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. 2020 Mar 26;30:10. doi: 10.1038/s41533-020-0169-z

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© The Author(s) 2020

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 1 — a–f The figure consists of six graphs showing the descriptive correlation between lung function at baseline (exposure) and development of medical health condition on different parameters. Outcomes in 1-year intervals are: number of contacts to general practitioner from 1991 to 2017 (panel a, b), redeemed prescriptions for respiratory medicine from 1995 to 2017 (panel c, d) and income level from 1991 to 2017 (panel e, f). X-axis: time (years), Y-axis: outcome (numbers). Unadjusted, crude mean numbers are shown in the top panel and adjusted IRRs (95% CI) in the bottom panels. Group three (FEV₁/FVC>75) is the reference group and the regressions is adjusted for sex, age and smoking status. GP general practitioner, FEV₁ forced expiratory volume in 1s, FVC forced vital capacity.