Longitudinal Asthma Patterns in Italian Adult General Population Samples: Host and Environmental Risk Factors
| Autor: | Maio, S., Baldacci, S., Simoni, M., Angino, A., La Grutta, S., Muggeo, V., Fasola, S., Viegi, G., Angino, AGAVE Sudy Group: A., Bresciani, M., Carrozzi, L., Cerrai, S., Martini, F., Pala, A. P., Pistelli, F., Sarno, G., Silvi, P. |
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| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
Population lcsh:Medicine comorbidities Article 03 medical and health sciences 0302 clinical medicine Environmental risk Internal medicine Epidemiology medicine 030212 general & internal medicine education Asthma Multinomial logistic regression vehicular traffic education.field_of_study business.industry lcsh:R Asthma symptoms latent transition analysis General Medicine cohort asthma medicine.disease respiratory tract diseases 030228 respiratory system smoke epidemiology Cohort Latent transition analysis business |
| Zdroj: | Journal of Clinical Medicine Volume 9 Issue 11 Journal of Clinical Medicine, Vol 9, Iss 3632, p 3632 (2020) Journal of clinical medicine (2020). doi:10.3390/jcm9113632 info:cnr-pdr/source/autori:Sara Maio; Sandra Baldacci; Marzia Simoni; Anna Angino; Stefania La Grutta; Vito Muggeo; Salvatore Fasola; Giovanni Viegi;2 and on behalf of the AGAVE Pisa Group;/titolo:Longitudinal Asthma Patterns in Italian Adult General Population Samples: Host and Environmental Risk Factors/doi:10.3390%2Fjcm9113632/rivista:Journal of clinical medicine/anno:2020/pagina_da:/pagina_a:/intervallo_pagine:/volume |
| ISSN: | 2077-0383 |
| DOI: | 10.3390/jcm9113632 |
| Popis: | Background: Asthma patterns are not well established in epidemiological studies. Aim: To assess asthma patterns and risk factors in an adult general population sample. Methods: In total, 452 individuals reporting asthma symptoms/diagnosis in previous surveys participated in the AGAVE survey (2011–2014). Latent transition analysis (LTA) was performed to detect baseline and 12-month follow-up asthma phenotypes and longitudinal patterns. Risk factors associated with longitudinal patterns were assessed through multinomial logistic regression. Results: LTA detected four longitudinal patterns: persistent asthma diagnosis with symptoms, 27.2% persistent asthma diagnosis without symptoms, 4.6% persistent asthma symptoms without diagnosis, 44.0% and ex -asthma, 24.1%. The longitudinal patterns were differently associated with asthma comorbidities. Persistent asthma diagnosis with symptoms showed associations with passive smoke (OR 2.64, 95% CI 1.10–6.33) and traffic exposure (OR 1.86, 95% CI 1.02–3.38), while persistent asthma symptoms (without diagnosis) with passive smoke (OR 3.28, 95% CI 1.41–7.66) and active smoke (OR 6.24, 95% CI 2.68–14.51). Conclusions: LTA identified three cross-sectional phenotypes and their four longitudinal patterns in a real-life setting. The results highlight the necessity of a careful monitoring of exposure to active/passive smoke and vehicular traffic, possible determinants of occurrence of asthma symptoms (with or without diagnosis). Such information could help affected patients and physicians in prevention and management strategies. |
| Databáze: | OpenAIRE |
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