Evidence map›Paper›PMID 34956673›Full record

ArticleJournal of obesity2021

Predictors of Weight Loss and Weight Gain in Weight Management Patients during the COVID-19 Pandemic.

Jennifer L Kuk, Rebecca A G Christensen, Elham Kamran Samani, Sean Wharton

Open access · goldAbstract read
In one paragraph

Article in Journal of obesity, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.2field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 16 citations in OpenAlex.

  1. Trial
  2. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Jennifer L KukSchool of Kinesiology and Health Science, York University, Toronto, Canada.ORCID 0000-0002-3425-6149
Rebecca A G ChristensenThe Wharton Medical Clinic, Hamilton, Canada.ORCID 0000-0001-5212-8688
Elham Kamran SamaniThe Wharton Medical Clinic, Hamilton, Canada.ORCID 0000-0001-5432-3487
Sean WhartonSchool of Kinesiology and Health Science, York University, Toronto, Canada.ORCID 0000-0003-0111-1530
York University · CAHamilton Medical Research Group · CAUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To examine the associations between patient struggles, health, and weight management changes during the COVID-19 pandemic. Methods: 585 patients attending a publicly funded clinical weight management program responded to an electronic survey. Results: Over half of the patients reported worsened overall health, mental health, physical activity, or diet during the pandemic. Approximately 30% of patients lost ≥3% of their body weight and 21% gained ≥3% of their body weight between March and July of the pandemic. Reports of social isolation was associated with increased odds for weight loss in women (OR = 2.0, 1.2-3.3), while low motivation (OR = 1.9, 1.0-3.7), depression (OR = 2.5, 1.0-6.3), and struggles with carbohydrate intake (OR = 2.1, 1.0-4.3) were associated with weight gain. Cooking more at home/eating less take out was associated with increased likelihood of weight loss (OR = 2.1, 1.1-3.9) and lower odds for weight gain (OR = 0.2, 0.1 to 0.97). Working from home was not associated with weight loss or weight gain ( Conclusion: The COVID-19 pandemic is associated with certain factors that may facilitate weight loss and other factors that promote weight gain. Thus, depending on the patient experience during the pandemic, prevention of weight gain may be more appropriate than weight loss.

Indexed as

COVID-19PandemicsFemaleHumansSARS-CoV-2Weight GainWeight Loss

Identifiers

PMID34956673
PMCPMC8709769
OpenAlexW4200010071

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.