Case-control geographic clustering for residential histories accounting for risk factors and covariates

BACKGROUND: Methods for analyzing space-time variation in risk in case-control studies typically ignore residential mobility. We develop an approach for analyzing case-control data for mobile individuals and apply it to study bladder cancer in 11 counties in southeastern Michigan. At this time data collection is incomplete and no inferences should be drawn – we analyze these data to demonstrate the novel methods. Global, local and focused clustering of residential histories for 219 cases and 437 controls is quantified using time-dependent nearest neighbor relationships. Business address histories for 268 industries that release known or suspected bladder cancer carcinogens are analyzed. A logistic model accounting for smoking, gender, age, race and education specifies the probability of being a case, and is incorporated into the cluster randomization procedures. Sensitivity of clustering to definition of the proximity metric is assessed for 1 to 75 k nearest neighbors. RESULTS: Global clustering is partly explained by the covariates but remains statistically significant at 12 of the 14 levels of k considered. After accounting for the covariates 26 Local clusters are found in Lapeer, Ingham, Oakland and Jackson counties, with the clusters in Ingham and Oakland counties appearing in 1950 and persisting to the present. Statistically significant focused clusters are found about the business address histories of 22 industries located in Oakland (19 clusters), Ingham (2) and Jackson (1) counties. Clusters in central and southeastern Oakland County appear in the 1930's and persist to the present day. CONCLUSION: These methods provide a systematic approach for evaluating a series of increasingly realistic alternative hypotheses regarding the sources of excess risk. So long as selection of cases and controls is population-based and not geographically biased, these tools can provide insights into geographic risk factors that were not specifically assessed in the case-control study design

Spatial clustering of emergency department visits by asthmatic children in an urban area: south-western Detroit, Michigan

Objective This ecological study evaluates the correlation of asthma clusters with outdoor air pollution, race, and household income in South-western Detroit, Michigan. Design To attain this objective (1) a geographic information aystem (GIS) is utilized to evaluate the relationships between rates of emergency department (ED) admissions for asthma, race, and socio-economic status at the neighborhood block group level of analysis; (2) cluster statistical analyses are performed using Geomed software; and (3) the asthma risk from industrial air pollution was evaluated with windrose data and Screen3 air pollution model. Sample Data from five major hospitals with ED admissions of asthma patients (code 493), aged 0–15 years, are used to select a region of analysis with good geographical representation based on the catchment areas of hospitals in the study. A total of 2067 of the reported cases between 1 January 1993 and 30 June 1998, are successfully geocoded to a map, generating a no-match rate of 8.4%. Data on racial characteristics, population density, and household income levels are obtained from neighborhood block groups in the 1990 census report. Locations of major polluting industries within the study area are obtained from the Toxics Release Inventory. Results Spatial analysis identified a local asthma cluster roughly 2 km east (the predominant downwind direction) of the second and third largest air polluters (in terms of tonnage) in Wayne County. Evaluation of the industrial pollution with a focused cluster test, Screen3 air pollution model, and windrose figures, displayed weak association between ED asthma admissions and estimated levels of outdoor air pollution from these two facilities. The neighborhood block groups in the local asthma cluster are more closely correlated with high proportions of African Americans and low median household income. Implications for practice This study illustrates the strengths and weaknesses of GIS in the public health arena. It highlights the difficulty of disentangling the effects of exposure to outdoor air pollutants and socio-economic factors on ED asthmatics (reflecting asthma severity) among an urban population. This study also illustrates the need for population-based, as opposed to hospital-based, asthma data, and the need for block-groups, as opposed to zip codes, as a spatial unit of analysis in the evaluation and analysis of asthma-related risk factors.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73994/1/j.1467-0658.2001.00143.x.pd

Visualization and exploratory analysis of epidemiologic data using a novel space time information system

Abstract Background Recent years have seen an expansion in the use of Geographic Information Systems (GIS) in environmental health research. In this field GIS can be used to detect disease clustering, to analyze access to hospital emergency care, to predict environmental outbreaks, and to estimate exposure to toxic compounds. Despite these advances the inability of GIS to properly handle temporal information is increasingly recognised as a significant constraint. The effective representation and visualization of both spatial and temporal dimensions therefore is expected to significantly enhance our ability to undertake environmental health research using time-referenced geospatial data. Especially for diseases with long latency periods (such as cancer) the ability to represent, quantify and model individual exposure through time is a critical component of risk estimation. In response to this need a STIS – a Space Time Information System has been developed to visualize and analyze objects simultaneously through space and time. Results In this paper we present a "first use" of a STIS in a case-control study of the relationship between arsenic exposure and bladder cancer in south eastern Michigan. Individual arsenic exposure is reconstructed by incorporating spatiotemporal data including residential mobility and drinking water habits. The unique contribution of the STIS is its ability to visualize and analyze residential histories over different temporal scales. Participant information is viewed and statistically analyzed using dynamic views in which values of an attribute change through time. These views include tables, graphs (such as histograms and scatterplots), and maps. In addition, these views can be linked and synchronized for complex data exploration using cartographic brushing, statistical brushing, and animation. Conclusion The STIS provides new and powerful ways to visualize and analyze how individual exposure and associated environmental variables change through time. We expect to see innovative space-time methods being utilized in future environmental health research now that the successful "first use" of a STIS in exposure reconstruction has been accomplished.http://deepblue.lib.umich.edu/bitstream/2027.42/112824/1/12942_2004_Article_41.pd

Improving exposure assessment in environmental epidemiology: Application of spatio-temporal visualization tools

A thorough assessment of human exposure to environmental agents should incorporate mobility patterns and temporal changes in human behaviors and concentrations of contaminants; yet the temporal dimension is often under-emphasized in exposure assessment endeavors, due in part to insufficient tools for visualizing and examining temporal datasets. Spatio-temporal visualization tools are valuable for integrating a temporal component, thus allowing for examination of continuous exposure histories in environmental epidemiologic investigations. An application of these tools to a bladder cancer case-control study in Michigan illustrates continuous exposure life-lines and maps that display smooth, continuous changes over time. Preliminary results suggest increased risk of bladder cancer from combined exposure to arsenic in drinking water (>25 μ g/day) and heavy smoking (>30 cigarettes/day) in the 1970s and 1980s, and a possible cancer cluster around automotive, paint, and organic chemical industries in the early 1970s. These tools have broad application for examining spatially- and temporally-specific relationships between exposures to environmental risk factors and disease.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47931/1/10109_2005_Article_149.pd

Genetic variation in Glutathione S-Transferase Omega-1, Arsenic Methyltransferase and Methylene-tetrahydrofolate Reductase, arsenic exposure and bladder cancer: a case–control study

Abstract Background Ingestion of groundwater with high concentrations of inorganic arsenic has been linked to adverse health outcomes, including bladder cancer, however studies have not consistently observed any elevation in risk at lower concentrations. Genetic variability in the metabolism and clearance of arsenic is an important consideration in any investigation of its potential health risks. Therefore, we examined the association between genes thought to play a role in the metabolism of arsenic and bladder cancer. Methods Single nucleotide polymorphisms (SNPs) in GSTO-1, As3MT and MTHFR were genotyped using DNA from 219 bladder cancer cases and 273 controls participating in a case–control study in Southeastern Michigan and exposed to low to moderate (<50 μg/L) levels of arsenic in their drinking water. A time-weighted measure of arsenic exposure was constructed using measures from household water samples combined with past residential history, geocoded and merged with archived arsenic data predicted from multiple resources. Results While no single SNP in As3MT was significantly associated with bladder cancer overall, several SNPs were associated with bladder cancer among those exposed to higher arsenic levels. Individuals with one or more copies of the C allele in rs11191439 (the Met287Thr polymorphism) had an elevated risk of bladder cancer (OR = 1.17; 95% CI = 1.04-1.32 per 1 μg/L increase in average exposure). However, no association was observed between average arsenic exposure and bladder cancer among TT homozygotes in the same SNP. Bladder cancer cases were also 60% less likely to be homozygotes for the A allele in rs1476413 in MTHFR compared to controls (OR = 0.40; 95% CI = 0.18-0.88). Conclusions Variation in As3MT and MTHFR is associated with bladder cancer among those exposed to relatively low concentrations of inorganic arsenic. Further investigation is warranted to confirm these findings.http://deepblue.lib.umich.edu/bitstream/2027.42/112833/1/12940_2012_Article_570.pd

Genetic variation in Glutathione S-Transferase Omega-1, Arsenic Methyltransferase and Methylene-tetrahydrofolate Reductase, arsenic exposure and bladder cancer: a case–control study

Abstract Background Ingestion of groundwater with high concentrations of inorganic arsenic has been linked to adverse health outcomes, including bladder cancer, however studies have not consistently observed any elevation in risk at lower concentrations. Genetic variability in the metabolism and clearance of arsenic is an important consideration in any investigation of its potential health risks. Therefore, we examined the association between genes thought to play a role in the metabolism of arsenic and bladder cancer. Methods Single nucleotide polymorphisms (SNPs) in GSTO-1, As3MT and MTHFR were genotyped using DNA from 219 bladder cancer cases and 273 controls participating in a case–control study in Southeastern Michigan and exposed to low to moderate (\u3c50 μg/L) levels of arsenic in their drinking water. A time-weighted measure of arsenic exposure was constructed using measures from household water samples combined with past residential history, geocoded and merged with archived arsenic data predicted from multiple resources. Results While no single SNP in As3MT was significantly associated with bladder cancer overall, several SNPs were associated with bladder cancer among those exposed to higher arsenic levels. Individuals with one or more copies of the C allele in rs11191439 (the Met287Thr polymorphism) had an elevated risk of bladder cancer (OR = 1.17; 95% CI = 1.04-1.32 per 1 μg/L increase in average exposure). However, no association was observed between average arsenic exposure and bladder cancer among TT homozygotes in the same SNP. Bladder cancer cases were also 60% less likely to be homozygotes for the A allele in rs1476413 in MTHFR compared to controls (OR = 0.40; 95% CI = 0.18-0.88). Conclusions Variation in As3MT and MTHFR is associated with bladder cancer among those exposed to relatively low concentrations of inorganic arsenic. Further investigation is warranted to confirm these findings