Modelling exposure to disinfection by-products in drinking water for an epidemiological study of adverse birth outcomes

Abstract

We are conducting an epidemiological study on the association between disinfection by-product concentrations in drinking water and adverse birth outcomes in the UK, using trihalomethane (THM) concentrations over defined water zones as an exposure index. Here we construct statistical models using sparse routinely collected THMs measurements to obtain quarterly estimates of mean THM concentrations for each water zone. We modelled the THM measurements using a Bayesian hierarchical mixture model, taking into account heterogeneity in THM concentrations between water originating from different source types, quarterly variation in THM concentrations and uncertainty in the true value of undetected and rounded measurements. Quarterly estimates of mean THM concentrations plus estimates of the water source type (ground, lowland surface or upland surface) were obtained for each water zone. THM concentration estimates were typically highest from July to September (third quarter), and varied considerably between water sources. Our exposure estimates were categorized into 'low', 'medium' and 'high' THM classes. Our modelled quarterly exposure estimates were compared to a simple alternative: annual means of the raw data for each water zone. In all, 15-25% of exposure estimates were classified differently. The modelled THM estimates led to slightly stronger and more precise estimates of association with risk of still birth and low birth weight than did the raw annual means. We conclude that our modelling approach enabled us to provide robust quarterly estimates of ecological exposure to THMs in a situation where the raw data were too sparse to base exposure assessment on empirical summaries alone.

Relation of Trihalomethane Concentrations in Public Water Supplies to Stillbirth and Birth Weight in Three Water Regions in England

“…This was done using a hierarchical mixture model in the software WinBUGS (Bayesian inference using Gibbs sampling) (Spiegelhalter et al 1996), as described elsewhere (Whitaker et al 2004). Briefly, modeling was carried out separately for each water company and year.…”

Chlorination by-products in tap water and semen quality in England and Wales

“…Our modelled THMs gave more precise estimates of THM concentrations in the water zone where the men resided than quarterly monitoring data would have done,27 and exposure information was weighted to 90 days prior to the semen sample collection. The uncertainty associated with the modelled THM estimates was on average less than 20% of the between-zone variability and therefore incorporation of this uncertainty via multiple imputation or Bayesian analysis would be unlikely to influence the results 33.…”

“…Men in this study lived in 1568 different water zones, and analysis of quarterly THM data from some of these water companies between 1998 and 2001 shows that variance in TTHM concentrations was greater between water zones than within 26. The THM data were modelled using Bayesian methods,27 to obtain more robust quarterly, water zone specific estimates of the mean concentration of each THM. The participant's postcode of residence was georeferenced and mapped to the corresponding water zone using ARCMap V.9.1 geographical information systems (GIS).…”

Health impacts of long-term exposure to disinfection by-products in drinking water in Europe: HIWATE

“…Statistical techniques will be employed to quantify the effect of these determinants on the formation of DBPs and use this to build a predictive model of DBP formation (Golfinopoulos & Arhonditsis 2002;Nikolaou et al 2004;Whitaker et al 2005). Furthermore, the correlation between THMs and other DBPs will be assessed.…”