US County-Level Trends in Mortality Rates for Major Causes of Death, 1980-2014

Life expectancy and geographic variation in mortality: an observational comparison study of six high-income Anglophone countries

OBJECTIVE

To compare life expectancy levels and within-country geographic variation in life expectancy across six high-income Anglophone countries between 1990 and 2018.

DESIGN

Demographic analysis using aggregated mortality data.

SETTING

Six high-income Anglophone countries (USA, UK, Canada, Australia, Ireland and New Zealand), by sex, including an analysis of subnational geographic inequality in mortality within each country.

POPULATION

Data come from the Human Mortality Database, the WHO Mortality Database and the vital statistics agencies of six high-income Anglophone countries.

MAIN OUTCOME MEASURES

Life expectancy at birth and age 65; age and cause of death contributions to life expectancy differences between countries; index of dissimilarity for within-country geographic variation in mortality.

RESULTS

Among six high-income Anglophone countries, Australia is the clear best performer in life expectancy at birth, leading its peer countries by 1.26-3.95 years for women and by 0.97-4.88 years for men in 2018. While Australians experience lower mortality across the age range, most of their life expectancy advantage accrues between ages 45 and 84. Australia performs particularly well in terms of mortality from external causes (including drug- and alcohol-related deaths), screenable/treatable cancers, cardiovascular disease and influenza/pneumonia and other respiratory diseases compared with other countries. Considering life expectancy differences across geographic regions within each country, Australia tends to experience the lowest levels of inequality, while Ireland, New Zealand and the USA tend to experience the highest levels.

CONCLUSIONS

Australia has achieved the highest life expectancy among Anglophone countries and tends to rank well in international comparisons of life expectancy overall. It serves as a potential model for lower-performing countries to follow to reduce premature mortality and inequalities in life expectancy.

Binge drinking at time of bariatric surgery is associated with liver disease, suicides, and increases long-term mortality

BACKGROUND AND AIMS

Alcohol use disorder has been reported in patients undergoing bariatric procedures, but the pattern of alcohol consumption has not been evaluated. We investigated the prevalence, risk factors, and impact of binge drinking (BD) at the time of surgery and during follow-up.

METHODS

A prospective, longitudinal study of subjects undergoing bariatric surgery was included in the LABS-2 registry between 2006 and 2009. Participants with AUDIT questionnaire at the time of surgery and a minimum of 12 months follow-up were included. BD was defined as consuming ≥5 drinks on at least 1 occasion in the previous month. Liver biopsies were obtained during bariatric procedures in not all cases. Survival analysis was performed with the adjusted Cox regression model and competing risk.

RESULTS

A total of 2257 subjects were included, with a median follow-up of 79 months. The prevalence of BD at time of surgery was 12%, and it raised up to 23% during follow-up. Patients with BD predominantly had a binge eating disorder (OR=1.35 [95% CI: 1.04-1.76]), regularly consumed fast food [OR=1.4 (95% CI: 1.07-1.85)] and used other drugs (OR=2.65 [95% CI: 1.74-4.04]). Within liver biopsies evaluation, BD showed higher hepatic iron deposits (OR=3.00 [95% CI: 1.25-7.21]). BD at the time of surgery was associated with a higher risk of BD during follow-up (OR=10.49 [95% CI: 7.86-14.00]) and long-term mortality (HR: 3.21 [95% CI: 1.67-6.18]). Specific causes of death in these patients with BD were liver disease (p=0.020), suicide (p=0.015), neoplasms (p=0.034), and respiratory (p=0.025).

CONCLUSIONS

The prevalence of BD in patients undergoing bariatric surgery is high and increases the risk of postoperative liver disease, suicides, and long-term mortality.

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).

Digital twin mathematical models suggest individualized hemorrhagic shock resuscitation strategies

BACKGROUND

Optimizing resuscitation to reduce inflammation and organ dysfunction following human trauma-associated hemorrhagic shock is a major clinical hurdle. This is limited by the short duration of pre-clinical studies and the sparsity of early data in the clinical setting.

METHODS

We sought to bridge this gap by linking preclinical data in a porcine model with clinical data from patients from the Prospective, Observational, Multicenter, Major Trauma Transfusion (PROMMTT) study via a three-compartment ordinary differential equation model of inflammation and coagulation.

RESULTS

The mathematical model accurately predicts physiologic, inflammatory, and laboratory measures in both the porcine model and patients, as well as the outcome and time of death in the PROMMTT cohort. Model simulation suggests that resuscitation with plasma and red blood cells outperformed resuscitation with crystalloid or plasma alone, and that earlier plasma resuscitation reduced injury severity and increased survival time.

CONCLUSIONS

This workflow may serve as a translational bridge from pre-clinical to clinical studies in trauma-associated hemorrhagic shock and other complex disease settings.

Geographical association of biodiversity with cancer and cardiovascular mortality rates: analysis of 39 distinct conditions

Background

Biodiversity has been recognized as a positive contributor to human health and wellbeing. Cardiovascular disease and cancer are the two most significant global health burdens, and understanding their relationship with biodiversity forms an essential step toward promoting biodiversity conservation and human health.

Methods

The species richness of birds is a common indicator of biodiversity, given their vast numbers, distinctive distribution, and acute sensitivity to environmental disturbances. This ecological study utilized avian observation data derived from the eBird database, human health data from the International Health Metrics and Evaluation, and county-level statistics, including population characteristics, socio-economics, healthcare service, residential environment, and geographic and climatic characteristics in 2014. We aimed to extensively explore the individual associations between biodiversity (i.e., avian species richness) and age-standardized cause-specific mortalities for different types of cancers (29 conditions) and cardiovascular diseases (10 conditions) across the United States (US).

Results

Our multiple regression analyses that adjusted for a variety of socio-demographic and geographical factors showed that increased rarefied species richness of birds was associated with reduced mortality rates for three of the five most common cancers, namely, tracheal, bronchus, and lung cancer, breast cancer (in women only), and colon and rectal cancer. For cardiovascular conditions, a similar relationship was observed for ischemic heart disease and cerebrovascular disease-the two most frequent causes of mortality. This study provided extended details regarding the beneficial effects of biodiversity on human health.

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).

HLA-B27, axial spondyloarthritis and survival

INTRODUCTION

Ankylosing spondylitis (AS), and carriage of HLA-B27 gene in otherwise healthy individuals, are reportedly associated with increased mortality. We evaluated this hypothesis, using data from both a 35-year AS follow-up study and UK Biobank data.

METHODS

In 1985, 363 members of the Swiss AS Patient Society and 806 relatives were screened clinically and then radiographically for AS/axial spondyloarthritis (axSpA). Life expectancy was analysed in 377 axSpA patients having available pelvic radiographs and HLA-B27 status, comparing with matched Swiss population data. Survival in relation to HLA-B27 status in the general population was studied in UK Biobank European-ancestry participants (n=407 480, n=30 419 deaths).

RESULTS

AS patients have increased standardised mortality rate (SMR) compared with the general population (1.37, 95% CI 1.11 to 1.62). This increase was significant for HLA-B27-positive AS (SMR 1.38, 95% CI 1.11 to 1.65). Shortened life expectancy was observed among both HLA-B27-positive AS women (SMR 1.77, 95% CI 1.09 to 2.70) and men (SMR 1.31, 95% CI 1.02 to 1.59). Patients with non-radiographic axSpA (nr-axSpA) had significantly lower SMR: 0.44 (95% CI 0.23 to 0.77), compared with the general population. In the UK Biobank European-ancestry population cohort, HLA-B27 carriage was not significantly associated with any change in mortality (HR 1, 95% CI 0.97 to 1.1, p=0.349, adjusted by sex), in either males (HR 1, 95% CI 0.98 to 1.1, p=0.281) or females (HR 0.96, 95% CI 0.9 to 1, p=0.232), and no increase in vascular disease mortality was observed.

DISCUSSION

AS patients, but not nr-axSpA patients, have a significantly shortened life expectancy. Increased mortality is particularly significant among women with HLA-B27-positive AS. HLA-B27 carriage in the European-ancestry general population does not influence survival, or the risk of death due to vascular disease.

Estimating the US Baseline Distribution of Health Inequalities Across Race, Ethnicity, and Geography for Equity-Informative Cost-Effectiveness Analysis

OBJECTIVES

Information on how life expectancy, disability-free life expectancy, and quality-adjusted life expectancy varies across equity-relevant subgroups is required to conduct distributional cost-effectiveness analysis. These summary measures are not comprehensively available in the United States, given limitations in nationally representative data across racial and ethnic groups.

METHODS

Through linkage of US national survey data sets and use of Bayesian models to address missing and suppressed mortality data, we estimate health outcomes across 5 racial and ethnic subgroups (non-Hispanic American Indian or Alaska Native, non-Hispanic Asian and Pacific Islander, non-Hispanic black, non-Hispanic white, and Hispanic). Mortality, disability, and social determinant of health data were combined to estimate sex- and age-based outcomes for equity-relevant subgroups based on race and ethnicity, as well as county-level social vulnerability.

RESULTS

Life expectancy, disability-free life expectancy, and quality-adjusted life expectancy at birth declined from 79.5, 69.4, and 64.3 years, respectively, among the 20% least socially vulnerable (best-off) counties to 76.8, 63.6, and 61.1 years, respectively, among the 20% most socially vulnerable (worst-off) counties. Considering differences across racial and ethnic subgroups, as well as geography, gaps between the best-off (Asian and Pacific Islander; 20% least socially vulnerable counties) and worst-off (American Indian/Alaska Native; 20% most socially vulnerable counties) subgroups were large (17.6 life-years, 20.9 disability-free life-years, and 18.0 quality-adjusted life-years) and increased with age.

CONCLUSIONS

Existing disparities in health across geographies and racial and ethnic subgroups may lead to distributional differences in the impact of health interventions. Data from this study support routine estimation of equity effects in healthcare decision making, including distributional cost-effectiveness analysis.

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

BACKGROUND

Large disparities in mortality exist across racial-ethnic groups and by location in the USA, but the extent to which racial-ethnic disparities vary by location, or how these patterns vary by cause of death, is not well understood. We aimed to estimate age-standardised mortality by racial-ethnic group, county, and cause of death and describe the intersection between racial-ethnic and place-based disparities in mortality in the USA, comparing patterns across health conditions.

METHODS

We applied small-area estimation models to death certificate data from the US National Vital Statistics system and population data from the US National Center for Health Statistics to estimate mortality by age, sex, county, and racial-ethnic group annually from 2000 to 2019 for 19 broad causes of death. 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). We adjusted these mortality rates to correct for misreporting of race and ethnicity on death certificates and generated age-standardised results using direct standardisation to the 2010 US census population.

FINDINGS

From 2000 to 2019, across 3110 US counties, racial-ethnic disparities in age-standardised mortality were noted for all causes of death considered. Mortality was substantially higher in the AIAN population (all-cause mortality 1028·2 [95% uncertainty interval 922·2-1142·3] per 100 000 population in 2019) and Black population (953·5 [947·5-958·8] per 100 000) than in the White population (802·5 [800·3-804·7] per 100 000), but substantially lower in the Asian population (442·3 [429·3-455·0] per 100 000) and Latino population (595·6 [583·7-606·8] per 100 000), and this pattern was found for most causes of death. However, there were exceptions to this pattern, and the exact order among racial-ethnic groups, magnitude of the disparity in both absolute and relative terms, and change over time in this magnitude varied considerably by cause of death. Similarly, substantial geographical variation in mortality was observed for all causes of death, both overall and within each racial-ethnic group. Racial-ethnic disparities observed at the national level reflect widespread disparities at the county level, although the magnitude of these disparities varied widely among counties. Certain patterns of disparity were nearly universal among counties; for example, in 2019, mortality was higher among the AIAN population than the White population in at least 95% of counties for skin and subcutaneous diseases (455 [97·8%] of 465 counties with unmasked estimates) and HIV/AIDS and sexually transmitted infections (458 [98·5%] counties), and mortality was higher among the Black population than the White population in nearly all counties for skin and subcutaneous diseases (1436 [96·6%] of 1486 counties), diabetes and kidney diseases (1473 [99·1%]), maternal and neonatal disorders (1486 [100·0%] counties), and HIV/AIDS and sexually transmitted infections (1486 [100·0%] counties).

INTERPRETATION

Disparities in mortality among racial-ethnic groups are ubiquitous, occurring across locations in the USA and for a wide range of health conditions. There is an urgent need to address the shared structural factors driving these widespread disparities.

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, US National Institutes of Health.

Influence of Place of Birth on Adult Mortality: The Case of Spain

We use a unique data set from Spain and we estimate life expectancy at age 50 for males and females by place of residence and place of birth. We show that, consistent with expectations regarding the influence of early conditions on adult health and mortality, the effects of place of birth on adult mortality are very strong, irrespective of place of residence. Furthermore, we find that mortality levels observed in a place are strongly influenced by the composition of migrants by place of birth. This is reflected in a new measure of heritability of early childhood conditions that attains a value in the range 0.42-0.43, implying that as much as 43 percent of the variance in Spain's life expectancy at age 50 is explained by place of birth. Finally, we find evidence of the healthy migrant effect, that is, positive health selection of migrants, at a regional level.

Comparison of Bayesian Spatiotemporal Models for Small-Area Life Expectancy: A Simulation Study

The purpose of this study was to assess the precision, uncertainty, and normality of small-area life expectancy estimates calculated using Bayesian spatiotemporal models. We hypothesized 6 scenarios in which all 247 districts of South Korea had the same year-specific female population of 500, 1,000, 2,000, 5,000, 10,000, and 25,000 individuals during the study period (2013-2017). We generated 1,000 hypothetical data sets for each scenario and calculated district-year life expectancies. The precision and uncertainty of life expectancy estimates were compared between 2 Bayesian spatiotemporal models and the traditional method and Bayesian spatial models. We examined the normality of the life expectancy distributions generated by each method and investigated an optimal cutoff value for the comparisons. The Bayesian spatiotemporal models produced precise life expectancy estimates. However, the 95% uncertainty interval contained the true value with a probability of less than 95%. The Bayesian spatiotemporal models violated the normality assumption in scenarios with small population sizes. Therefore, life expectancy comparisons should be conducted using a cutoff value that minimizes false-positive and false-negative rates. We propose 0.8 as a cutoff value for determining the statistical significance of the difference in life expectancy.

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).

Identifying Novel Data-Driven Dietary Patterns via Dimensionality Reduction and Associations with Socioeconomic Profile and Health Outcomes in Ireland

Dietary patterns and body mass index (BMI) play a significant role in the development of noncommunicable diseases (NCDs), which are the leading cause of mortality worldwide, including Ireland. A cross-sectional survey was conducted across Ireland to collate respondents' socioeconomic profiles, health status, and dietary patterns with a representative sample size of 957 adult respondents. Principal component analysis (PCA) and statistical analyses were subsequently employed. To the author's knowledge, this is the first study to use recent (2021) nationally representative data to characterise dietary patterns in Ireland via dimensionality reduction. Five distinct dietary patterns ("meat-focused", "dairy/ovo-focused", "vegetable-focused", "seafood-focused", and "potato-focused") were identified and statistically characterised. The "potato-focused" group exhibited the highest mean BMI (26.88 kg/m²), while the "vegetable-focused" group had the lowest (24.68 kg/m²). "Vegetable-focused" respondents were more likely to be associated with a categorically healthy BMI (OR = 1.90) and urban residency (OR = 2.03). Conversely, "meat-focused" respondents were more likely to have obesity (OR = 1.46) and rural residency (OR = 1.72) along with the "potato-focused" group (OR = 2.15). Results show that data-derived dietary patterns may better predict health outcomes than self-reported dietary patterns, and transitioning to diets focusing on vegetables, seafood, and lower meat consumption may improve health.

Indirect estimation of the need for palliative care during the COVID-19 pandemic: A descriptive cross-sectional study using mortality data in the Biobío Region, Chile

BACKGROUND

People with chronic diseases in their advanced phase require palliative care. This is essential to ensure their quality of life as it ends. However, a very low percentage of patients receive the necessary palliative care. The COVID-19 pandemic has adversely affected the planning and provision of palliative care. Despite this, in Chile, palliative care coverage was extended by law to cover nononcological chronic diseases. Implementation of this law is expected to be a significant challenge in terms of material resources, as well as the need for the formation of specialized palliative care teams. Therefore, it is essential to estimate the need for palliative care for all chronic diseases to generate useful input for planning and decision-making in public health.

OBJECTIVES

To indirectly estimate the need for palliative care among people with Chronic Oncological Diseases (COD) and Chronic Non-Oncological Diseases (CNOD) during the prepandemic and pandemic context due to COVID-19 in the Biobío Region in Chile.

METHODS

Cross-sectional study based on mortality data from chronic oncological and nononcological diseases during the prepandemic (2010-2018) and pandemic (2020-2021) contexts due to COVID-19 in a Region of Chile through indirect estimation using minimal estimate, standardized mortality rates and geographically weighted regression.

RESULTS

It was estimated that 76.25% of deaths from chronic diseases in the Biobío Region would have required palliative care, which represents 77,618 people who should have been included in these health benefits. The pandemic had a significant effect on the average number of deaths from CNOD. People belonging to this group were more likely to die from COVID-19 than from their baseline disease, unlike the deaths of people from COD, where no significant changes were observed.

CONCLUSION

These estimates highlight the potential size of the population requiring palliative care and emphasize the importance of recognizing the rights of individuals with COD and CNOD conditions. It is evident that there is a significant demand for palliative care services, as well as a pressing need for adequate resources, effective management, and strategic planning to cater to the needs of this population. This is particularly crucial in the heavily impacted areas and communes of the Biobío Region, Chile.

Molecular simulations required to target novel and potent inhibitors of cancer invasion

INTRODUCTION

Computer-aided drug design (CADD) is a computational approach used to discover, develop, and analyze drugs and active molecules with similar biochemical properties. Molecular simulation technology has significantly accelerated drug research and reduced manufacturing costs. It is an optimized drug discovery method that greatly improves the efficiency of novel drug development processes.

AREASCOVERED

This review discusses the development of molecular simulations of effective cancer inhibitors and traces the main outcomes of in silico studies by introducing representative categories of six important anticancer targets. The authors provide views on this topic from the perspective of both medicinal chemistry and artificial intelligence, indicating the major challenges and predicting trends.

EXPERT OPINION

The goal of introducing CADD into cancer treatment is to realize a highly efficient, accurate, and desired approach with a high success rate for identifying potent drug candidates. However, the major challenge is the lack of a sophisticated data-filtering mechanism to verify bottom data from mixed-quality references. Consequently, despite the continuous development of algorithms, computer power, and interface optimization, specific data filtering mechanisms will become an urgent and crucial issue in the future.

Relating biodiversity with health disparities of human population: An ecological study across the United States

Understanding biodiversity's contributions to human health is the first step toward fostering synergies between biodiversity conservation and health promotion - two major targets of UN's Sustainable Development Goals. The One Health approach acknowledges the health of people and biodiversity are interconnected and facing common threats. In this study, we aimed to unveil the geographical association between avian biodiversity and population health across the US. In this ecological study, we combined citizen science bird data from eBird, population health data from the Institute for Health Metrics and Evaluation, and county-level statistics of population characteristics, including socio-economics, healthcare service etc. Multivariate linear regression analyses were performed between bird biodiversity (measured by rarefied species richness of birds), key indicators of general public health (e.g., cause-specific mortality rate), and socio-economic health determinants of 2751 US counties. We found that a higher number of bird species was significantly associated with longer life expectancy after confounding adjustment (regression coefficient (95% CIs), 0·005 (0·003, 0·008)). Bird species richness calculated using the rarefied method consistently accounted for variance in age-specific mortality risks in both very young and old age groups (R² from 2% to 4%). Rarefied species richness of birds was negatively correlated with the majority of cause-specific deaths (12 out of 21 mutually exclusive causes of death), indicating a general synergy effect between biodiversity and human health. The associations with the top causes of deaths were regarded as highly significant, with considerable effect sizes, for example, for cardiovascular diseases (regression coefficient (95% CIs), -0·242 (-0·311, -0·174)). Our findings show human health is inseparable from the health of the shared environment and the well-being of all species. Bird species richness offers a valuable means to understand large-scale relationships between human health and the health of the environment. To enable equitable sharing of biodiversity's benefits to human health, more efforts should be made to understand two-way socio-ecological mechanism underlying human-biodiversity interactions.

Towards systems immunology of critical illness at scale: from single cell 'omics to digital twins

Single-cell 'omics methodology has yielded unprecedented insights based largely on data-centric informatics for reducing, and thus interpreting, massive datasets. In parallel, parsimonious mathematical modeling based on abstractions of pathobiology has also yielded major insights into inflammation and immunity, with these models being extended to describe multi-organ disease pathophysiology as the basis of 'digital twins' and in silico clinical trials. The integration of these distinct methods at scale can drive both basic and translational advances, especially in the context of critical illness, including diseases such as COVID-19. Here, I explore achievements and argue the challenges that are inherent to the integration of data-driven and mechanistic modeling approaches, highlighting the potential of modeling-based strategies for rational immune system reprogramming.

Current state of cause of death determinations in Japan and the need to list the precise underlying cause of death

When death is caused by a disease, the precise cause of the death must be determined to promote health and contribute to prevention efforts. The circumstances of death should also be clarified so that measures can be taken to prevent the recurrence. Statistics regarding the cause of death must be accurate, and such statistics are shaped by the determination of the cause of death. We examined the annual cause of death rankings and the mortality rate in Japan during the 25-year period 1993-2017. We identified improvements that are needed to provide more precision in the cause of death statistics, with a focus on variations in the rankings, and we describe the peculiar and vulnerable aspects of the Vital Statistics system in Japan; for example, at one time the national government advised physicians to not list "heart failure" as the terminal stage of a condition on a death certificate, and the "heart disease" mortality rate thus tended to decline in that period. The ranking of "heart disease" as a cause of death decreased, but its mortality rate subsequently increased again. In addition, the "pneumonia" mortality rate has remained high over the past few years, but it abruptly decreased in 2017, when "aspiration pneumonia" was separated as a cause from other pneumonias. The "senility" mortality rate has increased annually, and it is a leading cause of death. It is important that physicians understand the underlying causes of death and provide that without being influenced by the reporting customs of the times.

Geographical pattern of minerals and its association with health disparities in the USA

This study aimed to determine the common latent patterns of geographical distribution of health-related minerals across the USA and to evaluate the real-world cumulative effects of these patterns on overall population health. It was an ecological study using county-level data (3080 contiguous counties) on the concentrations of 14 minerals (i.e., aluminum, arsenic, calcium, copper, iron, lead, magnesium, manganese, mercury, phosphorus, selenium, sodium, titanium, zinc) in stream sediments (or surface soils), and the measurements of overall health including life expectancy at birth, age-specific mortality risks and cause-specific (summarized by 21 mutually exclusive groups) mortality rates. Latent class analysis (LCA) was employed to identify the common clusters of life expectancy-related minerals based on their concentration characteristics. Multivariate linear regression analyses were then conducted to examine the relationship between the LCA-derived clusters and the health measurements, with adjustment for potential confounding factors. Five minerals (i.e., arsenic, calcium, selenium, sodium and zinc) were associated with life expectancy and were analyzed in LCA. Three clusters were determined across the USA, the 'common' (n = 2056, 66.8%), 'infertile' (n = 739, 24.0%) and 'plentiful' (n = 285, 9.3%) clusters. Residents in counties with the 'infertile' profile were associated with the shortest life expectancy, highest mortality risks at all ages, and highest mortality rates for many reasons including the top five leading causes of death: cardiovascular diseases, neoplasms, neurological disorders, chronic respiratory conditions, and diabetes, urogenital, blood and endocrine diseases. Results remained statistically significant after confounding adjustment. Our study brings novel perspectives regarding environmental geochemistry to explain health disparities in the USA.

Explaining obesity disparities by urbanicity, 2006 to 2016: A decomposition analysis

OBJECTIVE

A large, and potentially growing, disparity in obesity prevalence exists between large central metros and less urban United States counties. This study examines its key predictors.

METHODS

Using a rich county-year data set spanning 2006 to 2016, the authors conducted a Gelbach decomposition to examine the relative importance of demographic, socioeconomic, environmental, and behavioral factors in shaping the baseline obesity gap and the growth rate over time between large central metros and other counties.

RESULTS

Predictors included in this model explain almost the entire obesity gap between large central metros and other counties in the baseline year but can explain only ~32% of the growing gap. At baseline, demographic predictors explain more than half the obesity gap, and socioeconomic and behavioral predictors explain the other half. Behavioral and socioeconomic predictors explain more than half the growing gap over time whereas controlling for environmental and demographic predictors decreases the obesity gap by urbanicity over time.

CONCLUSIONS

Results suggest policy makers should prioritize interventions targeting health behaviors of residents in non-large central metros to slow the growth of the obesity gap between large central metros and other counties. However, to fundamentally eliminate the obesity gap, in addition to improving health behaviors, policies addressing socioeconomic inequalities are needed.

Spatiotemporal trends and ecological determinants of cardiovascular mortality among 2844 counties in mainland China, 2006-2020: a Bayesian modeling study of national mortality registries

BACKGROUND

Cardiovascular disease (CVD) is the leading cause of death in China. No previous study has reported CVD mortality at county-level, and little was known about the nonmedical ecological factors of CVD mortality at such small scale in mainland China. Understanding the spatiotemporal variations of CVD mortality and examining its nonmedical ecological factors would be of great importance to tailor local public health policies.

METHODS

By using national mortality registration data in China, this study used hierarchical spatiotemporal Bayesian model to demonstrate spatiotemporal distribution of CVD mortality in 2844 counties during 2006 to 2020 and investigate how nonmedical ecological determinants have affected CVD mortality inequities from the spatial perspectives.

RESULTS

During 2006-2020, the age-standardized mortality rate (ASMR) of CVD decreased from 284.77 per 100,000 in 2006 to 241.34 per 100,000 in 2020. Among 2844 counties, 1144 (40.22%) were hot spots counties with a higher CVD mortality risk compared to the national average and located mostly in northeast, north central, and westernmost regions; on the contrary, 1551 (54.53%) were cold spots counties and located mostly in south and southeast coastal counties. CVD mortality risk decreased from 2006 to 2020 was larger in counties where CVD mortality rate had been higher in 2006 in most of the counties, vice versa. Nationwide, nighttime light intensity (NTL) was the major influencing factor of CVD mortality, a higher NTL appeared to be negatively associated with a lower CVD mortality, with one unit increase in NTL, and the CVD mortality risk will decrease 11% (relative risk of NTL was estimated as 0.89 with 95% confidence interval of 0.83-0.94).

CONCLUSIONS

Substantial between-county discrepancies of CVD mortality distribution were observed during past 15 years in mainland China. Nonmedical ecological determinants were estimated to significantly explain the overall and local spatiotemporal patterns of this CVD mortality risk. Targeted considerations are needed to integrate primary care with clinical care through intensifying further strategies to narrow unequally distribution of CVD mortality at local scale. The approach to county-level analysis with small area models has the potential to provide novel insights into Chinese disease-specific mortality burden.

Disparities in localized malignant lung cancer surgical treatment: A population‐based cancer registry analysis

BACKGROUND

Lung cancer (LC) continues to be the leading cause of cancer deaths in the United States. Surgical treatment has proven to offer a favorable prognosis and a better 5-year relative survival for patients with early or localized tumors. This novel study investigates the factors associated with the odds of receiving surgical treatment for localized malignant LC in Tennessee.

METHODS

Population-based data of 9679 localized malignant LC patients from the Tennessee Cancer Registry (2005-2015) were utilized to examine the factors associated with receiving surgical treatment for localized malignant LC. Bivariate and multivariate logistic regression analyses, cross-tabulation, and Chi-Square ( χ ² ) tests were conducted to assess these factors.

RESULTS

Patients with localized malignant LC who initiated treatment after 2.7 weeks were 46% less likely to receive surgery (adjusted odds ratio [AOR] = 0.54; 95% confidence interval [CI] = 0.50-0.59; p < 0.0001). Females had a greater likelihood (AOR = 1.14; CI = 1.03-1.24) of receiving surgical treatment compared to men. Blacks had lower odds (AOR = 0.76; CI = 0.65-0.98) of receiving surgical treatment compared to Whites. All marital groups had higher odds of receiving surgical treatment compared to those who were single/never married. Patients living in Appalachian county had lower odds of receiving surgical treatment (AOR = 0.65; CI = 0.59-0.71) compared with those in the non-Appalachian county. Patients with private (AOR = 2.09; CI = 1.55-2.820) or public (AOR = 1.42; CI = 1.06-1.91) insurance coverage were more likely to receive surgical treatment compared to self-pay/uninsured patients. Overall, the likelihood of patients receiving surgical treatment for localized malignant LC decreases with age.

CONCLUSION

Disparities exist in the receipt of surgical treatment among patients with localized malignant LC in Tennessee. Health policies should target reducing these disparities to improve the survival of these patients.

Advances in Nanotechnology for Cancer Immunoprevention and Immunotherapy: A Review

One of the most effective cancer therapies, cancer immunotherapy has produced outstanding outcomes in the field of cancer treatment. However, the cost is excessive, which limits its applicability. A smart way to address this issue would be to apply the knowledge gained through immunotherapy to develop strategies for the immunoprevention of cancer. The use of cancer vaccines is one of the most popular methods of immunoprevention. This paper reviews the technologies and processes that support the advantages of cancer immunoprevention over traditional cancer immunotherapies. Nanoparticle drug delivery systems and nanoparticle-based nano-vaccines have been employed in the past for cancer immunotherapy. This paper outlines numerous immunoprevention strategies and how nanotechnology can be applied in immunoprevention. To comprehend the non-clinical and clinical evaluation of these cancer vaccines through clinical studies is essential for acceptance of the vaccines.

Exploring inequalities in life expectancy and lifespan variation by race/ethnicity and urbanicity in the United States: 1990 to 2019

Background/Objective

Investigating trends in life expectancy and lifespan variation can highlight disproportionate mortality burdens among population subgroups. We examined inequalities in life expectancy and lifespan variation by race/ethnicity and by urbanicity in the US from 1990 to 2019.

Methods

Using vital registration data for 322.0 million people in 3,141 counties from the National Center for Health Statistics, we obtained life expectancy at birth and lifespan variation for 16 race/ethnicity-gender-urbanicity combinations in six 5-year periods (1990-1994 to 2015-2019). Race/ethnicity was categorized as Hispanic, and non-Hispanic White, Black, and Asian/Pacific Islander. Urbanicity was categorized as metropolitan vs nonmetropolitan areas, or in six further detailed categorizations. Life expectancy and lifespan variation (coefficient of variation) were computed using life tables.

Results

In 2015-2019, residents in metropolitan areas had higher life expectancies than their nonmetropolitan counterparts (79.6 years compared to 77.0 years). The widest inequality in life expectancy occurred between Asian/Pacific Islander women and Black men, with a 17.7-year gap for residents in metropolitan areas and a 16.9-year gap for residents in nonmetropolitan areas. Nonmetropolitan areas had greater dispersion around average age at death. Black individuals had the highest lifespan variations in both metropolitan and nonmetropolitan areas. Until the mid-2010s, life expectancy increased while lifespan variation decreased; however, recent trends show stagnation in life expectancy and increases in lifespan variation. Metropolitan-nonmetropolitan inequalities in both life expectancy and lifespan variation widened over time.

Conclusion

Despite previous improvements in longevity, life expectancy is now stagnating while lifespan variation is increasing. Our results highlight that early-life deaths (i.e., young- and middle-age mortality) disproportionately affect Black individuals, who not only live the shortest lifespans but also have the most variability with respect to age at death.

Socioeconomic status, cardiovascular risk profile, and premature coronary heart disease

Background

The combined influence of traditional cardiovascular risk factors and socioeconomic status (SES) on premature CHD (<65 years) remains understudied.

Methods

We used the National Health Interview Survey (NHIS) database (2012-2018) to examine the association of sociodemographic (income, education, insurance status) and cardiovascular risk profile (CRF: ranging from optimal (0–1 risk CV factor) to poor (≥4 risk CV factors)) with CHD in young (18- 44 years) and middle-aged (45–64 years) adults.

Results

Among the 168,969 included adults (young: 46.6%), the prevalence of CHD was 3%, translating to 6.4 million young and middle-aged adults. Adults with low family income, lesser education and no insurance were more likely to have CHD. While majority of young adults (65%) had optimal CRF profile and only 4% had poor CRF profile, 26% of middle-aged adults carried poor CRF profile. When examined by income status, education, and insurance status, odds of CHD were increased with worsening CRF profile. In multivariate regressions, low income participants who had a poor CRF (reference: optimal CRF) had higher odds of CHD in both young (aOR: 9.12 [95% CI, 6.16–13.50]) and middle-aged adults (aOR: 8.22 [95% CI, 6.12–11.05]). Within participants with a high school education or lower, those with a poor CRF profile (reference: optimal CRF) had increased odds of CHD in young (aOR: 10.35 [95% CI, 6.66–16.11]) and middle-aged adults (aOR: 10.40 [95% CI, 7.91–13.66]). In the uninsured, those with a poor CRF profile (reference: optimal CRF) had an 8-9 fold increased odds of CHD in young (aOR: 7.65 [95% CI, 4.26–13.73]) and middle-aged adults (aOR: 9.34 [95% CI, 5.90–14.79]).

Conclusions

In this national survey, individuals with poor CRF profile had higher odds of premature CHD than those with optimal profile, and burden of CHD increased with worsening of CRF profile.

Activation of the dorsal septum increases alcohol consumption in male C57BL/6J mice

Binge drinking is a common pattern of excessive alcohol consumption associated with Alcohol Use Disorder (AUD) and unraveling the neurocircuitry that promotes this type of drinking is critical to the development of novel therapeutic interventions. The septal region was once a focal point of alcohol research yet has seen limited study over the last decade in relation to binge drinking. Numerous studies point to involvement of the dorsal septum (dSep) in excessive drinking and withdrawal, but few studies have manipulated this region in the context of binge drinking behavior. The present experiments were primarily designed to determine the effect of chemogenetic manipulation of the dSep on binge-like alcohol drinking in male and female C57BL/6J mice. Mice received bilateral infusion of AAVs harboring hM4Di, hM3Dq, or mCherry into the dSep and subjects were challenged with systemic administration of clozapine-N-oxide (CNO) and vehicle in the context of binge-like alcohol consumption, locomotor activity, and sucrose drinking. CNO-mediated activation (hM3Dq) of the dSep resulted in increased binge-like alcohol consumption, locomotor activity, and sucrose intake in males. DSep activation promoted sucrose drinking in female mice, but alcohol intake and locomotor activity were unaffected. Conversely, silencing (hM4Di) of the dSep modestly decreased locomotor activity in males and did not influence alcohol or sucrose intake in either sex. These data support a role for the dSep in promoting binge-like drinking behavior in a sex-dependent fashion and suggests a broad role for the region in the modulation of general appetitive behaviors and locomotor activity.

Life expectancy by county, race, and ethnicity in the USA, 2000-19: a systematic analysis of health disparities

BACKGROUND

There are large and persistent disparities in life expectancy among racial-ethnic groups in the USA, but the extent to which these patterns vary geographically on a local scale is not well understood. This analysis estimated life expectancy for five racial-ethnic groups, in 3110 US counties over 20 years, to describe spatial-temporal variations in life expectancy and disparities between racial-ethnic groups.

METHODS

We applied novel small-area estimation models 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 sex-specific and age-specific mortality rates stratified by county and racial-ethnic group (non-Latino and non-Hispanic White [White], non-Latino and non-Hispanic Black [Black], non-Latino and non-Hispanic American Indian or Alaska Native [AIAN], non-Latino and non-Hispanic Asian or Pacific Islander [API], and Latino or Hispanic [Latino]) from 2000 to 2019. We adjusted these mortality rates to correct for misreporting of race and ethnicity on death certificates and then constructed abridged life tables to estimate life expectancy at birth.

FINDINGS

Between 2000 and 2019, trends in life expectancy differed among racial-ethnic groups and among counties. Nationally, there was an increase in life expectancy for people who were Black (change 3·9 years [95% uncertainty interval 3·8 to 4·0]; life expectancy in 2019 75·3 years [75·2 to 75·4]), API (2·9 years [2·7 to 3·0]; 85·7 years [85·3 to 86·0]), Latino (2·7 years [2·6 to 2·8]; 82·2 years [82·0 to 82·5]), and White (1·7 years [1·6 to 1·7]; 78·9 years [78·9 to 79·0]), but remained the same for the AIAN population (0·0 years [-0·3 to 0·4]; 73·1 years [71·5 to 74·8]). At the national level, the negative difference in life expectancy for the Black population compared with the White population decreased during this period, whereas the negative difference for the AIAN population compared with the White population increased; in both cases, these patterns were widespread among counties. The positive difference in life expectancy for the API and Latino populations compared with the White population increased at the national level from 2000 to 2019; however, this difference declined in a sizeable minority of counties (615 [42·0%] of 1465 counties) for the Latino population and in most counties (401 [60·2%] of 666 counties) for the API population. For all racial-ethnic groups, improvements in life expectancy were more widespread across counties and larger from 2000 to 2010 than from 2010 to 2019.

INTERPRETATION

Disparities in life expectancy among racial-ethnic groups are widespread and enduring. Local-level data are crucial to address the root causes of poor health and early death among disadvantaged groups in the USA, eliminate health disparities, and increase longevity for all.

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 Science Research, US National Institutes of Health.

Sociodemographic Factors and Health Insurance Coverage Are Associated with Invasive Breast Cancer in Tennessee: Appalachian and Non-Appalachian County Comparison

Background:

Tennessean women experience the 12th highest breast cancer (BC) mortality in the United States. Yet, few studies have examined BC outcomes among Tennessean women in and outside of Appalachia. We examined whether sociodemographic factors and health insurance status were associated with invasive BC in Tennessee by Appalachian and non-Appalachian county designation.

Materials and Methods:

Using the Tennessee Cancer Registry, we identified 52,187 women, aged ≥18, diagnosed with BC between 2005 and 2015. Multivariable logistic regression was performed to examine associations between invasive BC and sociodemographic characteristics, health insurance coverage, and county designation (Appalachian/non-Appalachian). Regression analyses stratified by county designation were subsequently performed.

Results:

In Tennessee, younger women had lower odds of invasive BC diagnosis (<45: odds ratio [OR] = 0.74, 95% confidence interval [CI] = 0.67–0.81; 55–64: OR = 0.91, 95% CI = 0.84–0.97) compared to women ≥65. Married Tennessean women had 12% (95% CI = 1.04–1.21) higher odds of invasive BC than single women. Further, both public (OR = 1.81, 95% CI = 1.41–2.33) and private (OR = 1.36, 95% CI = 1.06–1.76) health insurance were found to increase odds of invasive BC compared to no insurance/self-pay. Results from the subpopulation analyses were largely consistent with overall findings. In Appalachian counties, women on public health insurance had increased odds (OR = 1.42, 95% CI = 1.00–2.03) of invasive BC compared to uninsured/self-pay women, while in non-Appalachian counties, women insured both publicly (OR = 2.25, 95% CI = 1.57–3.24) and privately (OR = 1.68, 95% CI = 1.16–2.24) had increased odds of invasive BC.

Conclusions:

The results identify risk factors for Tennessean women in Appalachian and non-Appalachian counties whose malignancies evaded early detection, increasing risk of mortality.

County-Level Variation in Changes in Firearm Mortality Rates Across the US, 1989 to 1993 vs 2015 to 2019

IMPORTANCE

Firearm violence remains a critical public health challenge, disproportionately impacting some US regions. County-level variation may hold key insights into how firearm mortality rates vary across the US.

OBJECTIVE

To model county-level changes in firearm mortality rates (total, homicide, and suicide) from 1989 to 1993 vs 2015 to 2019 and identify and characterize hot spots showing unexpected changes over time.

DESIGN, SETTING, AND PARTICIPANTS

This is a cross-sectional study with 2 time points using a novel small area estimation method to analyze restricted access mortality microdata by cause of death and US county. The analysis included 3111 US counties from 49 states and the District of Columbia from January 1, 1989, to December 31, 2019. Bayesian spatial models were fitted to map geographical variation in changes in age-standardized firearm mortality rates (per 100 000 person-years) from 1989 to 1993 vs 2015 to 2019. County outliers (or hot spots) were defined as having observed rates that fell outside the 95% credible intervals of their expected posterior predictive distribution. These counties were characterized using visualization and descriptive statistics of their characteristics. Data were analyzed from June to December 2021.

EXPOSURES

County of residence.

MAIN OUTCOMES AND MEASURES

Five-year age-standardized mortality rates by US county, age, and cause of death for 1989 to 1993 and 2015 to 2019.

RESULTS

Between 1989 and 2019, 1 036 518 firearm deaths were recorded in counties across the US. Suicide was the most common cause of firearm mortality (589 285 deaths) followed by homicide (412 231 deaths). Age-standardized rates (deaths per 100 000 individuals) for firearm deaths and suicides increased from 1989 to 1993 vs 2015 to 2019 (mean [SD] change, 0.16 [8.78] for firearm deaths and 1.21 [6.91] for suicides), while firearm homicides decreased (mean [SD] change, -0.39 [3.96]). However, these national trends were not homogeneous across counties and often varied by geographical region. The West and Midwest showed the most pronounced increases in firearm suicide rates, whereas the Southeast showed localized increases in firearm homicide rates, despite the national decreasing trend. Critical hot spots were identified in urban counties of Alabama, and firearm homicide rates (per 100 000) in Baltimore City, Maryland, almost doubled from 29.71 to 47.43, and by 2015 to 2019 it accounted for 66.7% of all firearm homicide in Maryland. By contrast, District of Columbia showed promising improvements over time, decreasing from 56.5 firearm homicides per 100 000 in 1989 to 1993 to 14.45 in 2015 to 2019.

CONCLUSIONS AND RELEVANCE

There was substantial variation in rates and changes in firearm deaths among US counties. Geographical hot spots may be useful to inform targeted prevention efforts and local policy responses.

Demographic and State-Level Trends in Mortality Due to Ischemic Heart Disease in the United States from 1999 to 2019

Although there have been advances in ischemic heart disease (IHD) care, variation in IHD-related mortality trends across the United States has not been well described. We used the Centers for Disease Control and Prevention's Wide-ranging Online Data for Epidemiologic Research database to evaluate variation in IHD-related mortality for demographic groups in the United States between 1999 and 2019. Age-adjusted mortality rates (AAMRs) were stratified by gender, race, Hispanic ethnicity, and US state. Crude mortality rates were evaluated using 10-year age groups. IHD-related AAMRs decreased from 195 to 88 per 100,000 nationally, with slower a decrease from 2010 to 2019 (average annual percent change [AAPC] -2.6% [95% confidence interval -2.9% to -2.2%]) compared with 2002 to 2010 (AAPC -5.3% [95% confidence interval -5.6% to -4.9%]). All groups had decreases in AAMRs, although Black populations persistently had the highest AAMR, and women had greater relative decreases than men. AAPC was -3.7% for White men, -4.7% for White women, -3.9% for Black men, -4.9% for Black women, -4.1% for Hispanic men, and -5.1% for Hispanic women. Populations ≥65 years had greater relative mortality decreases than populations <65 years. The median AAMR (2019) and AAPC (1999 to 2019) across states was 86 (range 58 to 134) and -3.8% (range -1.7% to -4.8%), respectively. In conclusion, declines in IHD-related mortality have slowed in the United States, with a significant geographic variation. Black populations persistently had the highest AAMRs, and decreases were relatively greater for women and populations ≥65 years. The impact of demographics and geography on IHD should be further explored and addressed as part of public health measures.

Electroactive functional microenvironments from bioactive polymers: A new strategy to address cancer

The present work reports on a new approach based on electroactive microenvironments to mitigate skeletal muscle cancer. For that, piezoelectric films based on poly(vinylidene fluoride) have been applied to evaluate the influence of mechano- and/or electrical stimuli on rhabdomyosarcoma (RMS) proliferation. Human embryonal rhabdomyosarcoma (RD) cells were cultured on PVDF pristine films with different surface charge (non-poled, poled+ and poled-) and magnetic composites (10% and 20% Fe₃O₄, and 20% CFO filler content) to allow magneto-mechanical and magnetoelectrical stimulation films. Electrospun PVDF pristine (oriented and randomly) and magnetic (10% Fe₃O₄) fiber mats were also evaluated to take into consideration the morphology effect on cell response. It was found that the mechanical stimuli enhance RMS proliferation whereas the mechano-electrical decreases it. It was also verified that the RD cells proliferate better on randomly oriented fibers, whereas myoblast cells do it better in oriented ones. The obtained results confirm that electroactive microenvironments can be used to develop novel and effective approaches to deal with RMS cancer, that can be extrapolated to others cancer types.

Changes in County-Level Economic Prosperity Are Associated With Liver Disease-Related Mortality Among Working-Age Adults

BACKGROUND & AIMS

There is significant variability in county-level rates of liver disease-related mortality. Although this variability is explained partly by demographics, risk factors for liver disease, and access to specialty liver care, little is known about temporal changes in mortality, and its association with economic prosperity. Therefore, we sought to explore the association between changes in county-level economic prosperity and liver disease-related mortality.

METHODS

We performed a retrospective cohort study using county-level mortality data from the Centers for Disease Control and Prevention, economic prosperity measures from the Distressed Communities Index, and county-level markers of demographics, risk factors for liver disease, and access to health care. Primary analyses focused on adults aged 20 to 64 years of age. We used generalized linear mixed models (outcome = annual percentage change in age-adjusted liver disease-related mortality), with the primary exposure being an interaction between year and change in economic prosperity.

RESULTS

There was an inverse relationship between county-level changes in economic prosperity and changes in county-level age-adjusted liver disease-related mortality rates (eg, counties with the smallest increase in economic prosperity had the biggest annual increase in liver disease-related mortality). In generalized linear mixed models accounting for county-level covariates, there was a significant association between economic prosperity and liver disease-related mortality, that is, for every 10-point higher mean rank for change in economic prosperity, there was an additional 0.65% decrease (95% CI, 0.19%-1.10%; P = .006) in mortality per year.

CONCLUSIONS

County-level changes in economic prosperity, independent of other county-level clinical, demographic, and access-to-care variables, may play a role in population-level trends in liver disease-related deaths among the working age population.

Decomposing County-Level Working-Age Mortality Trends in the United States Between 1999-2001 and 2015-2017

Studies have documented significant geographic divergence in U.S. mortality in recent decades. However, few studies have examined the extent to which county-level trends in mortality can be explained by national, state, and metropolitan-level trends, and which county-specific factors contribute to remaining variation. Combining vital statistics data on deaths and Census data with time-varying county-level contextual characteristics, we use a spatially explicit Bayesian hierarchical model to analyze the associations between working-age mortality, state, metropolitan status and county-level socioeconomic conditions, family characteristics, labor market conditions, health behaviors, and population characteristics between 2000 and 2017. Additionally, we employ a Shapley decomposition to illustrate the additive contributions of each changing county-level characteristic to the observed mortality change in U.S. counties between 1999-2001 and 2015-2017 over and above national, state, and metropolitan-nonmetropolitan mortality trends. Mortality trends varied by state and metropolitan status as did the contribution of county-level characteristics. Metropolitan status predicted more of the county-level variance in mortality than state of residence. Of the county-level characteristics, changes in percent college-graduates, smoking prevalence and the percent of foreign-born population contributed to a decline in all-cause mortality over this period, whereas increasing levels of poverty, unemployment, and single-parent families and declines manufacturing employment slowed down these improvements, and in many nonmetropolitan areas were large enough to overpower the positive contributions of the protective factors.

Association Between Hospital Private Equity Acquisition and Outcomes of Acute Medical Conditions Among Medicare Beneficiaries

IMPORTANCE

As private equity (PE) acquisitions of short-term acute care hospitals (ACHs) continue, their impact on the care of medically vulnerable older adults remains largely unexplored.

OBJECTIVE

To investigate the association between PE acquisition of ACHs and access to care, patient outcomes, and spending among Medicare beneficiaries hospitalized with acute medical conditions.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used a generalized difference-in-differences approach to compare 21 091 222 patients admitted to PE-acquired vs non-PE-acquired short-term ACHs between January 1, 2001, and December 31, 2018, at least 3 years before to 3 years after PE acquisition. The analysis was conducted between December 28, 2020, and February 1, 2022. Differences were estimated using both facility and hospital service area fixed effects. To assess the robustness of findings, regressions were reestimated after including fixed effects of patient county of origin to account for geographic differences in underlying health risks. Two subset analyses were also conducted: (1) an analysis including only hospitals in hospital referral regions with at least 1 PE acquisition and (2) an analysis stratified by participation in the Hospital Corporation of America 2006 acquisition. The study included Medicare beneficiaries 66 years and older who were hospitalized with 1 of 5 acute medical conditions: acute myocardial infarction (AMI), acute stroke, chronic obstructive pulmonary disease exacerbation, congestive heart failure exacerbation, and pneumonia.

EXPOSURES

Acquisition of hospitals by PE firms.

MAIN OUTCOMES AND MEASURES

Comorbidity burden (measured by Elixhauser comorbidity score), hospital length of stay, in-hospital mortality, 30-day mortality, 30-day readmission, and 30-day episode payments.

RESULTS

Among 21 091 222 total Medicare beneficiaries admitted to ACHs between 2001 and 2018, 20 431 486 patients received care at non-PE-acquired hospitals, and 659 736 received care at PE-acquired hospitals. Across all admissions, the mean (SD) age was 79.45 (7.95) years; 11 727 439 patients (55.6%) were male, and 4 550 012 patients (21.6%) had dual insurance; 2 996 560 (14.2%) patients were members of racial or ethnic minority groups, including 2 085 128 [9.9%] Black and 371 648 [1.8%] Hispanic; 18 094 662 patients (85.8%) were White. Overall, 3 083 760 patients (14.6%) were hospitalized with AMI, 2 835 777 (13.4%) with acute stroke, 3 674 477 (17.4%) with chronic obstructive pulmonary disease exacerbation, 5 868 034 (27.8%) with congestive heart failure exacerbation, and 5 629 174 (26.7%) with pneumonia. Comorbidity burden decreased slightly among patients admitted with acute stroke (difference, -0.04 SDs; 95% CI, -0.004 to -0.07 SDs) at acquired hospitals compared with nonacquired hospitals but was unchanged across the other 4 conditions. Among patients with AMI, a greater decrease in in-hospital mortality was observed in PE-acquired hospitals compared with non-PE-acquired hospitals (difference, -1.14 percentage points, 95% CI, -1.86 to -0.42 percentage points). In addition, a greater decrease in 30-day mortality (difference, -1.41 percentage points; 95% CI, -2.26 to -0.56 percentage points) was found at acquired vs nonacquired hospitals. However, 30-day spending and readmission rates remained unchanged across all conditions. The extent and directionality of estimates were preserved across all robustness assessments and subset analyses.

CONCLUSIONS AND RELEVANCE

In this cross-sectional study using a difference-in-differences approach, PE acquisition had no substantial association with the patient-level outcomes examined, although it was associated with a moderate improvement in mortality among Medicare beneficiaries hospitalized with AMI.

Geospatial Disparities in the Treatment of Curable Breast Cancer Across the US

IMPORTANCE

Patient factors help explain disparities in breast cancer treatments and outcomes.

OBJECTIVE

To determine the extent to which geospatial variation in initial breast cancer care can be attributed to region vs patient factors with the aim of guiding quality improvement efforts.

DESIGN, SETTING, AND PARTICIPANTS

This was a retrospective population-based cohort study from January 1, 2007, through December 31, 2016, using the Surveillance, Epidemiology, and End Results (SEER)-Medicare database that included 31 571 patients diagnosed with stage I to III breast cancer from 2007 through 2013. Five metrics of care delivery were defined: stage I at diagnosis, chemotherapy receipt, radiation therapy receipt, endocrine therapy (ET) initiation (year 1), and ET continuation (years 3-5). Data analysis was performed from January to June 2021.

EXPOSURES

Stage I diagnosis and treatment with chemotherapy, radiation therapy, or ET.

MAIN OUTCOMES AND MEASURES

For each metric, total variance was attributed proportionally to 4 domains-random, patient factors (eg, age, race and ethnicity, socioeconomic status), region (health service area [HSA]), and unexplained-using hierarchical multivariable modeling.

RESULTS

Of 31 571 total patients (median [IQR] age, 71 [68-75] years), 19 391 (61.4%) had stage I disease at diagnosis. Among eligible patients, 17 297 of 21 190 (81.6%) received radiation therapy, 7204 of 9903 (72.8%) received chemotherapy, 13 115 of 26 855 (48.8%) initiated ET, and 13 944 of 26 855 (52.1%) continued ET. Geospatial density (ie, heat) maps highlight regional performance patterns. For all 5 metrics, region/HSA explained more observed variation (24%-48%) than patient factors (1%-4%); the largest share of variation was unexplained (35%-54%). The metrics with the largest proportion of total variance attributed to region/HSA were ET initiation and continuation (28% and 39%, respectively).

CONCLUSIONS AND RELEVANCE

In this cohort study, there was substantial unexplained geospatial variation in initial breast cancer care. The variance attributed to region/HSA was multifold larger than that explained by patient factors. The importance of patient factors such as race and ethnicity notwithstanding, future quality improvement efforts should focus on reducing unwarranted geospatial variation, especially including optimizing the delivery of ET in low-performing regions.

Association of race with receipt of definitive therapy for high risk prostate cancer in older men

OBJECTIVES

Black men are more likely to die of prostate cancer (PCa) than White men. Whether this difference is driven by biological versus sociodemographic and access to care differences is actively investigated. However, studies that have highlighted racial disparities in PCa outcomes have been poorly represented by elderly men, a notoriously undertreated group. Herein, we evaluated use of curative treatment between Black and White elderly men with aggressive PCa in a large US database.

METHODS

Men ≥80 years diagnosed with National Comprehensive Cancer Network-defined high risk PCa between 2004 and 2016 were analyzed from the National Cancer Database. Multivariable logistic regression was used to model the effect of race and sociodemographic factors on receipt of definitive therapy (surgery or radiation +/- androgen deprivation therapy [ADT]) versus non-definitive therapy (ADT alone or observation) in inverse probability weighted groups matched for stage, prostate-specific antigen, and Gleason score.

RESULTS

Between 2004 and 2016, utilization of definitive therapy with either surgery or radiation therapy increased in both White and Black men in the United States. However, we found that Black men compared with White men were significantly less likely to receive definitive therapy (OR 0.71, 95% CI 0.64-0.79, p < .001). Using multivariable modeling, effect size diminished after adjusting for sociodemographic variables. Notably, there is evidence of the racial disparity narrowing over time.

CONCLUSIONS

These findings highlight striking but improving racial disparities in elderly men with high risk PCa in the US, an overall undertreated population.

The rising burden of Alzheimer's disease mortality in rural America

Since the 1990s, there has been a striking urban-rural divergence in life expectancy within the United States, with metropolitan areas achieving strong life expectancy increases and nonmetropolitan areas experiencing stagnation or actual declines in life expectancy. While Alzheimer's disease and related dementias (ADRD) are likely to pose a particular challenge in nonmetropolitan areas, we know relatively little about the level of ADRD mortality in nonmetropolitan areas, how it has changed over time, and whether it is contributing to metropolitan/nonmetropolitan life expectancy gaps. This study finds that ADRD mortality has risen more rapidly in nonmetropolitan areas than in all other metro areas (large central metros, suburbs, and medium/small cities) between 1999 and 2019. While death rates from ADRD were nearly identical in large central metros and nonmetros in 1999, a clear metro/nonmetro gradient has emerged and widened substantially over the past two decades. Today, nonmetros now experience the highest levels of ADRD mortality, while large central metros have the lowest levels. These metro/nonmetro gaps in ADRD differ substantially by region, with the largest gaps observed in the Middle Atlantic and South Atlantic. The contribution of ADRD to metro/nonmetro differences life expectancy at age 65 is now considerable in many regions, reaching up to 30% for women and 13% for men. In several regions, ADRD's contribution to female life expectancy gaps is on par with or exceeds the contributions of other leading causes of death such as heart disease, cancer, and chronic lower respiratory diseases. The rising burden of Alzheimer's disease mortality is likely to pose a substantial challenge in rural areas of the United States which are aging rapidly, experiencing adverse mortality trends, and increasingly disadvantaged in terms of socioeconomic resources and health care infrastructure.

Federal Regulation and Mortality in the 50 States

Previous research speculates that some regulations are counterproductive in the sense that they increase (rather than decrease) mortality risk. However, few empirical studies have measured the extent to which this phenomenon holds across the regulatory system as a whole. Using a novel U.S. state panel data set spanning the period 2000-2014, we estimate the effect of U.S. federal regulation on state-level mortality. We find that a 1% increase in federal regulation of state economies is associated with an increase in an index of state mortality of between 0.53% and 1.35%. These findings are robust to the form of mortality measure, choice of covariates, and the inclusion/exclusion of various regions, states, and industries. We also provide an update of the "cost-per-life saved cutoff," which is the counterproductive risk threshold for expenditures. We find that expenditures in excess of $38.6 million (2019 dollars) per life saved can be expected to increase mortality risk. This article fills an important gap in the empirical literature and boosts the credibility of mortality risk analysis, whereby public policymakers weigh both the expected lives saved and lost due to a proposed regulation or other policy.

Trends and patterns of disparities in diabetes and chronic kidney disease mortality among US counties, 1980-2014

Introduction

Diabetes and chronic kidney diseases are associated with a large health burden in the USA and globally.

Objective

To estimate age-standardized mortality rates by county from diabetes mellitus and chronic kidney disease.

Design and setting

Validated small area estimation models were applied to de-identified death records from the National Center for Health Statistics (NCHS) and population counts from the census bureau, NCHS, and the Human Mortality Database to estimate county-level mortality rates from 1980 to 2014 from diabetes mellitus and chronic kidney disease (CKD).

Exposures

County of residence.

Main outcomes and measures

Age-standardized mortality rates by county, year, sex, and cause.

Results

Between 1980 and 2014, 2,067,805 deaths due to diabetes were recorded in the USA. The mortality rate due to diabetes increased by 33.6% (95% UI: 26.5%–41.3%) between 1980 and 2000 and then declined by 26.4% (95% UI: 22.8%–30.0%) between 2000 and 2014. Counties with very high mortality rates were found along the southern half of the Mississippi river and in parts of South and North Dakota, while very low rates were observed in central Colorado, and select counties in the Midwest, California, and southern Florida. A total of 1,659,045 deaths due to CKD were recorded between 1980 and 2014 (477,332 due to diabetes mellitus, 1,056,150 due to hypertension, 122,795 due to glomerulonephritis, and 2,768 due to other causes). CKD mortality varied among counties with very low mortality rates observed in central Colorado as well as some counties in southern Florida, California, and Great Plains states. High mortality rates from CKD were observed in counties throughout much of the Deep South, and a cluster of counties with particularly high rates was observed around the Mississippi river.

Conclusions and relevance

This study found large inequalities in diabetes and CKD mortality among US counties. The findings provide insights into the root causes of this variation and call for improvements in risk factors, access to medical care, and quality of medical care.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12963-022-00285-4.

S100A9 blockade improves the functional recovery after spinal cord injury via mediating neutrophil infiltration

Spinal cord injury (SCI) refers to damage to the spinal cord resulting from trauma, disease or degeneration. Controlling the inflammatory process and restoring neural homeostasis is hypothesized to prevent injury aggravation. S100 calcium-binding protein A9 (S100A9) is a pro-inflammatory alarm protein, which is expressed in and released by activated neutrophils. However, whether S100A9 could serve as an effective target for the treatment of SCI has not been reported to date. In the present study, a T10 spinal cord contusion injury model was established in Sprague-Dawley rats. S100A9 expression level was determined in the serum and injured spinal cord tissue via ELISA, reverse transcription-quantitative PCR (RT-qPCR) and western blotting. The S100A9-specific blocker, ABR-238901 (ABR), was administered during the inflammatory phase of SCI, as a form of treatment. Subsequently, the morphological structure, neuronal viability and inflammatory levels of injured spinal cord were observed by histopathology, immunohistochemistry and RT-qPCR. In the obtained results, S100A9 was found to be highly expressed in the injured spinal cord and serum in the first 3 days after SCI. However, at 28 days after surgery, ABR treatment significantly improved motor function, reduced the cavity formation and neutrophil infiltration in the lesion, which was verified via H&E staining and immunohistochemistry for myeloperoxidase. Furthermore, ABR treatment was found to effectively improve the survival and viability of neurons, as shown via Nissl staining and immunofluorescence of the synaptic plasticity markers, microtubule associated protein 2 and neurofilament 200. Moreover, S100A9 blockade effectively upregulated the mRNA expression level of the anti-inflammatory genes, IL-4 and IL-10 and downregulated the mRNA expression level of the pro-inflammatory factors, IL-1β, IL-6 and TNF-α. In addition, S100A9 blockade notably alleviated the apoptosis level of the injured nerve cells. Therefore, the findings of the present study revealed that S100A9 may be a useful target for the treatment of SCI.

Intermittent fasting and caloric restriction interact with genetics to shape physiological health in mice

Dietary interventions can dramatically affect physiological health and organismal lifespan. The degree to which organismal health is improved depends upon genotype and the severity of dietary intervention, but neither the effects of these factors, nor their interaction, have been quantified in an outbred population. Moreover, it is not well understood what physiological changes occur shortly after dietary change and how these may affect the health of an adult population. In this article, we investigated the effect of 6-month exposure of either caloric restriction (CR) or intermittent fasting (IF) on a broad range of physiological traits in 960 1-year old Diversity Outbred mice. We found CR and IF affected distinct aspects of physiology and neither the magnitude nor the direction (beneficial or detrimental) of effects were concordant with the severity of the intervention. In addition to the effects of diet, genetic variation significantly affected 31 of 36 traits (heritabilities ranged from 0.04 to 0.65). We observed significant covariation between many traits that was due to both diet and genetics and quantified these effects with phenotypic and genetic correlations. We genetically mapped 16 diet-independent and 2 diet-dependent significant quantitative trait loci, both of which were associated with cardiac physiology. Collectively, these results demonstrate the degree to which diet and genetics interact to shape the physiological health of adult mice following 6 months of dietary intervention.

Exploring Rural-Urban Differences in Polygenic Associations for Health among Older Adults in the United States

This paper contributes to research on health disparities among rural and urban residents by considering differences in the magnitude of genetic associations for physical health, mental health, and health behaviors across the two settings. Previous research has shown reduced genetic associations in rural compared to urban settings but none have utilized current genome-wide polygenic scores and none have focused on older adults. Using a sample of 14,994 adults from the 1992 to 2016 waves of the Health and Retirement Study our results suggest genetic associations for BMI (p<.018) and heart conditions (p < .023) are significantly reduced in rural compared to urban settings and we find weak evidence in support of this association for depression (p. < .065) and no evidence for smoking (p < 461). In sum, the weaker genetic associations in rural areas highlights the centrality of the social, economic, and built environment as a determinant of disparities.

Explainable artificial intelligence (XAI) for exploring spatial variability of lung and bronchus cancer (LBC) mortality rates in the contiguous USA

Machine learning (ML) has demonstrated promise in predicting mortality; however, understanding spatial variation in risk factor contributions to mortality rate requires explainability. We applied explainable artificial intelligence (XAI) on a stack-ensemble machine learning model framework to explore and visualize the spatial distribution of the contributions of known risk factors to lung and bronchus cancer (LBC) mortality rates in the conterminous United States. We used five base-learners-generalized linear model (GLM), random forest (RF), Gradient boosting machine (GBM), extreme Gradient boosting machine (XGBoost), and Deep Neural Network (DNN) for developing stack-ensemble models. Then we applied several model-agnostic approaches to interpret and visualize the stack ensemble model's output in global and local scales (at the county level). The stack ensemble generally performs better than all the base learners and three spatial regression models. A permutation-based feature importance technique ranked smoking prevalence as the most important predictor, followed by poverty and elevation. However, the impact of these risk factors on LBC mortality rates varies spatially. This is the first study to use ensemble machine learning with explainable algorithms to explore and visualize the spatial heterogeneity of the relationships between LBC mortality and risk factors in the contiguous USA.