The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
COVID‐19–Related School Closings and Risk of Weight Gain Among Children
Open accessAbstract
The coronavirus disease 2019 (COVID-19) pandemic is causing substantial morbidity and mortality, straining health care systems, shutting down economies, and closing school districts. While it is a priority to mitigate its immediate impact, we want to call attention to the pandemic's longer-term effect on children's health; COVID-19, via these school closures, may exacerbate the epidemic of childhood obesity and increase disparities in obesity risk. In many areas of the United States, the COVID-19 pandemic has closed schools, and some of these school systems are not expected to reopen this school year. The experiences in Hong Kong, Taiwan, and Singapore suggest that social distancing orders, if lifted after short periods, will have to be periodically reinstated to control COVID-19 flare-ups (1). In short, we anticipate that the COVID-19 pandemic will likely double out-of-school time this year for many children in the United States and will exacerbate the risk factors for weight gain associated with summer recess.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Franckle, R., Adler, R., & Davison, K. (2014) · Preventing Chronic Disease · doi:10.5888/pcd11.130355 · Cited by 230
Cited by
Popkin, B. M., Du, S., Green, W. D., Beck, M. A., Algaith, T., Herbst, C. H., Alsukait, R. F., Alluhidan, M., Alazemi, N., & Shekar, M. (2020) · Obesity Reviews · doi:10.1111/obr.13128 · Cited by 1,150
Dunton, G. F., Do, B., & Wang, S. D. (2020) · BMC Public Health · doi:10.1186/s12889-020-09429-3 · Cited by 916
Impact of COVID -19 on children: special focus on the psychosocial aspect
Ghosh, R., Dubey, M. J., Chatterjee, S., & Dubey, S. (2020) · Minerva Pediatrica · doi:10.23736/s0026-4946.20.05887-9 · Cited by 601
Pellegrini, M., Ponzo, V., Rosato, R., Scumaci, E., Goitre, I., Benso, A., Belcastro, S., Crespi, C., De Michieli, F., Ghigo, E., et al. (2020) · Nutrients · doi:10.3390/nu12072016 · Cited by 538
Prevalence of Depression, Anxiety, and Stress during COVID-19 Pandemic
Lakhan, R., Agrawal, A., & Sharma, M. (2020) · Journal of Neurosciences in Rural Practice · doi:10.1055/s-0040-1716442 · Cited by 421
Metadata
- Authors
- Rundle, A. G., Park, Y., Herbstman, J. B., Kinsey, E. W., & Wang, Y. C.
- Venue
- Obesity
- Publisher
- Wiley
- Published
- 2020-04-18
- Volume
- 28
- Issue
- 6
- Pages
- 1008-1009
- ISSN
- 1930-7381 (ISSN-L)
- 1930-739X
- OpenAlex
- W3013267885
- Cited by
- 827
- References
- 1
- FWCI
- 126.49
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
