Impact of COVID-19 Pandemic on Weight and BMI among UK Adults: A Longitudinal Analysis of Data from the HEBECO Study

  1. Samuel J. Dicken
  2. John J. Mitchell
  3. Jessica Newberry Le Vay
  4. Emma Beard
  5. Dimitra Kale
  6. Aleksandra Herbec
  7. Lion Shahab

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Abstract

COVID-19-related restrictions impacted weight and weight-related factors during the initial months of the pandemic. However, longitudinal analyses are scarce. An online, longitudinal study was conducted among self-selected UK adults (n = 1818), involving three surveys (May–June, August–September, November–December 2020), covering anthropometric, sociodemographic, COVID-19-related and behavioural measures. Data were analysed using generalised estimating equations. Self-reported average weight/body mass index (BMI) significantly increased between the May–June period and the August–September period (74.95 to 75.33 kg/26.22 kg/m2 to 26.36kg/m2, p < 0.001, respectively), and then significantly decreased to November–December (to 75.06 kg/26.27 kg/m2, p < 0.01), comparable to May–June levels (p = 0.274/0.204). However, there was great interindividual variation, 37.0%/26.7% increased (average 3.64 kg (95% confidence interval: 3.32, 3.97)/1.64 kg/m2 (1.49, 1.79)), and 34.5%/26.3% decreased (average 3.59 kg (3.34, 3.85)/1.53 kg/m2 (1.42, 1.63)) weight/BMI between May–June and November–December. Weight/BMI increase was significantly negatively associated with initial BMI, and positively associated with monthly high fat, salt and sugar (HFSS) snacks intake and alcohol consumption, and for BMI only, older age. Associations were time-varying; lower initial BMI, higher HFSS snacks intake and high-risk alcohol consumption were associated with maintaining weight/BMI increases between August–September and November–December. The average weight/BMI of UK adults fluctuated between May–June and November–December 2020. However, the substantial interindividual variation in weight/BMI trajectories indicates long-term health impacts from the pandemic, associated with food and alcohol consumption.

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  1. Version published to 10.3390/nu13092911
  2. ScreenIT

    SciScore for 10.1101/2021.07.10.21259585: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: The study was approved by the Ethics Committee at the UCL Division of Psychology and Language Sciences (CEHP/2020/759).
    Consent: Participants gave their consent prior to data collection.
    Sex as a biological variableExplanatory variables: Sociodemographic variables recorded at baseline included gender (female vs all other), BMI (continuous), age (continuous), ethnicity (white vs all other), occupation and work from home (categorical: unemployed (which includes retired persons and full-time parents/carers), employed and working from home, or employed and not working from home) and a socioeconomic score based on self-reported income, housing tenure and education.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data were captured and managed by the REDCap electronic data system at UCL [26,27].
    REDCap
    suggested: (REDCap, RRID:SCR_003445)
    Statistical Analysis: Statistical analysis was conducted in SPSS Statistics version 27 (IBM).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Strengths and limitations: This study has several strengths. This is the first UK study examining weight change across the first year of the COVID-19 pandemic from May to December 2020. This longitudinal study builds and expands upon the largely cross-sectional literature published to date, providing a greater understanding of the long-term impacts of the pandemic on weight management. The analysis included a range of variables that reflect the wide-ranging impact of the pandemic (including sociodemographics, lifestyle, wellbeing, and health behaviours), and with time-varying measures to reflect the changing conditions of the pandemic over time. An important further contribution of this study is that it assessed the associations of a range of health behaviours relevant to weight management (physical activity, diet, alcohol and smoking). The use of GEE modelling for the longitudinal analysis provided several advantages over typical analytical methods. Finally, the use of both weight and BMI as outcome measures, and complete case analyses and sensitivity analyses with binary cut-offs demonstrating largely consistent associations of baseline BMI, HFSS snacks intake and alcohol consumption with weight/BMI management indicates the robustness of these findings. However, several limitations may have introduced bias. First, the study sample was self-selected, and featured a predominantly female, younger, well-educated cohort. Second, there were differences in ethnic diversity between...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

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  3. Version published to 10.1101/2021.07.10.21259585v1 on medRxiv