The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Obesity and COVID-19 Severity in a Designated Hospital in Shenzhen, China
Abstract
OBJECTIVE: Patients with obesity are at increased risk of exacerbations from viral respiratory infections. However, the association of obesity with the severity of coronavirus disease 2019 (COVID-19) is unclear. We examined this association using data from the only referral hospital in Shenzhen, China. RESEARCH DESIGN AND METHODS: A total of 383 consecutively hospitalized patients with COVID-19 admitted from 11 January 2020 to 16 February 2020 and followed until 26 March 2020 at the Third People’s Hospital of Shenzhen were included. Underweight was defined as a BMI <18.5 kg/m2, normal weight as 18.5–23.9 kg/m2, overweight as 24.0–27.9 kg/m2, and obesity as ≥28 kg/m2. RESULTS: Of the 383 patients, 53.1% were normal weight, 4.2% were underweight, 32.0% were overweight, and 10.7% were obese at admission. Obese patients tended to have symptoms of cough (P = 0.03) and fever (P = 0.06) compared with patients who were not obese. Compared with normal weight patients, those who were overweight had 1.84-fold odds of developing severe COVID-19 (odds ratio [OR] 1.84, 95% CI 0.99–3.43, P = 0.05), while those who were obese were at 3.40-fold odds of developing severe disease (OR 3.40, 95% CI 1.40–2.86, P = 0.007), after adjusting for age, sex, epidemiological characteristics, days from disease onset to hospitalization, presence of hypertension, diabetes, cardiovascular disease, chronic obstructive pulmonary disease, liver disease, and cancer, and drug used for treatment. Additionally, after similar adjustment, men who were obese versus those who were normal weight were at increased odds of developing severe COVID-19 (OR 5.66, 95% CI 1.80–17.75, P = 0.003). CONCLUSIONS: In this study, obese patients had increased odds of progressing to severe COVID-19. As the severe acute respiratory syndrome coronavirus 2 may continue to spread worldwide, clinicians should pay close attention to obese patients, who should be carefully managed with prompt and aggressive treatment.
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
Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., Qiu, Y., Wang, J., Liu, Y., Wei, Y., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30211-7 · Cited by 21,415
Self-citationWu, Z., & McGoogan, J. M. (2020) · JAMA · doi:10.1001/jama.2020.2648 · Cited by 17,016
(2004) · The Lancet · doi:10.1016/s0140-6736(03)15268-3 · Cited by 12,717
Presumed Asymptomatic Carrier Transmission of COVID-19
Bai, Y., Yao, L., Wei, T., Tian, F., Jin, D.-Y., Chen, L., & Wang, M. (2020) · JAMA · doi:10.1001/jama.2020.2565 · Cited by 4,498
Metlay, J. P., Waterer, G. W., Long, A. C., Anzueto, A., Brozek, J., Crothers, K., Cooley, L. A., Dean, N. C., Fine, M. J., Flanders, S. A., et al. (2019) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201908-1581st · Cited by 3,657
Treatment of 5 Critically Ill Patients With COVID-19 With Convalescent Plasma
Shen, C., Wang, Z., Zhao, F., Yang, Y., Li, J., Yuan, J., Wang, F., Li, D., Yang, M., Xing, L., et al. (2020) · JAMA · doi:10.1001/jama.2020.4783 · Cited by 2,277
Self-citationLiu, Y., Yang, Y., Zhang, C., Huang, F., Wang, F., Yuan, J., Wang, Z., Li, J., Li, J., Feng, C., et al. (2020) · Science China Life Sciences · doi:10.1007/s11427-020-1643-8 · Cited by 2,031
Self-citationWorld Health Organization (2020) · Pediatria i Medycyna Rodzinna · doi:10.15557/pimr.2020.0003 · Cited by 1,329
Defining the Epidemiology of Covid-19 — Studies Needed
Lipsitch, M., Swerdlow, D. L., & Finelli, L. (2020) · New England Journal of Medicine · doi:10.1056/nejmp2002125 · Cited by 1,248
Characteristics of COVID-19 infection in Beijing
Tian, S., Hu, N., Lou, J., Chen, K., Kang, X., Xiang, Z., Chen, H., Wang, D., Liu, N., Liu, D., et al. (2020) · Journal of Infection · doi:10.1016/j.jinf.2020.02.018 · Cited by 1,231
Research works printed but not linked: 5
- Cai, Characteristics of liver tests in COVID-19 patients, J Hepatol
- Huang, Application and effects of fever screening system in the prevention of nosocomial infection in the only designated hospital of coronavirus disease 2019 (COVID-19) in Shenzhen, China, Infect Control Hosp Epidemiol
- Wang, Clinical outcome of 55 asymptomatic cases at the time of hospital admission infected with SARS-Coronavirus-2 in Shenzhen, China, J Infect Dis
- Yuan, PCR assays turned positive in 25 discharged COVID-19 patients, Clin Infect Dis
- Zhao, Early virus clearance and delayed antibody response in a case of COVID-19 with a history of co-infection with HIV-1 and HCV, Clin Infect Dis
Cited by
Heart Disease and Stroke Statistics—2022 Update: A Report From the American Heart Association
Tsao, C. W., Aday, A. W., Almarzooq, Z. I., Alonso, A., Beaton, A. Z., Bittencourt, M. S., Boehme, A. K., Buxton, A. E., Carson, A. P., Commodore-Mensah, Y., et al. (2022) · Circulation · doi:10.1161/cir.0000000000001052 · Cited by 5,987
Clinical Characteristics of Covid-19 in New York City
Goyal, P., Choi, J. J., Pinheiro, L. C., Schenck, E. J., Chen, R., Jabri, A., Satlin, M. J., Campion, T. R., Nahid, M., Ringel, J. B., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmc2010419 · Cited by 2,234
Alterations in Gut Microbiota of Patients With COVID-19 During Time of Hospitalization
Zuo, T., Zhang, F., Lui, G. C. Y., Yeoh, Y. K., Li, A. Y. L., Zhan, H., Wan, Y., Chung, A. C. K., Cheung, C. P., Chen, N., et al. (2020) · Gastroenterology · doi:10.1053/j.gastro.2020.05.048 · Cited by 1,537
Gandhi, R. T., Lynch, J. B., & del Rio, C. (2020) · New England Journal of Medicine · doi:10.1056/nejmcp2009249 · Cited by 1,307
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
Metadata
- Authors
- Cai, Q., Chen, F., Wang, T., Luo, F., Liu, X., Wu, Q., He, Q., Wang, Z., Liu, Y., Liu, L., Chen, J., & Xu, L.
- Venue
- Diabetes Care
- Publisher
- American Diabetes Association
- Published
- 2020-05-14
- Volume
- 43
- Issue
- 7
- Pages
- 1392-1398
- ISSN
- 0149-5992 (ISSN-L)
- 1935-5548
- OpenAlex
- W3014364276
- Cited by
- 706
- References
- 36
- FWCI
- 19.31
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Obesity and COVID-19 Severity in a Designated Hospital in Shenzhen, China. https://app.cochat.ai/papers/10.2337/dc20-0576
- The paper
- Cai, Q., Chen, F., Wang, T., Luo, F., Liu, X., Wu, Q., He, Q., Wang, Z., Liu, Y., Liu, L., Chen, J., & Xu, L. (2020). Obesity and COVID-19 Severity in a Designated Hospital in Shenzhen, China. Diabetes Care. https://doi.org/10.2337/dc20-0576
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.