Background We describe the epidemiology of asthma, chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD) from 2004 to 2023 in England, Wales, Scotland and Northern Ireland (NI) using a harmonised approach. Methods Data from the National Health Service England (NHSE), Clinical Practice Research Datalink Aurum in England, Secure Anonymised Information Linkage Databank in Wales, DataLoch in South-East Scotland and the Honest Broker Service in NI were used. A harmonised approach to COPD, asthma and ILD case definitions, study designs and study populations across the four nations was performed. Age-sex-standardised incidence rates and point prevalence were calculated between 2004 and 2023 depending on data availability. Logistic and negative binomial regression compared incidence and prevalence rates between the start and end of each study period. Linear extrapolation projected incidence rates between 2020 and 2023 to illustrate how observed and projected rates differed. Results Incidence rates were lower in 2019 versus 2005 for asthma (England: incidence rate ratio 0.89, 95% CI 0.88 to 0.90; Wales: 0.66, 0.65 to 0.68; Scotland: 0.67, 0.64 to 0.71; NI: 0.84, 0.81 to 0.86), COPD (England: 0.83, 0.82 to 0.85; Wales: 0.67, 0.65 to 0.69) and higher for ILD (England: 3.27, 3.05 to 3.50; Wales: 1.39, 1.27 to 1.53; Scotland: 1.63, 1.36 to 1.95; NI: 3.03, 2.47 to 3.72). In NHSE, the incidence of asthma was similar in June 2023 versus November 2019, but lower for COPD and higher for ILD. Prevalence of asthma in 2019 in England, Wales, Scotland and NI was 9.7%, 15.9%, 13.2% and 7.0%, respectively, for COPD 4.5%, 5.1%, 4.4% and 3.0%, and for ILD 0.4%, 0.5%, 0.6% and 0.3%. Projected incidence rates were 2.8, 3.4 and 1.8 times lower for asthma, COPD and ILD compared with observed rates at the height of the pandemic. Interpretation Asthma, COPD and ILD affect over 10 million people across the four nations, and a substantial number of diagnoses were missed during the pandemic.

This study aims to describe the prevalence of sleep disturbances and daytime fatigue and their association with socio-demographic and behavioral factors. Data from the Brazilian National Health Survey conducted in 2013 with 60,202 adults (≥ 18 years old) were used. The outcomes evaluated were self-reported sleep disturbances and daytime fatigue in the last two weeks. Sleep disturbance was defined as the presence of difficulty to fall asleep, frequently waking up during the night or sleeping more than usual; daytime fatigue was defined as the presence of not feeling rested and motivated during the day, feeling tired and lacking energy. Sociodemographic, lifestyle and chronic health aspects were explored as exposures for both outcomes. Prevalence of sleep disturbances and daytime fatigue were 14.9% (14.4-15.4) and 11.9% (11.4-12.3), respectively. Both outcomes were more common in women, older people, people with no formal education, smokers and among physically inactive individuals. The association with education was inverse (the highest the level of education the lower the prevalence ratio - PR - of sleep disturbances and daytime fatigue; adjusted p-value for trend < 0.001). Prevalence of sleep disturbances combined with daytime fatigue was 6.7% (6.4-7.1) and was about 6 times higher among those with three or more chronic health disturbances (PR = 6.2; 95%CI: 5.3-7.2). Strategies to decrease the prevalence of sleep disturbances and daytime fatigue should be encouraged and focused on chronically ill individuals that share other modifiable risk factors.

OBJECTIVE: To estimate the average of a sleep problems score and their associated factors in adults living in rural areas. METHODS: A population-based cross-sectional study with individuals from the rural area of the city of Pelotas, Southern Brazil. Twenty-four of the 50 census tracts that make up the eight rural districts of the city were randomly selected. Individuals of 18 years of age or older residing in the households chosen were considered eligible. Sleep problems were measured using the Mini Sleep Questionnaire, which ranged from 10 to 70 points and the higher the score, the greater the sleep problems. The independent variables evaluated included socioeconomic, demographic, behavioral and health characteristics. In the analysis, linear regression was used, obeying a previous hierarchical model. RESULTS: The sample consisted of 1,421 individuals. The average obtained for sleep problems was 29.4 points (95% CI 28.7-30.1). After adjusted analysis, the following variables were associated factors for greater sleep problems: female sex, age greater than or equal to 40 years, lower schooling level, depressive symptoms, pesticide poisoning, and poorer quality of life. CONCLUSIONS: The Mini Sleep Questionnaire average in this study was 4.4 points above the cut-off point that established sleep problems. The total points found in the score was high for the rural population. Strategies to improve sleep for these individuals should be focused on higher-risk groups such as women and the elderly and those with pesticide poisoning.

RRH: Rural and Remote Health. Published article number: 6937 - Rural–urban differences in physical activity and TV-viewing in Brazil

Resumo Objetivo: Estimar a prevalência de fatores de risco comportamentais à saúde e investigar clusters de ocorrência simultânea desses fatores em estudantes de universidade pública, Pelotas, RS, Brasil. Métodos: Estudo transversal entre universitários no segundo semestre de 2017. Os fatores estudados foram inatividade física, excesso de comportamento sedentário, tempo inadequado de sono e tabagismo. Avaliou-se simultaneidade de fatores de risco mediante análise de clusters, via razão entre prevalências observada/esperada, considerando-se clusters aqueles que não incluíram a unidade. Resultados: Entre 1.716 estudantes, as prevalências de tempo inadequado de sono, inatividade física, excesso de comportamento sedentário e tabagismo foram de 45,2% (IC95% 42,9;47,6), 44,4% (IC95% 42,7;47,2), 39,8% (IC95% 37,7;42,2) e 10,6% (IC95% 9,6;12,5) respectivamente. Mais de 80% dos estudantes apresentaram pelo menos um fator de risco. Os clusters identificados relacionaram-se ao tempo inadequado de sono (O/E=1,15) e inatividade física concomitante ao comportamento sedentário (O/E=1,24). Conclusão: Observaram-se altas prevalências para os quatro fatores de risco estudados e apenas dois clusters.