Narrative review of occupational exposures and noncommunicable diseases.

OBJECTIVE: Within the scope of the Exposome Project for Health and Occupational Research on applying the exposome concept to working life health, we aimed to provide a broad overview of the status of knowledge on occupational exposures and associated health effects across multiple noncommunicable diseases (NCDs) to help inform research priorities. METHODS: We conducted a narrative review of occupational risk factors that can be considered to have "consistent evidence for an association," or where there is "limited/inadequate evidence for an association" for 6 NCD groups: nonmalignant respiratory diseases; neurodegenerative diseases; cardiovascular/metabolic diseases; mental disorders; musculoskeletal diseases; and cancer. The assessment was done in expert sessions, primarily based on systematic reviews, supplemented with narrative reviews, reports, and original studies. Subsequently, knowledge gaps were identified, e.g. based on missing information on exposure-response relationships, gender differences, critical time-windows, interactions, and inadequate study quality. RESULTS: We identified over 200 occupational exposures with consistent or limited/inadequate evidence for associations with one or more of 60+ NCDs. Various exposures were identified as possible risk factors for multiple outcomes. Examples are diesel engine exhaust and cadmium, with consistent evidence for lung cancer, but limited/inadequate evidence for other cancer sites, respiratory, neurodegenerative, and cardiovascular diseases. Other examples are physically heavy work, shift work, and decision latitude/job control. For associations with limited/inadequate evidence, new studies are needed to confirm the association. For risk factors with consistent evidence, improvements in study design, exposure assessment, and case definition could lead to a better understanding of the association and help inform health-based threshold levels. CONCLUSIONS: By providing an overview of knowledge gaps in the associations between occupational exposures and their health effects, our narrative review will help setting priorities in occupational health research. Future epidemiological studies should prioritize to include large sample sizes, assess exposures prior to disease onset, and quantify exposures. Potential sources of biases and confounding need to be identified and accounted for in both original studies and systematic reviews.

Development of a quantitative North and Central European job exposure matrix for wood dust.

Wood dust is an established carcinogen also linked to several non malignant respiratory disorders. A major limitation in research on wood dust and its health effects is the lack of (historical) quantitative estimates of occupational exposure for use in general population-based case-control or cohort studies. The present study aimed to develop a multinational quantitative Job Exposure Matrix (JEM) for wood dust exposure using exposure data from several Northern and Central European countries. For this, an occupational exposure database containing 12653 personal wood dust measurements collected between 1978 and 2007 in Denmark, Finland, France, The Netherlands, Norway, and the United Kingdom (UK) was established. Measurement data were adjusted for differences in inhalable dust sampling efficiency resulting from the use of different dust samplers and analysed using linear mixed effect regression with job codes (ISCO-88) and country treated as random effects. Fixed effects were the year of measurement, the expert assessment of exposure intensity (no, low, and high exposure) for every ISCO-88 job code from an existing wood dust JEM and sampling duration. The results of the models suggest that wood dust exposure has declined annually by approximately 8%. Substantial differences in exposure levels between countries were observed with the highest levels in the United Kingdom and the lowest in Denmark and Norway, albeit with similar job rankings across countries. The jobs with the highest predicted exposure are floor layers and tile setters, wood-products machine operators, and building construction labourers with geometric mean levels for the year 1997 between 1.7 and 1.9 mg/m3. The predicted exposure estimates by the model are compared with the results of wood dust measurement data reported in the literature. The model predicted estimates for full-shift exposures were used to develop a time-dependent quantitative JEM for exposure to wood dust that can be used to estimate exposure for participants of general population studies in Northern European countries on the health effects from occupational exposure to wood dust.

Associations of Maternal Diabetes During Pregnancy With Psychiatric Disorders in Offspring During the First 4 Decades of Life in a Population-Based Danish Birth Cohort.

Importance: Maternal diabetes has been suggested as a risk factor for attention-deficit/hyperactivity disorder and autism in offspring, but evidence on its association with the full spectrum of psychiatric disorders remains lacking. Objective: To investigate the associations between maternal diabetes diagnosed before or during pregnancy and 10 types of psychiatric disorders in offspring during the first 4 decades of life. Design, Setting, and Participants: This population-based cohort study used data from several Danish nationwide medical and administrative registries in Denmark on all 2 413 335 live births from 1978 to 2016. Data were analyzed between October 1, 2019, and July 15, 2021. Exposures: Any maternal diabetes diagnosis during pregnancy (56 206 offspring [2.3%]) and 3 diabetes subtypes (pregestational type 1 diabetes, 22 614 offspring [1.0%]; pregestational type 2 diabetes, 6713 offspring [0.3%]; and gestational diabetes, 26 879 offspring [1.1%]). Main Outcomes and Measures: Outcomes included 10 types of psychiatric disorders: any psychiatric disorder, substance use disorders, schizophrenia, mood disorders, anxiety disorders, eating disorders, personality disorders, intellectual disorders, developmental disorders, and behavioral disorders. Hazard ratios (HRs) and 95% CIs were computed using Cox proportional hazards regression models. Covariates included maternal and paternal history of any psychiatric disorder, offspring sex, calendar period of birth, singleton status, and several maternal characteristics during pregnancy (ie, age, parity, educational level, smoking, cohabitation, residence, and body mass index). Sibship design and competing risk analyses were also conducted. Results: A total of 2 413 335 individuals (1 239 148 male participants [51%]; age range, 1-39 years; median age, 19.0 years [IQR, 5.8-20.8 years]) were included in this study. During the 39-year follow-up time, 151 208 offspring (6.4%) received a diagnosis of a psychiatric disorder. Offspring born to mothers with any diabetes diagnosis during pregnancy were at increased risk of developing any psychiatric disorder (HR, 1.15; 95% CI, 1.10-1.20), schizophrenia (HR, 1.55; 95% CI, 1.15-2.08), anxiety disorders (HR, 1.22; 95% CI, 1.09-1.36), intellectual disabilities (HR, 1.29; 95% CI, 1.11-1.50), developmental disorders (HR, 1.16; 95% CI, 1.03-1.30), and behavioral disorders (HR, 1.17; 95% CI, 1.08-1.27) compared with offspring born to mothers without a diabetes diagnosis during pregnancy. No association was observed for substance use disorders, mood disorders, eating disorders, and personality disorders. Conclusions and Relevance: This study shows a pattern that suggests that prenatal exposure to maternal diabetes during pregnancy was associated with increased risk of psychiatric disorders overall and most specific psychiatric disorders in offspring in their first 4 decades of life.

A Quantitative General Population Job Exposure Matrix for Occupational Daytime Light Exposure.

High daytime light levels may reduce the risk of affective disorders. Outdoor workers are during daytime exposed to much higher light intensities than indoor workers. A way to study daytime light exposure and disease on a large scale is by use of a general population job exposure matrix (JEM) combined with national employment and health data. The objective of this study was to develop a JEM applicable for epidemiological studies of exposure response between daytime light exposure, affective disorders, and other health effects by combining expert scores and light measurements. We measured light intensity during daytime work hours 06:00-17:59 for 1-7 days with Philips Actiwatch Spectrum® light recorders (Actiwatch) among 695 workers representing 71 different jobs. Jobs were coded into DISCO-88, the Danish version of the International Standard Classification of Occupations 1988. Daytime light measurements were collected all year round in Denmark (55-56°N). Arithmetic mean white light intensity (lux) was calculated for each hour of observation (n = 15,272), natural log-transformed, and used as the dependent variable in mixed effects linear regression models. Three experts rated probability and duration of outdoor work for all 372 jobs within DISCO-88. Their ratings were used to construct an expert score that was included together with month of the year and hour of the day as fixed effects in the model. Job, industry nested within job, and worker were included as random effects. The model estimated daytime light intensity levels specific for hour of the day and month of the year for all jobs with a DISCO-88 code in Denmark. The fixed effects explained 37% of the total variance: 83% of the between-jobs variance, 57% of the between industries nested in jobs variance, 43% of the between-workers variance, and 15% of the within-worker variance. Modeled daytime light intensity showed a monotonic increase with increasing expert score and a 30-fold ratio between the highest and lowest exposed jobs. Building construction laborers were based on the JEM estimates among the highest and medical equipment operators among the lowest exposed. This is the first quantitative JEM of daytime light exposure and will be used in epidemiological studies of affective disorders and other health effects potentially associated with light exposure.

A nationwide follow-up study of occupational organic dust exposure and risk of chronic obstructive pulmonary disease (COPD).

OBJECTIVES: To study exposure-response relations between cumulative organic dust exposure and incident chronic obstructive pulmonary disease (COPD) among subjects employed in the Danish farming and wood industry. METHODS: We studied exposure-response relations between cumulative organic dust exposure and incident COPD (1997-2013) among individuals born during 1950-1977 in Denmark ever employed in the farming or wood industry (n=1 75 409). Industry-specific employment history (1964-2007), combined with time-dependent farming and wood industry-specific exposure matrices defined cumulative exposure. We used logistic regression analysis with discrete survival function adjusting for age, sex and calendar year. Adjustment for smoking status was explored in a subgroup of 4023 with smoking information available. RESULTS: Cumulative organic dust exposure was inversely associated with COPD (adjusted rate ratios (RRadj (95% CIs) of 0.90 (0.82 to 0.99), 0.76 (0.69 to 0.84) and 0.52 (0.47 to 0.58) for intermediate-low, intermediate-high and high exposure quartiles, respectively, compared with the lowest exposure quartile). Lagging exposure 10 years was not consistently suggestive of an association between cumulative exposure and COPD; RRadj (95% CI): 1.05 (0.94 to 1.16), 0.92 (0.83 to 1.02) and 0.63 (0.56 to 0.70). Additional stratification by duration of employment showed no clear association between organic dust exposure and COPD except for the longer exposed (15-40 years) where an inverse association was indicated. Subgroup analyses showed that smoking had no impact on exposure-response estimates. CONCLUSIONS: Our findings show no increased risk of COPD with increasing occupational exposure to organic dust in the farming or wood industry. Potential residual confounding by smoking can, however, not be ruled out.

In utero exposure to persistent organochlorine pollutants and reproductive health in the human male.

Persistent organochlorine pollutants (POPs) are ubiquitous, bioaccumulative compounds with potential endocrine-disrupting effects. They cross the placental barrier thereby resulting in in utero exposure of the developing fetus. The objective of this study was to investigate whether maternal serum concentrations of polychlorinated biphenyls (PCBs) and p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE) during pregnancy are associated with son's semen quality and reproductive hormone levels. During 2008-2009, we recruited 176 male offspring from a Danish cohort of pregnant women who participated in a study in 1988-1989. Each provided semen and blood samples that were analyzed for sperm concentration, total sperm count, motility, and morphology, and reproductive hormone levels, respectively. The maternal blood samples were collected in pregnancy week 30 and were analyzed for the concentrations of six PCBs (PCB-118, -138, -153, -156, -170, and -180) and p,p'-DDE. The potential associations between in utero exposure to ΣPCBs (pmol/ml), Σdioxin like-(DL) PCBs (PCB-118 and -156) (pmol/ml), and p,p'-DDE and semen quality and reproductive hormone levels were investigated using multiple regression. Maternal median (range) exposure levels of ΣPCB, ΣDL-PCB, and p,p'-DDE were 10.0 (2.1-35.0) pmol/ml, 0.8 (0.2-2.7) pmol/ml, and 8.0 (0.7-55.3) pmol/ml, respectively, reflecting typical background exposure levels in the late 1980s in Denmark. Results suggested that in utero exposure to ΣPCB, ΣDL-PCB, and p,p'-DDE was not statistically significantly associated with semen quality measures or reproductive hormone levels. Thus, results based on maternal PCB and p,p'-DDE concentrations alone are not indicative of long-term consequences for male reproductive health; however, we cannot exclude that these POPs in concert with other endocrine-modulating compounds may have adverse effects.