Researchers Find Strong Association Between Males in Coal Mining Communities and Osteoarthritis and Rheumatoid Arthritis

ObjectivesWe previously showed increased coal mining-associated risk of rheumatoid arthritis (RA). Using additional survey data, we sought to delineate this risk further.MethodsWe used data from two cross-sectional, random-digit-dial, population-based surveys (males;≥50 years) in selected counties in the Appalachian region of the inland, mid-Atlantic USA with elevated pneumoconiosis mortality. Surveys ascertained age, smoking, coal mining and non-coal silica exposure jobs. In a subset, we surveyed ergonomic exposures, scored by intensity. We queried diagnosis of RA, corticosteroid use, and, in a subset, use of disease modifying antirheumatic drugs (DMARDs). Multivariable logistic regression modelled RA risk (defined by glucocorticoid or DMARDs use) associated with coal mining employment, other silica exposure, smoking status, and age and ergonomic exposures.ResultsWe analysed data for 2981 survey respondents (mean age 66.6 years; 15% current, 44% ex-smokers). The prevalence of glucocorticoid-treated and DMARD-treated RA was 11% and 4%, respectively. Glucocorticoid-treated RA was associated with coal mining (OR 3.5; 95% CI 2.5 to 4.9) and non-coal mining silica exposure (OR 3.2; 95% CI 2.4 to 4.4). For DMARD-treated RA, the odds associated with coal mining and other silica remained elevated: OR 2.3 (95% CI 1.18, 4.5) and OR 2.7 (95% CI 1.51, 5.0), respectively. In the same model, the highest intensity ergonomic exposure also was associated with increased odds of RA (OR 4.3; 95% CI 1.96 to 9.6).ConclusionsWe observed a strong association between coal mining and other silica-exposing dusty trades and RA. Clinicians and insurers should consider occupational histories in the aetiology of RA.

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A Bayesian Model for Prediction of Rheumatoid Arthritis from Risk Factors

10.1101/2020.07.09.20150326 ◽

2020 ◽

Author(s):

Leon Lufkin ◽

Marko Budišić ◽

Sumona Mondal ◽

Shantanu Sur

Keyword(s):

Rheumatoid Arthritis ◽

Risk Factors ◽

Predictive Model ◽

Characteristic Curve ◽

Strong Association ◽

Autoimmune Disorder ◽

Mixed Data ◽

Validation Dataset ◽

Third Order ◽

Organ Systems

Rheumatoid arthritis (RA) is a chronic autoimmune disorder that typically manifests as destructive joint inflammation but also affects multiple other organ systems. The pathogenesis of RA is complex where a variety of factors including comorbidities, demographic, and socioeconomic variables are known to influence the incidence and progress of the disease. In this work, we aimed to predict RA from a set of 11 well-known risk factors and their interactions using Bayesian logistic regression. We considered up to third-order interactions between the risk factors and implemented factor analysis of mixed data (FAMD) to account for both the continuous and categorical natures of these variables. The predictive model was further optimized over the area under the receiver operating characteristic curve (AUC) using a genetic algorithm (GA). We use data from the National Health and Nutrition Examination Survey (NHANES). Our optimal predictive model has a smoothed AUC of 0.826 (95% CI: 0.801 −0.850) on a validation dataset and 0.805 (95% CI: 0.781 −0.829) on a holdout test dataset. Our model identified multiple second- and third-order interactions that demonstrate a strong association with RA, implying the potential role of risk factor interactions in the disease mechanism. Interestingly, we find that the inclusion of higher-order interactions in the model only marginally improves overall predictive ability. Our findings on the contribution of RA risk factors and their interaction on disease prediction could be useful in developing strategies for early diagnosis of RA, thus opening potential avenues for improved patient outcomes and reduced healthcare burden to society.

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A Mining Film without a Disaster is like a Western without a Shoot-out: Representations of Coal Mining Communities in Feature Films

Towards a Comparative History of Coalfield Societies ◽

10.4324/9781315235936-6 ◽

2017 ◽

pp. 86-98

Author(s):

Bert Hogenkamp

Keyword(s):

Coal Mining ◽

Mining Communities ◽

Feature Films

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Representing Identity and Work in Transition: The Case of South Yorkshire Coal-mining Communities in the UK

Changing Work and Community Identities in European Regions ◽

10.1057/9780230353916_7 ◽

2012 ◽

pp. 184-216 ◽

Cited By ~ 3

Author(s):

John Kirk ◽

Steve Jefferys ◽

Christine Wall

Keyword(s):

Coal Mining ◽

Mining Communities ◽

The Uk

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Contrasting Female Identities: Women in Coal Mining Communities in Northumberland, England, 1900-1939

Journal of Women s History ◽

10.1353/jowh.2001.0049 ◽

2001 ◽

Vol 13 (2) ◽

pp. 107-131 ◽

Cited By ~ 2

Author(s):

Valerie Gordon Hall

Keyword(s):

Coal Mining ◽

Mining Communities

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Prevalence of Arthritis and Rheumatoid Arthritis in Coal Mining Counties of the United States

Arthritis Care & Research ◽

10.1002/acr.23874 ◽

2019 ◽

Vol 71 (9) ◽

pp. 1209-1215 ◽

Cited By ~ 8

Author(s):

Gabriela Schmajuk ◽

Laura Trupin ◽

Edward Yelin ◽

Paul D. Blanc

Keyword(s):

Rheumatoid Arthritis ◽

United States ◽

Coal Mining ◽

The United States

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The global energy transition and place attachment in coal mining communities: Implications for heavily industrialized landscapes

Energy Research & Social Science ◽

10.1016/j.erss.2020.101831 ◽

2021 ◽

Vol 71 ◽

pp. 101831

Author(s):

K. Svobodova ◽

J.R. Owen ◽

J. Harris

Keyword(s):

Coal Mining ◽

Place Attachment ◽

Energy Transition ◽

Global Energy ◽

Mining Communities

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Risk of venous thromboembolism in rheumatoid arthritis, and its association with disease activity: a nationwide cohort study from Sweden

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2020-218419 ◽

2020 ◽

pp. annrheumdis-2020-218419

Author(s):

Viktor Molander ◽

Hannah Bower ◽

Thomas Frisell ◽

Johan Askling

Keyword(s):

Rheumatoid Arthritis ◽

Cohort Study ◽

Venous Thromboembolism ◽

General Population ◽

Disease Activity ◽

Risk Ratio ◽

Strong Association ◽

Additional Tool ◽

Quality Register ◽

General Population Cohort

ObjectiveTo assess the incidence of venous thromboembolism (VTE) in rheumatoid arthritis (RA) relative to individuals without RA, and to investigate the relationship between aspects of clinical disease activity in RA and the risk of VTE.MethodsWe conducted a nationwide register-based cohort study 2006 through 2018 using the Swedish Rheumatology Quality Register linked to other national patient registers to identify all patients with RA with at least one registered rheumatologist visit during the study period (n=46 316 patients, 322 601 visits). The Disease Activity Score 28 erythrocyte sedimentation rate (ESR) (DAS28 ESR) and its components served as the exposure, and a VTE event within the year following the visit was the main outcome. We also included general population referents (1:5) matched on age, sex and residential area.ResultsBased on 2241 incident VTE events within 1 year of each included visit, and 5301 VTE events in the general population cohort, the risk ratio for VTE in RA was 1.88 (95% CI 1.65 to 2.15). Among patients with RA, the risk (and risk ratio) increased with increasing RA disease activity, from 0.52% following visits in remission to 1.08% following visits with DAS28 ESR high disease activity, RR compared with remission=2.03, 95% CI 1.73 to 2.38. Compared with the general population, also patients with RA in DAS28 ESR remission were at elevated VTE risk.ConclusionsThis study demonstrates a strong association between clinical RA disease activity measured by DAS28 ESR and the risk of VTE. RA disease activity can be used as an additional tool for VTE risk stratification in patients with RA.

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