Weight trends amongst adults with diabetes or hypertension during the COVID-19 pandemic: an observational study using OpenSAFELY.

Body Mass Index (BMI) Coronavirus 19 (COVID 19) Health inequalities Hypertension Primary Health Care Type 2 diabetes

Journal

The British journal of general practice : the journal of the Royal College of General Practitioners
ISSN: 1478-5242
Titre abrégé: Br J Gen Pract
Pays: England
ID NLM: 9005323

Informations de publication

Date de publication:
08 Feb 2024
Historique:
received: 19 09 2023
accepted: 16 01 2024
medline: 1 2 2024
pubmed: 1 2 2024
entrez: 31 1 2024
Statut: aheadofprint

Résumé

COVID-19 pandemic restrictions may have influenced behaviours related to weight. To describe patterns of weight change amongst adults living in England with Type 2 Diabetes (T2D) and/or hypertension during the COVID-19 pandemic. Design and Setting With the approval of NHS England, we conducted an observational cohort study using the routinely collected health data of approximately 40% of adults living in England, accessed through the OpenSAFELY service inside TPP. We investigated clinical and sociodemographic characteristics associated with rapid weight gain (>0·5kg/m We extracted data on adults with T2D (n=1,231,455, 44% female, 76% white British) or hypertension (n=3,558,405, 50% female, 84% white British). Adults with T2D lost weight overall (median δ = -0.1kg/m2/year [IQR: -0.7, 0.4]), however, rapid weight gain was common (20.7%) and associated with sex (male vs female: aOR 0.78[95%CI 0.77, 0.79]); age, older age reduced odds (e.g. 60-69-year-olds vs 18-29-year-olds: aOR 0.66[0.61, 0.71]); deprivation, (least-deprived-IMD vs most-deprived-IMD: aOR 0.87[0.85, 0.89]); white ethnicity (Black vs White: aOR 0.95[0.92, 0.98]); mental health conditions (e.g. depression: aOR 1.13 [1.12, 1.15]); and diabetes treatment (non-insulin treatment vs no pharmacological treatment: aOR 0.68[0.67, 0.69]). Adults with hypertension maintained stable weight overall (median δ = 0.0kg/m2/year [ -0.6, 0.5]), however, rapid weight gain was common (24.7%) and associated with similar characteristics as in T2D. Amongst adults living in England with T2D and/or hypertension, rapid pandemic weight gain was more common amongst females, younger adults, those living in more deprived areas, and those with mental health condition.

Sections du résumé

BACKGROUND BACKGROUND
COVID-19 pandemic restrictions may have influenced behaviours related to weight.
AIMS OBJECTIVE
To describe patterns of weight change amongst adults living in England with Type 2 Diabetes (T2D) and/or hypertension during the COVID-19 pandemic. Design and Setting With the approval of NHS England, we conducted an observational cohort study using the routinely collected health data of approximately 40% of adults living in England, accessed through the OpenSAFELY service inside TPP.
METHOD METHODS
We investigated clinical and sociodemographic characteristics associated with rapid weight gain (>0·5kg/m
RESULTS RESULTS
We extracted data on adults with T2D (n=1,231,455, 44% female, 76% white British) or hypertension (n=3,558,405, 50% female, 84% white British). Adults with T2D lost weight overall (median δ = -0.1kg/m2/year [IQR: -0.7, 0.4]), however, rapid weight gain was common (20.7%) and associated with sex (male vs female: aOR 0.78[95%CI 0.77, 0.79]); age, older age reduced odds (e.g. 60-69-year-olds vs 18-29-year-olds: aOR 0.66[0.61, 0.71]); deprivation, (least-deprived-IMD vs most-deprived-IMD: aOR 0.87[0.85, 0.89]); white ethnicity (Black vs White: aOR 0.95[0.92, 0.98]); mental health conditions (e.g. depression: aOR 1.13 [1.12, 1.15]); and diabetes treatment (non-insulin treatment vs no pharmacological treatment: aOR 0.68[0.67, 0.69]). Adults with hypertension maintained stable weight overall (median δ = 0.0kg/m2/year [ -0.6, 0.5]), however, rapid weight gain was common (24.7%) and associated with similar characteristics as in T2D.
CONCLUSION CONCLUSIONS
Amongst adults living in England with T2D and/or hypertension, rapid pandemic weight gain was more common amongst females, younger adults, those living in more deprived areas, and those with mental health condition.

Identifiants

pubmed: 38296356
pii: BJGP.2023.0492
doi: 10.3399/BJGP.2023.0492
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024, The Authors.

Auteurs

Miriam Samuel (M)

Queen Mary University of London, Wolfson Institute of Population Health, London, United Kingdom m.samuel@qmul.ac.uk.

Robin Y Park (RY)

Oxford University, Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford, United Kingdom.

Sophie V Eastwood (SV)

UCL, London, United Kingdom.

Fabiola Eto (F)

Queen Mary University of London, Wolfson Institute of Population Health, London, United Kingdom.

Caroline E Morton (CE)

Queen Mary University of London, Wolfson Institute of Population Health, London, United Kingdom.

Daniel Stow (D)

Queen Mary University of London, Wolfson Institute of Population Health, London, United Kingdom.

Sebastian Cj Bacon (SC)

Oxford University, Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford, United Kingdom.

Ben Goldacre (B)

Oxford University, Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford, United Kingdom.

Amir Mehrkar (A)

Oxford University, Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford, United Kingdom.

Jessica Morley (J)

Oxford University, Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford, United Kingdom.

Iain Dillingham (I)

Oxford University, Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford, United Kingdom.

Peter Inglesby (P)

Oxford University, Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford, United Kingdom.

William J Hulme (WJ)

Oxford University, Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford, United Kingdom.

Kamlesh Khunti (K)

University of Leicester, Leicester Diabetes Centre, Leicester General Hospital, Leicester, United Kingdom.

Rohini Mathur (R)

Queen Mary University of London, Wolfson Institute of Population Health, London, United Kingdom.

Jonathan Valabhji (J)

Imperial College London, Division of Metabolism, Digestion and Reproduction, London, United Kingdom.

Brian MacKenna (B)

Oxford University, Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, Oxford, United Kingdom.

Sarah Finer (S)

Queen Mary University of London, Wolfson Institute of Population Health, London, United Kingdom.

Classifications MeSH