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Background and objective: Obstructive sleep apnoea (OSA) and asthma are associated, and nocturnal breathing difficulty that is usually identified as asthma‐like symptoms can be present in both conditions. We investigated how nocturnal asthma‐like symptoms (NAS) and bronchial hyper‐reactivity (BHR) contribute to the association between OSA risk and current asthma, which is currently unknown but a clinically important question. Methods: We used data from 794 middle‐aged participants in a population‐based cohort who provided information on OSA risk (defined by a STOP‐Bang questionnaire score of at least 3), current asthma and NAS, and underwent methacholine bronchial challenge testing. Using regression models, we examined the association between OSA risk and current asthma‐NAS subgroups and investigated any effect modification by BHR. Results: The participants were aged 50 years (49.8% male). OSA risk was associated with NAS with or without current asthma (odds ratio (OR): 2.6; 95% CI = 1.3–5.0; OR: 4.2; 95% CI = 1.1–16.1, respectively), but not with current asthma in the absence of NAS. BHR was associated with current asthma with or without NAS (OR: 2.9; 95% CI = 1.4–5.9; OR: 3.4; 95% CI = 2.0–7.0, respectively) but not with NAS in the absence of current asthma. The associations between OSA risk and current asthma were neither modified nor mediated by BHR. Conclusion: Our findings suggest that some of the nocturnal symptoms perceived as asthma may be OSA symptoms. Patients with nocturnal asthma symptoms should be considered for possible OSA. We assessed the roles of nocturnal asthma‐like symptoms (NAS) and bronchial hyper‐reactivity (BHR) in obstructive sleep apnoea (OSA)–asthma association. OSA is associated with NAS with or without the presence of asthma, but BHR is not associated with NAS when asthma is absent. Some NAS perceived as nocturnal asthma could be symptoms of OSA. See relatedEditorial [ABSTRACT FROM AUTHOR]

Summary: The concordance of different indices from type‐4 sleep studies in diagnosing and categorising the severity of obstructive sleep apnoea is not known. This is a critical gap as type‐4 sleep studies are used to diagnose obstructive sleep apnoea in some settings. Therefore, we aimed to determine the concordance between flow‐based apnoea–hypopnoea index (AHIflow50%) and oxygen desaturation index (ODI3%) by measuring them concurrently. Using a random sub‐sample of 296 from a population‐based cohort who underwent two‐channel type‐4 sleep studies, we assessed the concordance between AHIflow50% and ODI3%. We compared the prevalence of obstructive sleep apnoea of various severities as identified by the two methods, and determined their concordance using coefficient Kappa(κ). Participants were aged (mean ± SD) 53 ± 0.9 years (48% male). The body mass index was 28.8 ± 5.2 kg m−2 and neck circumference was 37.4 ± 3.9 cm. The median AHIflow50% was 5 (inter‐quartile range 2, 10) and median ODI3% was 9 (inter‐quartile range 4, 15). The obstructive sleep apnoea prevalence reported using AHIflow50% was significantly lower than that reported using ODI3% at all severity thresholds. Although 90% of those with moderate–severe obstructive sleep apnoea classified using AHIflow50% were identified by using ODI3%, only 46% of those with moderate–severe obstructive sleep apnoea classified using ODI3% were identified by AHIflow50%. The overall concordance between AHIflow50% and ODI3% in diagnosing and classifying the severity of obstructive sleep apnoea was only fair (κ = 0.32), better for males (κ = 0.42 [95% confidence interval 0.32–0.57] versus 0.22 [95% confidence interval 0.09–0.31]), and lowest for those with a body mass index ≥ 35 (κ = 0.11). In conclusion, ODI3% and AHIflow50% from type‐4 sleep studies are at least moderately discordant. Until further evidence is available, the use of ODI3% as the measure of choice for type‐4 sleep studies is recommended cautiously. [ABSTRACT FROM AUTHOR]