Semiparametric modeling of the spatial distribution of occupational accident risk in the casual labor market, Piracicaba, southeast Brazil

The objective of this study was to estimate the spatial distribution of work accident risk in the informal work market in the urban zone of an industrialized city in southeast Brazil and to examine concomitant effects of age, gender, and type of occupation after controlling for spatial risk variation. The basic methodology adopted was that of a population-based case-control study with particular interest focused on the spatial location of work. Cases were all casual workers in the city suffering work accidents during a one-year period; controls were selected from the source population of casual laborers by systematic random sampling of urban homes. The spatial distribution of work accidents was estimated via a semiparametric generalized additive model with a nonparametric bidimensional spline of the geographical coordinates of cases and controls as the nonlinear spatial component, and including age, gender, and occupation as linear predictive variables in the parametric component. We analyzed 1,918 cases and 2,245 controls between 1/11/2003 and 31/10/2004 in Piracicaba, Brazil. Areas of significantly high and low accident risk were identified in relation to mean risk in the study region (p < 0.01). Work accident risk for informal workers varied significantly in the study area. Significant age, gender, and occupational group effects on accident risk were identified after correcting for this spatial variation. A good understanding of high-risk groups and high-risk regions underpins the formulation of hypotheses concerning accident causality and the development of effective public accident prevention policies.

Association between distressing non-work-related events and occupational injuries

The following is a report on a case-control study whose objective was to investigate the association between distressing non-work-related events and occupational injures. Ninety three injured workers (cases) were matched with 372 non-injured controls in a large metallurgical factory in southeastern Brazil. Exposure to distressing non-work-related events was measured through a questionnaire focusing on situations pertaining to personal problems unrelated to work activities. The data were analyzed by adjusting a conditional logistic regression model, where occurrence of the work injury was the dependent dichotomous variable and answers from the questionnaire were independent continuous variables. The analysis showed an association between some distressing non-work-related events and occupational injuries. These findings imply expanding the horizon of preventive measures used in targeting. work injuries which have traditionally been focused on the control of strictly workplace risks.

Stressful life events and occupational accidents

Objective: The purpose of this study was to examine the association between stressful life events and occupational accidents. Methods: This was a population-based case-control study, carried out in the city of Botucatu, in southeast Brazil. The cases consisted of 108 workers who had recently experienced occupational accidents. Each case was matched with three controls. The cases and controls answered a questionnaire about recent exposure to stressful life events. Results: Reporting of environmental problems, being a victim of assault, not having enough food at home and nonoccupational fatigue were found to be risk factors for work-related accidents with estimated incidence rate ratios of 1.4 [95% confidence interval (95% CI) 1.1-1.7], 1.3 (95% CI 1.1 1-1.7), 1.3 (95% CI 1.1-1.6), and 1.4 (95% CI 1.2-1.7) respectively. Conclusions: The findings of the study suggested that nonwork variables contribute to occupational accidents, thus broadening the understanding of these phenomena, which can support new approaches to the prevention of occupational accidents.

Occupational exposure to contaminated biological material: perceptions and feelings experienced among dental students

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)