102 research outputs found

    Work life of persons with asthma, rhinitis, and COPD: A study using a national, population-based sample

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    OBJECTIVE: To estimate the duration of work life among persons reporting a physician's diagnosis of COPD, asthma, or rhinitis compared to those with select non-respiratory conditions or none and to delineate the factors associated with continuance of employment. METHODS: Persons ages 55 to 75 reporting a physician's diagnosis of COPD, asthma, or rhinitis as well as those without any of these conditions were identified by random-digit dialing (RDD) in the continental U.S and administered a structured survey. We used Kaplan-Meier life table analysis to estimate the duration of work life among persons with and without the three conditions and Cox proportional hazard regression to examine the role of demographic and work characteristics in the proportion leaving employment in each time interval. RESULTS: Persons with COPD, asthma, and rhinitis were no less likely than the remainder of the population to have ever worked, but those with COPD were less likely to be working when interviewed or as of age 65, whichever came first. As of age 55, only 62 percent of persons with COPD continued to work versus 72 and 78 percent of persons with asthma and rhinitis, respectively. Persons with COPD, asthma, and rhinitis all had an elevated risk of leaving work prior to age 65 relative to those without chronic conditions, with and without adjustment for demographic and work characteristics. CONCLUSION: COPD and to a lesser extent asthma and rhinitis were associated with a substantially shortened work life, an effect not due to demographic and work characteristics

    Provision of preventive health care in systemic lupus erythematosus: data from a large observational cohort study

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    IntroductionCancer and infections are leading causes of mortality in systemic lupus erythematosus (SLE) after diseases of the circulatory system, and therefore preventing these complications is important. In this study, we examined two categories of preventive services in SLE: cancer surveillance (cervical, breast, and colon) and immunizations (influenza and pneumococcal). We compared the receipt of these services in SLE to the general population, and identified subgroups of patients who were less likely to receive these services.MethodsWe compared preventive services reported by insured women with SLE enrolled in the University of California, San Francisco Lupus Outcomes Study (n=685) to two representative samples derived from a statewide health interview survey, a general population sample (n=18,013) and a sample with non-rheumatic chronic conditions (n=4,515). In addition, using data from the cohort in both men and women (n=742), we applied multivariate regression analyses to determine whether characteristics of individuals (for example, sociodemographic and disease factors), health systems (for example, number of visits, involvement of generalists or rheumatologists in care, type of health insurance) or neighborhoods (neighborhood poverty) influenced the receipt of services.ResultsThe receipt of preventive care in SLE was similar to both comparison samples. For cancer surveillance, 70% of eligible respondents reported receipt of cervical cancer screening and mammography, and 62% reported colon cancer screening. For immunizations, 59% of eligible respondents reported influenza immunization, and 60% reported pneumococcal immunization. In multivariate regression analyses, several factors were associated with a lower likelihood of receiving preventive services, including younger age and lower educational attainment. We did not observe any effects by neighborhood poverty. A higher number of physician visits and involvement of generalist providers in care was associated with a higher likelihood of receiving most services.ConclusionsAlthough receipt of cancer screening procedures and immunizations in our cohort was comparable to the general population, we observed significant variability by sociodemographic factors such as age and educational attainment. Further research is needed to identify the physician, patient or health system factors contributing to this observed variation in order to develop effective quality improvement interventions

    Lifetime environmental tobacco smoke exposure and the risk of chronic obstructive pulmonary disease

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    BACKGROUND: Exposure to environmental tobacco smoke (ETS), which contains potent respiratory irritants, may lead to chronic airway inflammation and obstruction. Although ETS exposure appears to cause asthma in children and adults, its role in causing COPD has received limited attention in epidemiologic studies. METHODS: Using data from a population-based sample of 2,113 U.S. adults aged 55 to 75 years, we examined the association between lifetime ETS exposure and the risk of developing COPD. Participants were recruited from all 48 contiguous U.S. states by random digit dialing. Lifetime ETS exposure was ascertained by structured telephone interview. We used a standard epidemiologic approach to define COPD based on a self-reported physician diagnosis of chronic bronchitis, emphysema, or COPD. RESULTS: Higher cumulative lifetime home and work exposure were associated with a greater risk of COPD. The highest quartile of lifetime home ETS exposure was associated with a greater risk of COPD, controlling for age, sex, race, personal smoking history, educational attainment, marital status, and occupational exposure to vapors, gas, dusts, or fumes during the longest held job (OR 1.55; 95% CI 1.09 to 2.21). The highest quartile of lifetime workplace ETS exposure was also related to a greater risk of COPD (OR 1.36; 95% CI 1.002 to 1.84). The population attributable fraction was 11% for the highest quartile of home ETS exposure and 7% for work exposure. CONCLUSION: ETS exposure may be an important cause of COPD. Consequently, public policies aimed at preventing public smoking may reduce the burden of COPD-related death and disability, both by reducing direct smoking and ETS exposure

    Associations of baseline use of biologic or targeted synthetic DMARDs with COVID-19 severity in rheumatoid arthritis : Results from the COVID-19 Global Rheumatology Alliance physician registry

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    Funding Information: Competing interests JAS is supported by the National Institute of Arthritis and Funding Information: Musculoskeletal and Skin Diseases (grant numbers K23 AR069688, R03 AR075886, L30 AR066953, P30 AR070253 and P30 AR072577), the Rheumatology Research Foundation (K Supplement Award and R Bridge Award), the Brigham Research Institute, and the R Bruce and Joan M Mickey Research Scholar Fund. JAS has received research support from Amgen and Bristol-Myers Squibb and performed consultancy for Bristol-Myers Squibb, Gilead, Inova, Janssen and Optum, unrelated to this work. ZSW reports grant support from Bristol-Myers Squibb and Principia/ Sanofi and performed consultancy for Viela Bio and MedPace, outside the submitted work. His work is supported by grants from the National Institutes of Health. MG is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (grant numbers K01 AR070585 and K24 AR074534; JY). KLH reports she has received speaker’s fees from AbbVie and grant income from BMS, UCB and Pfizer, all unrelated to this study. KLH is also supported by the NIHR Manchester Biomedical Research Centre. LC has not received fees or personal grants from any laboratory, but her institute works by contract for laboratories such as, among other institutions, AbbVie Spain, Eisai, Gebro Pharma, Merck Sharp & Dohme España, Novartis Farmaceutica, Pfizer, Roche Farma, Sanofi Aventis, Astellas Pharma, Actelion Pharmaceuticals España, Grünenthal and UCB Pharma. LG reports research grants from Amgen, Galapagos, Janssen, Lilly, Pfizer, Sandoz and Sanofi; consulting fees from AbbVie, Amgen, BMS, Biogen, Celgene, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Samsung Bioepis, Sanofi Aventis and UCB, all unrelated to this study. EFM reports that LPCDR received support for specific activities: grants from AbbVie, Novartis, Janssen-Cilag, Lilly Portugal, Sanofi, Grünenthal, MSD, Celgene, Medac, Pharma Kern and GAfPA; grants and non-financial support from Pfizer; and non-financial support from Grünenthal, outside the submitted work. AS reports grants from a consortium of 13 companies (among them AbbVie, BMS, Celltrion, Fresenius Kabi, Lilly, Mylan, Hexal, MSD, Pfizer, Roche, Samsung, Sanofi Aventis and UCB) supporting the German RABBIT register, and personal fees from lectures for AbbVie, MSD, Roche, BMS and Pfizer, outside the submitted work. AD-G has no disclosures relevant to this study. His work is supported by grants from the Centers for Disease Control and Prevention and the Rheumatology Research Foundation. KMD is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (T32-AR-007258) and the Rheumatology Research Foundation. NJP is supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (T32-AR-007258). PD has received research support from Bristol-Myers Squibb, Chugai and Pfizer, and performed consultancy for Boehringer Ingelheim, Bristol-Myers Squibb, Lilly, Sanofi, Pfizer, Chugai, Roche and Janssen, unrelated to this work. NS is supported by the RRF Investigator Award and the American Heart Association. MFU-G reports grant support from Janssen and Pfizer. SB reports no competing interests related to this work. He reports non-branded consulting fees for AbbVie, Horizon, Novartis and Pfizer (all <10000).RGreportsnocompetinginterestsrelatedtothiswork.Outsideofthisworkshereportspersonaland/orspeakingfeesfromAbbVie,Janssen,Novartis,PfizerandCornerstones,andtravelassistancefromPfizer(all<10 000). RG reports no competing interests related to this work. Outside of this work she reports personal and/or speaking fees from AbbVie, Janssen, Novartis, Pfizer and Cornerstones, and travel assistance from Pfizer (all <10 000). JH reports no competing interests related to this work. He is supported by grants from the Rheumatology Research Foundation and the Childhood Arthritis and Rheumatology Research Alliance. He has performed consulting for Novartis, Sobi and Biogen, all unrelated to this work (<10000).JLhasreceivedresearchfundingfromPfizer,outsidethesubmittedwork.ESisaBoardMemberoftheCanadianArthritisPatientAlliance,apatientrun,volunteerbasedorganisationwhoseactivitiesarelargelysupportedbyindependentgrantsfrompharmaceuticalcompanies.PSreportsnocompetinginterestsrelatedtothiswork.HereportshonorariumfordoingsocialmediaforAmericanCollegeofRheumatologyjournals(<10 000). JL has received research funding from Pfizer, outside the submitted work. ES is a Board Member of the Canadian Arthritis Patient Alliance, a patient-run, volunteer-based organisation whose activities are largely supported by independent grants from pharmaceutical companies. PS reports no competing interests related to this work. He reports honorarium for doing social media for American College of Rheumatology journals (<10 000). PMM has received consulting/speaker’s fees from AbbVie, BMS, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche and UCB, all unrelated to this study (all <10000).PMMissupportedbytheNationalInstituteforHealthResearch(NIHR)UniversityCollegeLondonHospitals(UCLH)BiomedicalResearchCentre(BRC).PCRreportsnocompetinginterestsrelatedtothiswork.Outsideofthisworkhereportspersonalconsultingand/orspeakingfeesfromAbbVie,EliLilly,Janssen,Novartis,PfizerandUCB,andtravelassistancefromRoche(all<10 000). PMM is supported by the National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre (BRC). PCR reports no competing interests related to this work. Outside of this work he reports personal consulting and/or speaking fees from AbbVie, Eli Lilly, Janssen, Novartis, Pfizer and UCB, and travel assistance from Roche (all <10 000). JY reports no competing interests related to this work. Her work is supported by grants from the National Institutes of Health, Centers for Disease Control, and the Agency for Healthcare Research and Quality. She has performed consulting for Eli Lilly and AstraZeneca, unrelated to this project. Publisher Copyright: © Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.Objective To investigate baseline use of biologic or targeted synthetic (b/ts) disease-modifying antirheumatic drugs (DMARDs) and COVID-19 outcomes in rheumatoid arthritis (RA). Methods We analysed the COVID-19 Global Rheumatology Alliance physician registry (from 24 March 2020 to 12 April 2021). We investigated b/tsDMARD use for RA at the clinical onset of COVID-19 (baseline): abatacept (ABA), rituximab (RTX), Janus kinase inhibitors (JAKi), interleukin 6 inhibitors (IL-6i) or tumour necrosis factor inhibitors (TNFi, reference group). The ordinal COVID-19 severity outcome was (1) no hospitalisation, (2) hospitalisation without oxygen, (3) hospitalisation with oxygen/ventilation or (4) death. We used ordinal logistic regression to estimate the OR (odds of being one level higher on the ordinal outcome) for each drug class compared with TNFi, adjusting for potential baseline confounders. Results Of 2869 people with RA (mean age 56.7 years, 80.8% female) on b/tsDMARD at the onset of COVID-19, there were 237 on ABA, 364 on RTX, 317 on IL-6i, 563 on JAKi and 1388 on TNFi. Overall, 613 (21%) were hospitalised and 157 (5.5%) died. RTX (OR 4.15, 95% CI 3.16 to 5.44) and JAKi (OR 2.06, 95% CI 1.60 to 2.65) were each associated with worse COVID-19 severity compared with TNFi. There were no associations between ABA or IL6i and COVID-19 severity. Conclusions People with RA treated with RTX or JAKi had worse COVID-19 severity than those on TNFi. The strong association of RTX and JAKi use with poor COVID-19 outcomes highlights prioritisation of risk mitigation strategies for these people.publishersversionPeer reviewe

    Factors associated with COVID-19-related death in people with rheumatic diseases: results from the COVID-19 Global Rheumatology Alliance physician-reported registry.

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    OBJECTIVES: To determine factors associated with COVID-19-related death in people with rheumatic diseases. METHODS: Physician-reported registry of adults with rheumatic disease and confirmed or presumptive COVID-19 (from 24 March to 1 July 2020). The primary outcome was COVID-19-related death. Age, sex, smoking status, comorbidities, rheumatic disease diagnosis, disease activity and medications were included as covariates in multivariable logistic regression models. Analyses were further stratified according to rheumatic disease category. RESULTS: Of 3729 patients (mean age 57 years, 68% female), 390 (10.5%) died. Independent factors associated with COVID-19-related death were age (66-75 years: OR 3.00, 95% CI 2.13 to 4.22; >75 years: 6.18, 4.47 to 8.53; both vs ≤65 years), male sex (1.46, 1.11 to 1.91), hypertension combined with cardiovascular disease (1.89, 1.31 to 2.73), chronic lung disease (1.68, 1.26 to 2.25) and prednisolone-equivalent dosage >10 mg/day (1.69, 1.18 to 2.41; vs no glucocorticoid intake). Moderate/high disease activity (vs remission/low disease activity) was associated with higher odds of death (1.87, 1.27 to 2.77). Rituximab (4.04, 2.32 to 7.03), sulfasalazine (3.60, 1.66 to 7.78), immunosuppressants (azathioprine, cyclophosphamide, ciclosporin, mycophenolate or tacrolimus: 2.22, 1.43 to 3.46) and not receiving any disease-modifying anti-rheumatic drug (DMARD) (2.11, 1.48 to 3.01) were associated with higher odds of death, compared with methotrexate monotherapy. Other synthetic/biological DMARDs were not associated with COVID-19-related death. CONCLUSION: Among people with rheumatic disease, COVID-19-related death was associated with known general factors (older age, male sex and specific comorbidities) and disease-specific factors (disease activity and specific medications). The association with moderate/high disease activity highlights the importance of adequate disease control with DMARDs, preferably without increasing glucocorticoid dosages. Caution may be required with rituximab, sulfasalazine and some immunosuppressants

    Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

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    In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security
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