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Occupational health surveillance data are key to effective intervention. However, the US Bureau of Labor Statistics survey significantly underestimates the incidence of work-related injuries and illnesses. Researchers supplement these statistics with data from other systems not designed for surveillance. The authors apply the filter model of Webb et al. to underreporting by the Bureau of Labor Statistics, workers' compensation wage-replacement documents, physician reporting systems, and medical records of treatment charged to workers' compensation. Mechanisms are described for the loss of cases at successive steps of documentation. Empirical findings indicate that workers repeatedly risk adverse consequences for attempting to complete these steps, while systems for ensuring their completion are weak or absent.

Background Both women's and men's occupational health problems merit scientific attention. Researchers need to consider the effect of gender on how occupational health issues are experienced, expressed, defined, and addressed. More serious consideration of gender-related factors will help identify risk factors for both women and men. Methods The authors, who come from a number of disciplines (ergonomics, epidemiology, public health, social medicine, community psychology, economics, sociology) pooled their critiques in order to arrive at the most common and significant problems faced by occupational health researchers who wish to consider gender appropriately. Results This paper describes some ways that gender can be and has been handled in studies of occupational health, as well as some of the consequences. The paper also suggests specific research practices that avoid errors. Obstacles to gender-sensitive practices are considered. Conclusions Although gender-sensitive practices may be difficult to operationalize in some cases, they enrich the scientific quality of research and should lead to better data and ultimately to well-targeted prevention programs. Am. J. Ind. Med. 43:618-629, 2003. KEY WORDS: gender; sex; women; men; research methodology; epidemiology; ergonomics; confounding; effect modification; gender-based analysis INTRODUCTIONBoth women's and men's occupational health merit scientific attention. In the United States, women constitute 46% of the paid workforce [United States Department of Labor, 2002], and have one third of compensated occupational health and safety problems, resulting in 81% of claims on a per hour basis [McDiarmid and Gucer, 2001]. These injuries entail direct and indirect costs to workers and employers, as well as human suffering [deCarteret, 1994]. Therefore, appropriately including sex and gender is increasingly relevant for occupational health research. Although researchers are interested in developing studies involving these variables, they may not know exactly how to do this. This article supplies some suggestions. Many of the arguments presented here will apply to other sources of socially defined diversity such as age, race/ ethnicity, and social class [Krieger et al., 1993;Kilbom et al., 1997;Wegman, 1999; Chaturvedi, 2001]. Each of these factors has its own interactions with the work environment and health effects, but their discussion is beyond the scope of this paper.We have identified three types of problems in the way occupational health research has dealt with sex and gender. First, hazards in women's work have been underestimated [Rosenstock and Lee, 2000;Bäckman and Edling, 2001;London et al., 2002;McDiarmid and Gucer, 2001]. Women have been less often studied by occupational health scientists [Zahm et al., 1994;Messing, 1998a;Niedhammer et al., 2000]. Under-reporting and under-compensation, recognized problems in occupational health [Biddle et al., 1998;Davis et al., 2001;Harber et al., 2001], may be more of a problem for women [Lippel and Demers, 1996;Gluck and O...

No recent systematic review has examined definitions of precarious employment in the literature. This review showed how precarious employment was defined across 63 studies from different continents and research disciplines. Three dimensions of precarious employment emerged: employment insecurity, income inadequacy, and lack of rights and protection.

The aim of the present study was to evaluate the association and impact of occupational exposure and diseases of the shoulder and neck. Prevalence rates, odds ratios, aetiological fractions, and their confidence intervals were computed for pooled and non-pooled data of previous published reports. By comparison with office workers and farmers, dentists had an increased odds ratio for cervical spondylosis (two studies) and for shoulder joint osteoarthrosis. Meat carriers, miners, and "heavy workers" also had significantly higher rates of cervical spondylosis compared with referents. Compared with iron foundry workers, civil servants had a significant odds ratio (4-8) of cervical disc disease and a 0 79 aetiological fraction. Whether this was due to exposure or healthy worker effect was not clear. In four occupational groups with high shoulder-neck load an odds ratio of 4 0 was found for thoracic outlet syndrome with an aetiological fraction of 0 75. Rotator cuff tendinitis in occupational groups with work at shoulder level (two studies) showed an odds ratio of 11 and an aetiological fraction of 0 91. Keyboard operators had an odds ratio of 3 0 for tension neck syndrome (five studies). Unfortunately, owing to the scanty description of the work task, the exposure could be analysed only by job title. Examination of published reports shows clearly that certain job titles are associated with shoulder-neck disorders. High rates and aetiological fractions for rotator cuff tendinitis and tension neck syndrome suggest that preventive measures could be effective. Although job descriptions are brief, the associations noted suggest that highly repetitive shoulder muscle contractions, static contractions, and work at shoulder level are hazardous exposure factors. In reports of cross sectional studies of occupational shoulder-neck disorders presentation of age, exposure, and effect distribution may help for future meta-analysis.