Influence of Ambient Air Pollution on Rheumatoid Arthritis Disease Activity Score Index

Machine learning-based remission prediction in rheumatoid arthritis patients treated with biologic disease-modifying anti-rheumatic drugs: findings from the Kuwait rheumatic disease registry

Background

Rheumatoid arthritis (RA) is a common condition treated with biological disease-modifying anti-rheumatic medicines (bDMARDs). However, many patients exhibit resistance, necessitating the use of machine learning models to predict remissions in patients treated with bDMARDs, thereby reducing healthcare costs and minimizing negative effects.

Objective

The study aims to develop machine learning models using data from the Kuwait Registry for Rheumatic Diseases (KRRD) to identify clinical characteristics predictive of remission in RA patients treated with biologics.

Methods

The study collected follow-up data from 1,968 patients treated with bDMARDs from four public hospitals in Kuwait from 2013 to 2022. Machine learning techniques like lasso, ridge, support vector machine, random forest, XGBoost, and Shapley additive explanation were used to predict remission at a 1-year follow-up.

Results

The study used the Shapley plot in explainable Artificial Intelligence (XAI) to analyze the effects of predictors on remission prognosis across different types of bDMARDs. Top clinical features were identified for patients treated with bDMARDs, each associated with specific mean SHAP values. The findings highlight the importance of clinical assessments and specific treatments in shaping treatment outcomes.

Conclusion

The proposed machine learning model system effectively identifies clinical features predicting remission in bDMARDs, potentially improving treatment efficacy in rheumatoid arthritis patients.

Individual and joint exposure to air pollutants and patterns of multiple chronic conditions

Existing research on the detrimental effects of air pollution and its mixture on multiple chronic conditions (MCC) is not yet fully recognized. Our objective was to examine if individual and joint exposure to air pollution is associated with the incidence and patterns of MCC. Totally 10,231 CHARLS 2015 participants aged over 45 years and 1,938 without MCC were followed up in 2018 and 2020. Residential-levelcumulative personal exposure concentrations of PM1, PM10, PM2.5, CO, O3, NO2, SO2, NO3-, Cl-, NH4+, and SO42- at the residential level were determined utilizing a spatio-temporal random forest model with a spatial resolution of 0.1° × 0.1°. In the cross-sectional and longitudinal research, logistic regression, cox regression analysis, and quantile g-computation were utilized to estimate the single and joint effect with MCC and its patterns, respectively. Interaction analyses and stratified analyses were also performed. A correlation was observed between the prevalence of cardiovascular illnesses and the presence of all 11 major air pollutants. PM2.5, PM10, NH4+, NO3-, CO, and SO42- are associated with an increased frequency of respiratory disorders. An increase of PM2.5, PM1, PM10, NO2, and SO2 (a 10 µg/m3 rise), CO (a 0.1 mg/m3 rise), and PMCs (Cl-, NH4+, NO3-, and SO42-) (a 1 µg/m3 rise) corresponded to the HRs (95% CI) for developing MCC of 1.194 (95% CI: 1.043, 1.367), 1.362 (95% CI: 1.073, 1.728), 1.115 (95% CI: 1.026, 1.212), 1.443 (95% CI: 1.151, 1.808), 3.175 (95% CI: 2.291, 4.401), 1.272 (95% CI: 1.149,1.410), 1.382 (95% CI: 1.011, 1.888), 1.107 (95% CI: 1.003, 1.222), 1.035 (95% CI: 0.984, 1.088), and 1.122 (95% CI: 1.086, 1.160), respectively. SO2 was the predominant contributor to the combined effect (HR: 2.083, 95% CI: 1.659-2.508). Gender, age, drinking, and health status could modify the effects of air pollutants on MCC patterns. Long-term exposure to air pollution is correlated to the incidence and patterns of MCC in middle-aged and elderly Chinese individuals. Preventive methods are essential to safeguarding those susceptible to MCC.

Forecasting rheumatoid arthritis patient arrivals by including meteorological factors and air pollutants

The burden of rheumatoid arthritis (RA) has gradually elevated, increasing the need for medical resource redistribution. Forecasting RA patient arrivals can be helpful in managing medical resources. However, no relevant studies have been conducted yet. This study aims to construct a long short-term memory (LSTM) model, a deep learning model recently developed for novel data processing, to forecast RA patient arrivals considering meteorological factors and air pollutants and compares this model with traditional methods. Data on RA patients, meteorological factors and air pollutants from 2015 to 2022 were collected and normalized to construct moving average (MA)- and autoregressive (AR)-based and LSTM models. After data normalization, the root mean square error (RMSE) was adopted to evaluate models' forecast ability. A total of 2422 individuals were enrolled. Not using the environmental data, the RMSEs of the MA- and AR-based models' test sets are 0.131, 0.132, and 0.117 when the training set: test set ratio is 2:1, 3:1, and 7:1, while they are 0.110, 0.130, and 0.112 for the univariate LSTM models. Considering meteorological factors and air pollutants, the RMSEs of the MA- and AR-based model test sets were 0.142, 0.303, and 0.164 when the training set: test set ratio is 2:1, 3:1, and 7:1, while they were 0.108, 0.119, and 0.109 for the multivariable LSTM models. Our study demonstrated that LSTM models can forecast RA patient arrivals more accurately than MA- and AR-based models for datasets of all three sizes. Considering the meteorological factors and air pollutants can further improve the forecasting ability of the LSTM models. This novel method provides valuable information for medical management, the optimization of medical resource redistribution, and the alleviation of resource shortages.

Epidemiology and Risk Factors for Rheumatoid Arthritis Development

Rheumatoid arthritis (RA) is a prevalent chronic inflammatory arthritis worldwide, significantly impacting patients and population health. The disease affects women primarily, with a female-to-male ratio of three to one. Its pathogenesis is multifactorial, including genetic and environmental risk factors. Epidemiological studies highlight the link between the environment and genetic susceptibility to RA. The so-called shared epitope is the most significant risk factor that seems to act synergetic with other environmental factors in the disease occurrence. In addition, recent findings suggest a potential role of new substantial environmental factors, such as the observed pollution of the planet's natural resources, on the susceptibility and progression of the disease. This review summarises the most decisive evidence on epidemiology and genetic, environmental, and lifestyle risk factors for RA. It shows that studying genetic and environmental factors in correlation could lead to prevention strategies that may impact the natural history of the disease.

Potential roles of air pollutants on the induction and aggravation of rheumatoid arthritis: From cell to bedside studies

Rheumatoid arthritis (RA) is an involving chronic systemic inflammatory disease which mainly affects the joints. Several factors including genetic, environment and infections have been acknowledged as being involved in the pathogenesis and aggravation of RA. Air pollution, particularly particulate matter is widely recognized as a cause of health problems. This review is to summarize and discuss the association between air pollutants and the development or the aggravation of RA based on evidence from in vitro, in vivo and clinical studies. The results from the review found that air pollutants can stimulate immunological processes and stimulate inflammatory mediators and autoantibodies productions, both in intro and in vivo studies. In addition, air pollutants can induce RA and aggravate RA disease activity. Unfortunately, there also are some discrepancies in the results, which might be due to the type cell line and the concentration of air pollutants used in the in vitro and in vivo studies, as well as the concentration and duration of exposure in human studies. These findings suggest that future studies focused on elucidating these mechanisms using advanced techniques and identifying reliable biomarkers to assess individual susceptibility and disease activity should be carried out. Longitudinal studies, intervention strategies, and policy implications also should be explored. A comprehensive understanding on these association will facilitate targeted approaches for prevention and management of air pollutant-induced RA and improve health outcome.

Sinomenine ameliorates rheumatoid arthritis by modulating tryptophan metabolism and activating aryl hydrocarbon receptor via gut microbiota regulation

Gut microbiota dysbiosis is associated with the development of rheumatoid arthritis (RA). Sinomenine (SIN) is an effective immunosuppressive and anti-inflammatory drug used for treating RA, but how SIN regulates gut microbiota to alleviate RA remains underexplored. To identify the critical gut microbial species and microbial metabolites associated with the RA-protective effects of SIN, the microbiota-dependent anti-RA effects of SIN were assessed by 16S rRNA gene sequencing, antibiotic treatment, and fecal microbiota transplantation. Metabolomics analysis, transcriptional analysis, and targeted bacteria/metabolites gavage were conducted to explore how SIN regulates gut microbiota to reduce the severity of RA. SIN could restore intestinal microbial balance by mainly modulating the abundance of Lactobacillus, and significantly relieve collagen-induced arthritis (CIA) symptoms in a gut microbiota-dependent manner. SIN significantly elevated microbial tryptophan metabolites indole-3-acrylic acid (IA), indole-3-propionic acid (IPA), and indole-3-acetic acid (IAA). Tryptophan metabolites supplementation could activate aryl hydrocarbon receptor (AhR) and regulate Th17/Treg balance in CIA rats. Intriguingly, SIN relieved the arthritis symptoms involving the enrichment of two beneficial anti-CIA Lactobacillus species, L. paracasei and L. casei by mono-colonization. The promising therapeutic function of SIN was mostly attributed to the activation of AhR by explicitly targeting the Lactobacillus and microbial tryptophan metabolites. The intestinal bacterium L. paracasei and L. casei may be used to reduce the severity of CIA.

Influence of Air Pollutants on the Disease Activity and Quality of Life in Rheumatoid Arthritis, an Iranian Observational Longitudinal Study

Background

Environmental exposures and genetic predisposition interactions may result in autoimmune rheumatic diseases. This study aimed to determine the effect of outdoor air pollutants on the activity of rheumatoid arthritis (RA) in a longitudinal follow-up.

Methods

We longitudinally studied 50 patients with RA bimonthly over 6 months in Mashhad, one of the most polluted cities in Iran. Disease activity and health-related quality of life (HRQoL) were examined according to the disease activity score (DAS28ESR), health assessment questionnaires (HAQ), physical health component summary (PCS), and visual analogue scale (VAS) criteria. The outdoor air pollutant was measured by monitoring the average concentration of nitrogen oxide (NO), carbon monoxide (CO), O2 level, Sulfur dioxide (SO2), and some particles less than 10 and 2.5 micrometers in diameter (PM <10 µm, PM <2.5 µm). The temperature and humidity levels were also measured. The univariate and multivariate statistical analyses were used for data analysis and the role of confounding factors was determined using the generalized estimation equation method.

Results

Statistical analysis indicated a significant increase of the DAS28ESR (B = 0.04 [0.08]; P = 0.01) and VAS (B = 4.48 [1.73]; P = 0.01) by CO concentration. Moreover, a number of polluted days increased the VAS in patients. In addition, other air pollutants, temperature, and humidity were not affected significantly by the DAS28ESR and quality of life indexes by considering confounders such as medications, age, and job.

Conclusion

Based on our findings, CO concentration was the only effective outdoor air pollutant that could increase RA disease activity. In addition, CO concentration and the number of polluted days make patients feel more ill. As the role of indoor air pollutants is highly important, further research on this critical topic is required to establish the role of air pollution on RA disease activity.

Nanomedical approaches in the realm of rheumatoid arthritis

Rheumatoid arthritis (RA) is a heterogeneous autoimmune inflammatory disorder defined by the damage to the bone and cartilage in the synovium, which causes joint impairment and an increase in the mortality rate. It is associated with an incompletely elucidated pathophysiological mechanism. Even though disease-modifying antirheumatic drugs have contributed to recent improvements in the standard of care for RA, only a small fraction of patients is able to attain and maintain clinical remission without the necessity for ongoing immunosuppressive drugs. The evolution of tolerance over time as well as patients' inability to respond to currently available therapy can alter the overall management of RA. A significant increase in the research of RA nano therapies due to the possible improvements they may provide over traditional systemic treatments has been observed. New approaches to getting beyond the drawbacks of existing treatments are presented by advancements in the research of nanotherapeutic techniques, particularly drug delivery nano systems. Via passive or active targeting of systemic delivery, therapeutic drugs can be precisely transported to and concentrated in the affected sites. As a result, nanoscale drug delivery systems improve the solubility and bioavailability of certain drugs and reduce dose escalation. In the present paper, we provide a thorough overview of the possible biomedical applications of various nanostructures in the diagnostic and therapeutic management of RA, derived from the shortcomings of conventional therapies. Moreover, the paper suggests the need for improvement on the basis of research directions and properly designed clinical studies.

Association of distance to swine concentrated animal feeding operations with immune-mediated diseases: An exploratory gene-environment study

BACKGROUND

Concentrated animal feeding operations (CAFOs) are a source of environmental pollution and have been associated with a variety of health outcomes. Immune-mediated diseases (IMD) are characterized by dysregulation of the normal immune response and, while they may be affected by gene and environmental factors, their association with living in proximity to a CAFO is unknown.

OBJECTIVES

We explored gene, environment, and gene-environment (GxE) relationships between IMD, CAFOs, and single nucleotide polymorphisms (SNPs) of prototypical xenobiotic response genes AHR, ARNT, and AHRR and prototypical immune response gene PTPN22.

METHODS

The exposure analysis cohort consisted of 6,464 participants who completed the Personalized Environment and Genes Study Health and Exposure Survey and a subset of 1,541 participants who were genotyped. We assessed the association between participants' residential proximity to a CAFO in gene, environment, and GxE models. We recombined individual associations in a transethnic model using METAL meta-analysis.

RESULTS

In White participants, ARNT SNP rs11204735 was associated with autoimmune diseases and rheumatoid arthritis (RA), and ARNT SNP rs1889740 was associated with RA. In a transethnic genetic analysis, ARNT SNPs rs11204735 and rs1889740 and PTPN22 SNP rs2476601 were associated with autoimmune diseases and RA. In participants living closer than one mile to a CAFO, the log-distance to a CAFO was associated with autoimmune diseases and RA. In a GxE interaction model, White participants with ARNT SNPs rs11204735 and rs1889740 living closer than eight miles to a CAFO had increased odds of RA and autoimmune diseases, respectively. The transethnic model revealed similar GxE interactions.

CONCLUSIONS

Our results suggest increased risk of autoimmune diseases and RA in those living in proximity to a CAFO and a potential role of the AHR-ARNT pathway in conferring risk. We also report the first association of ARNT SNPs rs11204735 and rs1889740 with RA. Our findings, if confirmed, could allow for novel genetically-targeted or other preventive approaches for certain IMD.

Volatile organic compounds: A proinflammatory activator in autoimmune diseases

The etiopathogenesis of inflammatory and autoimmune diseases, including pulmonary disease, atherosclerosis, and rheumatoid arthritis, has been linked to human exposure to volatile organic compounds (VOC) present in the environment. Chronic inflammation due to immune breakdown and malfunctioning of the immune system has been projected to play a major role in the initiation and progression of autoimmune disorders. Macrophages, major phagocytes involved in the regulation of chronic inflammation, are a major target of VOC. Excessive and prolonged activation of immune cells (T and B lymphocytes) and overexpression of the master pro-inflammatory constituents [cytokine and tumor necrosis factor-alpha, together with other mediators (interleukin-6, interleukin-1, and interferon-gamma)] have been shown to play a central role in the pathogenesis of autoimmune inflammatory responses. The function and efficiency of the immune system resulting in immunostimulation and immunosuppression are a result of exogenous and endogenous factors. An autoimmune disorder is a by-product of the overproduction of these inflammatory mediators. Additionally, an excess of these toxicants helps in promoting autoimmunity through alterations in DNA methylation in CD4 T cells. The purpose of this review is to shed light on the possible role of VOC exposure in the onset and progression of autoimmune diseases.

Murine in utero exposure to simulated complex urban air pollution disturbs offspring gut maturation and microbiota during intestinal suckling-to-weaning transition in a sex-dependent manner

Background

Emerging data indicate that prenatal exposure to air pollution may lead to higher susceptibility to several non-communicable diseases. Limited research has been conducted due to difficulties in modelling realistic air pollution exposure. In this study, pregnant mice were exposed from gestational day 10–17 to an atmosphere representative of a 2017 pollution event in Beijing, China. Intestinal homeostasis and microbiota were assessed in both male and female offspring during the suckling-to-weaning transition.

Results

Sex-specific differences were observed in progeny of gestationally-exposed mice. In utero exposed males exhibited decreased villus and crypt length, vacuolation abnormalities, and lower levels of tight junction protein ZO-1 in ileum. They showed an upregulation of absorptive cell markers and a downregulation of neonatal markers in colon. Cecum of in utero exposed male mice also presented a deeply unbalanced inflammatory pattern. By contrast, in utero exposed female mice displayed less severe intestinal alterations, but included dysregulated expression of Lgr5 in colon, Tjp1 in cecum, and Epcam, Car2 and Sis in ileum. Moreover, exposed female mice showed dysbiosis characterized by a decreased weighted UniFrac β-diversity index, a higher abundance of Bacteroidales and Coriobacteriales orders, and a reduced Firmicutes/Bacteroidetes ratio.

Conclusion

Prenatal realistic modelling of an urban air pollution event induced sex-specific precocious alterations of structural and immune intestinal development in mice.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12989-022-00481-y.

Association of household solid fuel use and long-term exposure to PM2.5 with arthritis in middle-aged and older population in China: A cohort study

Air pollutants are common modifiable risk factors for arthritis. To explore the longitudinal effects of air pollution on arthritis based on a cohort study in middle-aged and elder people of China. Data was obtained from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2018. A total of 7449 participants aged 45 years and older were involved in our study. The generalized linear mixed models were conducted to examine the separate and joint effects of household air pollution and outdoor air pollution on arthritis, respectively. We found a strong significant association between air pollution and arthritis incidence. Individuals cooking primarily with solid fuel were more likely in higher risk of arthritis compared with cleaner fuel (OR= 1.15; 95% CI: 1.08-1.23). The group-based trajectory model identified four trajectory groups, compared with group "High-Decreasing rapidly", adjusted ORs of incident arthritis for group "Middle-Decreasing moderately", "Low-Decreasing slowly" and "Low-Stably" were 1.36 (95% CI, 1.03-1.79), 1.36 (95% CI, 1.01-1.83) and 1.81 (95% CI, 1.30-2.52), respectively. These associations were generally higher in participants younger than 65 years. In addition, solid fuel use and PM2.5 exposure had additive and multiplicative effects on arthritis. The results suggested that solid fuel use and long-term PM2.5 exposure were associated with a higher incidence of arthritis. Therefore, it is necessary to restrict solid fuel use to reduce household air pollution and make stronger environmental protection policies to reduce PM2.5 concentration.

Association between ambient air pollution and multiple sclerosis: a systemic review and meta-analysis

Recently, increasing attention has been paid to the effects of air pollutants on autoimmune diseases. The results of relationship between ambient air pollution and multiple sclerosis (MS) showed a variety of differences. Thus, the purpose of this study is to further clarify and quantify the relationship between ambient air pollutants and MS through meta-analysis. Through electronic literature search, literature related to our research topic was collected in Cochrane Library, Embase, and PubMed till August 18, 2020, according to certain criteria. Pooled risk estimate and 95% confidence intervals (95%CI) were calculated by random-effect model analysis. After removing copies, browsing titles and abstracts, and reading full text, 6 studies were finally included. The results showed that only particulate matter (PM) with aerodynamic diameter ≤ 10 (PM₁₀) was related to MS (pooled HR = 1.058, 95% CI = 1.050-1.066), and no correlation was found between PM with aerodynamic diameter < 2.5 (PM_2.5), nitrogen dioxide (NO₂), carbon monoxide (CO), ozone (O₃), benzene (C₆H₆), major road < 50 m, and MS. There was no publication bias, and the heterogeneity analysis results were stable. PM₁₀ is correlated with the disease MS, while other pollution is not connected with MS. Therefore, it is important for MS patients to take personal protection against particulate pollution and avoid exposure to higher levels of PM.

Management of Rheumatoid Arthritis: An Overview

Rheumatoid arthritis (RA) is a multifactorial autoimmune disease of unknown etiology, primarily affecting the joints, then extra-articular manifestations can occur. Due to its complexity, which is based on an incompletely elucidated pathophysiological mechanism, good RA management requires a multidisciplinary approach. The clinical status of RA patients has improved in recent years due to medical advances in diagnosis and treatment, that have made it possible to reduce disease activity and prevent systemic complications. The most promising results were obtained by developing disease-modifying anti-rheumatic drugs (DMARDs), the class to which conventional synthetic, biologic, and targeted synthetic drugs belong. Furthermore, ongoing drug development has led to obtaining molecules with improved efficacy and safety profiles, but further research is needed until RA turns into a curable pathology. In the present work, we offer a comprehensive perspective on the management of RA, by centralizing the existing data provided by significant literature, emphasizing the importance of an early and accurate diagnosis associated with optimal personalized treatment in order to achieve better outcomes for RA patients. In addition, this study suggests future research perspectives in the treatment of RA that could lead to higher efficacy and safety profiles and lower financial costs.

Handling missing data in a rheumatoid arthritis registry using random forest approach

Missing data in clinical epidemiological research violate the intention-to-treat principle, reduce the power of statistical analysis, and can introduce bias if the cause of missing data is related to a patient's response to treatment. Multiple imputation provides a solution to predict the values of missing data. The main objective of this study is to estimate and impute missing values in patient records. The data from the Kuwait Registry for Rheumatic Diseases was used to deal with missing values among patient records. A number of methods were implemented to deal with missing data; however, choosing the best imputation method was judged by the lowest root mean square error (RMSE). Among 1735 rheumatoid arthritis patients, we found missing values vary from 5% to 65.5% of the total observations. The results show that sequential random forest method can estimate these missing values with a high level of accuracy. The RMSE varied between 2.5 and 5.0. missForest had the lowest imputation error for both continuous and categorical variables under each missing data rate (10%, 20%, and 30%) and had the smallest prediction error difference when the models used the imputed laboratory values.

Potential Short-Term Air Pollution Effects on Rheumatoid Arthritis Activity in Metropolitan Areas in the North of Italy: A Cross-Sectional Study

Rheumatoid arthritis (RA) flare is related to increased joint damage, disability, and healthcare use. The impact of short-term air pollution exposure on RA disease activity is still a matter of debate. In this cross-sectional study, we investigated whether short-term exposure to particulate matter (PM)₁₀, PM_2.5, nitrogen dioxide (NO₂), and ozone (O₃) affected RA disease activity (DAS28 and SDAI) in 422 consecutive RA residents in Lombardy, North of Italy. Air pollutant concentrations, estimated by Regional Environmental Protection Agency (Lombardy—Italy) at the municipality level, were used to assign short-term exposure from the day of enrolment, back to seven days. Some significant negative associations emerged between RA disease activity, PM₁₀, and NO₂, whereas some positive associations were observed for O₃. Patients were also stratified according to their ongoing Disease-Modifying anti-Rheumatic Drugs (DMARDs) treatment: no DMARDs (n = 25), conventional synthetic DMARDs (n = 108), and biological or targeted synthetic DMARDs (n = 289). Therapy interaction seemed partially able to influence the relationship between short-term air pollution exposure and RA disease activity (PM_2.5 levels and DAS28 at the day of the visit-O₃ levels and disease activity scores for the seven days before the evaluation). According to our results, the impact of short-term air pollution exposure (seven days) minimally impacts disease activity. Moreover, our study suggests therapy could alter the response to environmental factors. Further evidence is needed to elucidate determinants of RA flare and its management.

Identification of public health priorities, barriers, and solutions for Kuwait using the modified Delphi method for stakeholder consensus

The rapid modernization and economic developments in Kuwait, have been accompanied by substantial lifestyle changes such as unhealthy diet and physical inactivity. These modifiable behaviours have contributed to increased rates of non-communicable diseases including diabetes and cardiovascular diseases. Delphi Consensus Method was implemented in the current study to draw stakeholders from all sectors together to develop a consensus on the major public health priorities, barriers and solutions. The process involves administration of a series of questions to selected stakeholders through an iterative process that ends when a consensus has been reached among participants. Results of the iteration process identified obesity, diabetes, cardiovascular diseases along with lack of enforcement of laws and regulation as priority health issues. Results also identified lack of national vision for the development of a public health system, lack of multidisciplinary research investigating sources of disease and methods of prevention and improving efficiency with existing resources in implementation and efficiency as the main barriers identified were. Solutions suggested included investing in healthcare prevention, strengthening communication between all involved sectors through intersectoral collaboration, awareness at the primary healthcare setting and use of electronic health records. The results offer an important opportunity for stakeholders in Kuwait to tackle these priority health issues employing the suggested approaches and solution.

Indoor solid fuel use and incident arthritis among middle-aged and older adults in rural China: A nationwide population-based cohort study

BACKGROUND

Many households in developing countries, including China, rely on the traditional use of solid fuels for cooking and heating. Arthritis is highly prevalent in middle-aged and older adults and is a major cause of disability. However, evidence linking indoor solid fuel use with arthritis is scarce in this age group (≥45 years) in developing countries.

OBJECTIVES

To investigate whether exposure to indoor solid fuel for cooking and heating is associated with arthritis in middle-aged and older adults in rural China.

METHODS

Data for the present study were extracted from the China Health and Retirement Longitudinal Study (CHARLS), a longitudinal national prospective study of adults aged 45 years and older enrolled in 2010 and followed up through 2015. We included 7807 rural participants without arthritis at baseline, of whom 1548 living in a central heating area in winter were included in the heating analysis (taking the Qinling-Huaihe line as the heating boundary). Cox proportional hazards models were used to examine the association between indoor solid fuel use and arthritis, controlling for age, sex, education, marital status, smoking status, drinking status, self-reported socioeconomic status, BMI, sleep time, napping time, independent cooking, hypertension, diabetes, dyslipidemia, heart problems and stroke. We also investigated the effect of switching primary fuels and using solid fuels for both cooking and heating on arthritis risk.

RESULTS

The mean (SD) age of the study participants was 59.2 (10.0) years old, and 48.0% of participants were women. A total of 64.8% and 63.0% of the participants reported primarily using solid fuel for cooking and heating, respectively. Arthritis incidence rates were lower among clean fuel users than solid fuel users. Compared to those using clean fuels, cooking and heating solid fuel users had a higher risk of arthritis, with hazard ratios (HRs) of 1.22 (95% confidence interval (CI): 1.01, 1.49) and 1.76 (95% CI: 1.07, 2.89), respectively. Switching from clean fuels to solid fuels for heating (HR: 3.28, 95% CI: 1.21, 7.91) and using solid fuels for both cooking and heating (HR, 1.71, 95% CI, 1.01-2.79) increased the risk of arthritis.

CONCLUSIONS

Long-term solid fuel use for indoor cooking and heating is associated with an increased risk of arthritis events among adults aged 45 years and older in rural China. The potential benefits of reducing indoor solid fuel use in groups at high risk for arthritis merit further exploration.

Environmental Air Pollution Is a Predictor of Poor Response to Biological Drugs in Chronic Inflammatory Arthritides

Background

There is increasing evidence that environmental air pollution is associated with the development of chronic inflammatory arthritides (CIA). The role of air pollutants on the biological treatment (biological disease‐modifying antirheumatic drugs [bDMARDs]) response of CIA is still unclear.

Methods

We retrieved longitudinal data on patients affected by CIA on biological therapies and on the daily concentration of air pollutants in the Verona area. We designed a case‐crossover study to compare the exposure to pollutants in the 60‐day period preceding a drug switch or swap due to disease progression referent to the 60‐day period preceding a visit with stable treatment for at least 6 months.

Results

A total of 1257 patients with CIA (863 with rheumatoid arthritis, 256 with psoriatic arthritis, and 138 with ankylosing spondylitis) with 5454 follow‐up visits were included in the study (median follow‐up 2.09 years [interquartile range: 0.82‐2.58 years]). A total of 282 patients were included in the case‐crossover study. We retrieved 13 636 daily air pollution records. We found that air pollutants’ concentrations were higher in the 60‐day period before a failure of bDMARD response and prior to a switch or swap compared with the period preceding a visit with stable bDMARD therapy for at least 6 months.

Conclusion

We found that environmental air pollution was a determinant of poor response to bDMARDs in a cohort of patients with CIA followed over a 5‐year period. An intervention aimed at decreasing fossil combustion emissions might have beneficial effects on biologic persistence rates of patients with CIA and economic expenditures related to switches and swaps.

Prospective correlational time-series analysis of the influence of weather and air pollution on joint pain in chronic rheumatic diseases

OBJECTIVES

The primary objective was to evaluate the association between weather variables and joint pain in patients with chronic rheumatic diseases (CRD: rheumatoid arthritis (RA), osteoarthritis (OA), and spondyloarthritis (SpA)). A secondary objective was to study the impact of air pollution indicators on CRD pain.

METHOD

The study is prospective, correlational, with time-series analysis. Patients with CRD, living in a predefined catchment area, filled their level of pain daily using a 0-10 numerical scale (NS), for 1 year. Weather (temperature, relative humidity (H), atmospheric pressure (P)) and air pollution indicators (particulate matters (PM₁₀, PM_2.5), nitrogen dioxide (NO₂), and ozone (O₃)) were recorded daily using monitoring systems positioned in the same area. Association between pain and weather and air pollution indicators was studied using Pearson's correlation. Time-series analysis methodology was applied to determine the temporal relationship between pain and indicators.

RESULTS

The study included 94 patients, 82% reported they were weather-sensitive. Pain variation was similar across diseases over a year. Pain was associated negatively with temperature, H, and O_3, and positively with P and NO₂. However, the strength of correlation was moderate; temperature explained 22% of pain variance. A drop of 10°C in temperature corresponded to an increase of 0.5 points in pain NS. Also, there was a significant interaction among environmental factors. In time-series analysis, temperature and NO₂ remained independently associated with pain.

CONCLUSIONS

The perception of joint pain in patients with CRD was correlated with weather and air pollution. The strength of association was moderate and independent of underlying disease. Key Points •Weather variation was moderately correlated with joint pain in chronic rheumatic diseases, with an inverse association with temperature, humidity, and O₃. • Air pollution indicators, mainly nitrogen dioxide and ozone, were correlated with joint pain; particulate matters were also correlated but to a lesser extent. • The influence of these environmental factors was independent of the type of rheumatic disease, thus raising the hypothesis of their impact on pain perception mechanisms.

Handling Complex Missing Data Using Random Forest Approach for an Air Quality Monitoring Dataset: A Case Study of Kuwait Environmental Data (2012 to 2018)

In environmental research, missing data are often a challenge for statistical modeling. This paper addressed some advanced techniques to deal with missing values in a data set measuring air quality using a multiple imputation (MI) approach. MCAR, MAR, and NMAR missing data techniques are applied to the data set. Five missing data levels are considered: 5%, 10%, 20%, 30%, and 40%. The imputation method used in this paper is an iterative imputation method, missForest, which is related to the random forest approach. Air quality data sets were gathered from five monitoring stations in Kuwait, aggregated to a daily basis. Logarithm transformation was carried out for all pollutant data, in order to normalize their distributions and to minimize skewness. We found high levels of missing values for NO2 (18.4%), CO (18.5%), PM10 (57.4%), SO2 (19.0%), and O3 (18.2%) data. Climatological data (i.e., air temperature, relative humidity, wind direction, and wind speed) were used as control variables for better estimation. The results show that the MAR technique had the lowest RMSE and MAE. We conclude that MI using the missForest approach has a high level of accuracy in estimating missing values. MissForest had the lowest imputation error (RMSE and MAE) among the other imputation methods and, thus, can be considered to be appropriate for analyzing air quality data.

Association between environmental air pollution and rheumatoid arthritis flares

Objectives

Environmental air pollution has been linked to the pathogenesis of RA. Nevertheless, evidence linking higher concentrations of air pollutants with the risk of RA reactivations is missing. The objective of the present study was to determine the association between RA flares and air pollution.

Methods

We collected longitudinal data of patients affected by RA and of the daily concentration of air pollutants in the Verona area. We designed a case-crossover study. We compared the exposure to pollutants in the 30-day and 60-day periods preceding an arthritic flare referent to the 30-day and 60-day preceding a low-disease activity visit.

Results

The study included 888 patients with RA with 3396 follow-up visits; 13 636 daily air pollution records were retrieved. We found an exposure–response relationship between the concentration of air pollutants and the risk of having abnormal CRP levels. Patients exposed to greater concentrations of air pollutants were at higher risk of having CRP levels ≥5 mg/l. Concentrations of CO, NO, NO2, NOx, PM10, PM2.5 and O3 were higher in the 60-day period preceding a flare.

Conclusions

We found a striking association between air pollution and RA disease severity and reactivations in a cohort of patients followed over a 5-year period. The exposure to high levels of air pollutants was associated with increased CRP levels and a higher risk of experiencing a flare of arthritis. This excessive risk was evident at very low levels of exposure.

Association between traffic-related air pollution and hospital readmissions for rheumatoid arthritis in Hefei, China: A time-series study

Air pollution is an important risk factor for autoimmune diseases, but its association with the recurrence of rheumatoid arthritis (RA) remains unclear so far. This study aimed to investigate the short-term association between traffic-related air pollutants and hospital readmissions for RA in Hefei, China. Data on daily hospital readmissions for RA and traffic-related air pollutants, including particulate matter (PM_2.5 and PM₁₀), nitrogen dioxide (NO₂), and carbon monoxide (CO), from 2014 to 2018 were retrieved. A time-series approach using generalized linear regression model was employed. The analysis was further stratified by sex, age and season. A total of 1153 readmissions for RA were reported during the study period. A significant association between high-concentration PM_2.5 (90th percentile) and RA readmissions was observed on lag1 (relative risk (RR) = 1.09, 95% confidence interval (CI): 1.01-1.19) and lasted until lag3 (RR = 1.06, 95%CI: 1.01-1.12). From lag2 to lag5, high-concentration NO₂ (90th percentile) was associated with increased risk of RA readmissions, with the highest RR observed at lag 4 (1.11, 95%CI: 1.05-1.17). Stratified analyses indicated that females and the elderly appeared to be more vulnerable to high-concentration PM_2.5 and NO₂ exposure. High-concentration PM_2.5 and NO₂ in cold seasons were consistently significantly associated with increased risk of RA readmissions. Exposure to high-concentration PM_2.5 and NO₂ was associated with increased risk of RA readmissions. Protective measures against the exposure to high-concentration PM_2.5 and NO₂ should be taken to reduce the recurrence risk in RA patients, especially in females, the elderly and during cold seasons.

Income Differentiation as a Factor of Unsustainability in Forestry

Environmental policy is a set of objectives put in place for the protection of natural resources including water, air, soil, food, and other renewable resources. In addition, it has a considerable impact on the labor market and the income of employees in the environmental and forestry sectors. Environmental policy both directly and indirectly creates new jobs, the so-called green jobs. These jobs are designed to be long-term and sustainable, working towards both environmental and socio-economic stability. The aim of the research was to determine if there was a difference in income between the forestry and the environmental policy sectors. The primary objective of this paper was to propose ideas and instruments for strengthening the income of employees in both sectors to the creators of the new State Environmental Policy. This objective was met through appropriate research methods, including the field survey technique. In terms of statistics, we used descriptive characteristics and tested the hypothesis using a T-test. The data from 70 respondents were collected from January 2019 to December 2019. Half of the respondents were from the forestry sector, and the other half worked in environmental protection. Their total income was compared by using two selective T-tests, and the results showed a strong discrepancy. The analysis indicated that the average incomes in forestry are significantly lower than incomes in the environmental protection sector (in the Czech Republic). The statistically higher income of environmental workers reflects that the State Environmental Policy is effective, which improves the position of employees in the labor market. The forestry sector deserves similar concentrated state assistance, and therefore we recommend that the new State Environmental Policy in the Czech Republic also addresses the problem of low income in forestry.