What Veteran Groups Really Had Most Excess Deaths?
WHITE RIVER JUNCTION, VT — A study team involving VA researchers looked at death rates during the COVID-19 pandemic through a different lens and came up with intriguing information from individual-level instead of aggregate data.
The study, which was led by researchers from the Yale School of Public Health in New Haven, CT, included participation from the White River Junction, VT, West Haven, CT, and Palo Alto, CA, VAMCs. It analyzed electronic health record data from more than 5.9 million veterans.
The data came from both a pre-pandemic period—March 2018 – February 2020—and the pandemic period of March 2020 to February 2022. The goal was to better understand COVID-19’s effect on mortality rates, and results were published in the International Journal of Epidemiology.1
What made the study dissimilar from many previous analyses of COVID-19 mortality is that researchers compared the difference between expected and observed death rates, “excess mortality,” as well as the absolute rates of excess mortality between groups to pinpoint variations.
“Most analyses of excess mortality during the COVID-19 pandemic have focused on evaluations of aggregate data, which may miss important individual-level drivers of excess mortality that may serve as future targets for improvement initiatives,” the authors explained.
The study team determined that, while absolute rates of excess mortality were typically highest in groups in which the baseline rate of mortality was higher, such as older age groups and among those with more comorbidities and higher levels of physiologic frailty, that wasn’t the case with relative measures of excess mortality. Those typically were greatest among younger age groups and among those with lower physiologic frailty and fewer comorbidities.
Because relative measures of excess mortality slowed down but remained elevated after the first documented SARS-CoV-2 infection, that suggested that “factors beyond SARS-CoV-2 infection contributed to the observed excess mortality during the pandemic.”
Those might have included issues such as disruptions in care, the researchers pointed out.
Of the nearly 6 million veterans included in the study, the median age was 65.8 years and 91% were men. The study found that the excess mortality rate was 10.0 deaths/1,000 person-years (PY), with a total of 103, 164 excess deaths and pandemic HR of 1.25 (95% CI 1.25–1.26).
“Excess mortality rates were highest among the most frail patients (52.0/1,000 PY) and those with the highest comorbidity burden (16.3/1000 PY),” the study advised. “However, the largest relative mortality increases were observed among the least frail (HR 1.31, 95% CI 1.30-1.32) and those with the lowest comorbidity burden (HR 1.44, 95% CI 1.43-1.46).”
The study team determined that patients with dementia showed the highest relative rates of mortality, although the highest number of deaths were in those who had diabetes, explaining that is because a large number of people have diabetes.
On the other hand, patients with metastatic cancer demonstrated no excess mortality during the initial pandemic years. The researchers posited that it was because of protective measures used by that cohort or the large-scale masking that was employed, which protected them from infectious disease more broadly.
Vaccination Effective in Preventing Mortality
Fully vaccinated individuals experienced no greater mortality compared to those who were not vaccinated, according to the study, further supporting the protective impact of vaccination.
The researchers explained that they undertook the study because so many factors could have contributed to mortality during the pandemic.
“During the COVID-19 pandemic, there was a substantial increase in rates of death due to any cause,” they explained. “Rates of deaths that exceed expected levels are referred to as excess deaths, which were observed globally”. Some geographic regions, risk groups and age groups experienced larger excesses, namely of which were directly attributed to the virus, particularly in older adults.
“Other evidence points to healthcare system-level factors, such as disruptions to healthcare system function, personal health management and healthcare utilization. However, the pandemic also caused major disruptions in society, possibly contributing to overdoses, suicides or violent crime. The risk of death due to COVID-19 as well as susceptibility to these secondary effects of the pandemic depends on a complex set of factors, including the underlying health status of an individual.”
The authors note that their findings are consistent with previous reports showing that the highest excess mortality on an absolute scale occurred in older patients and those who were frailer or had higher comorbidity burden. “However, these groups were observed to have the lowest excess mortality on a relative scale, likely because the baseline rate of death was already high in these groups and there are many competing causes of death,” they explained. “In addition, our calculations of the number of excess deaths, which incorporates the size of each subgroup, suggested that the largest aggregate burden was among patients aged 65–74 years and those who were the least frail or had no recorded comorbidity. Our findings strongly suggest that each of these metrics is important and offers a different story in terms of the impact of COVID-19 on excess mortality in the VA.”
The study team recommended that research estimating excess mortality should present findings on both the absolute and relative scales “to enable policymakers and operations managers to determine where to allocate resources as we emerge from the pandemic and in future similar outbreaks,” adding that the “lower relative increases in excess mortality among more frail groups and those with more comorbidities have important implications.”
The researchers their findings can help plan for future pandemic events.
“Individual-level data offered crucial clinical and operational insights into U.S. excess mortality patterns during the COVID-19 pandemic,” the authors concluded. “Notable differences emerged among clinical risk groups, emphasizing the need for reporting excess mortality in both absolute and relative terms to inform resource allocation in future outbreaks.”
- Weinberger DM, Bhaskaran K, Korves C, Lucas BP, Columbo JA, Vashi A, Davies L, Justice AC, Rentsch CT. Excess mortality in US Veterans during the COVID-19 pandemic: an individual-level cohort study. Int J Epidemiol. 2023 Oct 6:dyad136. doi: 10.1093/ije/dyad136. Epub ahead of print. PMID: 37802889.
Excess mortality estimates adjusted for age and demographic and clinical characteristics, with and without censoring of COVID-19 follow-up
| Characteristic | Age-adjusted HR (95% CI) | Fully adjusted HR (95% CI) | Censoring COVID-19 follow-up HR (95% CI) |
|---|---|---|---|
| Period | |||
| Pre-pandemic | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| Pandemic | 1.27 (1.26–1.27) | 1.25 (1.25–1.26) | 1.19 (1.19–1.20) |
| Sex | |||
| Men | 1.00 (ref) | 1.00 (ref) | |
| Women | 0.65 (0.64–0.66) | 0.65 (0.65–0.67) | |
| Race/ethnicity | |||
| White | 1.00 (ref) | 1.00 (ref) | |
| Black | 0.86 (0.85–0.87) | 0.85 (0.84–0.86) | |
| Hispanic | 0.75 (0.75–0.76) | 0.74 (0.73–0.75) | |
| Asian | 0.62 (0.61–0.65) | 0.62 (0.60–0.64) | |
| AI/AN | 1.11 (1.08–1.14) | 1.09 (1.06–1.13) | |
| PI/NH | 0.91 (0.89–0.94) | 0.90 (0.87–0.93) | |
| Mixed race | 0.96 (0.94–0.99) | 0.96 (0.93–0.99) | |
| Missing | 1.07 (1.06–1.08) | 1.08 (1.07–1.09) | |
| Region | |||
| South | 1.00 (ref) | 1.00 (ref) | |
| Midwest | 0.96 (0.96–0.97) | 0.96 (0.96–0.97) | |
| Northeast | 0.93 (0.93–0.94) | 0.93 (0.92–0.94) | |
| West | 1.01 (1.00–1.01) | 1.00 (1.00–1.01) | |
| Residence type | |||
| Rural | 1.00 (ref) | 1.00 (ref) | |
| Urban | 0.98 (0.98–0.99) | 0.98 (0.98–0.99) | |
| VACS Indexa | |||
| First quartile | 1.00 (ref) | 1.00 (ref) | |
| Second quartile | 1.93 (1.91–1.95) | 1.95 (1.93–1.97) | |
| Third quartile | 2.96 (2.93–2.98) | 3.01 (2.98–3.03) | |
| Fourth quartile | 4.95 (4.91–5.00) | 5.06 (5.01–5.10) | |
| Missing | 2.23 (2.21–2.25) | 2.28 (2.26–2.30) | |
| Charlson Comorbidity Indexb | |||
| 0 | 1.00 (ref) | 1.00 (ref) | |
| 1 | 1.63 (1.62–1.65) | 1.63 (1.62–1.64) | |
| 2 | 1.84 (1.83–1.85) | 1.83 (1.81–1.84) | |
| 3 | 2.36 (2.34–2.38) | 2.34 (2.32–2.36) | |
| 4 | 2.57 (2.55–2.59) | 2.54 (2.52–2.57) | |
| ≥5 | 3.87 (3.84–3.90) | 3.82 (3.79–3.85) | |
ref, referent category; AI/AN, American Indian/Alaska Native; COVID-19, coronavirus disease 2019; HR, hazard ratio; PI/NH, Pacific Islander/Native Hawaiian; VACS, Veterans Aging Cohort Study.
