The US Midlife Mortality Crisis Continues: Excess Cause-Specific Mortality During 2020
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Abstract
Whether monthly excess mortality in the United States during 2020 varied by age and cause of death is investigated in this analysis. Based on national-level death counts and population estimates for 1999–2020, sex-specific negative binomial regression models were used to estimate monthly cause-specific excess mortality by age group during 2020. Among men, 71% non-COVID excess deaths occurred at working ages (25–64 years), but those ages accounted for only 36% of non-COVID excess deaths among women. Many excess deaths resulted from external causes (particularly among men), heart disease, diabetes, Alzheimer disease (particularly among women), and cerebrovascular disease. For men, the largest share of non-COVID excess deaths resulted from external causes, nearly 80% of which occurred at working ages. Although incorrectly classified COVID-19 deaths may explain some excess non-COVID mortality, misclassification is unlikely to explain the increase in external causes of death. Auxiliary analyses suggested that drug-related deaths may be driving the increase in external mortality, but drug overdoses were already increasing for a full year before the pandemic. The oldest Americans bore the brunt of COVID-19 deaths, but working-age Americans, particularly men, suffered substantial numbers of excess non-COVID deaths, most commonly from external causes and heart disease.
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SciScore for 10.1101/2021.05.17.21257241: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.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:Limitations: These analyses are based on provisional death counts for 2020, which are likely to be under-estimated, particularly during Wave 3. Because of lags in reporting, it is possible that only about 85% of deaths for December were reported by late April 2021 (15), which is the latest date for which we have provisional estimates. …
SciScore for 10.1101/2021.05.17.21257241: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.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:Limitations: These analyses are based on provisional death counts for 2020, which are likely to be under-estimated, particularly during Wave 3. Because of lags in reporting, it is possible that only about 85% of deaths for December were reported by late April 2021 (15), which is the latest date for which we have provisional estimates. The data are likely to be even more incomplete for injury-related deaths (∼70%), especially drug overdoses (15). As mentioned earlier, problems of misclassification are likely to plague the cause-specific mortality data. Over the course of the pandemic, as the availability of testing increased and death certifiers became more experienced identifying COVID-19, cause-of-death reporting undoubtedly improved. Thus, part of the decline in apparent excess mortality as the pandemic progressed could be a statistical artifact of more accurate reporting of COVID-19 deaths. As yet, we are unable to examine age variation in excess mortality from more detailed causes such as drug- and alcohol-related mortality, homicide, motor vehicle accidents, and suicides. Once county-level data become available, we plan to explore geographic variation in the impact of the pandemic on the deaths of despair and other external mortality. There is already ample evidence that socioeconomically-disadvantaged communities were harder hit by COVID-19 than more advantaged communities (5,23–25). We wonder whether the pandemic further exacerbated socioeconomic disparities in drug- a...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).
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.
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- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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