Abstract
OBJECTIVE: To assess whether there are clusters of people with type 2 diabetes with distinct temporal profiles of lung function changes and characteristics. RESEARCH DESIGN AND METHODS: Group-based trajectory modeling (GBTM) identified groups of participants with type 2 diabetes from the community-based observational Fremantle Diabetes Study Phase II (FDS2) who had at least two biennial measurements of forced expiratory volume in 1 s as a percentage of predicted (FEV1%pred) over 6 years. Independent associates of group membership were assessed using multinomial regression. RESULTS: Of 1,482 potential FDS2 participants, 1,074 (72.5%; mean age, 65.2 years; 45.5% female; median diabetes duration, 8.0 years) were included in the modeling. The best fitting GBTM model identified four groups categorized by FEV1%pred trajectory: high (19.5%; baseline FEV1%pred, 106.5 +/- 9.5%; slope 0%/year), medium (47.7%; FEV1% pred, 87.3 +/- 8.7%; slope, -0.32%/year), low (25.0%; baseline FEV1%pred, 68.9 +/- 9.8%; slope, -0.72%/year), and very low (7.9%; baseline FEV1%pred, 48.8 +/- 9.6%; slope, 20.68%/year). Compared with the high group, the other groups were characterized by nonmodifiable and modifiable risk factors associated with lung function decline in the general population (including ethnicity, marital status, smoking, obesity, coronary heart disease, and chronic respiratory disease). The main, diabetes-specific, significant predictor of group membership was a higher HbA1c in the very low group. There was a graded increase in mortality from 6.7% in the high group to 22.4% in the very low group. CONCLUSIONS: Measurement of lung function in type 2 diabetes could help optimize clinical management and improve prognosis, including addressing glycemic control in those with a very low FEV1%pred.
| Original language | English |
|---|---|
| Pages (from-to) | 483-490 |
| Number of pages | 8 |
| Journal | Diabetes Care |
| Volume | 47 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Mar 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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