All data relating to Obesity and mortality during the coronavirus (COVID-19) pandemic, England: 24 January 2020 to 30 August 2022

Background: Cardiometabolic morbidity and medications, specifically Angiotensin Converting Enzyme inhibitors (ACEi) and Angiotensin Receptor Blockers (ARBs), have been linked with adverse outcomes from coronavirus disease 2019 (COVID-19). This study aims to investigate, factors associated with COVID-19 positivity in hospital for 1,436 UK Biobank participants; compared with individuals who tested negative, and with the untested, presumed negative, rest of the cohort.Methods: We studied 7,099 participants from the UK Biobank who had been tested for COVID-19 in hospital. We considered the following exposures: age, sex, ethnicity, body mass index (BMI), diabetes, hypertension, hypercholesterolaemia, ACEi/ARB use, prior myocardial infarction (MI), and smoking. We undertook comparisons between (1) COVID-19 positive and COVID-19 negative tested participants; and (2) COVID-19 tested positive and the remaining participants (tested negative plus untested, n = 494,838). Logistic regression models were used to investigate univariate and mutually adjusted associations.Results: Among participants tested for COVID-19, Black, Asian, and Minority ethnic (BAME) ethnicity, male sex, and higher BMI were independently associated with a positive result. BAME ethnicity, male sex, greater BMI, diabetes, hypertension, and smoking were independently associated with COVID-19 positivity compared to the remaining cohort (test negatives plus untested). However, similar associations were observed when comparing those who tested negative for COVID-19 with the untested cohort; suggesting that these factors associate with general hospitalization rather than specifically with COVID-19.Conclusions: Among participants tested for COVID-19 with presumed moderate to severe symptoms in a hospital setting, BAME ethnicity, male sex, and higher BMI are associated with a positive result. Other cardiometabolic morbidities confer increased risk of hospitalization, without specificity for COVID-19. ACE/ARB use did not associate with COVID-19 status.

The National Obesity Audit (NOA) publication series presents a developing set of nationally agreed measures, with the overarching aim to provide a comprehensive picture of activity, access to services and health outcomes of patients using weight management services (WMS) across England. This will allow providers to track, benchmark and improve the quality of these services in future. This release includes data from both Hospital Episode Statistics (HES) for Tier 4 WMS, and the Community Services Data Set (CSDS) for Tier 2 and Tier 3 WMS. More information about WMS tiers can be found on the NOA homepage (see Related Links). Disruption relating to the coronavirus illness (COVID-19) would seem to have affected the quality and coverage of some of our statistics, such as an increase in non-submissions for some datasets. We have also seen some different patterns in the submitted data. For example, fewer patients have been admitted to and discharged from hospital. Therefore, data should be interpreted with care over the COVID-19 period.

Data at the Local Authority (UK) level, for Covid-19 mortality rates and potential risk factors - median IMD score, population density, ethnicity, overweight/obesity, PM2.5 pollution. All data are in the public domain and references are given in the paper.

Objectives: We assessed whether lockdown had a disproportionate impact on physical activity behavior in groups who were, or who perceived themselves to be, at heightened risk from COVID-19.Methods: Physical activity intensity (none, mild, moderate, or vigorous) before and during the UK COVID-19 lockdown was self-reported by 9,190 adults between 2020-04-06 and 2020-04-22. Physician-diagnosed health conditions and topic composition of open-ended text on participants' coping strategies were tested for associations with changes in physical activity.Results: Most (63.9%) participants maintained their normal physical activity intensity during lockdown, 25.0% changed toward less intensive activity and 11.1% were doing more. Doing less intensive physical activity was associated with obesity (OR 1.25, 95% CI 1.08–1.42), hypertension (OR 1.25, 1.10–1.40), lung disease (OR 1.23, 1.08–1.38), depression (OR 2.05, 1.89–2.21), and disability (OR 2.13, 1.87–2.39). Being female (OR 1.25, 1.12–1.38), living alone (OR 1.20, 1.05–1.34), or without access to a garden (OR 1.74, 1.56–1.91) were also associated with doing less intensive physical activity, but being in the highest income group (OR 1.73, 1.37–2.09) or having school-age children (OR 1.29, 1.10–1.49) were associated with doing more. Younger adults were more likely to change their PA behavior compared to older adults. Structural topic modeling of narratives on coping strategies revealed associations between changes in physical activity and perceptions of personal or familial risks at work or at home.Conclusions: Policies on maintaining or improving physical activity intensity during lockdowns should consider (1) vulnerable groups of adults including those with chronic diseases or self-perceptions of being at risk and (2) the importance of access to green or open spaces in which to exercise.

Candidate genetic instruments of cardiometabolic diseases and traits.

This is the first release of data to form part of the National Obesity Audit (NOA). Data on NHS funded bariatric surgical procedures delivered in England, are presented in an interactive dashboard. All data is currently sourced from Hospital Episode Statistics (HES), NHS Digital. As more data starts to be submitted by other weight management services, the dashboard will develop to provide a comprehensive picture of commissioning, access and outcomes of weight management services across England. Future releases of the dashboard will add data from other sources and with additional functionality. See the metadata file for a list of measures published as part of this release. HES data continued to be submitted by providers throughout the pandemic. Disruption relating to the coronavirus illness (COVID-19) would seem to have affected the quality and coverage of some of our statistics, such as an increase in non-submissions for some datasets. We have also seen some different patterns in the submitted data. For example, fewer patients are being admitted to and discharged from hospital. Therefore, data should be interpreted with care over the COVID-19 period. Further information of how elective care including surgery will recover from the impact of COVID-19 is published by NHS England.

Background. Chronic obstructive pulmonary disease (COPD) is a debilitating lung condition characterised by progressive lung function limitation. COPD is an umbrella term and encompasses a spectrum of pathophysiologies including chronic bronchitis, small airways disease and emphysema. COPD caused an estimated 3 million deaths worldwide in 2016, and is estimated to be the third leading cause of death worldwide. The British Lung Foundation (BLF) estimates that the disease costs the NHS around £1.9 billion per year. COPD is therefore a significant public health challenge. This dataset explores the impact of hospitalisation in patients with COPD during the COVID pandemic.

PIONEER geography The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix. There is a higher than average percentage of minority ethnic groups. WM has a large number of elderly residents but is the youngest population in the UK. There are particularly high rates of physical inactivity, obesity, smoking & diabetes. The West Midlands has a high prevalence of COPD, reflecting the high rates of smoking and industrial exposure. Each day >100,000 people are treated in hospital, see their GP or are cared for by the NHS.

EHR. University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & 100 ITU beds. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”.

Scope: All hospitalised patients admitted to UHB during the COVID-19 pandemic first wave, curated to focus on COPD. Longitudinal & individually linked, so that the preceding & subsequent health journey can be mapped & healthcare utilisation prior to & after admission understood. The dataset includes ICD-10 & SNOMED-CT codes pertaining to COPD and COPD exacerbations, as well as all co-morbid conditions. Serial, structured data pertaining to process of care (timings, staff grades, specialty review, wards), presenting complaint, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations), all blood results, microbiology, all prescribed & administered treatments (fluids, nebulisers, antibiotics, inotropes, vasopressors, organ support), all outcomes. Linked images available (radiographs, CT).

Available supplementary data: More extensive data including wave 2 patients in non-OMOP form. Ambulance, 111, 999 data, synthetic data.

Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

The full methods for the cRCT have been described in the published study protocol, trial registration and main trial results publications:· Original trial protocol for a stepped-wedge trial: https://doi.org/10.1186/s13063-021-05167-y· Updated trial protocol for a cRCT, due to the COVID-19 pandemic: https://doi.org/10.1186/s13063-023-07243-x· Trial registration: https://doi.org/10.1186/ISRCTN42219712Briefly, Alfadanga upazila was divided into 12 clusters of approximately equal population size using government census data. Within these 12 clusters, between 2-5 villages were purposefully selected to achieve between 800-1000 households per cluster, according the following eligibility criteria: a) they do not sit on a border with a neighbouring study cluster; b) they are not a major trading centre or administrative centre; c) they have a minimum of 50 households. A population census was conducted between November 2019 – January 2020 to form a sampling frame, with each household within purposefully selected villages visited, and all household members aged 25 and older registered. A unique study ID was assigned to each individual using the following formulation.Clusters were randomised to either control or community mobilisation through Participatory Learning and Action (PLA), which works through facilitated community groups actively engaging communities in identifying the causes of health problems and working together to design and implement ways to address these health problems, and reflect on their progress. Three cross-sectional surveys were conducted: a) pre-COVID-19 baseline; b) post-COVID-19 baseline; c) endline. For each survey, a random sample of individuals were selected using two-stage simple random sampling, with the household randomly selected then one eligible individual selected from these households. For the endline survey, individuals who were identified as living with intermediate hyperglycaemia in the post-COVID-19 baseline survey were purposefully selected.

Introduction: Adults with overweight and obesity are vulnerable to weight gain and mental health deterioration during the COVID-19 pandemic. We developed a web-based, guided self-help intervention based on Acceptance and Commitment Therapy (ACT) that aims to support adults with overweight and obesity to prevent weight gain by helping them to manage their eating behaviours, be more physically active and protect their emotional wellbeing (“SWiM-C”). SWiM-C is a guided self-help programme using non-specialist guides to enhance scalability and population reach while minimising cost. This study evaluated the effect of SWiM-C on bodyweight, eating behaviour, physical activity and mental wellbeing in adults with overweight and obesity over 4 months during the COVID-19 pandemic in the UK.

Methods: We randomised adults (BMI≥25kg/m2) to SWiM-C or to a wait-list standard advice group. Participants completed outcome assessments online at baseline and 4 months. The primary outcome was self-measured weight; secondary outcomes were eating behaviour, physical activity, experiential avoidance/psychological flexibility, depression, anxiety, stress, and wellbeing. We estimated differences between study groups in change in outcomes from baseline to 4 months using linear regression, adjusted for outcome at baseline and the randomisation stratifiers (BMI, sex). The trial was pre-registered (ISRCTN12107048).

Results: 486 participants were assessed for eligibility; 388 participants were randomised (196 standard advice, 192 SWiM-C) and 324 were analysed. The adjusted difference in weight between SWiM-C and standard advice was -0.60kg (-1.67 to 0.47, p=0.27). SWiM-C led to improvements in uncontrolled eating (-3.61 [-5.94 to -1.28]), cognitive restraint (5.28 [2.81 to 7.75]), experiential avoidance (-3.39 [-5.55 to -1.23]), and wellbeing (0.13 [0.07 to 0.18]).

Conclusions: SWiM-C improved several psychological determinants of successful weight management and had a protective effect on wellbeing during the pandemic. However, differences in weight and some other outcomes were compatible with no effect of the intervention, suggesting further refinement of the intervention is needed.

Further information is available from the gov.uk National Diet and Nutrition Survey webpage.

This study was a follow-up of National Diet and Nutrition Survey Rolling Programme (NDNS RP) participants and aimed to describe, and assess the impact of the COVID-19 pandemic on, the diet and physical activity of people in the UK in 2020. Self-reported diet and physical activity data was collected between August and October 2020 for around 1,000 adults and children which was compared with their diet and activity data obtained at the time of their original NDNS RP interview. Data on food security, financial security and changes in dietary and health-related behaviours since the start of the COVID-19 pandemic in the UK in February 2020 were also collected in this study (but not previously in the NDNS RP) through a web questionnaire with the aim of helping to understand the context for any changes in diet and activity. Participants were also asked to complete 4 online dietary recalls over a 2 to 3 week period to assess their current diet. This was compared with their reported diet when originally assessed in the NDNS RP (on average 2 years 7 months earlier). Adults were also asked to complete a Recent Physical Activity Questionnaire (RPAQ), again to compare with their reported physical activity when originally assessed in the NDNS RP.

Latest edition information

For the second edition (September 2022), the Food Level dietary data file has been replaced with a new version, with the variable 'FoodNumber' added. An Excel format nutrient database has also been added to the study, and the documentation updated accordingly.

The main NDNS study can be found under SN 6533.