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Taito Niemelä,1 Hannu Kankaanranta,1– 3 Iida Vähätalo,2 Juho Loponen,1,2 Leena E Tuomisto,2 Onni Niemelä,1,4 Mari Hämäläinen,5 Eeva Moilanen,5 Pinja Ilmarinen1,2 1Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; 2Department of Respiratory Medicine, Seinäjoki Central Hospital, Seinäjoki, Finland; 3Krefting Research Centre, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden; 4Department of Laboratory Medicine, Seinäjoki Central Hospital, Seinäjoki, Finland; 5The Immunopharmacology Research Group, Faculty of Medicine and Health Technology, Tampere University and Tampere University Hospital, Tampere, FinlandCorrespondence: Pinja Ilmarinen, Department of Respiratory Medicine, Seinäjoki Central Hospital, Seinäjoki, Finland, Tel +35 850 420 0596, Email pinja.ilmarinen@epshp.fiBackground: Soluble urokinase plasminogen activator receptor (suPAR) has emerged as a novel biomarker for various inflammatory conditions and has been proposed to associate with the severity of asthma. However, the relationship between suPAR and clinical asthma features is poorly understood.Objective: To examine associations of serum suPAR levels with clinical characteristics of asthma and to define the phenotype with high suPAR levels in patients with adult-onset asthma.Methods: Serum suPAR levels were measured with ELISA from patients with adult-onset asthma participating in the 12-year follow-up visit in the Seinäjoki Adult Asthma Study.Results: In total, 201 patients were divided into quartiles according to suPAR values. High suPAR patients had more severe asthma symptoms and poorer asthma control. They also had higher levels of interleukin 8 (IL-8), interleukin 6 (IL-6), matrix metalloproteinase 9 (MMP-9), and blood neutrophil counts than those with low suPAR levels. The use of high-dose inhaled and oral corticosteroids was more common in patients with elevated suPAR. Such patients also had visited healthcare more frequently during

Smoking, exposure to environmental tobacco smoke (ETS) and occupational exposure to vapours, gases, dusts or fumes (VGDF) increase asthma symptoms. The impact of combined exposure is less well established. We aimed to evaluate the risk of combined exposure to smoking, ETS and VGDF on the prevalence of current asthma and asthma-related symptoms with a postal survey among a random population of 16,000 adults, aged 20–69 years (response rate 51.5%). The 836 responders with physician-diagnosed asthma were included in the analysis. Of them, 81.9% had current asthma defined as physician-diagnosed asthma with current asthma medication use or reported symptoms. There was a consistently increasing trend in the prevalence of current asthma by increased exposure. The highest prevalence of multiple symptoms was in smokers with VGDF exposure (92.1%) compared to the unexposed (73.9%, p = 0.001). In logistic regression analysis, combined exposure to several exposures increased the risk in all analysed symptoms (p = 0.002–0.007). In conclusion, smoking and exposure to ETS or VGDF increased the prevalence of current asthma and multiple symptoms. The combined exposure carried the highest risk. Preventive strategies are called for to mitigate exposure to tobacco smoke and VGDF.

Background: Nonsteroidal anti-inflammatory drugs (NSAIDs) may exacerbate respiratory symptoms. A recent European Academy of Allergy and Clinical Immunology position paper recommended the use of an acronym, N-ERD (NSAID-exacerbated respiratory disease), for this hypersensitivity associated with asthma or chronic rhinosinusitis with or without nasal polyposis. Our aim was to estimate the prevalence of N-ERD and identify factors associated with N-ERD. Methods: In 2016, a cross-sectional questionnaire survey of a random adult population of 16 000 subjects aged 20–69 years was performed in Helsinki and Western Finland. The response rate was 51.5%. Results: The prevalence was 1.4% for N-ERD, and 0.7% for aspirin-exacerbated respiratory disease (AERD). The prevalence of N-ERD was 6.9% among subjects with asthma and 2.7% among subjects with rhinitis. The risk factors for N-ERD were older age, family history of asthma or allergic rhinitis, long-term smoking and exposure to environmental pollutants. Asthmatic subjects with N-ERD had a higher risk of respiratory symptoms, severe hypersensitivity reactions and hospitalisations than asthmatic subjects without N-ERD. The subphenotype of N-ERD with asthma was most symptomatic. Subjects with rhinitis associated with N-ERD, which would not be included in AERD, had the fewest symptoms. Conclusion: We conclude that the prevalence of N-ERD was 1.4% in a representative Finnish adult population sample. Older age, family history of asthma or allergic rhinitis, cumulative exposure to tobacco smoke, secondhand smoke, and occupational exposures increased odds of N-ERD. N-ERD was associated with significant morbidity.

Objective: Education in itself and as a proxy for socioeconomic status, may influence asthma control, but remains poorly studied in adult-onset asthma. Our aim was to study the association between the level of education and asthma control in adult-onset asthma. Methods: Subjects with current asthma with onset >15 years were examined within the Obstructive Lung Disease in Northern Sweden study (OLIN, n = 593), Seinäjoki Adult Asthma Study (SAAS, n = 200), and West Sweden Asthma Study (WSAS, n = 301) in 2009–2014 in a cross-sectional setting. Educational level was classified as primary, secondary and tertiary. Uncontrolled asthma was defined as Asthma Control Test (ACT) score ≤19. Altogether, 896 subjects with complete data on ACT and education were included (OLIN n = 511, SAAS n = 200 and WSAS n = 185). Results: In each cohort and in pooled data of all cohorts, median ACT score was lower among those with primary education than in those with secondary and tertiary education. Uncontrolled asthma was most common among those with primary education, especially among daily ICS users (42.6% primary, 28.6% secondary and 24.2% tertiary; p = 0.001). In adjusted analysis, primary education was associated with uncontrolled asthma in daily ICS users (OR 1.92, 95% CI 1.15–3.20). When stratified by atopy, the association between primary education and uncontrolled asthma was seen in non-atopic (OR 3.42, 95% CI 1.30–8.96) but not in atopic subjects. Conclusions: In high-income Nordic countries, lower educational level was a risk factor for uncontrolled asthma in subjects with adult-onset asthma. Educational level should be considered in the management of adult-onset asthma.

Background: Difference in dyspnea mMRC >= 2 between Finnish speaking and Swedish-speaking populations in Finland has not been previously studied. Methods: In February 2016, a respiratory questionnaire was sent to 8000 randomly selected subjects aged 20-69 years in western Finland with a response rate of 52.3%. The registered native language of each subject determined whether questionnaire in Finnish or Swedish was applied. Multiple logistic regression was performed to calculate Odds Ratios (OR) with 95% CI for the simultaneous effects of independent variables on dyspnea mMRC >= 2. Results: Of all participants, 2780 (71.9%) were Finnish speakers and 1084 (28.1%) were Swedish speakers. Finnish speakers had a higher prevalence of dyspnea mMRC >= 2 (11.1% vs 6.5% p < 0.001) when compared to Swedish speakers. Finnish speakers smoked more often, had higher BMI, spent less time moving during the day, had more often occupational exposure to vapours, gases, dusts or fumes (VGDF), and had lower socioeconomic status based on occupation. Significant risk factors for dyspnea mMRC >= 2 were COPD (OR = 10.94), BMI >35 (OR = 9.74), asthma (OR = 4.78), female gender (OR = 2.38), older age (OR = 2.20), current smoking (OR = 1.59), and occupational exposure to VGDF (OR = 1.47). Conclusions: Swedish speakers had less dyspnea mMRC >= 2 which is explained by a healthier lifestyle. Smoking, obesity, and occupational exposures should be in focus to improve respiratory health.

Heidi Andersén,1 Pinja Ilmarinen,1 Jasmin Honkamäki,1 Leena E Tuomisto,2 Hanna Hisinger-Mölkänen,3 Helena Backman,4 Bo Lundbäck,5 Eva Rönmark,4 Lauri Lehtimäki,1 Anssi Sovijärvi,3 Päivi Piirilä,3 Hannu Kankaanranta1 1Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland; 2Department of Respiratory Medicine, Seinäjoki Central Hospital, Seinäjoki, Etelä-Pohjanmaa, Finland; 3Faculty of Medicine, University of Helsinki, Helsinki, Uusimaa, Finland; 4Department of Public Health and Clinical Medicine, Umeå University, Umeå, Norrbotten, Sweden; 5Department of Internal Medicine, Krefting Research Center, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Västra Götaland, SwedenCorrespondence: Heidi AndersénFaculty of Medicine and Health Technology, Tampere University, Kalevantie 4, Tampere, 33100, FinlandEmail heidi.andersen@tuni.fiPurpose: Asthma is a heterogeneous disease, and factors associated with different asthma phenotypes are poorly understood. Given the higher prevalence of farming exposure and late diagnosis of asthma in more rural Western Finland as compared with the capital of Helsinki, we investigated the relationship between childhood farming environment and age at asthma diagnosis.Methods: A cross-sectional population-based study was carried out with subjects aged 20– 69 years in Western Finland. The response rate was 52.5%. We included 3864 participants, 416 of whom had physician-diagnosed asthma at a known age and with data on the childhood environment. The main finding was confirmed in a similar sample from Helsinki. Participants were classified as follows with respect to asthma diagnosis: early diagnosis (0– 11 years), intermediate diagnosis (12– 39 years), and late diagnosis (40– 69 years).Results: The prevalence of a

Purpose: Asthma is a heterogeneous disease, and factors associated with different asthma phenotypes are poorly understood. Given the higher prevalence of farming exposure and late diagnosis of asthma in more rural Western Finland as compared with the capital of Helsinki, we investigated the relationship between childhood farming environment and age at asthma diagnosis. Methods: A cross-sectional population-based study was carried out with subjects aged 20– 69 years in Western Finland. The response rate was 52.5%. We included 3864 participants, 416 of whom had physician-diagnosed asthma at a known age and with data on the childhood environment. The main finding was confirmed in a similar sample from Helsinki. Participants were classified as follows with respect to asthma diagnosis: early diagnosis (0– 11 years), intermediate diagnosis (12–39 years), and late diagnosis (40–69 years). Results: The prevalence of asthma was similar both without and with childhood exposure to a farming environment (11.7% vs 11.3%). Allergic rhinitis, family history of asthma, ex-smoker, occupational exposure, and BMI ≥ 30 kg/m2 were associated with a higher like-lihood of asthma. Childhood exposure to a farming environment did not increase the odds of having asthma (aOR, 1.10; 95% CI, 0.87–1.40). It did increase the odds of late diagnosis (aOR, 2.30; 95% CI, 1.12–4.69), but the odds were lower for early (aOR, 0.49; 95% CI, 0.30–0.80) and intermediate diagnosis of asthma (aOR, 0.75; 95% CI, 0.47–1.18). Conclusion: Odds were lower for early diagnosis of asthma and higher for late diagnosis of asthma in a childhood farming environment. This suggests a new hypothesis concerning the etiology of asthma when it is diagnosed late.