Background: Few data are available on the temporal pattern of respiratory disease phenotypes in general population. Aim: To detect longitudinal patterns of disease phenotypes related to risk factors and physician visits. Methods: Pisan general population sample from 2 cross-sectional studies (PI1: 1991-93; PI2: 2009-11; n=1107), questionnaire-based data. Latent transition analysis (LTA) was performed to assess respiratory disease phenotypes at PI1 and PI2, labelled according to disease/symptom occurrence. Possible patterns were persistence, worsening and improvement of the phenotype. Multiple logistic regression models were estimated to assess the association among phenotype patterns, risk factors (smoking habits-SH and occupational exposure-OE) and physician visits, adjusting for age, sex and educational level. Results: 4 cross-sectional phenotypes were ranked by severity in PI1 and in PI2: healthy (H) (59 and 55%), allergic rhinitis (AR) (28 and 27%), cough/phlegm (CP) (11 and 15%), asthma (A) (3 and 4%). The longitudinal patterns were: persistent H (53%), persistent AR (27%), persistent CP (9%), improvement (2%), worsening (10%). Significant associations: persistent CP with persistent SH (OR 5.9), persistent OE (OR 2.9) and incident OE (OR 2.2); persistent CP and worsening of phenotype with current visits of family physician (OR 5.4 and OR 4.7, respectively) and of specialist (OR 2.7 and OR 3.9, respectively). Conclusions: LTA allowed to identify four different phenotypes based on respiratory symptoms/diseases and their longitudinal patterns over 18 years. Such analysis brings new perspectives in the analyses of population-based data.

Maio S, F.S. (2018). Respiratory disease phenotypes in a general population sample: latent transition analysis. EUROPEAN RESPIRATORY JOURNAL, 52(62) [10.1183/13993003.congress-2018.PA4492].

Respiratory disease phenotypes in a general population sample: latent transition analysis

Maio S
;
Fasola S;Muggeo V;
2018

Abstract

Background: Few data are available on the temporal pattern of respiratory disease phenotypes in general population. Aim: To detect longitudinal patterns of disease phenotypes related to risk factors and physician visits. Methods: Pisan general population sample from 2 cross-sectional studies (PI1: 1991-93; PI2: 2009-11; n=1107), questionnaire-based data. Latent transition analysis (LTA) was performed to assess respiratory disease phenotypes at PI1 and PI2, labelled according to disease/symptom occurrence. Possible patterns were persistence, worsening and improvement of the phenotype. Multiple logistic regression models were estimated to assess the association among phenotype patterns, risk factors (smoking habits-SH and occupational exposure-OE) and physician visits, adjusting for age, sex and educational level. Results: 4 cross-sectional phenotypes were ranked by severity in PI1 and in PI2: healthy (H) (59 and 55%), allergic rhinitis (AR) (28 and 27%), cough/phlegm (CP) (11 and 15%), asthma (A) (3 and 4%). The longitudinal patterns were: persistent H (53%), persistent AR (27%), persistent CP (9%), improvement (2%), worsening (10%). Significant associations: persistent CP with persistent SH (OR 5.9), persistent OE (OR 2.9) and incident OE (OR 2.2); persistent CP and worsening of phenotype with current visits of family physician (OR 5.4 and OR 4.7, respectively) and of specialist (OR 2.7 and OR 3.9, respectively). Conclusions: LTA allowed to identify four different phenotypes based on respiratory symptoms/diseases and their longitudinal patterns over 18 years. Such analysis brings new perspectives in the analyses of population-based data.
28th International Congress of the European-Respiratory-Society (ERS)
Paris, France
SEP 15-19, 2018
https://erj.ersjournals.com/content/52/suppl_62/PA4492
Maio S, F.S. (2018). Respiratory disease phenotypes in a general population sample: latent transition analysis. EUROPEAN RESPIRATORY JOURNAL, 52(62) [10.1183/13993003.congress-2018.PA4492].
File in questo prodotto:
File Dimensione Formato  
20180219144044 7ED29CY7E8V3F7K3.pdf

accesso aperto

Descrizione: abstract congresso ERS
Tipologia: Pre-print
Dimensione 76.41 kB
Formato Adobe PDF
76.41 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10447/301147
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? 0
social impact