Background: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 provides a comprehensive assessment of health and risk factor trends.

Objective: Describe the burden of diseases, injuries, and risk factors in the United States and compare across states.

Methods: The study leveraged multiple data sources to produce comprehensive estimates that are comparable across states, years, ages, and sexes. Trends in life expectancy (LE), mortality, years lived with disability (YLDs), and risk factor exposure and attributable burden were analyzed.

Results: In 2023, the US ranked 52nd in LE and 95th in healthy life expectancy (HALE) among the 204 countries included in the GBD, a decline since 1990. Age-standardized mortality rates declined between 1990 and 2023 for many leading causes of death, most notably cardiovascular diseases and neoplasms, but the rates of decline slowed after 2010. Mortality and YLD rates varied among states, with Hawaii having the lowest age-standardized mortality rate (435 per 100,000) and YLD rate (12,478) and West Virginia having the highest (737 and 15,669, respectively) in 2023. Low back pain was the leading cause of YLDs in 2023 followed by drug use disorders. High systolic blood pressure, high body mass index, and smoking had the highest age-standardized rate of attributable deaths in 2023.

Conclusions: GBD 2023 provides valuable information for US policy makers, health-care professionals, and researchers to prioritize interventions, allocate resources effectively, and evaluate the impact of health policies and programs.

Background: Mortality rates vary widely across racial and ethnic populations and locations, and these patterns vary by cause and over time. Comprehensive, timely estimates of cause-specific mortality at the county level and stratified by race and ethnicity are needed to fully understand and better address racial and ethnic and place-based disparities in mortality.

Objective: To estimate mortality by county, race and ethnicity, and year (2000–2023) for approximately 175 causes, and to describe intersecting patterns of racial and ethnic and place-based disparities in mortality by cause.

Methods: We applied small area estimation models to data from the National Vital Statistics System to estimate mortality by cause, county, race and ethnicity, sex, and age. We adjusted the estimated mortality rates to correct for misreported race and ethnicity on death certificates.

Results: Analysis of data through 2019 revealed substantial disparities for most causes of death. Many causes share the same pattern of racial and ethnic disparity: substantially elevated mortality rates for the American Indian or Alaska Native and Black populations compared to the White population, and substantially lower mortality rates for the Asian and Latino populations; however, there are exceptions, and the ordering and size of the disparity varied substantially by cause of death. Large place-based disparities are also ubiquitous, but the spatial pattern of mortality varied widely among causes.

Conclusions: Action is needed to reduce the pervasive place-based and racial and ethnic disparities in mortality and to address the specific mechanisms driving disparities for particular causes of death.

Background: Examining lung cancer mortality trends at the county level would better inform our understanding of racial, ethnic, and geographic differences in the USA.

Objective: To analyze lung cancer mortality trends by race and/or ethnicity (American Indian or Alaska Native [AIAN], Asian, Black, Latino, and White), sex, and county.

Methods: Data from the National Vital Statistics System and National Center for Health Statistics (2000–2019) were used to estimate age-standardized lung cancer mortality in 3,110 counties, adjusted for misclassification.

Results: From 2000 to 2019, lung cancer mortality decreased from 68.3 (95% uncertainty interval [UI]: 67.9-68.7) to 42.5 (42.3-42.8) deaths per 100,000. Males experienced a larger decrease (44.8%) than females (29.4%). Similar patterns were observed at the county level, with considerable geographic variation within and across racial and/or ethnic populations. In 2019, higher rates among Black and White populations were observed in the Mississippi River watershed and Appalachia and among AIAN populations in the upper Midwest, Northeast, North Carolina, Oklahoma, and Kansas. From 2000 to 2019, for males and females combined, lung cancer mortality rates increased in 57 counties (12.0%) for the AIAN population, with a median increase of 7.5 deaths per 100,000. Increases in counties were less common among Asian (n=36, 5.4%), Latino (n=36, 2.4%), and White (n=1) populations, while no county showed an increase for Black individuals.

Conclusions: Despite marked reductions in lung cancer mortality, geographic and racial and/or ethnic differences persist, which emphasizes the need for targeted interventions to further improve lung cancer outcomes for all populations.

Background: Chronic diseases pose significant public health challenges in the USA. Recent confirmation of stalled progress in reducing mortality rates and related health disparities calls for innovative, community-driven solutions. The NIH-wide CEAL Initiative has built a community-engaged research (CEnR) platform to develop and test community intervention strategies to address this challenge.

Objective: Describe the CEAL platform and explore its role in supporting communities to improve health.

Methods: CEAL comprises regional research teams (RRT) in 21 states, Puerto Rico, the District of Columbia, and related research programs. The 21 RRTs conduct a multi-year effort on rigorous community interventions addressing upstream drivers of chronic conditions and risks. A consultative resource (CEACR) serves as a channel for soliciting contextualized community insights and best practices for promoting inclusive participation in research. A CEnR focus on strengthening community resilience to the impacts of climate on health (ACE-CH). A CEnR network for primary care research (NCPCR) is testing the feasibility of using a data ecosystem to support the execution of focuses on randomized controlled clinical trial in uncontrolled hypertension and diabetes complicated by social risks. An Enrichment Initiative in indigenous communities (AI/AN-NHP-EI) is tackling upstream risks related to diet, physical activity, and community social risks that impact chronic cardiometabolic conditions. Two community implementation programs are addressing maternal health (MH-CIP) and strategies to improve pregnancy outcomes (IMPROVE-CIP).

Results: CEAL programs use CEnR to grow trust in science and empower communities to improve their health.

Conclusions: CEAL programs play crucial roles in addressing the burden of chronic diseases.