The REgulate your SItting Time (RESIT) is a tailored intervention targeting reductions and breaks in sitting in adults with type 2 diabetes mellitus (T2DM). A feasibility trial of RESIT had been conducted and the purpose of this paper is to report findings from the process evaluation.

A mixed-methods process evaluation within a randomised controlled feasibility trial.

The study was conducted remotely in the community.

Ambulatory individuals with T2DM aged 18–85 years.

A tailored intervention comprising an online education session, regular health coaching and technology for self-monitoring behaviour and prompting breaks in sitting.

Questionnaires (intervention participants n=22 at both 3 and 6 months; control participants n=21 at 3 months, n=29 at 6 months) and interviews (n=30, with n=13 intervention participants, n=12 control participants, n=5 health coaches) to assess perceptions of the intervention components, strategies and barriers for sitting less, the role of the study evaluation measures, and reasons for taking part.

The trial operated a largely successful online education element for those in the intervention group (82% completion; ≥76% engagement in individual educational elements). There was good use of self-monitoring and prompt technology (apps and wearables) with 73% of participants reporting using these at 6 months. Health coaching had high engagement and was perceived as enjoyable and useful. Data revealed strategies used for behaviour change (eg, active functional tasks) alongside barriers to change (eg, restrictions at work). There were also potential behavioural influences from the study evaluation measures (eg, activity measures increasing awareness and execution of behaviours) for both intervention and control participants.

A comprehensive process evaluation identified successful intervention elements (ie, online education, health coaching, wearables and smartphone apps) alongside strategies and barriers to behaviour change. These findings can inform future sedentary behaviour interventions for adults with T2DM and a definitive randomised controlled trial evaluating RESIT.

ISRCTN14832389.

Asthma is a chronic respiratory disorder requiring ongoing medical management. This ecological study investigated the spatial and temporal patterns of notification rates for asthma from clinic visits and hospital discharges and identified demographic, meteorological and environmental factors that drive asthma in Bhutan.

Monthly numbers of asthma notifications from 2016 to 2022 were obtained from the Bhutan Ministry of Health. Climatic variables (rainfall, relative humidity, minimum and maximum temperature) were obtained from the National Centre for Hydrology and Meteorology, Bhutan. The Normalised Difference Vegetation Index (NDVI) and surface particulate matter (PM2.5) were extracted from open sources. A multivariable zero-inflated Poisson regression (ZIP) model was developed in a Bayesian framework to quantify the relationship between risk of asthma and sociodemographic and environmental correlates, while also identifying the underlying spatial structure of the data.

There were 12 696 asthma notifications, with an annual average prevalence of 244/100 000 population between 2016 and 2022. In ZIP analysis, asthma notifications were 3.4 times (relative risk (RR)=3.39; 95% credible interval (CrI) 3.047 to 3.773) more likely in individuals aged >14 years than those aged ≤14 years, and 43% (RR=1.43; 95% CrI 36.5% to 49.2%) more likely for females than males. Asthma notification increased by 0.8% (RR=1.008, 95% CrI 0.2% to 1.5%) for every 10 cm increase in rainfall, and 1.7% (RR=1.017; 95% CrI 1.2% to 2.3%) for a 1°C increase in maximum temperature. An increase in one unit of NDVI and 10 µg/m³ PM2.5 was associated with 27.3% (RR=1.273; 95% CrI 8.7% to 49.2%), and 2.0% (RR=1.02; 95% CrI 1.0% to 4.0%) increase in asthma notification, respectively. The high-risk spatial clusters were identified in the south and southeastern regions of Bhutan, after accounting for covariates.

Environmental risk factors and spatial clusters of asthma notifications were identified. Identification of spatial clusters and environmental risk factors can help develop targeted interventions that maximise impact of limited public health resources for controlling asthma in Bhutan.

Post-COVID-19 conditions (PCC) may include pulmonary sequelae, fatigue and other symptoms, but its mechanisms are not fully elucidated.

This study investigated the correlation between fatigue and the presence of pulmonary abnormalities in PCC patients with respiratory involvement 6–12 months after hospitalisation.

Cross-sectional study.

A tertiary hospital in Brazil.

315 patients, aged ≥18 years, were considered eligible based on SARS-CoV-2 infection confirmed by reverse transcription-PCR.

Pulmonary function tests (PFT), cardiopulmonary exercise tests (CPET), chest CT and hand grip were performed. The following scales were applied: Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) scale, Euroqol 5 Dimensions quality of life (EQ-5D) and Hospital Anxiety and Depression Scale (HADS). Participants were divided between the fatigue group (FACIT-F≤30) and the non-fatigue group (FACIT-F>30). For the statistical analysis, the primary outcome was the difference in the diffusing capacity of the lungs for carbon monoxide (DLCO) between groups. Considered secondary outcomes were differences in PFT, CPET, chest CT, hand grip, EQ-5D and HADS.

The fatigue group had 81 patients (25.7%) against 234 (74.3%). PFT and CPET showed no significant difference in DLCO and oxygen consumption peak values between groups. The fatigue group had a lower workload (mean 55.3±21.3 watts vs 66.5±23.2 watts, p=0.003), higher breathing reserve (median 41.9% (33.8–52.5) vs 37.7% (28.9–47.1), p=0.028) and lower prevalence of ground glass opacity (60.8% vs 77.7%, p=0.003) and reticulation (36.7% vs 54.9%, p=0.005) in chest CT. The fatigue group had higher anxiety (57% vs 24%, p

Fatigue in patients with PCC 6–12 months after hospitalisation is relatively common and had weak correlation with pulmonary disorders. Our results suggested fatigue could be strongly related with peripheral disorders such as reduced musculoskeletal strength or psychosocial limitations.