A sensitivity analysis of bias in relative risk estimates due to disinfection by-product exposure misclassification

Abstract

We conducted a sensitivity analysis of relative risk estimates using local area mean disinfection by-product exposures. We used Monte Carlo simulations to generate data representing 100 towns, each with 100 births (n ¼ 10,000). Each town was assigned a mean total trihalomethane (TTHM) exposure value (mean ¼ 45, SD ¼ 28) based on a variable number of sampling locations (range 2-10). True maternal TTHM exposure was randomly assigned from a lognormal distribution using that town's true mean value. We compared the effect of a 20 mg/l increase in TTHM exposure on the risk of small-forgestational age infancy using the true maternal exposure compared to various weighting measures of the town mean exposures. The exposure metrics included: (1) unweighted town mean, (2) town mean weighted by the inverse variance of the town mean, (3) town mean weighted by the inverse standard deviation of the town mean, (4) town mean weighted by 1À(standard deviation of sites per town/mean across all towns), and (5) a randomly selected value from one of the sites within the town of residence. To estimate the magnitude of misclassification bias from using the town mean concentrations, we compared the true exposure odds ratios (1.00, 1.20, 1.50, and 2.00) to the mean exposure odds ratios from the five exposure scenarios. Misclassification bias from the use of unweighted town mean exposures ranged from 19 to 39%, increasing in proportion to the size of the true effect estimates. Weighted town mean TTHM exposures were less biased than the unweighted estimates of maternal exposure, with bias ranging from 0 to 23%. The weighted town mean analyses showed that attenuation of the true effect of DBP exposure was diminished when town mean concentrations with large variability were downweighted. We observed a trade-off between bias and precision in the weighted exposure analyses, with the least biased effects estimates having the widest confidence intervals. Effect attenuation due to intrasystem variability was most evident in absolute and relative terms for larger odds ratios.

Case control study of the geographic variability of exposure to disinfectant byproducts and risk for rectal cancer

“…Although colorectal cancer risk has been linked with a variety of ecological based water studies [27-29], with the exception of rodent studies, we found no strong previous evidence in the literature suggesting and/or supporting a specific association of rectal cancer risk with exposure to bromoform in humans. Studies of risk associated with exposure to DBPs are often based on indirect exposure assessments that rely on relatively large scales of geographic classifications of DBPs [54], and classification of exposed and unexposed groups is often made based on town, parish, or areas served by specific water treatment systems [28,29,31,42,55]. …”

Identifying public water facilities with low spatial variability of disinfection by-products for epidemiological investigations

“…This method may be appropriate for adjustment of biased exposure estimates when systems with high spatial variability must be utilised; however, as recently reported in a paper by Wright and Bateson, the applicability of this method may depend on degree of spatial variability and magnitude of ''true'' risk estimated for a given birth outcome. 4 We evaluated two methods for selection of populations served by water distribution systems with minimal spatial variability in the concentrations of TTHMs. Using the two way ANOVA method, we compared TTHM levels between four sampling points in the distribution system controlling Table 2 Total and individual THMs and sum of 5 HAAs (mg/l) for plants categorised into each of three profiles by the ANOVA and cut-points methods for the influence of season and identified 17 sites with low spatial variability in four consecutive seasons.…”

“…2 However, there is general agreement that limitations in exposure assessment have resulted in substantial misclassification of exposure in these studies, making the true risk difficult to determine. [1][2][3][4] For example, in most epidemiological studies conducted to date, all persons living within the boundaries of a water distribution system have been assigned a common exposure value based on facility-wide averages of trihalomethane (THM) concentrations for a point in time of interest. Use of public water facility monitoring data can result in exposure misclassification when persons living at different locations within a distribution system are exposed to significantly different concentrations of THMs but are assigned a common exposure level.…”

Variability and predictors of changes in water use during pregnancy

“…Studies of pregnant women are particularly susceptible because the lifealtering event of pregnancy might cause direct changes in selfawareness and intentional changes in behavior over a relatively short-time period. Previous research has suggested that exposure to disinfection by-products (DBPs) in public tap water may be associated with adverse pregnancy outcomes (Nieuwenhuijsen et al, 2000;Graves et al, 2001;Bove et al, 2002), but many of the existing studies have relied solely on concentration of DBPs in municipal water sources, potentially resulting in exposure misclassification by ignoring variation in behaviors (Waller et al, 2001;Wright and Bateson 2005;Wright et al, 2006). Recent improvements in exposure assessment have resulted in collection and integration of information about individual women's water use habits .…”