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Objectives. To estimate state-level excess death rates during 2020 to 2023 and examine differences by region and partisan orientation. Methods. We modeled death and population counts from the Centers for Disease Control and Prevention to estimate excess death rates for the United States, 9 census divisions, and 50 states. We compared excess death rates for states with different partisan orientations, measured by the party of the seated governor and the level of partisan representation in state legislatures. Results. The United States experienced 1 277 697 excess deaths between March 2020 and July 2023. Almost 90% of these deaths were attributed to COVID-19, and 51.5% occurred after vaccines were available. The highest excess death rates first occurred in the Northeast and then shifted to the South and Mountain states. Between weeks ending June 20, 2020, through March 19, 2022, excess death rates were higher in states with Republican governors and greater Republican representation in state legislatures. Conclusions. Excess death rates during the COVID-19 pandemic varied considerably across the US states and were associated with partisan representation in state government, although the influence of confounding variables cannot be excluded. (Am J Public Health. 2024;114(9):882–891. https://doi.org/10.2105/AJPH.2024.307731) [ABSTRACT FROM AUTHOR]

PurposeTechnology could transform routine decision making by anticipating patients' information needs, assessing where patients are with decisions and preferences, personalizing educational experiences, facilitating patient-clinician information exchange, and supporting follow-up. This study evaluated whether patients and clinicians will use such a decision module and its impact on care, using 3 cancer screening decisions as test cases.MethodsTwelve practices with 55,453 patients using a patient portal participated in this prospective observational cohort study. Participation was open to patients who might face a cancer screening decision: women aged 40 to 49 who had not had a mammogram in 2 years, men aged 55 to 69 who had not had a prostate-specific antigen test in 2 years, and adults aged 50 to 74 overdue for colorectal cancer screening. Data sources included module responses, electronic health record data, and a postencounter survey.ResultsIn 1 year, one-fifth of the portal users (11,458 patients) faced a potential cancer screening decision. Among these patients, 20.6% started and 7.9% completed the decision module. Fully 47.2% of module completers shared responses with their clinician. After their next office visit, 57.8% of those surveyed thought their clinician had seen their responses, and many reported the module made their appointment more productive (40.7%), helped engage them in the decision (47.7%), broadened their knowledge (48.1%), and improved communication (37.5%).ConclusionsMany patients face decisions that can be anticipated and proactively facilitated through technology. Although use of technology has the potential to make visits more efficient and effective, cultural, workflow, and technical changes are needed before it could be widely disseminated.

Objectives: Approximately half of US pregnancies are unintended and 43% of these end in induced abortions. Male partners and their involvement in reproductive decisions is not well understood. We examined the association between couple pregnancy intentions and induced abortion in US women. Materials and Methods: Data came from the National Survey of Family Growth (2006-2010). Primiparous women who lived with one husband or partner before conception of their first pregnancy were included in the analysis (N=4263). Multiple logistic regression was used to assess the relationship between couple pregnancy intentions and induced abortion of first pregnancy. Results: Approximately 17.1% of women reported discordant intentions and 32.3% reported that pregnancy was unintended by both parents. Among these couples, the women were more likely to be unmarried, minorities, of lower income and education, and 19 years of age or younger at conception than were couples in which both parents intended pregnancy. Compared to couples with a mutually intended pregnancy, those with discordant pregnancy intentions were significantly more likely to have induced abortion, even in women who desired pregnancy. Conclusion: Partners had a vital role in decisions to have an induced abortion. Health providers should consider the interpersonal decision-making process in couples to best prevent induced abortions due to unintended pregnancy. Providers should also be aware of the role of violence on reproductive decisions in couples with discordant pregnancy intentions. Women in healthy relationships can benefit from having frequent conversations about pregnancy with their partners.

Awareness of the impact of education on health remains relatively low among the public, professionals, and policy makers. Virginia Commonwealth University's Center on Society and Health sought to raise awareness among key decision makers about the impact of education on health outcomes through its Education and Health Initiative (EHI). EHI utilized four key strategies to raise awareness: user-oriented research, strategic communication, local and national stakeholder engagement, and policy outreach to decision makers. We review the research highlighted in four stages of EHI product releases, as well as the development, process, products, and key outcomes associated with this initiative.

Key Points: Question: What causes of death are associated with the widening disparities in mortality among US youth of different races and ethnicities in recent years? Findings: In this cross-sectional study of mortality in youth aged 1 to 19 years in the US, injuries, especially firearm injuries, were associated with worsening disparities between Black and American Indian or Alaska Native and White youth. Between 2016 and 2020, the homicide rate in Black youth was 12.81 per 100 000 youth (rate ratio with White youth, 10.20), and the suicide rate for American Indian or Alaska Native youth was 11.37 per 100 000 youth (rate ratio with White youth, 2.60). Meaning: In this study, racial and ethnic disparities were observed for almost all leading causes of injury and disease and were associated with recent increases in US mortality rates. Importance: Mortality rates in US youth have increased in recent years. An understanding of the role of racial and ethnic disparities in these increases is lacking. Objective: To compare all-cause and cause-specific mortality trends and rates among youth with Hispanic ethnicity and non-Hispanic American Indian or Alaska Native, Asian or Pacific Islander, Black, and White race. Design, Setting, and Participants: This cross-sectional study conducted temporal analysis (1999-2020) and comparison of aggregate mortality rates (2016-2020) for youth aged 1 to 19 years using US Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research database. Data were analyzed from June 30, 2023, to January 17, 2024. Main Outcomes and Measures: Pooled, all-cause, and cause-specific mortality rates per 100 000 youth (hereinafter, per 100 000) for leading underlying causes of death were compared. Injuries were classified by mechanism and intent. Results: Between 1999 and 2020, there were 491 680 deaths among US youth, including 8894 (1.8%) American Indian or Alaska Native, 14 507 (3.0%) Asian or Pacific Islander, 110 154 (22.4%) Black, 89 251 (18.2%) Hispanic, and 267 452 (54.4%) White youth. Between 2016 and 2020, pooled all-cause mortality rates were 48.79 per 100 000 (95% CI, 46.58-51.00) in American Indian or Alaska Native youth, 15.25 per 100 000 (95% CI, 14.75-15.76) in Asian or Pacific Islander youth, 42.33 per 100 000 (95% CI, 41.81-42.86) in Black youth, 21.48 per 100 000 (95% CI, 21.19-21.77) in Hispanic youth, and 24.07 per 100 000 (95% CI, 23.86-24.28) in White youth. All-cause mortality ratios compared with White youth were 2.03 (95% CI, 1.93-2.12) among American Indian or Alaska Native youth, 0.63 (95% CI, 0.61-0.66) among Asian or Pacific Islander youth, 1.76 (95% CI, 1.73-1.79) among Black youth, and 0.89 (95% CI, 0.88-0.91) among Hispanic youth. From 2016 to 2020, the homicide rate in Black youth was 12.81 (95% CI, 12.52-13.10) per 100 000, which was 10.20 (95% CI, 9.75-10.66) times that of White youth. The suicide rate for American Indian or Alaska Native youth was 11.37 (95% CI, 10.30-12.43) per 100 000, which was 2.60 (95% CI, 2.35-2.86) times that of White youth. The firearm mortality rate for Black youth was 12.88 (95% CI, 12.59-13.17) per 100 000, which was 4.14 (95% CI, 4.00-4.28) times that of White youth. American Indian or Alaska Native youth had a firearm mortality rate of 6.67 (95% CI, 5.85-7.49) per 100 000, which was 2.14 (95% CI, 1.88- 2.43) times that of White youth. Black youth had an asthma mortality rate of 1.10 (95% CI, 1.01-1.18) per 100 000, which was 7.80 (95% CI, 6.78-8.99) times that of White youth. Conclusions and Relevance: In this study, racial and ethnic disparities were observed for almost all leading causes of injury and disease that were associated with recent increases in youth mortality rates. Addressing the increasing disparities affecting American Indian or Alaska Native and Black youth will require efforts to prevent homicide and suicide, especially those events involving firearms. This cross-sectional study compares all-cause and cause-specific mortality trends and rates among youth from different races and ethnicities between 1999 and 2021. [ABSTRACT FROM AUTHOR]

The health of Americans is in decline, a crisis that has been building for some years. Since the 1980s, US life expectancy has risen at a slower pace than in [...]

The author discusses an article by Vandenbroucke and Pearce, published in the issue, on technical issues surrounding the measurement of excess deaths during the COVID-19 pandemic. Topics include evidence of deteriorating health among Americans, explanations for the complacency on the deteriorating health outcomes, and concerns of powerful corporations and their shareholders.

We estimated changes in life expectancy between 2019 and 2021 in the United States (in the total population and separately for 5 racial/ethnic groups) and 20 high-income peer countries. For each country's total population, we decomposed the 2019–2020 and 2020–2021 changes in life expectancy by age. For US populations, we also decomposed the life expectancy changes by age and number of coronavirus disease 2019 (COVID-19) deaths. Decreases in US life expectancy in 2020 (1.86 years) and 2021 (0.55 years) exceeded mean changes in peer countries (a 0.39-year decrease and a 0.23-year increase , respectively) and disproportionately involved COVID-19 deaths in midlife. In 2020, Native American, Hispanic, Black, and Asian-American populations experienced larger decreases in life expectancy and greater losses in midlife than did the White population. In 2021, the White population experienced the largest decrease in US life expectancy, although life expectancy in the Native American and Black populations remained much lower. US losses during the pandemic were more severe than in peer countries and disproportionately involved young and middle-aged adults, especially adults of this age in racialized populations. The mortality consequences of the COVID-19 pandemic deepened a US disadvantage in longevity that has been growing for decades and exacerbated long-standing racial inequities in US mortality. [ABSTRACT FROM AUTHOR]

Policy PointsThe increasing political polarization of states reached new heights during the COVID‐19 pandemic, when response plans differed sharply across party lines.This study found that states with Republican governors and larger Republican majorities in legislatures experienced higher death rates during the COVID‐19 pandemic—and in preceding years—but these associations often lost statistical significance after adjusting for the average income and health status of state populations and for the policy orientations of the states.Future research may help clarify whether the higher death rates in these states result from policy choices or have other explanations, such as the tendency of voters with lower incomes or poorer health to elect Republican candidates. Context: Increasing polarization of states reached a high point during the COVID‐19 pandemic, when the party affiliation of elected officials often predicted their policy response. The health consequences of these divisions are unclear. Prior studies compared mortality rates based on presidential voting patterns, but few considered the partisan orientation of state officials. This study examined whether the partisan orientation of governors or legislatures was associated with mortality outcomes during the COVID‐19 pandemic. Methods: Data on deaths and the partisan orientation of governors and legislators were obtained from the Centers for Disease Control and Prevention and the National Conference of State Legislatures, respectively. Linear regression was used to measure the association between Republican representation (percentage of seats held) in legislatures and (1) age‐adjusted, all‐cause mortality rates (AAMRs) in 2015–2021 and (2) excess death rates during three phases of the COVID‐19 pandemic, controlling for median household income, the prevalence of four risk factors (obesity, chronic obstructive pulmonary disease, heart attack, stroke), and state policy orientation. Associations between excess death rates and the governor's party were also examined. Findings: States with Republican governors or greater Republican representation in legislatures experienced higher AAMRs during 2015–2021, lower excess death rates during Phase 1 of the COVID‐19 pandemic (weeks ending March 28, 2020, through June 13, 2020), and higher excess death rates in Phases 2 and 3 (weeks ending June 20, 2020, through April 30, 2022; p < 0.05). Most associations lost statistical significance after adjustment for control variables. Conclusions: Mortality was higher in states with Republican governors and greater Republican legislative representation before and during much of the pandemic. Observed associations could be explained by the adverse effects of policy choices, reverse causality (e.g., popularity of Republican candidates in states with lower socioeconomic and health status), or unmeasured factors that predominate in states with Republican leaders. [ABSTRACT FROM AUTHOR]

The article discusses lessons learned from measuring excess deaths in the U.S. during the COVID-19 pandemic. Topics include explanations for the sizable gap in the number of deaths, how states contributed to excess deaths, and percentage of excess deaths by state at height of COVID-19 Delta variant surge.

Objectives. To document the evolution of the US life expectancy disadvantage and regional variation across the US states. Methods. I obtained life expectancy estimates in 2022 from the United Nations, the Human Mortality Database, and the US Mortality Database, and calculated changes in growth rates, US global position (rank), and state-level trends. Results. Increases in US life expectancy slowed from 1950 to 1954 (0.21 years/annum) and 1955 to 1973 (0.10 years/annum), accelerated from 1974 to 1982 (0.34 years/annum), and progressively deteriorated from 1983 to 2009 (0.15 years/annum), 2010 to 2019 (0.06 years/annum), and 2020 to 2021 (–0.97 years/annum). Other countries experienced faster growth in each phase except 1974 to 1982. During 1933 to 2021, 56 countries on 6 continents surpassed US life expectancy. Growth in US life expectancy was slowest in Midwest and South Central states. Conclusions. The US life expectancy disadvantage began in the 1950s and has steadily worsened over the past 4 decades. Dozens of globally diverse countries have outperformed the United States. Causal factors appear to have been concentrated in the Midwest and South. Public Health Implications. Policies that differentiate the United States from other countries and circumstances associated with the Midwest and South may have contributed. (Am J Public Health. 2023;113(9):970–980. https://doi.org/10.2105/AJPH.2023.307310) [ABSTRACT FROM AUTHOR]

This article discusses the importance of disaggregating racial and ethnic data to accurately understand disparities in youth mortality rates in the United States. The authors acknowledge that grouping diverse populations into broad categories can obscure important differences. They explain the historical changes in race categories used in data collection and highlight the challenges of using bridged-race data. The authors emphasize the need for more precise racial and ethnic groups in public health research and note that the CDC has transitioned to providing single-race death counts. They conclude by emphasizing the importance of interpreting racial and ethnic trends over time as institutions adopt more precise categories. [Extracted from the article]

This Viewpoint explores increasing mortality rates in the US due to a variety of causes unrelated to the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

The rise in working-age mortality rates in the United States in recent decades largely reflects stalled declines in cardiovascular disease (CVD) mortality alongside rising mortality from alcohol-induced causes, suicide, and drug poisoning; and it has been especially severe in some U.S. states. Building on recent work, this study examined whether U.S. state policy contexts may be a central explanation. We modeled the associations between working-age mortality rates and state policies during 1999 to 2019. We used annual data from the 1999–2019 National Vital Statistics System to calculate state-level age-adjusted mortality rates for deaths from all causes and from CVD, alcohol-induced causes, suicide, and drug poisoning among adults ages 25–64 years. We merged that data with annual state-level data on eight policy domains, such as labor and taxes, where each domain was scored on a 0–1 conservative-to-liberal continuum. Results show that the policy domains were associated with working-age mortality. More conservative marijuana policies and more liberal policies on the environment, gun safety, labor, economic taxes, and tobacco taxes in a state were associated with lower mortality in that state. Especially strong associations were observed between certain domains and specific causes of death: between the gun safety domain and suicide mortality among men, between the labor domain and alcohol-induced mortality, and between both the economic tax and tobacco tax domains and CVD mortality. Simulations indicate that changing all policy domains in all states to a fully liberal orientation might have saved 171,030 lives in 2019, while changing them to a fully conservative orientation might have cost 217,635 lives. [ABSTRACT FROM AUTHOR]

Objectives. We estimated how many deaths would be averted if the entire population of Virginia experienced the mortality rates of the 5 most affluent counties or cities. Methods. Using census data and vital statistics for the years 1990 through 2006, we applied the mortality rates of the 5 counties/cities with the highest median household income to the populations of all counties and cities in the state. Results. If the mortality rates of the reference population had applied to the entire state, 24.3% of deaths in Virginia from 1990 through 2006 (range=21.8%-28.1%) would not have occurred. An annual mean of 12954 deaths would have been averted (range=10548-14569), totaling 220211 deaths from 1990 through 2006. In some of the most disadvantaged areas of the state, nearly half of deaths would have been averted. Conclusions. Favorable conditions that exist in areas with high household incomes exert a major influence on mortality rates. The corollary--that health suffers when society is exposed to economic stresses--is especially timely amid the current recession. Further research must clarify the extent to which individual-level factors (e.g., earnings, education, race, health insurance) and community characteristics can improve health outcomes. (Am J Public Health. 2010;100:750-755. doi:10.2105/AJPH.2009.165142)

Social factors such as income, education, race and ethnicity have a significant impact on health, but are largely ignored in the formulation of U.S. health policy. The author recommends that the health consequences of social policies need to be included in the development of health policy to ensure better health outcomes.

Importance: The COVID-19 pandemic caused a large decrease in US life expectancy in 2020, but whether a similar decrease occurred in 2021 and whether the relationship between income and life expectancy intensified during the pandemic are unclear.Objective: To measure changes in life expectancy in 2020 and 2021 and the relationship between income and life expectancy by race and ethnicity.Design, Setting, and Participants: Retrospective ecological analysis of deaths in California in 2015 to 2021 to calculate state- and census tract-level life expectancy. Tracts were grouped by median household income (MHI), obtained from the American Community Survey, and the slope of the life expectancy-income gradient was compared by year and by racial and ethnic composition.Exposures: California in 2015 to 2019 (before the COVID-19 pandemic) and 2020 to 2021 (during the COVID-19 pandemic).Main Outcomes and Measures: Life expectancy at birth.Results: California experienced 1 988 606 deaths during 2015 to 2021, including 654 887 in 2020 to 2021. State life expectancy declined from 81.40 years in 2019 to 79.20 years in 2020 and 78.37 years in 2021. MHI data were available for 7962 of 8057 census tracts (98.8%; n = 1 899 065 deaths). Mean MHI ranged from $21 279 to $232 261 between the lowest and highest percentiles. The slope of the relationship between life expectancy and MHI increased significantly, from 0.075 (95% CI, 0.07-0.08) years per percentile in 2019 to 0.103 (95% CI, 0.098-0.108; P < .001) years per percentile in 2020 and 0.107 (95% CI, 0.102-0.112; P < .001) years per percentile in 2021. The gap in life expectancy between the richest and poorest percentiles increased from 11.52 years in 2019 to 14.67 years in 2020 and 15.51 years in 2021. Among Hispanic and non-Hispanic Asian, Black, and White populations, life expectancy declined 5.74 years among the Hispanic population, 3.04 years among the non-Hispanic Asian population, 3.84 years among the non-Hispanic Black population, and 1.90 years among the non-Hispanic White population between 2019 and 2021. The income-life expectancy gradient in these groups increased significantly between 2019 and 2020 (0.038 [95% CI, 0.030-0.045; P < .001] years per percentile among Hispanic individuals; 0.024 [95% CI: 0.005-0.044; P = .02] years per percentile among Asian individuals; 0.015 [95% CI, 0.010-0.020; P < .001] years per percentile among Black individuals; and 0.011 [95% CI, 0.007-0.015; P < .001] years per percentile among White individuals) and between 2019 and 2021 (0.033 [95% CI, 0.026-0.040; P < .001] years per percentile among Hispanic individuals; 0.024 [95% CI, 0.010-0.038; P = .002] years among Asian individuals; 0.024 [95% CI, 0.011-0.037; P = .003] years per percentile among Black individuals; and 0.013 [95% CI, 0.008-0.018; P < .001] years per percentile among White individuals). The increase in the gradient was significantly greater among Hispanic vs White populations in 2020 and 2021 (P < .001 in both years) and among Black vs White populations in 2021 (P = .04).Conclusions and Relevance: This retrospective analysis of census tract-level income and mortality data in California from 2015 to 2021 demonstrated a decrease in life expectancy in both 2020 and 2021 and an increase in the life expectancy gap by income level relative to the prepandemic period that disproportionately affected some racial and ethnic minority populations. Inferences at the individual level are limited by the ecological nature of the study, and the generalizability of the findings outside of California are unknown. [ABSTRACT FROM AUTHOR]

Objectives. We estimated the costs associated with reducing class sizes in kindergarten through grade 3 as well as the effects of small class sizes on selected outcomes such as quality-adjusted life-years and future earnings. Methods. We used multiple data sets to predict changes in the outcomes assessed according to level of educational attainment. We then used a Markov model to estimate future costs and benefits incurred and quality-adjusted life-years gained per additional high school graduate produced over time. Results. From a societal perspective (incorporating earnings and health outcomes), class-size reductions would generate a net cost savings of approximately $168 000 and a net gain of 1.7 quality-adjusted life-years for each high school graduate produced by small classes. When targeted to low-income students, the estimated savings would increase to $196 000 per additional graduate. From a governmental perspective (incorporating public expenditures and revenues), the results of reducing class sizes ranged from savings in costs to an additional cost of $15 000 per quality-adjusted life-year gained. Conclusions. Reducing class sizes may be more cost-effective than most public health and medical interventions. (doi:10.2105/AJPH.2006.105478)

Objectives: Social determinants of health, such as inadequate education, contribute greatly to mortality rates. We examined whether correcting the social conditions that account for excess deaths among individuals with inadequate education might save more lives than medical advances (e.g., new drugss and devices). Methods. Using US vital statistics data fro 1996 through 2002, we applied indirect standardization techniques to estimate the maximum number of averted deaths attributable to medical advances and the number of deaths that would have been averted if mortality rates among adults with lesser education had been the same as those among college-educated adults. Results. Medical advances averted a maximum of 178 193 deaths during the study period. Correcting disparities in education-associated mortality rates would have saved 1 369 335 lives during the same period, a ratio of 8:1. Conclusions. Higher mortality rates among individuals with inadequate education reflect a complex causal pathway and the influence of confounding disparities, but the changes would save more lives than would society's current heavy investment in medical advances. Spending large sums of money on such advances at the expense of social change may be jeopardizing public health. (doi:10.2105/AJPH.2005.084848)

The importance of reordering priorities are illustrated by providing examples from some areas of practice and policy, such as choosing effective services, delivering care, preventing disease and fostering social change. The healthcare leaders, officials and the public they serve should adapt the concept that lives are lost by disproportion and should try to resolve and improve the outcomes.

The US health system spends far more on the 'technology' of care (e.g., drugs, devices) than on achieving equity in its delivery. For 1991 to 2000, we contrasted the number of lives saved by medical advances with the number of deaths attributable to excess mortality among African Americans, Medical advances averted 176633 deaths, but equalizing the mortality rates of Whites and African Americans would have averted 886202 deaths. Achieving equity may do more for health than perfecting the technology of care.

Objectives Since the 1980s, life expectancy at birth (e 0) in the United States has fallen steadily behind that of other high-income countries, widening the U.S. e 0 disadvantage. We estimate how that disadvantage was affected by high mortality rates in 2020, the first full year of the coronavirus disease 2019 pandemic. Methods We contrast male and female e 0 in the United States and 18 peer countries for years 1980, 1995, 2010, 2019, and 2020. Using Arriaga decomposition, we show how differences in age-specific death rates have contributed to U.S. e 0 disadvantages. Results In 2020, U.S. male and female e 0 changed by −2.33 (−2.50, −2.15) and −1.69 (−1.85, −1.53) years, respectively, whereas corresponding changes in peer countries averaged −0.67 (−0.82, −0.51) and −0.50 (−0.65, −0.35) years, respectively. This accelerated a longstanding and widening U.S. e 0 disadvantage relative to its peers, which increased from 3.49 to 5.15 years in males and from 2.78 to 3.97 years in females between 2019 and 2020. Whereas deaths before age 65 accounted for 55% and 40% of declines in U.S. male and female life expectancy, respectively, they accounted for only 24% and 11% of the respective declines in peer countries. Discussion U.S. life expectancy declines in 2020 were larger than in peer countries and involved deaths across a broader age range, particularly among young and middle-aged adults. Both the longstanding U.S. e 0 disadvantage and acute losses of life in 2020 signal the need for systemic policy changes in the United States. [ABSTRACT FROM AUTHOR]