Tap water perceptions and water filter use vary with sociodemographic characteristics and influence water consumption in university students

Abstract Objective The goal of this study is to evaluate university students’ perceptions of tap water safety and water filter use, and determine how these perceptions and behaviors affect water and sugar sweetened beverage intake. Design Cross-sectional; online survey conducted in Fall 2021. Setting A large, public Midwestern university in the United States Participants 793 undergraduate students Results Students who experienced food insecurity, were on a Pell grant, were first generation college students or were racial/ethnic minorities were less likely to trust tap water safety. Tap water filtration behavior also varied by age and race/ethnicity. Students who did not agree with the statement “my local tap water is safe to drink” had lower odds of consuming ≥3 cups of total water per day (OR=0.45, 95% CI: 0.32, 0.62), lower odds of consuming tap water ≥3 times/day (OR=0.46, 95% CI: 0.34, 0.64), higher odds of drinking bottled water ≥1 time per day (OR=1.80, 95% CI: 1.22, 2.66), and higher odds of drinking SSBs ≥1 time per day (OR=1.47, 95% CI: 1.01, 2.14) than those who agreed. Students who always or sometimes filtered their tap water had lower odds of consuming ≥3 cups of total water per day (OR=0.59, 95% CI: 0.39, 0.90) than students who never filtered their tap water. Conclusions Tap water perceptions and behaviors affect tap and bottled water and SSB intake among university students. Tap water perceptions and behaviors in this demographic provide important context for university programming promoting healthy beverage initiatives

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

Toenails as a biomarker of arsenic exposure in Michigan: Refinements in characterization, validation, and application.

Toenails are used in epidemiological studies to assess arsenic exposure from various environmental pathways. To ensure sound application of the biomarker, validity of this tool must first be considered. The objective of this research is to refine knowledge surrounding toenails as an arsenic exposure biomarker, with application to an ongoing population-based case-control study. Utilizing data from 400 bladder cancer cases and 500 controls, this work aims to establish the exposure-biomarker relationship, investigate intra-individual variability of measurements, and assess the relationship between the biomarker value and disease. Participants residing in an eleven-county region of Michigan with historically high groundwater arsenic concentrations answered questions on demographics, smoking, dietary intake and drinking water intake. Drinking water and toenail samples were collected and analyzed for total arsenic. A subpopulation (n=330) was selected for a follow-up visit during which additional drinking water and toenail samples and drinking water intake data were collected. Drinking water arsenic concentration was a significant predictor (p2=0.32). Inclusion of arsenic intake from consumption of beverages made from tap water markedly increased the correlation (R2=0.48). Arsenic concentrations in drinking water samples were highly correlated over time (r=0.88, p<0.0001, n=196), while a substantial amount of variability was detected between toenail samples collected roughly 14 months apart (r=0.43, p<0.0001, n=236). Change in drinking water consumption was significant in predicting temporal differences in toenail arsenic concentration. Stronger correlations between drinking water arsenic concentration and intake and toenail arsenic concentration were observed when two toenail samples were averaged. From these preliminary data, toenail arsenic concentration does not appear to be a significant predictor of bladder cancer risk. These results indicate that toenails can be used as a biomarker of recent arsenic intake via drinking water, and may be useful to retrospectively assess exposure for a population with temporally invariable drinking water arsenic concentrations. Collection of multiple samples or application of the biomarker to prospective studies may minimize exposure misclassification. By supporting biomarker validation and application efforts, this research provides critical insight into the analysis of public health risks associated with low-level arsenic exposure.Ph.D.EpidemiologyHealth and Environmental SciencesPublic healthUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/126823/2/3276295.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.</p