ABSTRACT
IntroductionNight shift work and sleep deprivation have been associated with lower antibody responses induced by vaccination against seasonal influenza, meningitis-C and hepatitis A. We examined the association of exposure to night shift work and sleep deprivation with antibody levels induced by COVID-19 vaccines.Materials and MethodsThis study was nested in an ongoing population-based cohort in Catalonia, Spain. Blood samples were collected in 2021 from a random subsample of 1,090 participants. We measured 3 immunoglobulins (Ig)M, IgG, and IgA antibodies against 5 SARS-CoV-2 antigens, including RBD (receptor-binding domain), S (spike-protein), and S2 (subunit 2 from spike-protein). We collected data on night shift work (current night work, frequency, duration) and sleep metrics (sleep duration, sleep problems, changes in sleep duration since the beginning of the pandemic). We adjusted linear regression estimates (% change) for individual- and area-level covariates, time since vaccination, vaccine doses and type. Analyses were restricted to participants without previous COVID-19 infection (N=639). Infection status was defined using questionnaires, SARS-CoV-2 test registry and serology information (seropositivity to N-antigen).ResultsParticipants' mean age was 57.6 years, 57% were female, 73% received 2 vaccine doses (42% Pfizer, 44% AstraZeneca),5.8% were current night workers and 36.5% of the sample reported sleep problems. No overall association pattern was observed between current? night work and vaccine-induced antibody responses. IgG levels tended to be lower (differences in the range of 3.6–53.7%) among night workers, compared to day workers but differences were not statistically significant. Participants with short sleep (<=6 hours) had significantly lower IgM antibody levels compared to those that reported 7 hours of sleep. No clear pattern was observed with sleep quality.ConclusionsFurther research in larger studies is needed to evaluate the influence of night shift work and impaired sleep on vaccine induced immune responses and risk of breakthrough infections.
ABSTRACT
IntroductionWorking life exposures contribute significantly to non-communicable disease development. However, the challenge remains on how to map occupational exposures during the entire career and link exposures with health outcomes. In this context, the EU EPHOR project aims to characterize the internal exposome, by characterizing exposure biomarkers and biological pathways to link external exposure and health effects. While there is a range of strategies available to monitor the internal exposome, these conventional methods often require invasive collection of biological samples and/or high volumes. However, the ongoing COVID-19 pandemic forces us to look also at other approaches to obtain biological samples.ObjectiveWe aimed to explore the use of self-sampling techniques in an occupational exposome context.MethodsWe have conducted a semi-systematic literature review to identify self-sampling techniques used to generate high quality data on several biomarkers of exposure and effect. We are exploring the possibility of using these self-sampling techniques through a pilot study. A tiered analytical approach along with a biological sequence will be followed to efficiently analyze the samples (i.e. blood, urine, saliva, exhaled breath, exhaled breath aerosols and exhaled breath condensate) for a broad spectrum of biomarkers and omics. Additionally, non-invasive targeted and non-targeted exposome markers of acute lung function decline and inflammation will be developed through proteomic analysis of exhaled breath condensate (EBC), and exhaled breath VOCs using the ReCIVA Breath Sampler. These data will be integrated to generate signatures or ‘fingerprints’ of exposomes, at individual and group levels.Results and ConclusionThe developed methodology will be applied in 2 cohorts within the EPHOR project: shift-workers and workers with asthma or allergic rhinitis to assess the internal exposure and elucidate biological pathways in disease development.