Non-communicable diseases, sociodemographic vulnerability and the risk of mortality in hospitalised children and adolescents with COVID-19 in Brazil: a cross-sectional observational study

  1. Braian Lucas Aguiar Sousa
  2. Alexandra Brentani
  3. Cecilia Claudia Costa Ribeiro
  4. Marisa Dolhnikoff
  5. Sandra Josefina Ferraz Ellero Grisi
  6. Ana Paula Scoleze Ferrer
  7. Alexandre Archanjo Ferraro

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Abstract

To analyse how previous comorbidities, ethnicity, regionality and socioeconomic development are associated with COVID-19 mortality in hospitalised children and adolescents.

Design

Cross-sectional observational study using publicly available data from the Brazilian Ministry of Health.

Setting

Nationwide.

Participants

5857 patients younger than 20 years old, all of them hospitalised with laboratory-confirmed COVID-19, from 1 January 2020 to 7 December 2020.

Main outcome measure

We used multilevel mixed-effects generalised linear models to study in-hospital mortality, stratifying the analysis by age, region of the country, presence of non-communicable diseases, ethnicity and socioeconomic development.

Results

Individually, most of the included comorbidities were risk factors for mortality. Notably, asthma was a protective factor (OR 0.4, 95% CI 0.24 to 0.67). Having more than one comorbidity increased almost tenfold the odds of death (OR 9.67, 95% CI 6.89 to 13.57). Compared with white children, Indigenous, Pardo (mixed) and East Asian had significantly higher odds of mortality (OR 5.83, 95% CI 2.43 to 14.02; OR 1.93, 95% CI 1.48 to 2.51; OR 2.98, 95% CI 1.02 to 8.71, respectively). We also found a regional influence (higher mortality in the North—OR 3.4, 95% CI 2.48 to 4.65) and a socioeconomic association (lower mortality among children from more socioeconomically developed municipalities—OR 0.26, 95% CI 0.17 to 0.38)

Conclusions

Besides the association with comorbidities, we found ethnic, regional and socioeconomic factors shaping the mortality of children hospitalised with COVID-19 in Brazil. Our findings identify risk groups among children that should be prioritised for public health measures, such as vaccination.

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  1. Version published to 10.1136/bmjopen-2021-050724
  2. ScreenIT

    SciScore for 10.1101/2021.02.11.21251591: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our study had several limitations. Our analysis relied on secondary data, with case ascertainment bias being a possibility. There was also a high rate of missingness for ethnicity, which could imbalance the results if the missingness was differential for some groups, but no evidence was found in literature to support this hypothesis. Ethnicity was defined on the basis of self-declared skin color or appearance, rather than ancestry, and there’s a significant overlap between the Pardo and Black categories. Underreporting is also an issue, especially in less advantageous socioeconomic contexts, which might have underestimated the effect size in our models. As for the SES analysis, using municipality development as a proxy for socioeconomic status can hide major discrepancies within each city, especially in large metropolises. We were not able to fully address healthcare availability by ethnicity, socioeconomic status, and region, since our analysis was restricted to children only. Noticeably, the GeoSES index does not include a health component in its dimensions.18 Therefore, the different levels of socioeconomic status derived from the index do not cover health access or morbidity and mortality risks. We didn’t have data on out-of-hospital mortality, which might be substantial especially in lower socioeconomic settings, possibly resulting in an underestimation of the pandemic effect in these settings. In conclusion, we have described how the presence of NCDs and sociodemographi...

    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.

    About SciScore

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  3. Version published to 10.1101/2021.02.11.21251591v1 on medRxiv