with crop patterns. METHODS: Prostate cancer mortality rates (1950-2000) in four northern plains states (MN, MT, ND, and SD) were compared to rates for 46 other U.S. states. Within the four states, county rates in urban, less urban, and rural areas also were compared. For additional analysis, urban counties and counties with <10% of county area in crops were excluded. The average percent of county area in total cropland 1930-1950 and 1954-1974 was estimated. Using Poisson regression, we investigated whether the average percentage of county area in total cropland, 1930-1950 and 1954-1974, was associated with prostate cancer mortality rates, 1975-2000, respectively. Poisson regression analyses were also used to evaluate associations between rates and major crops, which included spring and durum wheat, winter wheat, corn, and other crops. Population centroids of the Census 2000 block groups were used to estimate the percentage of males aged 35 and older residing in close proximity to small grains crops. RESULTS: Mortality rates were higher in rural compared to urban counties in 1950-2000 (rate ratio [RR]=1.032; 95% CI=1.001-1.063). Rates in 1950-1974 were significantly associated with production of corn and other crops in 1930-1950 (corn: RR per 10% increase=1.033, 95% CI=1.012-1.054; other crops: RR=1.042, 95% CI=1.021-1.063). Mortality rates in 1975-2000 were significantly associated with spring and durum wheat production in 1954-1974 (RR per 10% increase=1.042, 95% CI=1.017-1.067). Prostate cancer mortality rates increased as the percentage of population living within 500 m of small grains crops increased. CONCLUSIONS: Epidemiologic studies to evaluate agricultural practices are warranted to further evaluate the observed associations.

Adult↗

PubMed2006

Proximity to crops and residential exposure to agricultural herbicides in iowa.

Rural residents can be exposed to agricultural pesticides through the proximity of their homes to crop fields. Previously, we developed a method to create historical crop maps using a geographic information system. The aim of the present study was to determine whether crop maps are useful for predicting levels of crop herbicides in carpet dust samples from residences. From homes of participants in a case-control study of non-Hodgkin lymphoma in Iowa (1998-2000), we collected vacuum cleaner dust and measured 14 herbicides with high use on corn and soybeans in Iowa. Of 112 homes, 58% of residences had crops within 500 m of their home, an intermediate distance for primary drift from aerial and ground applications. Detection rates for herbicides ranged from 0% for metribuzin and cyanazine to 95% for 2,4-dichlorophenoxyacetic acid. Six herbicides used almost exclusively in agriculture were detected in 28% of homes. Detections and concentrations were highest in homes with an active farmer. Increasing acreage of corn and soybean fields within 750 m of homes was associated with significantly elevated odds of detecting agricultural herbicides compared with homes with no crops within 750 m (adjusted odds ratio per 10 acres = 1.06; 95% confidence interval, 1.02-1.11). Herbicide concentrations also increased significantly with increasing acreage within 750 m. We evaluated the distance of crop fields from the home at < 100, 101-250, 251-500, and 501-750 m. Including the crop buffer distance parameters in the model did not significantly improve the fit compared with a model with total acres within 750 m. Our results indicate that crop maps may be a useful method for estimating levels of herbicides in homes from nearby crop fields.

Case-Control Studies↗

PubMed2006

Agricultural pesticide use and hypospadias in eastern Arkansas.

INTRODUCTION: We assessed the relationship between hypospadias and proximity to agricultural pesticide applications using a GIS-based exposure method. METHODS: We obtained information for 354 cases of hypospadias born between 1998 and 2002 in eastern Arkansas; 727 controls were selected from birth certificates. We classified exposure on pounds of pesticides (estimated by crop type) applied or persisting within 500 m of each subject's home during gestational weeks 6 to 16. We restricted our analyses to 38 pesticides with some evidence of reproductive, developmental, estrogenic, and/or antiandrogenic effects. We estimated timing of pesticide applications using crop phenology and published records. RESULTS: Gestational age at birth [odds ratio (OR) = 0.91; 95% confidence interval (CI), 0.83-0.99], parity (OR = 0.79; 95% CI, 0.65-0.95), and delaying prenatal care until the third trimester (OR = 4.04; 95% CI, 1.46-11.23) were significantly associated with hypospadias. Risk of hypospadias increased by 8% for every 0.05-pound increase in estimated exposure to diclofop-methyl use (OR = 1.08; 95% CI, 1.01-1.15). Pesticide applications in aggregate (OR = 0.82; 95% CI, 0.70-0.96) and applications of alachlor (OR = 0.56; 95% CI, 0.35-0.89) and permethrin (OR = 0.37; 95% CI, 0.16-0.86) were negatively associated with hypospadias. CONCLUSIONS: Except for diclofop-methyl, we did not find evidence that estimated exposure to pesticides known to have reproductive, developmental, or endocrine-disrupting effects increases risk of hypospadias. Further research on the potential effects of exposure to diclofop-methyl is recommended.

Agricultural Workers' Diseases↗

PubMed2005

Positional accuracy of two methods of geocoding.

BACKGROUND: Geocoding is often used in epidemiologic studies to map residences with geographic information systems (GIS). The accuracy of the method is usually not determined. METHODS: We collected global positioning system (GPS) measurements at homes in a case-control study of non-Hodgkin lymphoma in Iowa. We geocoded the addresses by 2 methods: (1) in-house, using ArcView 3.2 software and the U.S. Census Bureau TIGER 2000 street database; and (2) automated geocoding by a commercial firm. We calculated the distance between the geocoded and GPS location (positional error) overall and separately for homes within towns and outside (rural). We evaluated the error in classifying homes with respect to their proximity to crop fields. RESULTS: Overall, the majority of homes were geocoded with positional errors of less than 100 m by both methods (ArcView/TIGER 2000, median = 62 m [interquartile range = 39-103]; commercial firm, median = 61 m [interquartile range = 35-137]). For town residences, the percent geocoded with errors of </=100 m was 81% for ArcView/TIGER 2000 and 84% for the commercial firm. For rural residences, a smaller percent of addresses were geocoded with this level of accuracy, especially by the commercial firm (ArcView/TIGER 2000, 56%; commercial firm, 28%). Geocoding errors affected our classification of homes according to their proximity to agricultural fields at 100 m, but not at greater distances (250-500 m). CONCLUSIONS: Our results indicate greater positional errors for rural addresses compared with town addresses. Using a commercial firm did not improve accuracy compared with our in-house method. The effect of geocoding errors on exposure classification will depend on the spatial variation of the exposure being studied.

Adult↗

PubMed2005

Influence of tap water quality and household water use activities on indoor air and internal dose levels of trihalomethanes.

Individual exposure to trihalomethanes (THMs) in tap water can occur through ingestion, inhalation, or dermal exposure. Studies indicate that activities associated with inhaled or dermal exposure routes result in a greater increase in blood THM concentration than does ingestion. We measured blood and exhaled air concentrations of THM as biomarkers of exposure to participants conducting 14 common household water use activities, including ingestion of hot and cold tap water beverages, showering, clothes washing, hand washing, bathing, dish washing, and indirect shower exposure. We conducted our study at a single residence in each of two water utility service areas, one with relatively high and the other low total THM in the residence tap water. To maintain a consistent exposure environment for seven participants, we controlled water use activities, exposure time, air exchange, water flow and temperature, and nonstudy THM sources to the indoor air. We collected reference samples for water supply and air (pre-water use activity), as well as tap water and ambient air samples. We collected blood samples before and after each activity and exhaled breath samples at baseline and post-activity. All hot water use activities yielded a 2-fold increase in blood or breath THM concentrations for at least one individual. The greatest observed increase in blood and exhaled breath THM concentration in any participant was due to showering (direct and indirect), bathing, and hand dishwashing. Average increase in blood THM concentration ranged from 57 to 358 pg/mL due to these activities. More research is needed to determine whether acute and frequent exposures to THM at these concentrations have public health implications. Further research is also needed in designing epidemiologic studies that minimize data collection burden yet maximize accuracy in classification of dermal and inhalation THM exposure during hot water use activities.

Air Pollutants↗

PubMed2004

Using geographic information systems for exposure assessment in environmental epidemiology studies.

Geographic information systems (GIS) are being used with increasing frequency in environmental epidemiology studies. Reported applications include locating the study population by geocoding addresses (assigning mapping coordinates), using proximity analysis of contaminant source as a surrogate for exposure, and integrating environmental monitoring data into the analysis of the health outcomes. Although most of these studies have been ecologic in design, some have used GIS in estimating environmental levels of a contaminant at the individual level and to design exposure metrics for use in epidemiologic studies. In this article we discuss fundamentals of three scientific disciplines instrumental to using GIS in exposure assessment for epidemiologic studies: geospatial science, environmental science, and epidemiology. We also explore how a GIS can be used to accomplish several steps in the exposure assessment process. These steps include defining the study population, identifying source and potential routes of exposure, estimating environmental levels of target contaminants, and estimating personal exposures. We present and discuss examples for the first three steps. We discuss potential use of GIS and global positioning systems (GPS) in the last step. On the basis of our findings, we conclude that the use of GIS in exposure assessment for environmental epidemiology studies is not only feasible but can enhance the understanding of the association between contaminants in our environment and disease.

Cluster Analysis↗

PubMed2003

Neurobehavioral effects of exposure to trichloroethylene through a municipal water supply.

We studied a population-based sample of 143 residents of a community in which the municipal water supply had been contaminated with trichloroethylene (TCE) and related chemicals from several adjacent hazardous waste sites between 1981 and 1986. A hydraulic simulation model was used in conjunction with a geographic information system (GIS) to estimate residential water supply exposures to TCE; 80% of the participants had potential TCE exposure exceeding the maximum contaminant level (5 ppb). The Neurobehavioral Core Test Battery (NCTB), tests of visual contrast sensitivity, and the profile of mood states (POMS) were administered approximately 6 years following peak concentrations of TCE in municipal drinking water. Multivariate analysis of variance adjusted for potential confounders was used to compare mean test scores of residents classified by estimated TCE exposure (< or =5, >5-10, >10-15, >15 ppb). TCE exposure >15 ppb was associated with poorer performance on the digit symbol, contrast sensitivity C test, and contrast sensitivity D test and higher mean scores for confusion, depression, and tension. We found evidence of a strong interaction between exposure to TCE and alcohol consumption; the associations for the NCTB and POMS among persons in the high-exposure group who also consumed alcohol were stronger and were statistically significant for the Benton, digit symbol, digit span, and simple reaction time tests, as well as for confusion, depression, and tension. This study adds to the evidence that long-term exposure to low concentrations of TCE is associated with neurobehavioral deficits and demonstrates the usefulness of GIS-based modeling in exposure assessment.

Adult↗

PubMed2002

Sampling private wells at past homes to estimate arsenic exposure: a methodologic study in New England.

We are conducting a collaborative, population-based case-control study in Maine, New Hampshire, and Vermont to investigate the reasons for the elevated bladder cancer mortality in northern New England. Arsenic in drinking water is one of the primary exposures under investigation. To estimate subjects' lifetime exposure to waterborne arsenic, it will be necessary to obtain water samples from private wells that subjects used in the past. We conducted a methodologic study to assess the feasibility of locating and sampling from private wells at subjects' past residences. Ninety-eight New Hampshire residents (mean age 67 years) completed a questionnaire requesting the complete address, dates of occupancy, and drinking water sources for each home lived in since birth. An interviewer then asked subjects for more detailed information about each home to assist in a field search of past homes in the three-state study area of Maine, New Hampshire, and Vermont. Fifty-eight of the 98 subjects indicated that they had used a total of 103 private wells in 95 previous homes located in these three states. We conducted a field search to locate these 95 homes, visited town offices to find the properties on tax maps and obtain the current owners' names and addresses, attempted to obtain permission from the current owners to sample the wells, and collected water samples. In all, 48 (47%) of the 103 past wells in the study area were sampled successfully. The remaining wells were not sampled because the homes were not located (22%) or had been demolished (2%), permission to sample the wells was not obtained (17%), the wells had been destroyed (7%) or could not be found on the grounds of the residence (3%), or for other reasons (2%). Various approaches for improving the success rates for sampling water from private wells are discussed, as is the use of predictive modeling to impute exposures when sampling is not feasible.

Adult↗