GBD US Health Disparities Collaborators. Cause-specific mortality by county, race, and ethnicity in the USA, 2000-19: a systematic analysis of health disparities

Burden and social distribution of occupational psychosocial exposures in the United States workforce, 2022

OBJECTIVE

To characterize the burden and social distribution of occupational psychosocial exposures in the United States (US).

METHODS

We merged 2022 US employment and demographic data from the Current Population Survey (CPS) with occupational characteristic data from the Occupational Information Network (O*NET), wage data from the Occupational Employment and Wage Statistics Survey, and hours worked from the CPS, to estimate the number and proportion of US workers at risk of exposure to 19 psychosocial hazards. We additionally estimated the number and proportion of US workers over- or underrepresented in exposure burden.

RESULTS

Of the exposures examined, US workers were most commonly employed in occupations with high time pressure (67.5 million US workers exposed; 43.2% US workers exposed), high emotional labor (57.1 million; 36.6%), and low wages (47.8 million; 30.6%). The burden of exposures was uneven across sociodemographic strata, attributable to occupational segregation. The full data set is available online at https://deohs.washington.edu/us-exposure-burden.

CONCLUSIONS

Work-related psychosocial exposures are ubiquitous and should be considered in occupational and public health research, policy, and interventions to reduce the burden of disease and health inequities in the United States.

Lead-associated mortality in the US 1999-2020: a time-stratified analysis of a national cohort

OBJECTIVES

We undertook time-stratified analyses of the National Health and Nutrition Examination Survey in the US to assess time trends (1999-2020) in the associations of blood lead (BL) with blood pressure, mortality, the BL-associated population attributable fraction (PAF).

METHODS

Vital status of participants, 20-79 years old at enrolment, was ascertained via the National Death Index. Regressions, mediation analyses and PAF were multivariable adjusted and standardized to 2020 US Census data.

RESULTS

In time-stratified analyses, BL decreased from 1.76 μg/dl in 1999-2004 to 0.93 μg/dl in 2017-2020, while the proportion of individuals with BL < 1 μg/dl increased from 19.2% to 63.0%. Total mortality was unrelated to BL (hazard ratio (HR) for a fourfold BL increment: 1.05 [95% confidence interval, CI: 0.93-1.17]). The HR for cardiovascular death was 1.44 (1.01-2.07) in the 1999-2000 cycle, but lost significance thereafter. BL was directly related to cardiovascular mortality, whereas the indirect BL pathway via BP was not significant. Low socioeconomic status (SES) was directly related to BL and cardiovascular mortality, but the indirect SES pathway via BL lost significance in 2007-2010. From 1999-2004 to 2017-2020, cardiovascular PAF decreased ( P  < 0.001) from 7.80% (0.17-14.4%) to 2.50% (0.05-4.68%) and number of lead-attributable cardiovascular deaths from 53 878 (1167-99 253) to 7539 (160-14 108).

CONCLUSION

Due to implementation of strict environmental policies, lead exposure is no longer associated with total mortality, and the mildly increased cardiovascular mortality is not associated with blood lead via blood pressure in the United States.

Mortality due to falls by county, age group, race, and ethnicity in the USA, 2000-19: a systematic analysis of health disparities

BACKGROUND

Fall-related mortality has increased rapidly over the past two decades in the USA, but the extent to which mortality varies across racial and ethnic populations, counties, and age groups is not well understood. The aim of this study was to estimate age-standardised mortality rates due to falls by racial and ethnic population, county, and age group over a 20-year period.

METHODS

Redistribution methods for insufficient cause of death codes and validated small-area estimation methods were applied to death registration data from the US National Vital Statistics System and population data from the US National Center for Health Statistics to estimate annual fall-related mortality. Estimates from 2000 to 2019 were stratified by county (n=3110) and five mutually exclusive racial and ethnic populations: American Indian or Alaska Native (AIAN), Asian or Pacific Islander (Asian), Black, Latino or Hispanic (Latino), and White. Estimates were corrected for misreporting of race and ethnicity on death certificates using published misclassification ratios. We masked (ie, did not display) estimates for county and racial and ethnic population combinations with a mean annual population of less than 1000. Age-standardised mortality is presented for all ages combined and for age groups 20-64 years (younger adults) and 65 years and older (older adults).

FINDINGS

Nationally, in 2019, the overall age-standardised fall-related mortality rate for the total population was 13·4 deaths per 100 000 population (95% uncertainty interval 13·3-13·6), an increase of 65·3% (61·9-68·8) from 8·1 deaths per 100 000 (8·0-8·3) in 2000, with the largest increases observed in older adults. Fall-related mortality at the national level was highest across all years in the AIAN population (in 2019, 15·9 deaths per 100 000 population [95% uncertainty interval 14·0-18·2]) and White population (14·8 deaths per 100 000 [14·6-15·0]), and was about half as high among the Latino (8·7 deaths per 100 000 [8·3-9·0]), Black (8·1 deaths per 100 000 [7·9-8·4]), and Asian (7·5 deaths per 100 000 [7·1-7·9]) populations. The disparities between racial and ethnic populations varied widely by age group, with mortality among younger adults highest for the AIAN population and mortality among older adults highest for the White population. The national-level patterns were observed broadly at the county level, although there was considerable spatial variation across ages and racial and ethnic populations. For younger adults, among almost all counties with unmasked estimates, there was higher mortality in the AIAN population than in all other racial and ethnic populations, while there were pockets of high mortality in the Latino population, particularly in the Mountain West region. For older adults, mortality was particularly high in the White population within clusters of counties across states including Florida, Minnesota, and Wisconsin.

INTERPRETATION

Age-standardised mortality due to falls increased over the study period for each racial and ethnic population and almost every county. Wide variation in mortality across geography, age, and race and ethnicity highlights areas and populations that might benefit most from efficacious fall prevention interventions as well as additional prevention research.

FUNDING

US National Institutes of Health (Intramural Research Program, National Institute on Minority Health and Health Disparities; National Heart, Lung, and Blood Institute; Intramural Research Program, National Cancer Institute; National Institute on Aging; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Office of Disease Prevention; and Office of Behavioral and Social Sciences Research).

The burden of cirrhosis mortality by county, race, and ethnicity in the USA, 2000-19: a systematic analysis of health disparities

BACKGROUND

Cirrhosis is responsible for substantial health and economic burden in the USA. Reducing this burden requires better understanding of how rates of cirrhosis mortality vary by race and ethnicity and by geographical location. This study describes rates and trends in cirrhosis mortality for five racial and ethnic populations in 3110 US counties from 2000 to 2019.

METHODS

We estimated cirrhosis mortality rates by county, race and ethnicity, and year (2000-19) using previously validated small-area estimation methods, death registration data from the US National Vital Statistics System, and population data from the US National Center for Health Statistics. Five racial and ethnic populations were considered: American Indian or Alaska Native (AIAN), Asian or Pacific Islander (Asian), Black, Latino or Hispanic (Latino), and White. Cirrhosis mortality rate estimates were age-standardised using the age distribution from the 2010 US census as the standard. For each racial and ethnic population, estimates are presented for all counties with a mean annual population greater than 1000.

FINDINGS

From 2000 to 2019, national-level age-standardised cirrhosis mortality rates decreased in the Asian (23·8% [95% uncertainty interval 19·6-27·8], from 9·4 deaths per 100 000 population [8·9-9·9] to 7·1 per 100 000 [6·8-7·5]), Black (22·8% [20·6-24·8], from 19·8 per 100 000 [19·4-20·3] to 15·3 per 100 000 [15·0-15·6]), and Latino (15·3% [13·3-17·3], from 26·3 per 100 000 [25·6-27·0] to 22·3 per 100 000 [21·8-22·8]) populations and increased in the AIAN (39·3% [32·3-46·4], from 45·6 per 100 000 [40·6-50·6] to 63·5 per 100 000 [57·2-70·2] in 2000 and 2019, respectively) and White (25·8% [24·2-27·3], from 14·7 deaths per 100 000 [14·6-14·9] to 18·5 per 100 000 [18·4-18·7]) populations. In all years, cirrhosis mortality rates were lowest among the Asian population, highest among the AIAN population, and higher in males than females for each racial and ethnic population. The degree of heterogeneity in county-level cirrhosis mortality rates varied by racial and ethnic population, with the narrowest IQR in the Asian population (median 8·0 deaths per 100 000, IQR 6·4-10·4) and the widest in the AIAN population (55·1, 30·3-78·8). Cirrhosis mortality increased over the study period in almost all counties for the White (2957 [96·9%] of 3051 counties) and AIAN (421 [88·8%] of 474) populations, but in a smaller proportion of counties for the Asian, Black, and Latino populations. For all racial and ethnic populations, cirrhosis mortality rates increased in more counties between 2000 and 2015 than between 2015 and 2019.

INTERPRETATION

Cirrhosis mortality increased nationally and in many counties from 2000 to 2019. Although the magnitude of racial and ethnic disparities decreased in some places, disparities nonetheless persisted, and mortality remained high in many locations and communities. Our findings underscore the need to implement targeted and locally tailored programmes and policies to reduce the burden of cirrhosis at both the national and local level.

FUNDING

US National Institutes of Health (Intramural Research Program, National Institute on Minority Health and Health Disparities; National Heart, Lung, and Blood Institute; Intramural Research Program, National Cancer Institute; National Institute on Aging; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Office of Disease Prevention; and Office of Behavioral and Social Sciences Research).

Area deprivation index and social vulnerability index in Milwaukee County: Impact on hospital outcomes after traumatic injuries

BACKGROUND

Predisposing factors for traumatic injuries are complex and variable. Neighborhood environments may influence injury mechanism or outcomes. The Social Vulnerability Index (SVI) identifies areas at risk for emergencies; Area Deprivation Index (ADI) measures socioeconomic disadvantage. The objective was to assess the impact of SVI or ADI on hospital length of stay (LOS) and mortality for injured patients to determine whether SVI or ADI indicated areas where injury prevention may be most impactful.

METHODS

Adult patients who resided in Milwaukee County and were treated for injuries from 2015 to 2022 at a level I trauma center were included. Patients' addresses were geocoded and merged with 2020 state-level SVI and ADI measures. SVI ranks census tracts 0-100 from least to most vulnerable. ADI ranks census block groups 1-10 from least to most disadvantaged. ADI and SVI rankings were converted to deciles. Statistical analyses included descriptive statistics, chi-square tests, and regression models for LOS and in-hospital mortality, adjusted for either SVI or ADI within separate models, age, sex, race or ethnicity, mechanism of injury (MOI), injury severity score (ISS).

RESULTS

14,542 patients were included; 63 % were male. Mean total hospital LOS was 6.4 ± 9.8 days, and in-hospital mortalities occurred in 5.2 % of patients. Based on SVI and ADI, 5,280 (36 %) patients resided in high vulnerability areas and 5,576 (39 %) lived in highly disadvantaged areas, respectively. After adjusting for patient factors, SVI deciles #6, 9, 10 were associated with increased hospital LOS, and SVI decile #5 was associated with in-hospital mortality (OR = 2.22, 95 %CI:1.06-4.63; p = 0.034). When adjusted for ADI, the 7th-10th deciles were associated with increased hospital LOS. Greater age and ISS were associated with increased hospital LOS and mortality when adjusted for SVI and ADI.

CONCLUSIONS

SVI and ADI identified a similar proportion of patients in high vulnerability or disadvantaged areas. Higher SVI and ADI deciles were associated with longer hospital LOS, and only the 5th SVI decile was associated with in-hospital mortality. Highly disadvantaged or vulnerable areas may have a longer LOS, but SVI and ADI have limited influence on trauma mortality. Continued research on neighborhood and community factors and trauma outcomes is needed.

Continuous Glucose Monitor: Reclaiming Type 2 Diabetes Self-efficacy and Mitigating Disparities

Context

The rise in continuous glucose monitor (CGM) use has been characterized by widening disparities between the least and most socially marginalized. Given access barriers, there is limited CGM patient experience information that is inclusive of those with type 2 diabetes mellitus from socially marginalized backgrounds.

Objective

To understand the CGM usage experience in the primary care setting across a US Medicaid population with type 2 diabetes at federally qualified health centers.

Methods

This qualitative study used semi-structured phone interviews with 28 English- or Spanish-speaking participants prescribed the CGM who were enrolled in a US Medicaid program that subsidized CGMs. Audio recordings of interviews were transcribed and analyzed by reflective thematic analysis.

Results

Twenty-eight participants (75% female, median age 56 years with interquartile-range 48-60 years) were interviewed. Participants were from different racial/ethnic backgrounds: 21% non-Hispanic White, 57% Hispanic, and 18% non-Hispanic Black. Participants primarily spoke English (68%) or Spanish (32%), and 53% reported 9 or fewer years of formal education. We identified 6 major themes: initial expectations and overcoming initiation barriers, convenience and ease promote daily use, increased knowledge leads to improved self-management, collaboration with provider and clinical team, improved self-reported outcomes, and barriers and burdens are generally tolerated.

Conclusion

CGM use was experienced as easy to understand and viewed as a tool for diabetes self-efficacy. Expanded CGM access for socially marginalized patients with type 2 diabetes can enhance diabetes self-management to help mitigate diabetes outcome disparities.

Advancing Health Disparities Science Through Social Epigenomics Research

Importance

Although scientific and technological discoveries have improved the health of the US population overall, racial and ethnic minority (American Indian and Alaska Native, Asian, Black or African American, Hispanic or Latino, or Native Hawaiian and Pacific Islander persons) and socioeconomically disadvantaged populations continue to experience a disproportionate burden of disease and other adverse health conditions. To better understand and address the drivers of health disparities and inform the development of effective interventions, integrative mechanistic studies examining the dynamic interplay of multiple factors across the life course and even between generations are needed. The emerging field of social epigenomics, which seeks to link social stressors and protective factors to health status through the examination of epigenomic modifications of various biological pathways, is one promising area of research contributing to this need.

Observations

This thematic issue of JAMA Network Open highlights new findings from the grantees of the National Institutes of Health (NIH) Social Epigenomics Program. These findings, taken together, examine the associations of a variety of social, behavioral, and structural factors throughout the life course with epigenomic and other biological changes among populations experiencing health disparities. The studies link early-life exposures, structural inequities, and behavioral factors and interventions to epigenetic changes, and in some studies, later health outcomes. While there is still more work to be done to fully characterize the mechanistic pathways linking social exposures to epigenetic changes and health outcomes, the body of work presented in this special issue represents solid progress toward this goal.

Conclusions and Relevance

The studies highlighted in this special issue demonstrate important scientific progress in the complex integration of social determinants of health and health disparities with biological pathways and health outcomes to improve understanding of the mechanisms underlying health disparities among various underserved populations. Continued progress remains important in integrating different disciplines to transform the field of health disparities research.

Normal Lung Function and Mortality in World Trade Center Responders and National Health and Nutrition Examination Survey III Participants

Rationale: Low FEV1 is a biomarker of increased mortality. The association of normal lung function and mortality is not well described. Objectives: To evaluate the FEV1-mortality association among participants with normal lung function. Methods: A total of 10,999 Fire Department of the City of New York (FDNY) responders and 10,901 Third National Health and Nutrition Examination Survey (NHANES III) participants, aged 18-65 years with FEV1 ⩾80% predicted, were analyzed, with FEV1 percent predicted calculated using Global Lung Function Initiative Global race-neutral reference equations. Mortality data were obtained from linkages to the National Death Index. Cox proportional hazards models estimated the association between FEV1 and all-cause mortality, controlling for age, sex, race/ethnicity, smoking history, and, for FDNY, work assignment. Cohorts were followed for a maximum of 20.3 years. Measurements and Main Results: We observed 504 deaths (4.6%) of 10,999 for FDNY and 1,237 deaths (9.4% [weighted]) of 10,901 for NHANES III. Relative to FEV1 ⩾120% predicted, mortality was significantly higher for FEV1 100-109%, 90-99%, and 80-89% predicted in the FDNY cohort. In the NHANES III cohort, mortality was significantly higher for FEV1 90-99% and 80-89% predicted. Each 10% higher predicted FEV1 was associated with 15% (hazard ratio, 0.85; 95% confidence interval, 0.80-0.91) and 23% (hazard ratio, 0.77; 95% confidence interval, 0.71-0.84) lower mortality for FDNY and NHANES III, respectively. Conclusions: In both cohorts, higher FEV1 is associated with lower mortality, suggesting higher FEV1 is a biomarker of better health. These findings demonstrate that a single cross-sectional measurement of FEV1 is predictive of mortality over two decades, even when FEV1 is in the normal range.

Health equity assessment of machine learning performance (HEAL): a framework and dermatology AI model case study

Background

Artificial intelligence (AI) has repeatedly been shown to encode historical inequities in healthcare. We aimed to develop a framework to quantitatively assess the performance equity of health AI technologies and to illustrate its utility via a case study.

Methods

Here, we propose a methodology to assess whether health AI technologies prioritise performance for patient populations experiencing worse outcomes, that is complementary to existing fairness metrics. We developed the Health Equity Assessment of machine Learning performance (HEAL) framework designed to quantitatively assess the performance equity of health AI technologies via a four-step interdisciplinary process to understand and quantify domain-specific criteria, and the resulting HEAL metric. As an illustrative case study (analysis conducted between October 2022 and January 2023), we applied the HEAL framework to a dermatology AI model. A set of 5420 teledermatology cases (store-and-forward cases from patients of 20 years or older, submitted from primary care providers in the USA and skin cancer clinics in Australia), enriched for diversity in age, sex and race/ethnicity, was used to retrospectively evaluate the AI model's HEAL metric, defined as the likelihood that the AI model performs better for subpopulations with worse average health outcomes as compared to others. The likelihood that AI performance was anticorrelated to pre-existing health outcomes was estimated using bootstrap methods as the probability that the negated Spearman's rank correlation coefficient (i.e., "R") was greater than zero. Positive values of R suggest that subpopulations with poorer health outcomes have better AI model performance. Thus, the HEAL metric, defined as p (R >0), measures how likely the AI technology is to prioritise performance for subpopulations with worse average health outcomes as compared to others (presented as a percentage below). Health outcomes were quantified as disability-adjusted life years (DALYs) when grouping by sex and age, and years of life lost (YLLs) when grouping by race/ethnicity. AI performance was measured as top-3 agreement with the reference diagnosis from a panel of 3 dermatologists per case.

Findings

Across all dermatologic conditions, the HEAL metric was 80.5% for prioritizing AI performance of racial/ethnic subpopulations based on YLLs, and 92.1% and 0.0% respectively for prioritizing AI performance of sex and age subpopulations based on DALYs. Certain dermatologic conditions were significantly associated with greater AI model performance compared to a reference category of less common conditions. For skin cancer conditions, the HEAL metric was 73.8% for prioritizing AI performance of age subpopulations based on DALYs.

Interpretation

Analysis using the proposed HEAL framework showed that the dermatology AI model prioritised performance for race/ethnicity, sex (all conditions) and age (cancer conditions) subpopulations with respect to pre-existing health disparities. More work is needed to investigate ways of promoting equitable AI performance across age for non-cancer conditions and to better understand how AI models can contribute towards improving equity in health outcomes.

Funding

Google LLC.

Hypertension: Causes and Consequences of Circadian Rhythms in Blood Pressure

Hypertension is extremely common, affecting approximately 1 in every 2 adults globally. Chronic hypertension is the leading modifiable risk factor for cardiovascular disease and premature mortality worldwide. Despite considerable efforts to define mechanisms that underlie hypertension, a potentially major component of the disease, the role of circadian biology has been relatively overlooked in both preclinical models and humans. Although the presence of daily and circadian patterns has been observed from the level of the genome to the whole organism, the functional and structural impact of biological rhythms, including mechanisms such as circadian misalignment, remains relatively poorly defined. Here, we review the impact of daily rhythms and circadian systems in regulating blood pressure and the onset, progression, and consequences of hypertension. There is an emphasis on the impact of circadian biology in relation to vascular disease and end-organ effects that, individually or in combination, contribute to complex phenotypes such as cognitive decline and the loss of cardiac and brain health. Despite effective treatment options for some individuals, control of blood pressure remains inadequate in a substantial portion of the hypertensive population. Greater insight into circadian biology may form a foundation for novel and more widely effective molecular therapies or interventions to help in the prevention, treatment, and management of hypertension and its related pathophysiology.

Burden of liver cancer mortality by county, race, and ethnicity in the USA, 2000-19: a systematic analysis of health disparities

BACKGROUND

Understanding how specific populations are affected by liver cancer is important for identifying priorities, policies, and interventions to mitigate health risks and reduce disparities. This study aims to provide comprehensive analysis of rates and trends in liver cancer mortality for different racial and ethnic populations in the USA nationally and at the county level from 2000 to 2019.

METHODS

We applied small-area estimation methods to death registration data from the US National Vital Statistics System and population data from the US National Center for Health Statistics to estimate liver cancer mortality rates by county, racial and ethnic population, and year (2000-19) in the USA. Race and ethnicity were categorised as non-Latino and non-Hispanic American Indian or Alaska Native (AIAN), non-Latino and non-Hispanic Asian or Pacific Islander (Asian), non-Latino and non-Hispanic Black (Black), Latino or Hispanic (Latino), and non-Latino and non-Hispanic White (White). Estimates were adjusted using published misclassification ratios to correct for inaccuracies in race or ethnicity as recorded on death certificates, and then age-standardised. Mortality rate estimates are presented for all county and racial and ethnic population combinations with a mean annual population greater than 1000.

FINDINGS

Nationally, the age-standardised liver cancer mortality rate increased between the years 2000 (4·2 deaths per 100 000 population [95% uncertainty interval 4·1-4·3]) and 2016 (6·0 per 100 000 [5·9-6·1]), followed by a stabilisation in rates from 2016 to 2019 (6·1 per 100 000 [6·0-6·2]). Similar trends were observed across the AIAN, Black, Latino, and White populations, whereas the Asian population showed an overall decrease across the 20-year study period. Qualitatively similar trends were observed in most counties; however, the mortality rate and the rate of change varied substantially across counties, both within and across racial and ethnic populations. For the 2016-19 period, mortality continued to increase at a substantial rate in some counties even while it stabilised nationally. Nationally, the White population had the lowest mortality rate in all years, while the racial and ethnic population with the highest rate changed from the Asian population in 2000 to the AIAN population in 2019. Racial and ethnic disparities were substantial: in 2019, mortality was highest in the AIAN population (10·5 deaths per 100 000 [9·1-12·0]), notably lower for the Asian (7·5 per 100 000 [7·1-7·9]), Black (7·6 per 100 000 [7·3-7·8]), and Latino (7·7 per 100 000 [7·5-8·0]) populations, and lowest for the White population (5·5 [5·4-5·6]). These racial and ethnic disparities in mortality were prevalent throughout the country: in 2019, mortality was higher in minoritised racial and ethnic populations than in the White population living in the same county in 408 (87·7%) of 465 counties with unmasked estimates for the AIAN population, 604 (90·6%) of 667 counties for the Asian population, 1207 (81·2%) of 1486 counties for the Black population, and 1073 (73·0%) of 1469 counties for the Latino population.

INTERPRETATION

Although the plateau in liver cancer mortality rates in recent years is encouraging, mortality remains too high in many locations throughout the USA, particularly for minoritised racial and ethnic populations. Addressing population-specific risk factors and differences in access to quality health care is essential for decreasing the burden and disparities in liver cancer mortality across racial and ethnic populations and locations.

FUNDING

US National Institutes of Health (Intramural Research Program, National Institute on Minority Health and Health Disparities; National Heart, Lung, and Blood Institute; Intramural Research Program, National Cancer Institute; National Institute on Aging; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Office of Disease Prevention; and Office of Behavioral and Social Sciences Research).

Ending Race-Conscious College Admissions and Its Potential Impact on the Infectious Disease Workforce

On 29 June 2023, the Supreme Court of the United States ruled that race-conscious consideration for college admission is unconstitutional. We discuss the consequences of this ruling on the delivery of equitable care and health system readiness to combat current and emerging pandemics. We propose strategies to mitigate the negative impact of this ruling on diversifying the infectious disease (ID) workforce.

Life Expectancy and Causes of Premature Death by Subgroup for Community-Based Action in Marin County, California, 2017-2021

INTRODUCTION

Marin is a medium-sized county in California's San Francisco Bay Area. Despite its historically higher-than-average life expectancy and socioeconomic level, known economic and health disparities by race, ethnicity, and geography became more visible during the COVID-19 pandemic.  Methods: We calculated life expectancy, measured years of potential life lost (YPLLs), and described premature mortality for the five years of 2017-2021 by race, ethnicity, census tract, and resource level (as measured by Healthy Places Index [HPI]) to provide data on inequities to guide community-centered action to reduce premature mortality.  Results: Life expectancy for the county was 85.2 years. The non-Hispanic African American/Black population experienced the lowest life expectancy of 77.1 years, 11.6 years lower than the non-Hispanic Asian population which had the highest life expectancy (88.7 years). There was a 14.9-year difference in life expectancy between the census tracts with the lowest (77.1 years) and highest (92.0 years) estimates. We found a moderate, positive association between census tract resource level (HPI) and life expectancy (r=0.58, p<0.01). The leading causes of premature death were cancer, diseases of the circulatory system, and accidental overdoses, with variation by subgroup.  Conclusion: These data highlight health disparities that persist in Marin County and can inform data-driven public health strategies to narrow gaps in longevity between communities.

Racial/Ethnic disparities in the chains of morbid events leading to death: network analysis of US multiple cause of death data

Multiple-cause-of-death data have not yet been applied to the study of racial/ethnic differences in causal chains of events leading to death, nor they have been used to examine racial/ethnic disparities in cause-of-death certification. We use publicly available 2019 US death certificate data to reassemble chains of morbid events leading to death. From them, we construct and analyze directed multiple cause of death networks by race and sex of deaths aged 60+. Three perspectives to measure disparities are employed: (i) relative prevalence of cause-of-death-pairs, (ii) strength of associations between diseases, (iii) similarities in transition matrices. Non-Hispanic Blacks (NHB) had overall lower prevalence of cause of death pairs, Hispanics (HIS) were burdened more by alcohol-related mortality and Asian and Pacific Islanders (API) exceeded in transitions to cerebrovascular diseases. Lower similarity was observed in transitions to external causes of death, dementia and Alzheimer's disease, pulmonary heart diseases, interstitial respiratory diseases, and diseases of the liver. After excluding rare diseases, the similarity further decreased for ill-defined conditions, diabetes mellitus, other cardiovascular diseases, diseases of the pleura, and anemia. To sum up, races/ethnicities not only vary in structure and timing of death but they differ in morbid processes leading to death as well.

The burden of stomach cancer mortality by county, race, and ethnicity in the USA, 2000-2019: a systematic analysis of health disparities

Background

There are persistent disparities in stomach cancer mortality among racial-ethnic groups in the USA, but the extent to which these patterns vary geographically is not well understood. This analysis estimated age-standardised mortality for five racial-ethnic groups, in 3110 USA counties over 20 years, to describe spatial-temporal variations in stomach cancer mortality and disparities between racial-ethnic groups.

Methods

Redistribution methods for insufficient cause of death codes and validated small area estimation methods were applied to death registration data from the US National Vital Statistics System and population data from the US National Center for Health Statistics to estimate annual stomach cancer mortality rates. Estimates were stratified by county and racial-ethnic group (non-Latino and non-Hispanic [NL] American Indian or Alaska Native [AIAN], NL Asian or Pacific Islander [Asian], NL Black [Black], Latino or Hispanic [Latino], and NL White [White]) from 2000 to 2019. Estimates were corrected for misreporting of racial-ethnic group on death certificates using published misclassification ratios. We masked (ie, did not display) estimates for county and racial-ethnic group combinations with a mean annual population of less than 1000; thus, we report estimates for 3079 (of 3110) counties for the total population, and 474, 667, 1488, 1478, and 3051 counties for the AIAN, Asian, Black, Latino, and White populations, respectively.

Findings

Between 2000 and 2019, national age-standardised stomach cancer mortality was lowest among the White population in every year. Nationally, stomach cancer mortality declined for all racial-ethnic groups across this time period, with the most rapid declines occurring among the Asian (percent decline 48.3% [45.1-51.1]) and Black populations (42.6% [40.2-44.6]). Mortality among the other racial-ethnic groups declined more moderately, decreasing by 36.7% (35.3-38.1), 35.1% (32.2-37.7), and 31.6% (23.9-38.0) among the White, Latino, and AIAN populations, respectively. Similar patterns were observed at the county level, although with wide geographic variation. In 2019, a majority of counties had higher mortality rates among minoritised racial-ethnic populations compared to the White population: 81.1% (377 of 465 counties with unmasked estimates for both racial-ethnic groups) among the AIAN population, 88.2% (1295 of 1469) among the Latino population, 99.4% (663 of 667) among the Asian population, and 99.9% (1484 of 1486) among the Black population. However, the size of these disparities ranged widely across counties, with the largest range from 0.3 to 17.1 among the AIAN population.

Interpretation

Stomach cancer mortality has decreased substantially across populations and geographies in the USA. However, disparities in stomach cancer mortality among racial-ethnic groups are widespread and have persisted over the last two decades. Local-level data are crucial to understanding the scope of this unequal burden among minoritised groups in the USA.

Funding

National Institute on Minority Health and Health Disparities; National Heart, Lung, and Blood Institute; National Cancer Institute; National Institute on Aging; National Institute of Arthritis and Musculoskeletal and Skin Diseases; Office of Disease Prevention; and Office of Behavioral and Social Sciences Research, National Institutes of Health (contract #75N94019C00016).