Sociodemographic inequalities and excess non-COVID-19 mortality during the COVID-19 pandemic: A data-driven analysis of 1,069,174 death certificates in Mexico

  1. Neftali Eduardo Antonio-Villa
  2. Carlos A. Fermín-Martínez
  3. José Manuel Aburto
  4. Luisa Fernández-Chirino
  5. Daniel Ramírez-García
  6. Julio Pisanty-Alatorre
  7. Armando González-Díaz
  8. Arsenio Vargas-Vázquez
  9. Jacqueline A. Seiglie
  10. Simón Barquera
  11. Luis Miguel Gutiérrez-Robledo
  12. Omar Yaxmehen Bello-Chavolla

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

BACKGROUND

In 2020, Mexico experienced one of the highest rates of excess mortality globally. However, the extent to which non-COVID deaths contributed to excess mortality, its regional characterization, and the association between municipal-and individual-level sociodemographic inequality has not been characterized.

METHODS

We conducted a retrospective municipal an individual-level study using death certificate data in Mexico from 2016-2020. We analyzed mortality related to COVID-19 and to non-COVID-19 causes using ICD-10 codes to identify cause-specific mortality. Excess mortality was estimated as the increase in deaths in 2020 compared to the average of 2016-2019, disaggregated by primary cause of death, death setting (in-hospital and out-of-hospital) and geographical location. We evaluated correlates of non-COVID-19 mortality at the individual level using mixed effects logistic regression and correlates of non-COVID-19 excess mortality in 2020 at the municipal level using negative binomial regression.

RESULTS

We identified 1,069,174 deaths in 2020 (833.5 per 100,000 inhabitants), which was 49% higher compared to the 2016-2019 average (557.38 per 100,000 inhabitants). Overall excess mortality (276.11 deaths per 100,000 inhabitants) was attributable in 76.1% to COVID-19; however, non-COVID-19 causes comprised one-fifth of excess deaths. COVID-19 deaths occurred primarily in-hospital, while excess non-COVID-19 deaths decreased in this setting and increased out-of-hospital. Excess non-COVID-19 mortality displayed geographical heterogeneity linked to sociodemographic inequalities with clustering in states in southern Mexico. Municipal-level predictors of non-COVID-19 excess mortality included levels of social security coverage, higher rates of COVID-19 hospitalization, and social marginalization. At the individual level, lower educational attainment, blue collar workers, and lack of medical care assistance were associated with non-COVID-19 mortality during 2020.

CONCLUSION

Non-COVID-19 causes of death, largely chronic cardiometabolic conditions, comprised up to one-fifth of excess deaths in Mexico during 2020. Non-COVID-19 excess deaths occurred disproportionately out-of-hospital and were associated with both individual-and municipal-level sociodemographic inequalities. These findings should prompt an urgent call to action to improve healthcare coverage and access to reduce health and sociodemographic inequalities in Mexico to reduce preventable mortality in situations which increase the stress of healthcare systems, including the ongoing COVID-19 pandemic.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2022.05.12.22274973: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    RandomizationFor this model, we used the municipality of death occurrence as a random intercept to account for intermunicipal variability in death registration in the model and to establish a hierarchical relationship between individual and municipal-level variables.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our study has some strengths and limitations. Amongst the strengths, we highlight the use of 1,069,174 nationwide mortality registries to compare all-cause and cause-specific excess mortality during the COVID-19 pandemic in Mexico in 2020. This approach allowed us to estimate with higher confidence state and municipal-level excess morality rates that helped us to study the regional impact of the COVID-19 pandemic and identify vulnerable zones in Mexico which were especially affected during 2020 compared to previous years. Additionally, the use of sociodemographic variables at different levels gave us insights to evaluate municipal and individual-level determinants which shaped excess and non-COVID-19 mortality. Nevertheless, limitations to be acknowledged include the lack of specific clinical information and comorbidity assessment for predictors which have been proven to be crucial determinants that increase the risk of death for COVID-19 and non-COVID-19 causes, particularly regarding control of chronic cardio-metabolic conditions. Second, we could not ascertain the number of non-COVID-19 deaths which occurred due to exacerbation of underlying chronic conditions by current or previous SARS-CoV-2 infection, as it has been proven that it could increase the risk of long-term complications, including cardiovascular diseases (3). Third, our COVID-19 death construct included cases which could have been misclassified by atypical pneumonia or severe acute respiratory infections of u...

    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.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2022.05.12.22274973v1 on medRxiv