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BackgroundOccupational exposures are thought to be responsible for 10-15% of new-onset asthma cases in adults, with disparities across sectors. Because most of the data are derived from registries and cross-sectional studies, little is known about incidence of occupational asthma (OA) during the first years after inception of exposure. This paper describes the design of a study that focuses on this early asthma onset period among young workers in the bakery, pastry making and hairdressing sectors in order to assess early incidence of OA in these "at risk" occupations according to exposure duration, and to identify risk factors of OA incidence.Methods/DesignThe study population is composed of subjects who graduated between 2001 and 2006 in these sectors where they experience exposure to organic or inorganic allergenic or irritant compounds (with an objective of 150 subjects by year) and 250 young workers with no specific occupational exposure. A phone interview focusing on respiratory and 'Ear-Nose-Throat' (ENT) work-related symptoms screen subjects considered as "possibly OA cases". Subjects are invited to participate in a medical visit to complete clinical and lung function investigations, including fractional exhaled nitric oxide (FENO) and carbon monoxide (CO) measurements, and to collect blood samples for IgE (Immunoglobulin E) measurements (total IgE and IgE for work-related and common allergens). Markers of oxidative stress and genetic polymorphisms exploration are also assessed. A random sample of 200 "non-cases" (controls) is also visited, following a nested case-control design.DiscussionThis study may allow to describ a latent period between inception of exposure and the rise of the prevalence of asthma symptoms, an information that would be useful for the prevention of OA. Such a time frame would be suited for conducting screening campaigns of this emergent asthma at a stage when occupational hygiene measures and adapted therapeutic interventions might be effective.Trial registrationClinical trial registration number is NCT01096537.

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Identifying deprived patients in hospital databases using routinely collected area-based indicators is feasible. The relation of these latter with LOS is consistent with previous studies. Further multicenter investigations are needed to confirm the interest of using such indicators for cost and morbidity predictions.