Rapid evaluation of human biomonitoring data using pattern recognition systems.

Assessing human biomonitoring data often necessitates dealing with fragmentary prior knowledge and a complex set of variables. A procedure for explorative data analysis via decision-tree analysis was undertaken to obtain high-level descriptive summary information on human exposure on a timely basis. This study is based on a subset of monitoring data of the Environmental Specimen Bank for Human Tissues within the German Environmental Specimen Bank (n sigma: 2401: 42/58% males/females; 34/66% born in East/West Germany). Three well-known xenobiotic organochlorines (XOCs) [sum of polychlorinated biphenyls (PCBs) 138 + 153 + 180, pentachlorophenol (PCP), and hexachlorobenzene (HCB)] were used as target variables. Meta-data regarding the samples and individuals were collected via a self-reported questionnaire and used as potential predictor variables. Prior to decision-tree analysis, XOC levels were adjusted (trend, lipids, creatinine, total protein) via stepwise linear regression. Adjusted XOC levels were subsequently utilized to identify relevant predictors of human XOC exposure using Exhaustive CHAID as a common decision-tree algorithm. Although overall tree model quality is generally poor, consistent and plausible predictors for human exposure were identified. Besides time trend and clinical parameters, the predominant predictors for HCB and PCB exposure were birthplace, gender, age, body mass index (BMI), and consumption of milk/dairy products or animal fats. For PCP, predominant predictors were sampling site, gender, and consumption of animal fats. Summing results of decision-tree models and regression models, explained variances for metric scaled XOC are: PCB (34.2%) > HCB (30.3%) > PCP (17.2%). Explorative analysis of human biomonitoring data based on simple decision-tree analysis provides valuable information for planning further investigations and statistical data for analyses to support prediction, consequences, and regulation of XOC.

The German Multicentre Study on Multiple Chemical Sensitivity (MCS).

In this multicentre study on multiple chemical sensitivity (MCS) 291 consecutive environmental medicine (EM) outpatients were examined in several environmental medicine outpatient centres/units throughout Germany in 2000/2003. Of the EM outpatients, 89 were male (30.6%) and 202 were female (69.4%), aged 22-80 (mean 48 years, S.D.=12 years). The sample was representative for university-based environmental outpatient departments and represented a cross-sectional study design with an integrated clinical-based case-control comparison (MCS vs. non-MCS). Three classifications of MCS were used: self-reported MCS (sMCS), clinically diagnosed MCS (cMCS), and formalised computer-assisted MCS with two variants (f1MCS, f2MCS). Data were collected by means of an environmental medicine questionnaire, psychosocial questionnaires, the German version of the Composite International Diagnostic Interview (CIDI), and a medical baseline documentation, as well as special examinations in partial projects on olfaction and genetic susceptibility markers. The hypothesis guided evaluation of the project showed that the patients' heterogenic health complaints did not indicate a characteristic set of symptoms for MCS. No systematic connection could be observed between complaints and the triggers implicated, nor was there any evidence for a genetic predisposition, or obvious disturbances of the olfactory system. The standardised psychiatric diagnostics applying CIDI demonstrated that the EM patients in general and the subgroup with MCS in particular suffered more often from mental disorders compared to an age and gender matched sample of the general population and that in most patients these disorders commenced many years before environment-related health complaints. Our results do not support the assumption of a toxicogenic-somatic basis of the MCS phenomenon. In contrast, numerous indicators for the relevance of behavioural accentuations, psychic alterations or psychosomatic impairments were found in the group of EM-outpatients with subjective "environmental illness".