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. 2023 Sep 25;9(5):00035-2023.
doi: 10.1183/23120541.00035-2023. eCollection 2023 Sep.

High prevalence of interstitial lung abnormalities in middle-aged never-smokers

Affiliations

High prevalence of interstitial lung abnormalities in middle-aged never-smokers

Ida Pesonen et al. ERJ Open Res. .

Abstract

Background: Interstitial lung abnormalities (ILA) are incidental findings on chest computed tomography (CT). These patterns can present at an early stage of fibrotic lung disease. Our aim was to estimate the prevalence of ILA in the Swedish population, in particular in never-smokers, and find out its association with demographics, comorbidities and symptoms.

Methods: Participants were recruited to the Swedish CArdioPulmonary BioImage Study (SCAPIS), a population-based survey including men and women aged 50-64 years performed at six university hospitals in Sweden. CT scan, spirometry and questionnaires were performed. ILA were defined as cysts, ground-glass opacities, reticular abnormality, bronchiectasis and honeycombing.

Findings: Out of 29 521 participants, 14 487 were never-smokers and 14 380 were men. In the whole population, 2870 (9.7%) had ILA of which 134 (0.5%) were fibrotic. In never-smokers, the prevalence was 7.9% of which 0.3% were fibrotic. In the whole population, age, smoking history, chronic bronchitis, cancer, coronary artery calcium score and high-sensitive C-reactive protein were associated with ILA. Both ILA and fibrotic ILA were associated with restrictive spirometric pattern and impaired diffusing capacity of the lung for carbon monoxide. However, individuals with ILA did not report more symptoms compared with individuals without ILA.

Interpretation: ILA are common in a middle-aged Swedish population including never-smokers. ILA may be at risk of being underdiagnosed among never-smokers since they are not a target for screening.

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Conflict of interest statement

Conflict of interest: I. Pesonen reports fees from Boehringer Ingelheim for lectures and participation on advisory boards. Conflict of interest: A. Egeston reports consulting fees from BioCryst, payment/honoraria from AstraZeneca and an unrestricted research grant from CSL-Behring. Conflict of interest: Ö.I. Emilsson reports payment from study work from Boehringer Ingelheim, unrelated to this publication. Conflict of interest: E. Hagström reports payments to institution from Pfizer and Amgen, small personal fees from Amgen, NovoNordisk, Bayer and AstraZeneca, and a small personal fee from Amarin AB for participation on an advisory board. He is the co-chair of the Swedish secondary prevention registry and the national coordinator for the trials DalCore DAL301 DalGne, Regeneron R1500-CL-1643 and Aegis II/Perfuse. Conflict of interest: L.E.G.W. Vanfleteren reports grants paid to his institution from the Swedish Heart and Lung Foundation and the family Kamprad foundation, and payments/honoraria from AstraZeneca, GSK, Boehringer, Novartis, Chiesi, Pulmonx for lectures and presentations. He also reports personal payments for participation on a data safety monitoring board or advisory board for AstraZeneca. He was member of the board for the Swedish National Airway registry. He is as associate editor of this journal. Conflict of interest: P. Wollmer received fees for lectures from Chiesi Pharma outside the scope of the study. He also has a patent issued for a device and method for pulmonary function measurement outside the scope of the study. Conflict of interest: S. Zaigham reports a research project grant from Magnus Bergvalls Stiftelse, and support for meeting attendance from the Swedish Heart and Lung Foundation and Bror Hjerpstedts Stiftelse. Conflict of interest: C.M. Sköld reports research grants from Boehringer Ingelheim for pulmonary fibrosis research, payments for lectures and educational activities related to pulmonary fibrosis, and participation on advisory boards related to pulmonary fibrosis. Conflict of interest: All other authors declare no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Participant flow for the Swedish CardioPulmonary BioImage Study. ILA: interstitial lung abnormalities; CT: computed tomography.
FIGURE 2
FIGURE 2
Multivariable logistic regression to assess factors associated with interstitial lung abnormalities (ILA) comparing a) ILA with no ILA and b) fibrotic ILA with no ILA. Sex: OR is for comparison of male with female. Age: OR is for each additional year older. BMI: OR is for 1 kg·m−2 increase in BMI. Pack-years: OR is for each additional pack-year smoked. Occ. exp: OR is for comparison of moderate and high exposure with low exposure. CACS: OR is for comparison of the three groups with CACS=0. Chronic bronchitis: OR is for comparison of chronic bronchitis with no chronic bronchitis. Rheumatic disease: OR is for comparison of rheumatic disease with no rheumatic disease. Cancer: OR is for comparison of cancer with no cancer. hs-CRP: OR is for each 5-unit increase in hs-CRP. BMI: body mass index; CACS: coronary artery calcium score; hs-CRP: high-sensitivity C-reactive protein (mg·L−1); Occ. exp.: occupational exposure to vapour, gas, dust and fumes. #: significant factors after Benjamini–Hochberg correction.
FIGURE 3
FIGURE 3
Multivariable logistic regression to assess factors associated with interstitial lung abnormalities (ILA) comparing a) ILA with no ILA and b) fibrotic ILA with no ILA among never-smokers. Sex: OR is for comparison of male with female. Age: OR is for each additional year older. BMI: OR is for 1 kg·m−2 increase in BMI. Occ. exp: OR is for comparison of moderate and high exposure with low exposure. CACS: OR is for comparison of the three groups with CACS=0. Chronic bronchitis: OR is for comparison of chronic bronchitis with no chronic bronchitis. Rheumatic disease: OR is for comparison of rheumatic disease with no rheumatic disease. Cancer: OR is for comparison of cancer with no cancer. hs-CRP: OR is for each 5-unit increase in hs-CRP. BMI: body mass index; CACS: coronary artery calcium score; hs-CRP: high-sensitivity C-reactive protein (mg·L−1); Occ. exp.: occupational exposure to vapour, gas, dust and fumes. #: significant factors after Benjamini–Hochberg correction.

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