Background We investigated which clinical and sociodemographic characteristics were associated with unhealthy patterns of weight gain amongst adults living in England during the pandemic. Methods With the approval of NHS England we conducted an observational cohort study of Body Mass Index (BMI) changes between March 2015 and March 2022 using the OpenSAFELY–TPP platform. We estimated individual rates of weight gain before and during the pandemic, and identified individuals with rapid weight gain (>0.5kg/m2/year) in each period. We also estimated the change in rate of weight gain between the prepandemic and pandemic period and defined extreme-accelerators as the ten percent of individuals with the greatest increase (>1.84kg/m2/year). We estimated associations with these outcomes using multivariate logistic regression. Findings We extracted data on 17,742,365 adults (50.1% female, 76.1% White British). Median BMI increased from 27.8kg/m2[IQR:24.3 to 32.1] in 2019 (March 2019 to February 2020) to 28.0kg/m2 [24.4 to 32.6] in 2021. Rapid pandemic weight gain (n=3,214,155) was associated with female sex (male vs female: aOR 0.76 [95%CI:0.76 to 0.76]); younger age (50 to 59 years vs 18 to 29 years: aOR 0.60 [0.60 to 0.61]); White British ethnicity (Black Caribbean vs White British: aOR 0.91 [0.89 to 0.94]); deprivation (least–deprived–IMD–quintile vs most–deprived:aOR 0.77 [0.77 to 0.78]); and long-term conditions, of which mental health conditions had the greatest effect (e.g. depression (aOR 1.18[1.17 to 1.18])). Similar characteristics increased risk of extreme acceleration (n=2,768,695). Interpretation We found female sex, younger age, deprivation and mental health conditions increased risk of unhealthy patterns of pandemic weight gain. This highlights the need to incorporate sociodemographic, physical, and mental health characteristics when formulating post-pandemic research, policies, and interventions targeting BMI. Funding NIHR

MS salary costs have been supported through a National Institute for Health and Care Research (NIHR) funded academic clinical fellowship in primary care and NIHR grant funding (NIHR AI-MULTIPLY Consortium NIHR203982). RYP is supported by the EPSRC Centre for Doctoral Training in Health Data Science (EP/S02428X/1). RYP was previously employed as a data scientist for the Bennet Institute which is funded by grants from the Bennett Foundation, Wellcome Trust, NIHR Oxford Biomedical Research Centre, NIHR Applied Research Collaboration Oxford and Thames Valley, Mohn-Westlake Foundation. SVE is funded by a Diabetes UK Sir George Alberti research training fellowship (grant number: 17/0005588). FE salary cost is supported by MRC (MR/S027297/1). DS is funded by the NIHR (NIHR203982). AM is a senior clinical researcher at the University of Oxford in the Bennett Institute, which is funded by grants from the Bennett Foundation, Wellcome Trust, NIHR Oxford Biomedical Research Centre, NIHR Applied Research Collaboration Oxford and Thames Valley, Mohn-Westlake Foundation. AM has consulted for https://inductionhealthcare.com/. AM is a member of the RCGP health informatics group and the NHS Digital GP data Professional Advisory Group that advises on access to GP Data for Pandemic Planning and Research (GDPPR); payment direct to me for the GDPPR role. RM is supported by Barts Charity (MGU0504). JV is National Clinical Director for Diabetes & Obesity at NHS England. BMK is also employed by NHS England. KK is supported by the National Institute for Health Research (NIHR) Applied Research Collaboration East Midlands (ARC EM) and the NIHR Leicester Biomedical Research Centre (BRC). KK has acted as a consultant, speaker or received grants for investigator-initiated studies for Astra Zeneca, Bayer, Novartis, Novo Nordisk, Sanofi-Aventis, Lilly and Merck Sharp & Dohme, Boehringer Ingelheim, Oramed Pharmaceuticals, Roche and Applied Therapeutics. SF has received grants from the NIHR (NIHR 31672, NIHR 202635) and MRC (MR/W014416/1, MR/V004905/1, MR/S027297/1). SF, RM, CM are part of the Genes & Health programme, which is part-funded (including salary contributions) by a Life Sciences Consortium comprising Astra Zeneca PLC, Bristol-Myers Squibb Company, GlaxoSmithKline Research and Development Limited, Maze Therapeutics Inc, Merck Sharp & Dohme LLC, Novo Nordisk A/S, Pfizer Inc, Takeda Development Centre Americas Inc. This research used data assets made available as part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant ref MC_PC_20058). In addition, the OpenSAFELY Platform is supported by grants from the Wellcome Trust (222097/Z/20/Z); MRC (MR/V015757/1, MC_PC-20059, MR/W016729/1); NIHR (NIHR135559, COV-LT2-0073), and Health Data Research UK (HDRUK2021.000, 2021.0157).

This study was undertaken by MS as part of her National Institute of Health Care Research (NIHR) funded academic clinical fellowship in primary care. There was no other direct funding for this analysis.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The London School of Hygiene & Tropical Medicine Ethics Board (reference 26536)gave ethical approval for this work

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

All data were linked, stored and analysed securely within the OpenSAFELY-TPP platform, https://opensafely.org/, containing pseudonymised data on approximately 40% of the English population, including coded diagnoses, medications and physiological parameters. No free text data are included. Detailed pseudonymised patient data is potentially re-identifiable and therefore not shared. All code for data management and analysis, as well as codelists is shared openly for review and re-use under MIT open license, available at https://github.com/opensafely/BMI-and-Metabolic-Markers.

https://github.com/opensafely/BMI-and-Metabolic-Markers