Socioeconomic, Disease-Related, and Personal Factors Associated With Participation in Remote Follow-Up in Rheumatoid Arthritis: A Cross-Sectional Study

OBJECTIVE

To identify socioeconomic, disease-related, and personal factors associated with participation in remote follow-up in patients with rheumatoid arthritis (RA).

METHODS

Following the implementation of a patient-reported outcome-based remote follow-up intervention in RA patients in Denmark, a cross-sectional study was conducted among 775 prevalent patients. In 2019, an electronic questionnaire was sent to eligible RA patients, covering health literacy and patient experience regarding involvement and confidence with remote care. Questionnaire data were linked to nationwide registries regarding socioeconomic status, labor market affiliation, and comorbidity level. Associations between registry- and questionnaire-based factors and remote follow-up were analyzed using multiple logistic regression analysis.

RESULTS

All 775 patients were included in the registry-based analyses, but only 394 of 646 (61%) completed the questionnaire. No attachment to the labor market or low household income was associated with lower odds of remote follow-up participation (odds ratio [OR] 0.53 [95% confidence interval (95% CI) 0.34-0.83]) and (OR 0.69 [95% CI 0.48-1.00]). Further, a high level of comorbidity was associated with lower odds of remote follow-up participation compared to a low/medium level of comorbidity (OR 0.53 [95% CI 0.34-0.81]). No association was found between health literacy and remote follow-up, but remote follow-up attendees reported more confidence in remote care (OR 1.33 [95% CI 1.21-1.47]).

CONCLUSION

Participation in remote follow-up was associated with attachement to the labor market, household income, degree of comorbidity, and confidence with remote care. Additional research is necessary to investigate whether a larger and more divergent group of RA patients should be considered for inclusion in remote follow-up programs.

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.

Systemic reactogenicity following homologues and heterologous prime-boost AZD1222 and BNT162b2 COVID-19 vaccination of 2862 healthcare workers compared with an unvaccinated population

During spring 2021, AZD1222 and BNT162b2 were used as prime and BNT162b2 as booster COVID-19 vaccines in Denmark. We obtained self-reported information on systemic reactogenicity day-by-day during two weeks for 2862 healthcare workers vaccinated with heterologous AZD1222 + BNT162b2 or homologous BNT162b2 + BNT162b2 regimens and compared prevalences of symptoms with unvaccinated healthcare workers. We found comparable systemic reactogenicity during the first week in the two vaccine regimens and no reactogenicity during the second week. Most of the symptoms returned to a level equal to the control population four days after booster vaccination.

Dust exposure and the impact on hospital readmission of farming and wood industry workers for asthma and chronic obstructive pulmonary disease (COPD)

Objectives:

It is still not well established how occupational air pollutants affect the prognosis of asthma or chronic obstructive pulmonary disease (COPD). This study uses nationwide Danish registers and quantitative dust industry exposure matrices (IEM) for the farming and wood industries to estimate whether previous year dust exposure level impacts hospital readmissions for workers diagnosed with asthma or COPD.

Methods:

We identified all individuals with a first diagnosis of either asthma (769 individuals) or COPD (342 individuals) between 1997 and 2007 and followed them until the next hospital admission for asthma or COPD, emigration, death or 31 December 2007. We included only individuals who worked in either the wood or farming industries at least one year during follow-up. We used logistic regression analysis to investigate associations between dust exposure level in the previous year and hospital readmission, adjusting for sex, age, time since first diagnosis, socioeconomic status, and labor force participation.

Results:

Asthma readmissions for individuals with low and high dust exposure were increased [adjusted rate ratio (RR_adj) 2.52, 95% confidence interval (CI) 1.45–4.40] and RR_adj 2.64 (95% CI 1.52–4.60), respectively. For COPD readmission, the risk estimates were RR_adj 1.36 (95% CI 0.57–3.23) for low and RR_adj 1.20 (95% CI 0.49–2.95) for high exposure level in the previous year. For asthma readmission, stratified analyses by type of dust exposure during follow-up showed increased risks for both wood dust [RR_adj 2.67 (95% CI 1.35–5.26) high exposure level] and farming dust [RR_adj 3.59 (95% CI 1.11–11.59) high exposure level]. No clear associations were seen for COPD readmissions.

Conclusions:

This study indicates that exposure to wood or farm dust in the previous year increases the risk of hospital readmission for individuals with asthma but not for those with COPD.

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 (RR_adj (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; RR_adj (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.

Noise-Induced Hearing Loss - A Preventable Disease? Results of a 10-Year Longitudinal Study of Workers Exposed to Occupational Noise

Aims:

To survey current, Danish industrial noise levels and the use of hearing protection devices (HPD) over a 10-year period and to characterise the association between occupational noise and hearing threshold shift in the same period. Furthermore, the risk of hearing loss among the baseline and the follow-up populations according to first year of occupational noise exposure is evaluated.

Materials and Methods:

In 2001–2003, we conducted a baseline survey of noise- and hearing-related disorders in 11 industries with suspected high noise levels. In 2009–2010, we were able to follow up on 271 out of the 554 baseline workers (49%). Mean noise levels per industry and self-reported HPD use are described at baseline and follow-up. The association between cumulative occupational noise exposure and hearing threshold shift over the 10-year period was assessed using linear regression, and the risk of hearing loss according to year of first occupational noise exposure was evaluated with logistic regression.

Results:

Over the 10-year period, mean noise levels declined from 83.9 dB(A) to 82.8 dB(A), and for workers exposed >85 dB(A), the use of HPD increased from 70.1 to 76.1%. We found a weak, statistically insignificant, inverse association between higher ambient cumulative noise exposure and poorer hearing (−0.10 dB hearing threshold shift per dB-year (95% confidence interval (CI): −0.36; 0.16)). The risk of hearing loss seemed to increase with earlier first year of noise exposure, but odds ratios were only statistically significant among baseline participants with first exposure before the 1980s (odds ratio: 1.90, 95% CI: 1.11; 3.22).

Conclusions:

We observed declining industrial noise levels, increased use of HPD and no significant impact on hearing thresholds from current ambient industrial noise levels, which indicated a successful implementation of Danish hearing conservation programs.