Differences Between Reported COVID-19 Deaths and Estimated Excess Deaths in Counties Across the United States, March 2020 to February 2022

Accurate and timely tracking of COVID-19 deaths is essential to a well-functioning public health surveillance system. The extent to which official COVID-19 death tallies have captured the true toll of the pandemic in the United States is unknown. In the current study, we develop a Bayesian hierarchical model to estimate monthly excess mortality in each county over the first two years of the pandemic and compare these estimates to the number of deaths officially attributed to Covid-19 on death certificates. Overall, we estimated that 268,176 excess deaths were not reported as Covid-19 deaths during the first two years of the Covid-19 pandemic, which represented 23.7% of all excess deaths that occurred. Differences between excess deaths and reported COVID-19 deaths were substantial in both the first and second year of the pandemic. Excess deaths were less likely to be reported as COVID-19 deaths in the Mountain division, in the South, and in nonmetro counties. The number of excess deaths exceeded COVID-19 deaths in all Census divisions except for the New England and Middle Atlantic divisions where there were more COVID-19 deaths than excess deaths in large metro areas and medium or small metro areas. Increases in excess deaths not assigned to COVID-19 followed similar patterns over time to increases in reported COVID-19 deaths and typically preceded or occurred concurrently with increases in reported COVID-19 deaths. Estimates from this study can be used to inform targeting of resources to areas in which the true toll of the COVID-19 pandemic has been underestimated.

Prospective association between e-cigarette use frequency patterns and cigarette smoking abstinence among adult cigarette smokers in the United States

AIMS

To estimate the association of longitudinal patterns of e-cigarette use with cigarette smoking abstinence, after accounting for time-dependent confounding and selection bias.

DESIGN

Secondary analysis of longitudinal national cohort data. Using marginal structural models and four waves of the population assessment of tobacco and health (wave 1, 2013-14; wave 2, 2014-15; wave 3, 2015-16; wave 4, 2016-18), we estimated the association of vaping frequency across waves 2 and 3 with 12-month sustained cigarette smoking abstinence at wave 4, adjusting for time-dependent confounders at waves 1 and 2 and selection bias due to drop-out with inverse probability of treatment and censoring weights.

SETTING

United States.

PARTICIPANTS/CASES

A total of 5699 adults (18+ years) who smoked cigarettes and did not vape at wave 1.

MEASUREMENTS

The exposure was vaping frequency at waves 2 and 3 (non-use, non-daily use, daily use), representing nine possible combinations of vaping frequency across two waves. Non-use at both waves was the exposure reference group. The primary outcome was sustained 12-month cigarette smoking abstinence at wave 4.

FINDINGS

Among 5699 adults who smoked cigarettes at wave 1, a total of 560 (9.8%) reported smoking abstinence at wave 4. Compared with nonuse at both waves, daily vaping at both waves [risk ratio (RR) = 3.82, 95% confidence interval (CI) = 2.59-5.64] and non-use at wave 2 followed by daily vaping at wave 3 (RR = 2.50, 95% CI = 1.66-3.77) were positively associated with smoking abstinence; non-daily vaping at both waves was inversely associated with smoking abstinence (RR = 0.28, 95% CI = 0.11-0.75). Results persisted after accounting for misclassification of e-cigarette use and cigarette smoking abstinence and after restricting to participants with plans to quit smoking.

CONCLUSIONS

In a US cohort of adult smokers, longitudinal patterns of vaping frequency appear to predict smoking abstinence, even after accounting for several sources of systematic error. Consistent daily vaping is associated with increased chances of cigarette smoking abstinence, while consistent non-daily vaping is associated with decreased chances of smoking abstinence.

Increased all-cause mortality following occupational injury: a comparison of two states

OBJECTIVES

To measure the impact of lost-time occupational injuries on all-cause mortality in Washington State and, using the same data elements and study design, to determine whether the estimated impact was similar to previous estimates for New Mexico.

METHODS

We linked injuries in the Washington workers' compensation system with Social Security Administration data on earnings and mortality. We estimated Cox survival models of mortality for women and men with lost-time compared with medical-only injuries, adjusting for age, pre-injury earnings and industry. We used quantitative bias analysis to account for confounding by pre-injury smoking and obesity.

RESULTS

The estimated mortality HR was 1.24 for women (95% CI 1.21 to 1.28) and 1.22 for men (95% CI 1.20 to 1.24). After adjusting for unmeasured pre-injury smoking and obesity, the estimated HR for women was 1.10, 95% simulation interval (SI) 1.00 to 1.21; for men, it was 1.15, 95% SI 1.04 to 1.27.

CONCLUSIONS

All-cause mortality for Washington workers with lost-time injuries was higher than for those with medical-only injuries. Estimated HRs for Washington were consistent with those previously estimated for New Mexico, a less populous state with lower median wages and a different workers' compensation insurance mechanism. This suggests that the relationship between workplace injury and long-term mortality may be generalisable to other US states. These findings support greater efforts to enhance safety and to investigate factors that improve postinjury employment opportunities and long-term health. This association should be examined in additional locations, with different study conditions, or using additional data on pre-injury risk factors.

Monthly excess mortality across counties in the United States during the Covid-19 pandemic, March 2020 to February 2022

Excess mortality is the difference between expected and observed mortality in a given period and has emerged as a leading measure of the overall impact of the Covid-19 pandemic that is not biased by differences in testing or cause-of-death assignment. Spatially and temporally granular estimates of excess mortality are needed to understand which areas have been most impacted by the pandemic, evaluate exacerbating and mitigating factors, and inform response efforts, including allocating resources to affected communities. We estimated all-cause excess mortality for the United States from March 2020 through February 2022 by county and month using a Bayesian hierarchical model trained on data from 2015 to 2019. An estimated 1,159,580 excess deaths occurred during the first two years of the pandemic (first: 620,872; second: 538,708). Overall, excess mortality decreased in large metropolitan counties, but increased in nonmetro counties, between the first and second years of the pandemic. Despite the initial concentration of mortality in large metropolitan Northeast counties, beginning in February 2021, nonmetro South counties had the highest cumulative relative excess mortality. These results highlight the need for investments in rural health as the pandemic's disproportionate impact on rural areas continues to grow.

Dynamics of racial disparities in all-cause mortality during the COVID-19 pandemic

As research documenting disparate impacts of COVID-19 by race and ethnicity grows, little attention has been given to dynamics in mortality disparities during the pandemic and whether changes in disparities persist. We estimate age-standardized monthly all-cause mortality in the United States from January 2018 through February 2022 for seven racial/ethnic populations. Using joinpoint regression, we quantify trends in race-specific rate ratios relative to non-Hispanic White mortality to examine the magnitude of pandemic-related shifts in mortality disparities. Prepandemic disparities were stable from January 2018 through February 2020. With the start of the pandemic, relative mortality disadvantages increased for American Indian or Alaska Native (AIAN), Native Hawaiian or other Pacific Islander (NHOPI), and Black individuals, and relative mortality advantages decreased for Asian and Hispanic groups. Rate ratios generally increased during COVID-19 surges, with different patterns in the summer 2021 and winter 2021/2022 surges, when disparities approached prepandemic levels for Asian and Black individuals. However, two populations below age 65 fared worse than White individuals during these surges. For AIAN people, the observed rate ratio reached 2.25 (95% CI = 2.14, 2.37) in October 2021 vs. a prepandemic mean of 1.74 (95% CI = 1.62, 1.86), and for NHOPI people, the observed rate ratio reached 2.12 (95% CI = 1.92, 2.33) in August 2021 vs. a prepandemic mean of 1.31 (95% CI = 1.13, 1.49). Our results highlight the dynamic nature of racial/ethnic disparities in mortality and raise alarm about the exacerbation of mortality inequities for Indigenous groups due to the pandemic.

Motivations for E-cigarette use and associations with vaping frequency and smoking abstinence among adults who smoke cigarettes in the United States

INTRODUCTION

In observational studies, vaping daily is positively associated with cigarette smoking abstinence, while non-daily vaping is associated with less smoking abstinence (versus no e-cigarette use). It remains unknown whether cigarette smokers who vape daily have different motivations for using e-cigarettes than those who vape non-daily.

METHODS

Using latent class analysis and 10 self-reported reasons for vaping, we identified sub-groups of participants based on vaping motivations among 1544 adult (≥18 y) dual users of e-cigarettes and cigarettes at wave 4 of the Population Assessment of Tobacco and Health (2016-2018). We examined the association of motivation sub-groups with vaping frequency at wave 4, and subsequent cigarette smoking abstinence at wave 5 (2018-2019). Additional analyses examined the association of vaping frequency with smoking abstinence before and after adjustment for motivation sub-groups.

RESULTS

Four distinct sub-groups of e-cigarette users emerged, including 54 % of participants who were "Vaping Enthusiasts", 20 % who vaped for "Convenience and Social Acceptability", 10 % classified as "Experimenters", and 16 % who vaped for "Quitting Smoking and Harm Reduction." The Convenience and Social Acceptability sub-group were less likely than "Vaping Enthusiasts" (AOR=0.29, 95 %CI[0.20-0.42]) and "Quitting Smoking and Harm Reduction" (AOR=0.41, 95 %CI[0.24-0.71]) classes to vape daily (versus non-daily). Sub-groups were not associated with smoking abstinence after one year. Adjustment for motivation sub-groups did not attenuate a positive association of daily vaping with smoking abstinence.

CONCLUSIONS

Cigarette smokers who vaped for convenience and social acceptability were less frequent e-cigarette users than those with other vaping motivations. Vaping motivations were not associated with subsequent smoking abstinence.

COVID-19 mortality and excess mortality among working-age residents in California, USA, by occupational sector: a longitudinal cohort analysis of mortality surveillance data

BACKGROUND

During the first year of the COVID-19 pandemic, workers in essential sectors had higher rates of SARS-CoV-2 infection and COVID-19 mortality than those in non-essential sectors. It is unknown whether disparities in pandemic-related mortality across occupational sectors have continued to occur during the periods of SARS-CoV-2 variants and vaccine availability.

METHODS

In this longitudinal cohort study, we obtained data from the California Department of Public Health on all deaths occurring in the state of California, USA, from Jan 1, 2016, to Dec 31, 2021. We restricted our analysis to residents of California who were aged 18-65 years at time of death and died of natural causes. We classified the occupational sector into nine essential sectors; non-essential; or unemployed or without an occupation provided on the death certificate. We calculated the number of COVID-19 deaths in total and per capita that occurred in each occupational sector. Separately, using autoregressive integrated moving average models, we estimated total, per-capita, and relative excess natural-cause mortality by week between March 1, 2020, and Nov 30, 2021, stratifying by occupational sector. We additionally stratified analyses of occupational risk into counties with high versus low vaccine uptake, categorising high-uptake regions as counties where at least 50% of the population were fully vaccinated according to US guidelines by Aug 1, 2021.

FINDINGS

From March 1, 2020, to Nov 30, 2021, 24 799 COVID-19 deaths were reported in residents of California aged 18-65 years and an estimated 28 751 (95% prediction interval 27 853-29 653) excess deaths. People working in essential sectors were associated with higher COVID-19 deaths and excess deaths than were those working in non-essential sectors, with the highest per-capita COVID-19 mortality in the agriculture (131·8 per 100 000 people), transportation or logistics (107·1 per 100 000), manufacturing (103·3 per 100 000), facilities (101·1 per 100 000), and emergency (87·8 per 100 000) sectors. Disparities were wider during periods of increased infections, including during the Nov 29, 2020, to Feb 27, 2021, surge in infections, which was driven by the delta variant (B.1.617.2) and occurred during vaccine uptake. During the June 27 to Nov 27, 2021 surge, emergency workers had higher COVID-19 mortality (113·7 per 100 000) than workers from any other sector. Workers in essential sectors had the highest COVID-19 mortality in counties with low vaccination uptake, a difference that was more pronounced during the period of the delta infection surge during Nov 29, 2020, to Feb 27, 2021.

INTERPRETATION

Workers in essential sectors have continued to bear the brunt of high COVID-19 and excess mortality throughout the pandemic, particularly in the agriculture, emergency, manufacturing, facilities, and transportation or logistics sectors. This high death toll has continued during periods of vaccine availability and the delta surge. In an ongoing pandemic without widespread vaccine coverage and with anticipated threats of new variants, the USA must actively adopt policies to more adequately protect workers in essential sectors.

FUNDING

US National Institute on Aging, Swiss National Science Foundation, and US National Institute on Drug Abuse.

Association of Weight at Different Ages and All-Cause Mortality Among Older Adults in the US

Objective: Assess the association of BMI and BMI change with mortality. Methods: Using data from the Wisconsin Longitudinal Study (WLS) on participants born mainly in 1939 (n=4922), we investigated the associations between various measures of BMI across the life course (age 54 BMI; age 65 BMI; age 72 BMI; lifetime maximum BMI; BMI change between ages 54 and 65; BMI change between ages 65 and 72) and mortality. We also assessed whether these associations are mediated by late life health. Results: BMI at age 54 was more strongly associated with late life mortality than BMI at older ages. The association between BMI change and mortality varied based on the timing of weight change. Health at age 72, particularly self-rated health, diabetes, and physical functioning, mediated the observed associations. Conclusion: Knowing older people's weight at midlife and how their weight has changed may be more important in assessing late life mortality risk than their current weight.

Association of device type, flavours and vaping behaviour with tobacco product transitions among adult electronic cigarette users in the USA

BACKGROUND

Few studies assess whether electronic cigarette (e-cigarette) device characteristics or flavours impact longitudinal patterns of cigarette and e-cigarette use.

DESIGN

We examined data from waves 2-4 of the Population Assessment of Tobacco and Health Study (2014-2018). Among adult (≥18 years) current e-cigarette users at wave 2 who were current smokers (dual users; n=1759) and former smokers (exclusive e-cigarette users; n=470), we classified participants into four use patterns at wave 3 (~12 months later) and wave 4 (~24 months later): (1) dual use of e-cigarettes and cigarettes; (2) exclusive cigarette smoking; (3) exclusive e-cigarette use; (4) non-use of both products. We used multinomial logistic regression to assess correlates of changing use patterns at 24 months, relative to no change, adjusting for sociodemographic factors.

RESULTS

At 24 months, 26.5% of baseline exclusive e-cigarette users, and 9% of baseline dual users, abstained from both vaping and smoking. Participants who vaped non-tobacco flavours (vs tobacco flavours), and used refillable tank or modifiable devices (vs disposable, cartridges and other devices) were less likely to transition to non-use of both products and to exclusive cigarette smoking. Baseline daily vaping (vs non-daily) was positively associated with exclusive e-cigarette use at 24 months for baseline daily cigarette smokers, but negatively associated with exclusive e-cigarette use and non-use of both products at 24 months for baseline non-daily smokers.

CONCLUSIONS

Non-tobacco flavours, daily vaping and modifiable e-cigarette devices may help some smokers abstain from cigarette smoking via transitioning to exclusive e-cigarette use, but are also associated with ongoing exclusive e-cigarette use.

Geographic and Temporal Patterns in Covid-19 Mortality by Race and Ethnicity in the United States from March 2020 to February 2022

Prior research has established that American Indian, Alaska Native, Black, Hispanic, and Pacific Islander populations in the United States have experienced substantially higher mortality rates from Covid-19 compared to non-Hispanic white residents during the first year of the pandemic. What remains less clear is how mortality rates have changed for each of these racial/ethnic groups during 2021, given the increasing prevalence of vaccination. In particular, it is unknown how these changes in mortality have varied geographically. In this study, we used provisional data from the National Center for Health Statistics (NCHS) to produce age-standardized estimates of Covid-19 mortality by race/ethnicity in the United States from March 2020 to February 2022 in each metro-nonmetro category, Census region, and Census division. We calculated changes in mortality rates between the first and second years of the pandemic and examined mortality changes by month. We found that when Covid-19 first affected a geographic area, non-Hispanic Black and Hispanic populations experienced extremely high levels of Covid-19 mortality and racial/ethnic inequity that were not repeated at any other time during the pandemic. Between the first and second year of the pandemic, racial/ethnic inequities in Covid-19 mortality decreased-but were not eliminated-for Hispanic, non-Hispanic Black, and non-Hispanic AIAN residents. These inequities decreased due to reductions in mortality for these populations alongside increases in non-Hispanic white mortality. Though racial/ethnic inequities in Covid-19 mortality decreased, substantial inequities still existed in most geographic areas during the pandemic's second year: Non-Hispanic Black, non-Hispanic AIAN, and Hispanic residents reported higher Covid-19 death rates in rural areas than in urban areas, indicating that these communities are facing serious public health challenges. At the same time, the non-Hispanic white mortality rate worsened in rural areas during the second year of the pandemic, suggesting there may be unique factors driving mortality in this population. Finally, vaccination rates were associated with reductions in Covid-19 mortality for Hispanic, non-Hispanic Black, and non-Hispanic white residents, and increased vaccination may have contributed to the decreases in racial/ethnic inequities in Covid-19 mortality observed during the second year of the pandemic. Despite reductions in mortality, Covid-19 mortality remained elevated in nonmetro areas and increased for some racial/ethnic groups, highlighting the need for increased vaccination delivery and equitable public health measures especially in rural communities. Taken together, these findings highlight the continued need to prioritize health equity in the pandemic response and to modify the structures and policies through which systemic racism operates and has generated racial health inequities.

Longitudinal evidence on treatment discontinuation, adherence, and loss of hypertension control in four middle-income countries

Managing hypertension is a highly dynamic process, yet current evidence on hypertension control in middle-income countries (MICs) is largely based on cross-sectional data. Using multiple waves of population-based cohort data from four MICs (China, Indonesia, Mexico, and South Africa), we undertook a longitudinal investigation into how individuals with hypertension move through care over time. We classified adults aged 40 years and over (N = 8527) into care stages at both baseline and follow-up waves and estimated the probability of transitioning between stages using Poisson regression models. Over a 5- to 9-year follow-up period, only around 30% of undiagnosed individuals became diagnosed [Mexico, 27% (95% confidence interval: 23%, 31%); China, 30% (26%, 33%); Indonesia, 30% (28%, 32%); and South Africa, 36% (31%, 41%)], and one in four untreated individuals became treated [Indonesia, 11% (10%, 12%); Mexico, 24% (20%, 28%); China, 26% (23%, 29%); and South Africa, 33% (29%, 38%)]. The probability of reaching blood pressure (BP) control was lower [Indonesia, 2% (1%, 2%); China, 9% (7%, 11%); Mexico, 12% (9%, 14%); and South Africa, 24% (20%, 28%)] regardless of treatment status. A substantial proportion of individuals discontinued treatment [Indonesia, 70% (67%, 73%); China, 36% (32%, 40%); Mexico, 34% (29%, 39%); and South Africa, 20% (15%, 25%)], and most individuals lost BP control by follow-up [Indonesia, 92% (89%, 96%); Mexico, 77% (71%, 83%); China, 76% (69%, 83%); and South Africa 45% (36%, 54%)]. Our results highlight that policies solely aimed at improving diagnosis or initiating treatment may not lead to long-term hypertension control improvements in MICs.

e-Cigarette Use and Combustible Cigarette Smoking Initiation Among Youth: Accounting for Time-Varying Exposure and Time-Dependent Confounding

BACKGROUND

Youth e-cigarette use is associated with the initiation of combustible cigarette smoking, but prior studies have rarely accounted for time-varying measures of e-cigarette exposure or time-dependent confounding of e-cigarette use and smoking initiation.

METHODS

Using five waves of the Population Assessment of Tobacco and Health (2013-2019), we estimated marginal structural models with inverse probability of treatment and censoring weights to examine the association between time-varying e-cigarette initiation and subsequent cigarette smoking initiation among e-cigarette- and cigarette-naïve youth (12-17 years) at baseline. Time-dependent confounders used as predictors in inverse probability weights included tobacco-related attitudes or beliefs, mental health symptoms, substance use, and tobacco-marketing exposure.

RESULTS

Among 9,584 youth at baseline, those who initiated e-cigarettes were 2.4 times as likely to subsequently initiate cigarette smoking as youth who did not initiate e-cigarettes (risk ratio = 2.4, 95% confidence interval [CI] = 2.1, 2.7), after accounting for time-dependent confounding and selection bias. Among youth who initiated e-cigarettes, more frequent vaping was associated with greater risk of smoking initiation (risk ratio ≥3 days/month = 1.8, 95% CI = 1.4, 2.2; 1-2 days/month = 1.2; 95% CI = 0.93, 1.6 vs. 0 days/month). Weighted marginal structural model estimates were moderately attenuated compared with unweighted estimates adjusted for baseline-only confounders. At the US population level, we estimated over half a million youth initiated cigarette smoking because of prior e-cigarette use over follow-up.

CONCLUSIONS

The association between youth vaping and combustible cigarette smoking persisted after accounting for time-dependent confounding. We estimate that e-cigarette use accounts for a considerable share of cigarette initiation among US youth. See video abstract at, http://links.lww.com/EDE/B937.

Excess natural-cause deaths in California by cause and setting: March 2020 through February 2021

Excess mortality has exceeded reported deaths from Covid-19 during the pandemic. This gap may be attributable to deaths that occurred among individuals with undiagnosed Covid-19 infections or indirect consequences of the pandemic response such as interruptions in medical care; distinguishing these possibilities has implications for public health responses. In the present study, we examined patterns of excess mortality over time and by setting (in-hospital or out-of-hospital) and cause of death using death certificate data from California. The estimated number of excess natural-cause deaths from 2020 March 1 to 2021 February 28 (69,182) exceeded the number of Covid-19 diagnosed deaths (53,667) by 29%. Nearly half, 47.4% (32,775), of excess natural-cause deaths occurred out of the hospital, where only 28.6% (9,366) of excess mortality was attributed to Covid-19. Over time, increases or decreases in excess natural non-Covid-19 mortality closely mirrored increases or decreases in Covid-19 mortality. The time series were positively correlated in out-of-hospital settings, particularly at time lags when excess natural-cause deaths preceded reported Covid-19 deaths; for example, when comparing Covid-19 deaths to excess natural-cause deaths in the week prior, the correlation was 0.73. The strong temporal association of reported Covid-19 deaths with excess out-of-hospital deaths from other reported natural-cause causes suggests Covid-19 deaths were undercounted during the first year of the pandemic.

Racial and Ethnic Disparities in Estimated Excess Mortality From External Causes in the US, March to December 2020

This cross-sectional study examines racial and ethnic disparities in estimated excess deaths from homicide, suicide, transportation, and drug overdoses during the COVID-19 pandemic.

Assessment of Patterns in e-Cigarette Use Among Adults in the US, 2017-2020

Importance

Updated data on the patterns of e-cigarette use among adults in the US are needed.

Objective

To examine recent patterns in current and daily e-cigarette use among US adults.

Design, Setting, and Participants

This repeated cross-sectional study used data from the 2017, 2018, and 2020 Behavioral Risk Factor Surveillance System, a nationally representative state-based survey of noninstitutionalized US adults. A total of 994 307 adults 18 years and older who were living in states and territories that provided data on e-cigarette use in 2017 (53 states and territories), 2018 (36 states and Guam), and 2020 (42 states and Guam) were included.

Main Outcomes and Measures

The weighted prevalence of current (past 30 days) and daily e-cigarette use was estimated for each year, and changes in prevalence from 2017 to 2020 were assessed, first overall and then stratified by participant characteristics, including state or territory of residence.

Results

Among 994 307 adults from states with data on e-cigarette use, 429 370 individuals (weighted 51.3% female) were participants in the 2017 survey, 280 184 (weighted 52.1% female) were participants in the 2018 survey, and 284 753 (weighted 52.1% female) were participants in the 2020 survey. The weighted proportions of young adults aged 18 to 24 years were 12.6% in 2017, 11.8% in 2018, and 11.9% in 2020. Across all 3 years, 17 035 participants (weighted, 1.0%) were American Indian or Alaska Native, 22 313 (weighted, 4.6%) were Asian, 75 780 (weighted, 12.2%) were Black, 72 190 (weighted, 15.1%) were Hispanic, 4817 (weighted, 0.2%) were Native Hawaiian, 757 140 (weighted, 65.1%) were White, 20 332 (weighted, 1.3%) were multiracial, and 6245 (weighted, 0.5%) were of other races and/or ethnicities. The prevalence of current e-cigarette use was 4.4% (95% CI, 4.3%-4.5%) in 2017, which increased to 5.5% (95% CI, 5.4%-5.7%) in 2018 and decreased slightly to 5.1% (95% CI, 4.9%-5.3%) in 2020. The recent decrease, though modest, was observed mainly among young adults aged 18 to 20 years (from 18.9% [95% CI, 17.2%-20.7%] to 15.6% [95% CI, 14.1%-17.1%]; P = .004). However, the prevalence of daily e-cigarette use increased consistently from 1.5% (95% CI, 1.4%-1.6%) in 2017 to 2.1% (95% CI, 2.0%-2.2%) in 2018 and 2.3% (95% CI, 2.2%-2.4%) in 2020. Among young adults aged 21 to 24 years, there was a slight, albeit insignificant, increase in the prevalence of current e-cigarette use (from 13.5% [95% CI, 12.3%-14.7%] to 14.5% [95% CI, 13.2%-15.9%]; P = .28) but a significant increase in the prevalence of daily e-cigarette use (from 4.4% [95% CI, 3.8%-5.1%] to 6.6% [95% CI, 5.6%-7.6%]; P < .001) between 2018 and 2020. State-level patterns in the prevalence of current e-cigarette use were heterogeneous, with states like Massachusetts (from 5.6% [95% CI, 4.8%-6.5%] to 4.1% [95% CI, 3.1%-5.3%]; P = .03) and New York (from 5.4% [95% CI, 4.9%-5.9%] to 4.1% [95% CI, 3.5%-4.7%]; P = .001) recording significant decreases between 2018 and 2020. In contrast, Guam (from 5.9% [95% CI, 4.5%-7.9%] to 11.4% [95% CI, 8.7%-14.8%]; P = .002) and Utah (from 6.1% [95% CI, 5.5%-6.7%] to 7.2% [95% CI, 6.5%-8.0%]; P = .02) recorded significant increases in current e-cigarette use over the same period.

Conclusions and Relevance

In this study, a slight decrease in the prevalence of current e-cigarette use was found between 2018 and 2020; this decrease was mainly observed among young adults aged 18 to 20 years. In contrast, daily e-cigarette use consistently increased, particularly among young adults aged 21 to 24 years. This increase in daily use suggests greater nicotine dependence among those who use e-cigarettes, warranting continued surveillance.

"Pandemic of the unvaccinated"? At midlife, white people are less vaccinated but still at less risk of Covid-19 mortality in Minnesota

Introduction

Recent research underscores the exceptionally young age distribution of Covid-19 deaths in the United States compared with international peers. This brief characterizes how high levels of Covid mortality at midlife ages (45-64) are deeply intertwined with continuing racial inequity in Covid-19 mortality.

Methods

Mortality data from Minnesota in 2020-2022 were analyzed in June 2022. Death certificate data and published vaccination rates in Minnesota allow vaccination and mortality rates to be observed with greater age and temporal precision than national data.

Results

Black, Hispanic, and Asian adults under age 65 were all more highly vaccinated than white populations of the same ages during most of Minnesota's substantial and sustained Delta surge and all of the subsequent Omicron surge. However, white mortality rates were lower than those of all other groups. These disparities were extreme; at midlife ages (ages 45-64), during the Omicron period, more highly-vaccinated populations had COVID-19 mortality that was 164% (Asian-American), 115% (Hispanic), or 208% (Black) of white Covid-19 mortality at these ages. In Black, Indigenous, and People of Color (BIPOC) populations as a whole, Covid-19 mortality at ages 55-64 was greater than white mortality at 10 years older.

Conclusions

This discrepancy between vaccination and mortality patterning by race/ethnicity suggests that, if the current period is a "pandemic of the unvaccinated," it also remains a "pandemic of the disadvantaged" in ways that can decouple from vaccination rates. This result implies an urgent need to center health equity in the development of Covid-19 policy measures.

Associations of Smokeless Tobacco Use With Cardiovascular Disease Risk: Insights From the Population Assessment of Tobacco and Health Study

INTRODUCTION

Cigarette smoking is strongly associated with the development of cardiovascular disease (CVD). However, evidence is limited as to whether smokeless tobacco (ST) use is associated with CVD.

AIMS AND METHODS

Using data from 4347 adults in the Population Assessment of Tobacco and Health Study (2013-2014), we compared geometric mean concentrations of CVD-related harm biomarkers and biomarkers of exposure among exclusive ST users and exclusive cigarette smokers-in relation to recent nicotine exposure-and never tobacco users, adjusting for age, sex, race/ethnicity, income, body mass index, and CVD. Biomarker levels among exclusive ST users who were former established cigarette smokers were compared with exclusive cigarette smokers.

RESULTS

Compared with cigarette smokers, ST users had significantly higher concentrations of total nicotine equivalents (TNE) but lower concentrations of inflammatory (high-sensitivity C-reactive protein, interleukin-6, intercellular adhesion molecule, fibrinogen) and oxidative stress (8-isoprostane) biomarkers (all p < .05). Biomarker levels among ST users were similar to never smokers. ST users who were former cigarette smokers had lower levels of inflammatory and oxidative stress biomarkers and biomarkers of exposure (cadmium, lead, 1-hydroxypyrene, acrylonitrile, and acrolein), compared with cigarettes smokers (p < .05), despite having higher TNE levels (p < .05). Among cigarette smokers, but not among ST users, inflammatory biomarkers and TNE were highly correlated.

CONCLUSIONS

ST use is not associated with increases in biomarkers of CVD-related harm and exposure, compared with never smokers, despite exposure to nicotine at levels higher than those observed among cigarette smokers. These findings support the concept that increases in CVD risk among cigarette smokers is caused primarily by constituents of tobacco smoke other than nicotine.

IMPLICATIONS

Despite having higher levels of nicotine and compared with exclusive cigarette smokers, exclusive ST users (including those who were former cigarette smokers) had significantly lower concentrations of inflammatory and oxidative stress biomarkers, comparable to levels observed among never tobacco users. These findings suggest that increases in CVD risk among cigarette smokers is caused primarily by tobacco constituents other than nicotine and that switching to ST is likely associated with lower CVD risk.

Association of Electronic Cigarette Use with Respiratory Symptom Development among U.S. Young Adults

Rationale: Electronic cigarette (e-cigarette) use is highly prevalent among young adults. However, longitudinal data assessing the association between e-cigarette use and respiratory symptoms are lacking. Objectives: To determine whether e-cigarette use is associated with the development of respiratory symptoms in young adults. Methods: Data are derived from the PATH (Population Assessment of Tobacco and Health) study waves 2 (2014-2015), 3 (2015-2016), 4 (2016-2018), and 5 (2018-2019). Young adults aged 18-24 years at baseline with no prevalent respiratory disease or symptoms were included in the analyses. Binary logistic regression models with a generalized estimating equation were used to estimate time-varying and time-lagged associations of e-cigarette use during waves 2-4, with respiratory symptom development approximately 12 months later at waves 3-5. Measurements and Main Results: The per-wave prevalence of former and current e-cigarette use was 15.2% and 5.6%, respectively. Former e-cigarette use was associated with higher odds of developing any respiratory symptom (adjusted odds ratio [aOR], 1.20; 95% confidence interval [CI], 1.04-1.39) and wheezing in the chest (aOR, 1.41; 95% CI, 1.08-1.83) in multivariable adjusted models. Current e-cigarette use was associated with higher odds for any respiratory symptom (aOR, 1.32; 95% CI, 1.06-1.65) and wheezing in the chest (aOR, 1.51; 95% CI, 1.06-2.14). Associations persisted among participants who never smoked combustible cigarettes. Conclusions: In this nationally representative cohort of young adults, former and current e-cigarette use was associated with higher odds of developing wheezing-related respiratory symptoms, after accounting for cigarette smoking and other combustible tobacco product use.

Excess all-cause mortality across counties in the United States, March 2020 to December 2021

Official Covid-19 death counts have underestimated the mortality impact of the Covid-19 pandemic in the United States. Excess mortality, which compares observed deaths to deaths expected in the absence of the pandemic, is a useful measure for assessing the total effect of the pandemic on mortality levels. In the present study, we produce county-level estimates of excess mortality for 3,127 counties between March 2020 and December 2021. We fit two hierarchical linear models to county-level death rates from January 2015 to December 2019 and predict expected deaths for each month during the pandemic. We compare observed deaths to these estimates to obtain excess deaths for each county-month. An estimated 936,911 excess deaths occurred during 2020 and 2021, of which 171,168 (18.3%) were not assigned to Covid-19 on death certificates as an underlying cause of death. Urban counties in the Far West, Great Lakes, Mideast, and New England experienced a substantial mortality disadvantage in 2020, whereas rural counties in these regions had higher mortality in 2021. In the Southeast, Southwest, Rocky Mountain, and Plains regions, there was a rural mortality disadvantage in 2020, which was exacerbated in 2021. The proportion of excess deaths assigned to Covid-19 was lower in 2020 (76.3%) than in 2021 (87.0%), suggesting that a larger fraction of excess deaths was assigned to Covid-19 later in the pandemic. However, in rural areas and in the Southeast and Southwest a large share of excess deaths was still not assigned to Covid-19 during 2021.

SIGNIFICANCE

Deaths during the Covid-19 pandemic have been primarily monitored through death certificates containing reference to Covid-19. This approach has missed more than 170,000 deaths related to the pandemic between 2020 and 2021. While the ascertainment of Covid-19 deaths improved during 2021, the full effects of the pandemic still remained obscured in some regions. County-level estimates of excess mortality are useful for studying geographic inequities in the mortality burden associated with the pandemic and identifying specific regions where the full mortality burden was significantly underreported (i.e. Southeast). They can also be used to inform resource allocation decisions at the federal and state levels and encourage uptake of preventive measures in communities with low vaccine uptake.

Association of Online Search Trends With Vaccination in the United States: June 2020 Through May 2021

Stagnating COVID-19 vaccination rates and vaccine hesitancy remain a threat to public health. Improved strategies for real-time tracking and estimation of population-level behavior regarding vaccinations are needed. The aim of this study was to evaluate whether online search trends for COIVD-19 and influenza mirror vaccination rates. State-level weekly fraction of online searches for top vaccination-related search terms and CDC vaccination data were obtained from June 1, 2020, to May 31, 2021. Next, trends in online search and vaccination data for COVID-19 and influenza were analyzed for visual and quantitative correlation patterns using Spearman’s rank correlation analysis. Online searches in the US for COVID-19 vaccinations increased 2.71-fold (95% CI: 1.98-3.45) in the 4 weeks after the FDA emergency authorization compared to the precedent 4 weeks. In March-April 2021, US online searches reached a plateau that was followed by a decline of 83.3% (95% CI: 31.2%-135.3%) until May 31, 2021. The timing of peaks in online searches varied across US states. Online searches were strongly correlated with vaccination rates (r=0.71, 95% CI: 0.45 - 0.87), preceding actual reported vaccination rates in 44 of 51 states. Online search trends preceded vaccination trends by a median of 3.0 weeks (95% CI: 2.0-4.0 weeks) across all states. For influenza vaccination searches, seasonal peaks in September-October between 2016-2020 were noted. Influenza search trends highly correlated with the timing of actual vaccinations for the 2019-2020 (r=0.82, 95% CI: 0.64 – 0.93) and 2020-2021 season (r=0.91, 95% CI: 0.78 – 0.97). Search trends and real-world vaccination rates are highly correlated. Temporal alignment and correlation levels were higher for influenza vaccinations; however, only online searches for COVID-19 vaccination preceded vaccination trends. These findings indicate that US online search data can potentially guide public health efforts, including policy changes and identifying geographical areas to expand vaccination campaigns.

Evaluation of Age Patterns of COVID-19 Mortality by Race and Ethnicity From March 2020 to October 2021 in the US

This cross-sectional study examines age-specific COVID-19 mortality rates in the US from March 2020 to October 2021 by sex and race and ethnicity.

County-level estimates of excess mortality associated with COVID-19 in the United States

The COVID-19 pandemic in the U.S. has been largely monitored using death certificates containing reference to COVID-19. However, prior analyses reveal that a significant percentage of excess deaths associated with the pandemic were not directly assigned to COVID-19. In this study, we estimated a generalized linear model of expected mortality based on historical trends in deaths by county of residence between 2011 and 2019. We used the results of the model to generate estimates of excess mortality and excess deaths not assigned to COVID-19 in 2020 for 1470 county sets in the U.S. representing 3138 counties. Across the country, we estimated that 438,386 excess deaths occurred in 2020, among which 87.5% were assigned to COVID-19. Some regions (Mideast, Great Lakes, New England, and Far West) reported the most excess deaths in large central metros, whereas other regions (Southwest, Southeast, Plains, and Rocky Mountains) reported the highest excess mortality in nonmetro areas. The proportion assigned to COVID-19 was lowest in large central metro areas (79.3%). Regionally, the proportion of excess deaths assigned to COVID-19 was lowest in the Southeast (81.6%), Southwest (82.6%), Far West (83.7%), and Rocky Mountains (86.7%). Across the regions, the number of excess deaths exceeded the number of directly assigned COVID-19 deaths in most counties. The exception to this pattern occurred in New England, which reported more directly assigned COVID-19 deaths than excess deaths in metro and nonmetro areas. Many county sets had substantial numbers of excess deaths that were not accounted for in direct COVID-19 death counts. Estimates of excess mortality at the local level can inform the allocation of resources to areas most impacted by the pandemic and contribute to positive behavior feedback loops, such as increases in mask-wearing and vaccine uptake.