PONE-D-23-02121The impacts of social restrictions during the COVID-19 pandemic on the physical activity levels of over 50-year olds: the CHARIOT COVID-19 Rapid Response (CCRR) cohort studyPLOS ONE

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“I have read the journal's policy and the authors of this manuscript have the following competing interests: Sara Ahmadi-Abhari declares funding from EIT-health for a brain ageing PhD school programme, and is an unpaid advisor for small-sized chronic care management start-up (Medsien);  Chi Udeh-Momoh declares: funding from a project grant funding consortia that included Janssen R&D, Gates Foundation, Merck and Takeda, a project grant from RoseTrees Foundation Trust and a project grant from Alzheimers Research UK; funding for a speaking engagement at the Lausanne IX workshop, an engagement at the Meeting of the Minds Neuroscience Conference, and was an invited speaker at the Reserve in Dementia Conference; is a scientific advisor at the Brain and Mind Institute, Aga Khan University, Nairobi; and is an unpaid executive committee member at Biofluids-based Biomarker Professional Interest Area for iSTAART, and a board of trustee member for the British Society for Neuroendocrinology; Lefkos T. Middleton reports research funding from Janssen, Novartis, Merck and Takeda, outside the submitted work and had unpaid leadership roles at the Clinical Trials in Alzheimer’s Disease (CTAD) executive committee, WW FINGERS, and the European Consortium of Alzheimer’s Disease; Celeste A. de Jager Loots received a 1-year research contract from the Foundations FINGERS Brain Health Institute, Sweden which contributed to her salary, and receives annual payments from the MCI and B Vitamin project from the University of Oxford, and has an unpaid advisory role membership at foodforthebrain.org; David Salman is funded by an Imperial College and National Institute of Health Research (NIHR) Biomedical Research Centre (BRC) fellowship, and is an unpaid advisory board member for the Primary Care Rheumatology and Musculoskeletal Medicine society (PCRMM). All authors have have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf.”

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Additional Editor Comments:

Dear Dr. Salman,

I have now received two expert reviews for your submitted manuscript. Both reviewers commend the large sample size but also raise significant concerns that should be addressed. I fully agree with their assessment that more information should be provided on how MET was calculated and that the models right now are not precisely described. An explicit model description providing the actual lmer specifications is necessary for the readers to understand what was calculated. While reading the manuscript, I also noted that your assessment of loneliness is rather unusual by asking one month in retrospect how participants rated their loneliness. A more common approach would be to use a dedicated questionnaire like the UCLA loneliness scale which provides a numeric and metric scale. Your questionnaire has ordinal properties as the difference between sometimes and never might not be equal compared to sometimes and often etc. This makes a linear model a strong assumption given that the predictor might not be linear and could represent an exponential increase in loneliness. The authors should consider using generalized linear mixed models with different specifications to check if treating loneliness as a linear predictor provides the best model fit. This kind of assessment should also be listed as a limitation. Furthermore, as reviewer 2 notes, high power also requires qualification of significant vs. meaningful. The authors could use Bayesian models using the brms and bayestestR packages to check for evidence in favor or against the null hypothesis in addition to frequentist statistics.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: I Don't Know

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: No

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors investigate the associations of self-reported loneliness and shielding at the beginning of the COVID-19 pandemic and self-reported physical activity (PA) in the course of the pandemic in a large sample of cognitively healthy adults 50 years and older in the UK. Participants were grouped according to loneliness and shielding at the beginning of the study, and linear mixed effects models were employed to investigate the associations of these predictors with MET minutes, the employed physical activity measure. Results indicate that participants feeling lonely often and/or were shielding at baseline showed less MET minutes than those feeling never lonely or not shielding. These associations diminished when including health and lifestyle factors, such as BMI, health conditions, and relationship status. With their paper, especially due to the large sample size, the authors make a scientific contribution to understanding the associations of physical (in)activity and loneliness/social isolation in (older) adults, which might inform future prevention targets.

Still, I have some comments and suggestions for the authors:

Major comments:

- There seems to be a mismatch of the number of surveys depicted in Fig. 1, Table 1, and the text: On p. 9 it says baseline + 5 surveys, in Figure 1, however, there are seven survey waves in total. In Table 1 it says that the final survey was on 08/05/21, whereas Fig. 1 indicates surveys on 08/03/21 and 08/06/21. So perhaps you could streamline the figure with the text and table?

- Further, I noticed in Fig. 1 that the surveys were done under varying restrictions: Did you take a look whether it had an impact on your analyses if surveys were done under lockdown or eased restrictions?

- Perhaps you could also explain some more how exactly MET minutes are calculated? Is it all minutes > 1 MET? Since you used the IPAQ I assume that it’s only minutes > 3 MET? I.e., only minutes for vigorous or moderate physical activity or walking (measured by the IPAQ)? Further, is it simply a sum of minutes or is the intensity (i.e., the difference in MET for, e.g., walking vs. MVPA) somehow reflected in the score? For me, the term “MET minutes” is simply a bit confusing as all activities (i.e., also lying quietly) have a certain MET, which also depends on the individual, and it is probably difficult to assess all activities and associated METs based on survey data, so perhaps you could clarify the scores some more and discuss its limitations? Perhaps you could also give an example of what 1 MET minute represents?

- I am not quite sure about your dependent PA variable: Is it all PA surveys? I.e., baseline and the 5/6 follow-ups? And is it absolute PA values or changes in PA? From your methods and results section, I understand that it is absolute PA values (i.e., MET minutes per person per survey wave), in the Limitations (and Figure descriptions), however, you state that you measured changes in PA instead of absolute levels? Perhaps you could clarify this?

- Models: PA ~ loneliness + (1|participant) Is this the correct univariable model equation? I.e., there is no time variable indicating how much time has passed since baseline/loneliness assessment? Did you check whether time has an impact?

- How does the random intercept “allow[ed] for differing baseline (pre-pandemic) PA levels”? (p. 10) Are (retrospective) pre-pandemic PA levels also included in the univariable model?

- Missings of BMI: According to Table 2, BMI is missing for 66.7% of the participants, according to the text it’s 70.1%. Either way, I am wondering how missings impact Models 2 and 3. Perhaps you could include in S3 how many observations and participants were included in each model? Also, you might include the coefficients for the covariates? Then it might be easier to retrace model equations etc.

- I am also wondering whether you included loneliness and shielding in one model and took a look at the incremental effects?

Minor comments:

- 4.2: „Those who were „often lonely” at the onset of COVID-19 restrictions completed significantly less PA per week over the …”, “per” missing?

- 2.2: “whether the participant was living alone (yes no)”, p. 10 “/” missing

- P. 18: “Therefore, the negative health consequences of the pandemic will have longer term effects and impact beyond direct morbidity and mortality attributable to COVID-19” – perhaps be more careful and use “might”? After all, loneliness was only assessed at the beginning of the pandemic and loneliness and PA might have a bidirectional association or an association independent from the COVID pandemic?

- P 19. “However, these limitations are largely due to the fact that loneliness is subjective” “that” missing

- P. 19 “This may have been over- or under-estimated.” “these”?

Reviewer #2: The authors study a topic of high societal relevance and the strengths of the investigation include a large data set, however, the retrospective methods used limit the evidence and especially the statistics and its interpretation remain non-transparent to me.

Major comments:

1. The authors use multi level modelling, but it remains non-transparent whether they investigate a) within-person changes (e.g., PA changes from baseline to pandemic), or b) between-person changes (e.g., differences in PA between participants at baseline/or in pandemic conditions), or c) an interaction of both. This I could not detect neither from the methods/stats description nor the results section wording. To make this clear to readers I would suggests the authors to describe the multi level used in very detail, including the model equations. Moreover, I would suggest to carefully indicate whether this is focusing, within-, between-person change or both throughout the manuscript, also in the results and discussion parts.

2. The large sample size comes with high power and thus favors to significant findings. Therefore, I would suggest the authors to additionally report standardized effect sizes, and/or unstandardized ones, such as changes in MET minutes in relation to the MET intercept if all other predictors are kept zero. This can help to interpret practical relevance of findings. Related to this, absolute MET minutes per week should be included into the abstract, too.

3. BMI data was only available for about 1/4 of your sample. Co-variate models were non-significant. This was interpreted as a co-founding issue. Which role would you assign to the missing BMI data – May this be another interpretation for the non-significance?

4. Figures 2 and 3 appear to have the very similar content to me – did there potentially anything mix up?

5. Limitations, first point: One could also argue that this limitation is rather more critical when looking at changes compared to looking at absolute values since the range is smaller and low reliability matters more. I would suggest to rephrase.

Minor comments:

6. For readers not familiar with MET minutes I would suggest to introduce this parameter in details, e.g., stating current norms, recommendations etc..

7. For reliability of retrospective PA and loneliness questionnaires, I would suggest to at least include a detailed discussion how accelerometry and momentary social contact ratings on electronic diaries could make measurements more reliable. The following resources may guide this: https://www.sciencedirect.com/science/article/abs/pii/S146902921930809X?via%3Dihub; https://pubmed.ncbi.nlm.nih.gov/32831643/

8. I would suggest to include a frequency table on the distribution of loneliness and contact ratings.

9. page 18: “the pandemic will have” – this is not proven, suggest to use “may”

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Reviewer #1: No

Reviewer #2: No

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The impacts of social restrictions during the COVID-19 pandemic on the physical activity levels of over 50-year olds: the CHARIOT COVID-19 Rapid Response (CCRR) cohort study

PONE-D-23-02121R1

Dear Dr. Salman,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Julian Packheiser

Academic Editor

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Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: (No Response)

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Reviewer #1: No

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