Neurobehavioural effects of occupational exposure to organic solvents among construction painters. 1987

A T Fidler, and E L Baker, and R E Letz

A cross sectional study of 101 construction painters was performed to investigate the relation between exposure to mixed organic solvents and changes in central nervous system function. Solvent exposure was estimated using questionnaire data to derive an exposure index (a measure of intensity of exposure) and to estimate the duration and frequency of exposure. Adverse effects on the central nervous system were assessed by self reported questionnaires and eight tests of a computer administered neurobehavioural evaluation system. Factor analysis of both measures of effect yielded factors both biologically plausible and in agreement with other empirical evidence. A consistent positive association was observed between most measures of exposure and the occurrence of neurotoxic symptoms, notably dizziness, nausea, fatigue, problems with arm strength, and feelings of getting "high" from chemicals at work. Associations with exposure were found with the neurobehavioural evaluation system tests of symbol digit substitution and digit span; however, no consistent pattern of effect on neurobehavioural function was observed. This pattern of the occurrence of neurotoxic symptoms without clear evidence of function deficit is consistent with the type 1 toxic central nervous system disorder as classified by the World Health Organisation.

UI MeSH Term Description Entries
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D009784 Occupational Diseases Diseases caused by factors involved in one's employment. Diseases, Occupational,Occupational Illnesses,Disease, Occupational,Illnesse, Occupational,Illnesses, Occupational,Occupational Disease,Occupational Illnesse
D010150 Paint An emulsion of solid color which when spread over a surface leaves a thin decorative and or protective coating. Varnish,Paints
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D002493 Central Nervous System Diseases Diseases of any component of the brain (including the cerebral hemispheres, diencephalon, brain stem, and cerebellum) or the spinal cord. CNS Disease,Central Nervous System Disease,Central Nervous System Disorder,CNS Diseases,Central Nervous System Disorders
D003430 Cross-Sectional Studies Studies in which the presence or absence of disease or other health-related variables are determined in each member of the study population or in a representative sample at one particular time. This contrasts with LONGITUDINAL STUDIES which are followed over a period of time. Disease Frequency Surveys,Prevalence Studies,Analysis, Cross-Sectional,Cross Sectional Analysis,Cross-Sectional Survey,Surveys, Disease Frequency,Analyses, Cross Sectional,Analyses, Cross-Sectional,Analysis, Cross Sectional,Cross Sectional Analyses,Cross Sectional Studies,Cross Sectional Survey,Cross-Sectional Analyses,Cross-Sectional Analysis,Cross-Sectional Study,Cross-Sectional Surveys,Disease Frequency Survey,Prevalence Study,Studies, Cross-Sectional,Studies, Prevalence,Study, Cross-Sectional,Study, Prevalence,Survey, Cross-Sectional,Survey, Disease Frequency,Surveys, Cross-Sectional
D005163 Factor Analysis, Statistical A set of statistical methods for analyzing the correlations among several variables in order to estimate the number of fundamental dimensions that underlie the observed data and to describe and measure those dimensions. It is used frequently in the development of scoring systems for rating scales and questionnaires. Analysis, Factor,Analysis, Statistical Factor,Factor Analysis,Statistical Factor Analysis,Analyses, Factor,Analyses, Statistical Factor,Factor Analyses,Factor Analyses, Statistical,Statistical Factor Analyses
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000328 Adult A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available. Adults
D000368 Aged A person 65 years of age or older. For a person older than 79 years, AGED, 80 AND OVER is available. Elderly

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