Alaska Native Populations Research Articles

Racial and Ethnic Disparities in Regulatory Air Quality Monitor Locations in the US

Understanding exposure to air pollution is important to public health, and disparities in the spatial distribution of regulatory air quality monitors could lead to exposure misclassification bias. To determine whether racial and ethnic disparities exist in Environmental Protection Agency (EPA) regulatory air quality monitor locations in the US. This national cross-sectional study included air quality monitors in the EPA Air Quality System regulatory monitoring repository, as well as 2022 American Community Survey Census block group estimates for racial and ethnic composition and population size. Bayesian mixed-effects models of the count of criteria pollutant monitors measuring an area were used, adjusting for population size and accounting for spatial autocorrelation. Data were analyzed from March to June 2024. Census block group-level racial and ethnic composition. Number of regulatory monitors measuring a census block group by criteria pollutant (particulate matter [PM], ozone [O3], nitrogen dioxide [NO2], sulfur dioxide [SO2], lead [Pb], and carbon monoxide [CO]). This analysis included 329 725 481 individuals living in 237 631 block groups in the US (1 936 842 [0.6%] American Indian and Alaska Native, 18 554 697 [5.6%] Asian, 40 196 302 [12.2%] Black, 60 806 969 [18.4%] Hispanic, 555 712 [0.2%] Native Hawaiian and Other Pacific Islander, 196 010 370 [59.4%] White, 1 208 267 [0.3%] some other race, and 10 456 322 [0.4%] 2 or more races). Adjusting for population size, monitoring disparities were identified for each criteria pollutant. Relative to the White non-Latino population, all groups were associated with fewer NO2, O3, Pb, and PM monitors. Disparities were consistently largest for Native Hawaiian and Other Pacific Islander populations, followed by American Indian and Alaska Native populations and those of 2 or more races. An increase in percentage of Native Hawaiian and Other Pacific Islander race was associated with fewer monitors for SO2 (adjusted odds ratio [aOR], 0.91; 95% BCI, 0.90-0.91), CO (aOR, 0.95; 95% BCI, 0.94-0.95), O3 (aOR, 0.95; 95% BCI, 0.94-0.95), NO2 (aOR, 0.97; 95% BCI, 0.91-0.94), and PM (aOR, 0.96; 95% BCI, 0.95-0.96). An increase in the percentage of those of Asian race was associated with slightly more SO2 (aOR, 1.04; 95% BCI, 1.03-1.04) monitors. This cross-sectional study of racial and ethnic disparities in the location of EPA regulatory monitors determined that data may not be equitably representative of air quality, particularly for areas with predominantly Native Hawaiian and Other Pacific Islander or American Indian or Alaska Native populations. Integration of multiple data sources may aid in filling monitoring gaps across race and ethnicity. Where possible, researchers should quantify uncertainty in exposure estimates.

Trends in Hepatocellular Carcinoma Mortality Rates in the US and Projections Through 2040

ImportanceThe burden of liver cancer varies worldwide. An upward trend in both hepatocellular carcinoma (HCC) incidence and mortality in the past 2 decades has been observed.ObjectiveTo assess observed HCC-related age-standardized mortality rates (ASMRs) in the US for 2006 to 2022 and provide ASMR projections through 2040.Design, Setting, and ParticipantsThis cross-sectional study used data from the National Vital Statistics System, which is accessible through the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research website. Data on deaths attributed to HCC (from January 1, 2006, to December 31, 2022) were obtained for adults 25 years or older and were stratified by liver disease etiology, age, sex, and race and ethnicity. Etiologies included alcohol-associated liver disease (ALD), hepatitis B virus (HBV), hepatitis C virus (HCV), and metabolic dysfunction–associated steatotic liver disease (MASLD).Main Outcomes and MeasuresThe main outcomes were (1) observed ASMRs of HCC per 100 000 persons using Joinpoint regression (National Cancer Institute) to assess trends during 2006 to 2022 and (2) ASMRs projected for 2023 to 2040 using Prophet and AutoARIMA modeling.ResultsThis study included 188 280 HCC-related deaths from 2006 to 2022. Most deaths occurred among males (77.4%). The annual percentage change was 4.1% (95% CI, 2.2% to 7.7%) for 2006 to 2009 and decreased to 1.8% (95% CI, 0.7% to 2.0%) for 2009 to 2022, with an overall observed ASMR of 5.03 per 100 000 persons in 2022 and a projected ASMR of 6.39 per 100 000 persons by 2040, with consistent trends for both sexes. By etiology, ASMRs decreased for HCV- and HBV-related mortality but increased for ALD- and MASLD-related mortality. In 2022, MASLD surpassed HBV as the third-leading cause of HCC-related death and was projected to overtake HCV in 2032 as the second-leading cause; ALD was projected to be the leading cause of HCC-related death in 2026. In 2022, the ASMR was higher among individuals aged 65 years or older compared with those aged 25 to 64 years (18.37 vs 1.79 per 100 000 persons). The American Indian or Alaska Native population had the largest increase in projected ASMR by 2040 (14.71 per 100 000 persons) compared with the Asian population (3.03 per 100 000 persons).Conclusions and RelevanceIn this cross-sectional study, ASMRs for ALD- and MASLD-related HCC death increased rapidly from 2006 to 2022; ALD-related HCC was projected to be the leading cause by 2026, with MASLD as the second-leading cause by 2032. These findings may serve as a reference for public health decision-making and timely identification of groups at high risk of HCC death.

Binge drinking in American Indian Alaskan Native college attending students

ABSTRACT Objectives American Indian and Alaskan Native (AIAN) populations have the highest rate of alcohol use disorder (AUD). Binge drinking is a known predecessor of AUD and is prevalent in college-attending populations. However, little is known about the prevalence and risk factors related to AIAN college student binge drinking. The current study examines prevalence of binge drinking and association with socio-demographic features, other substance use, exposure to discrimination and feelings of belonging within collegiate institutions. Design Data were collected by the Healthy Minds Study. Present analyses were restricted to 2- and 4-year college attending students in the 2021–2022 academic year who identified as AIAN (n = 1383). We used descriptive, bivariate and multivariate Poisson weighted models to evaluate distributions and associations of binge drinking, age, gender, socioeconomic status, degree program, military experience, substance use, sexual assault, discrimination, and feelings of belonging within the institution. Results In the prior 2 weeks, 26.3% of AIAN students reported binge drinking. Binge drinking commonly overlapped with other substance use. AIAN students aged 21–34 reported the highest rates of binge drinking, as did students pursuing bachelor’s degrees. AIAN students who identified as trans or queer gender were less likely to report binge drinking, while across gender identities those reporting sexual assault or racial discrimination were more likely to report binge drinking in multivariate analyses. Conclusion There are multiple factors associated with binge drinking, representing individual and contextual influences on AIAN students. Developing prevention and intervention activities to address overlap in substance use and high concurrence of sexual assault and binge drinking are critical. Additionally, colleges must make concerted efforts to reduce racial discrimination and be more inclusive of AIAN students to reduce institutional-based features that exacerbate risk.

Performance of Machine Learning Suicide Risk Models in an American Indian Population

Few suicide risk identification tools have been developed specifically for American Indian and Alaska Native populations, even though these populations face the starkest suicide-related inequities. To examine the accuracy of existing machine learning models in a majority American Indian population. This prognostic study used secondary data analysis of electronic health record data collected from January 1, 2017, to December 31, 2021. Existing models from the Mental Health Research Network (MHRN) and Vanderbilt University (VU) were fitted. Models were compared with an augmented screening indicator that included any previous attempt, recent suicidal ideation, or a recent positive suicide risk screen result. The comparison was based on the area under the receiver operating characteristic curve (AUROC). The study was performed in partnership with a tribe and local Indian Health Service (IHS) in the Southwest. All patients were 18 years or older with at least 1 encounter with the IHS unit during the study period. Data were analyzed between October 6, 2022, and July 29, 2024. Suicide attempts or deaths within 90 days. Model performance was compared based on the ability to distinguish between those with a suicide attempt or death within 90 days of their last IHS visit with those without this outcome. Of 16 835 patients (mean [SD] age, 40.0 [17.5] years; 8660 [51.4%] female; 14 251 [84.7%] American Indian), 324 patients (1.9%) had at least 1 suicide attempt, and 37 patients (0.2%) died by suicide. The MHRN model had an AUROC value of 0.81 (95% CI, 0.77-0.85) for 90-day suicide attempts, whereas the VU model had an AUROC value of 0.68 (95% CI, 0.64-0.72), and the augmented screening indicator had an AUROC value of 0.66 (95% CI, 0.63-0.70). Calibration was poor for both models but improved after recalibration. This prognostic study found that existing risk identification models for suicide prevention held promise when applied to new contexts and performed better than relying on a combined indictor of a positive suicide risk screen result, history of attempt, and recent suicidal ideation.

Racial and Ethnic Disparities in Age-Specific All-Cause Mortality During the COVID-19 Pandemic

The end of the COVID-19 public health emergency (PHE) provides an opportunity to fully describe pandemic-associated racial and ethnic mortality disparities. Age-specific excess mortality differences have important downstream implications, especially in minoritized race and ethnicity populations. To characterize overall and age-specific all-cause excess mortality by race and ethnicity during the COVID-19 PHE and assess whether measured differences reflected changes from prepandemic disparities. This cross-sectional study analyzed data of all US residents and decedents during the COVID-19 PHE, aggregated by observed race and ethnicity (at time of death) and age. Statistical analysis was performed from March 2020 to May 2023. COVID-19 PHE period (March 2020 to May 2023). All-cause excess mortality (incident rates, observed-to-expected ratios) and all-cause mortality relative risks before and during the PHE. For the COVID-19 PHE period, data for 10 643 433 death certificates were available; mean (SD) decedent age was 72.7 (17.9) years; 944 318 (8.9%) were Hispanic; 78 973 (0.7%) were non-Hispanic American Indian or Alaska Native; 288 680 (2.7%) were non-Hispanic Asian, 1 374 228 (12.9%) were non-Hispanic Black or African American, 52 905 (0.5%) were non-Hispanic more than 1 race, 15 135 (0.1%) were non-Hispanic Native Hawaiian or Other Pacific Islander, and 7 877 996 (74.1%) were non-Hispanic White. More than 1.38 million all-cause excess deaths (observed-to-expected ratio, 1.15 [95% CI, 1.12-1.18]) occurred, corresponding to approximately 23 million years of potential life lost (YPLL) during the pandemic. For the total population (all ages), the racial and ethnic groups with the highest observed-to-expected all-cause mortality ratios were the American Indian or Alaska Native (1.34 [95% CI, 1.31-1.37]) and Hispanic (1.31 [95% CI, 1.27-1.34]) populations. However, higher ratios were observed in the US population aged 25 to 64 years (1.20 [95% CI, 1.18-1.22]), greatest among the American Indian or Alaska Native (1.45 [95% CI, 1.42-1.48]), Hispanic (1.40 [95% CI, 1.38-1.42]), and Native Hawaiian or Other Pacific Islander (1.39 [95% CI, 1.34-1.44]) groups. In the total population aged younger than 25 years, the Black population accounted for 51.1% of excess mortality, despite representing 13.8% of the population. Had the rate of excess mortality observed among the White population been observed among the total population, more than 252 000 (18.3%) fewer excess deaths and more than 5.2 million (22.3%) fewer YPLL would have occurred. In this cross-sectional study of the US population during the COVID-19 PHE, excess mortality occurred in all racial and ethnic groups, with disparities affecting several minoritized populations. The greatest relative increases occurred in populations aged 25 to 64 years. Documented differences deviated from prepandemic disparities.

Disparities in infectious disease-related health care utilization between Medicaid-enrolled American Indians and non-Hispanic Whites-Lessons from the first 16 months of coronavirus disease 2019 and a decade of flu seasons.

To understand why American Indian and Alaskan Native (AIAN) populations have had exceptionally high COVID-19 mortality, we compare patterns of healthcare utilization and outcomes for two serious infectious respiratory diseases-Influenza-like-illness (ILI) and coronavirus disease 2019 (COVID-19)-between American Indian and Alaskan Native (AIAN) populations (as identified in Medicaid data) and non-Hispanic Whites over the 2009-2021 period. We select all people under the age of 65 years identified as non-Hispanic White or AIAN in the New York State Medicaid claims data between 2009 and 2021. We analyze data across 10 ILI cohorts (between September 2009 and August 2020) and 4 COVID-19 cohorts (March-June 2020, July-September 2020, October-December 2020, and January-June 2021). We examine mortality and utilization rates using logistic regressions, adjusting for demographic characteristics, prior chronic conditions, and geographic location (including residence near a reservation). We stratify the analysis by rural vs. nonrural counties. We use the New York State Medicaid claims data for the analysis. We find that even among Medicaid beneficiaries, who are similar in socioeconomic status and identical in health insurance coverage, AIAN populations have much lower rates of use of outpatient services and much higher rates of acute (inpatient and emergency room) service utilization for both ILI and COVID-19 than non-Hispanic Whites. Prior to COVID-19, demographic and health status-adjusted all-cause mortality rates, including from ILI, were lower among American Indians than among non-Hispanic Whites on New York State Medicaid, but this pattern reversed during the COVID-19 pandemic. Both findings are driven by nonrural counties. We did not observe significant differences in all-cause mortality and acute service utilization comparing AIAN to non-Hispanic Whites in rural areas. The utilization and mortality disparities we identify within the Medicaid population highlight the need to move beyond insurance in addressing poor health outcomes in the American Indian population.

Cultural tailoring advance care planning for an American Indian community: make your wishes about you

ABSTRACT Background Advance care planning empowers people by allowing them some control over certain healthcare decisions in the event they are unable. Yet, advance care planning rates in the American Indian and Alaska Native populations are low. Thus, we culturally tailored the Make Your Wishes About You (MY WAY), an intervention to improve advance care planning access and completion for American Indian peoples. Methods In partnership with an American Indian Tribe, the project took a community-based participatory orientation and relied on a Community Advisory Board and a Professional Advisory Board. The culturally tailoring was a 15-step process. These steps allowed us to ensure that the tailoring reflects community-specific norms and preferences, greater reliance on visual images and local idioms of expression, more appropriate attention to family roles, and inclusion of spiritual elements. Results A four-phase cultural tailoring framework emerged with each phase centering around listening, learning, and analyzing with tailoring occurring between each phase. A culturally tailored MY WAY was created, which was delivered in a manner that reflected Tribal citizenss' preferences. Materials included Tribal language, local idioms of expression, attention to family roles, and appropriate inclusion of spiritual elements. The materials were rated high on a content validity index by the advisory board members. Conclusion There is a growing interest in tailoring existing evidence-based programs with relatively little in the literature offering guidance. By sharing our efforts and experiences in culturally tailoring an advance care planning program for an American Indian Tribe, we hope that it will serve useful for future efforts in ensuring that evidence-based programming reaches those in greatest need. While this project was rooted in the core Indigenous values of community, ceremony or spirituality, language, and place it also lends itself to broader translation across different populations.

Use of Haemophilus influenzae Type b-Containing Vaccines Among American Indian and Alaska Native Infants: Updated Recommendations of the Advisory Committee on Immunization Practices - United States, 2024.

Invasive Haemophilus influenzae type b (Hib) disease is a serious bacterial infection that disproportionally affects American Indian and Alaska Native (AI/AN) populations. Hib vaccination with a monovalent Hib conjugate vaccine consisting of Hib capsular polysaccharide (polyribosylribitol phosphate [PRP]) conjugated to outer membrane protein complex of Neisseria meningitidis serogroup B, PRP-OMP (PedvaxHIB, Merck and Co., Inc.) has historically been preferred for AI/AN infants, who are at increased risk for invasive Hib disease, because it provides substantial protection after the first dose. On June 26, 2024, CDC's Advisory Committee on Immunization Practices (ACIP) recommended that a hexavalent, combined diphtheria and tetanus toxoids and acellular pertussis (DTaP), inactivated poliovirus (IPV), Hib conjugate, and hepatitis B (HepB) vaccine, DTaP-IPV-Hib-HepB (Vaxelis, MSP Vaccine Company) should be included with monovalent PRP-OMP in the preferential recommendation for AI/AN infants because of the PRP-OMP Hib component. A primary Hib vaccination series consisting of either 1) monovalent PRP-OMP (2-dose series at ages 2 and 4 months) or 2) DTaP-IPV-Hib-HepB (3-dose series at ages 2, 4, and 6 months) is preferred for AI/AN infants. DTaP-IPV-Hib-HepB is only indicated for use in infants at ages 2, 4, and 6 months and should not be used for the booster doses of Hib, DTaP, or IPV vaccines. For the booster dose of Hib vaccine, no vaccine formulation is preferred for AI/AN children; any Hib vaccine (except DTaP-IPV-Hib-HepB) should be used. This report summarizes evidence considered for these recommendations and provides clinical guidance for the use of Hib-containing vaccines among AI/AN infants and children.

Obtaining the Most Accurate, Explainable Model for Predicting Chronic Obstructive Pulmonary Disease: Triangulation of Multiple Linear Regression and Machine Learning Methods.

Lung disease is a severe problem in the United States. Despite the decreasing rates of cigarette smoking, chronic obstructive pulmonary disease (COPD) continues to be a health burden in the United States. In this paper, we focus on COPD in the United States from 2016 to 2019. We gathered a diverse set of non-personally identifiable information from public data sources to better understand and predict COPD rates at the core-based statistical area (CBSA) level in the United States. Our objective was to compare linear models with machine learning models to obtain the most accurate and interpretable model of COPD. We integrated non-personally identifiable information from multiple Centers for Disease Control and Prevention sources and used them to analyze COPD with different types of methods. We included cigarette smoking, a well-known contributing factor, and race/ethnicity because health disparities among different races and ethnicities in the United States are also well known. The models also included the air quality index, education, employment, and economic variables. We fitted models with both multiple linear regression and machine learning methods. The most accurate multiple linear regression model has variance explained of 81.1%, mean absolute error of 0.591, and symmetric mean absolute percentage error of 9.666. The most accurate machine learning model has variance explained of 85.7%, mean absolute error of 0.456, and symmetric mean absolute percentage error of 6.956. Overall, cigarette smoking and household income are the strongest predictor variables. Moderately strong predictors include education level and unemployment level, as well as American Indian or Alaska Native, Black, and Hispanic population percentages, all measured at the CBSA level. This research highlights the importance of using diverse data sources as well as multiple methods to understand and predict COPD. The most accurate model was a gradient boosted tree, which captured nonlinearities in a model whose accuracy is superior to the best multiple linear regression. Our interpretable models suggest ways that individual predictor variables can be used in tailored interventions aimed at decreasing COPD rates in specific demographic and ethnographic communities. Gaps in understanding the health impacts of poor air quality, particularly in relation to climate change, suggest a need for further research to design interventions and improve public health.

Demographics and mortality trends of valvular heart disease in older adults in the United States: Insights from CDC-wonder database 1999–2019

BackgroundValvular heart disease (VHD) represents a spectrum of cardiac conditions, including valvular stenosis, valvular regurgitation, or mixed lesions affecting single or multiple valves. The severity of VHD has emerged as a major cause of cardiovascular (CV) morbidity and mortality among the older population in the United States (U.S). ObjectiveTo evaluate temporal trends in mortality associated with VHD in the elderly U.S population between 1999 and 2019. MethodsWe utilized the CDC WONDER database for VHD mortality in adults ≥75 from 1999 to 2019, using ICD-10 codes. Age-adjusted mortality rates (AAMR) per 100,000 people with associated annual percentage change (APC) were calculated. Joinpoint regression was used to assess the overall trends and trends for demographic, geographic, and type of valvular disease subgroups. ResultsA total of 666,765 VHD deaths in older adults from 1999 to 2019 was identified, with an initial decline in AAMR until 2007 with an APC: 0.62, 95 % CI (−1.66-0.33), stability until 2014, and a significant decrease until 2019 (APC: 1.47, 95 % CI [-2.24-1.04], P < 0.0001). Men consistently had higher AAMRs compared to women (overall AAMR men: 173.6; women: 138.2). The AAMRs were found to be highest in the White (166.5), followed by American Indian or Alaska Native population at (93.8) Hispanic or Latino at (80.7), Black or African American populations at (74.1) and lastly Asian or Pacific Islander (73.4). Non-metropolitan areas manifested higher AAMRs for deaths related to VHD than metropolitan areas (overall AAMRs 160.5 vs 149.5) respectively. State-wide AAMRs varied, with the highest in Vermont at 324.2 (95 % CI [313.0–335.4], P < 0.0001) and the lowest in Mississippi at 88.0 (95 % CI [85.0–91.0], P < 0.0001). Non-rheumatic and aortic valve disorders in adults ≥75 years had higher mortality rates compared to rheumatic or mitral valve conditions in those <75 years. ConclusionOur study showed a decline in U.S. VHD mortality from 1999 to 2019 but found persistent disparities by gender, race, age, region, and VHD type. Targeted policies for prevention and early diagnosis are needed to address these inequalities.

Quantifying the Burden of Opioid Use Disorder and Non-fatal Opioid Overdose in American Indian and Alaskan Native Populations Using the Cerner Real-World Data™ Database.

This study evaluated the prevalence and incidence of opioid use disorder (OUD), rates of opioid overdose (OD), and rates of non-fatal (NF) OD in American Indian/Alaskan Native (AI/AN) populations. We used de-identified patient data from Oracle Cerner Real-World Data™. Rates were estimated over time, and stratified by sex, age, marital status, insurance, and region. Mann-Kendall trend tests and Theil-Sen slopes assessed changes over time for each group while autoregressive modeling assessed differences between groups. The study identified trends in OUD and OD among 700,225 AI/AN patients aged 12 and above. Between 2012 and 2022, there was a significant upward trend in both OUD and OD rates(p < 0.05) , with OUD diagnosed in 1.75% and OD in 0.38% of the population. The Western region of the US exhibited the highest rates of OUD and OD. The 35-49 age group showed the highest rates of OUD, while the 12-34 age group had the highest rates of OD. Marital status analysis revealed higher rates of OUD and OD among separated, widowed, or single patients. Additionally, individuals with Medicare or Medicaid insurance demonstrated the highest rates of OUD and OD. Results show that rates of OUD, OD, and NF OD continue to rise among AI/AN individuals, with some regional and demographic variation. Our study provides foundational estimates of key AI/AN populations bearing greater burdens of opioid-related morbidity that federal, state, and tribal organizations can use to direct and develop targeted resources that can improve the health and well-being of AI/AN communities.

Motor vehicle traffic fatalities by race and ethnicity (2010 – 2021)

Motor vehicle traffic fatalities (MVTFs) are a public health issue that substantially affects the growing Black or African American, Indigenous, and People of Color (BIPOC) population. To further understand the racial discrepancies that exist in MVTFs, data from the Fatality Analysis Reporting System (FARS) and U.S. Census were utilized to explore factors such as rurality, urbanicity, restraint use, and alcohol-impairment. Calculations considered yearly driver and occupant fatality rates per 100,000 population for each race and ethnicity from 2010 through 2021. A Poisson regression model was used to quantify the relationship between the MVTF rates and the factors of interest. Results demonstrated that the American Indian or Alaska Native population was statistically the most overrepresented group in fatality rates across all factors explored. Additionally, the American Indian or Alaska Native population and Black or African American populations were the only groups to have statistically significant increases in fatality rates in recent years when accounting for factors such as unrestrained vehicle driver/occupants and alcohol-impaired fatality rate. In contrast, the Native Hawaiian or Pacific Islander population has consistently experienced one of the largest statistically significant reductions in driver and occupant fatality rates over time. Further analysis is necessary to develop and implement countermeasures that may reduce the increasing fatality rates of the most vulnerable populations while continuing to decrease rates for others as well. Despite limitations of FARS and population data, these results provide a pathway to reducing MVTFs and associated racial inequities that exist in the nation, particularly as the BIPOC population continues to grow.

Nutritional Barriers to the Adherence to the Mediterranean Diet in Non-Mediterranean Populations.

Adherence to the Mediterranean diet has been shown to lower the risk of developing chronic non-communicable diseases like cardiovascular and neurodegenerative diseases and cancer. Improvements in depression, participation in daily activities in older individuals, weight loss and a reduction in adverse pregnancy outcomes are associated with adherence to the Mediterranean diet. The number of studies that have evaluated barriers to adherence to the Mediterranean diet in the US and, in particular, in racial and ethnic minority populations within the US are few. Among Native American and Alaskan Native populations, studies evaluating traditional or alternative Mediterranean diet adherence for chronic non-infectious diseases is unavailable. Mediterranean diet scoring instruments used in studies in European and Mediterranean countries and among white participants in the US fail to capture the dietary patterns of racial and ethnic minority populations. In this narrative review, the food components of the traditional Mediterranean diet are discussed, adherence to the Mediterranean diet is examined in Mediterranean and non-Mediterranean countries and barriers preventing adherence to the Mediterranean diet in the US and among racial and ethnic minority populations is reviewed. Recommendations for improving nutrition education and intervention and for increasing adherence and cultural adaptions to the Mediterranean diet are provided.

Trends and disparities in the incidence and mortality of stomach cancer in the United States.

e16102 Background: Stomach cancer is the fifth most common cancer worldwide and has one of the lowest survival rates across all malignancies. There is a constant need to define current stomach cancer incidence and incidence-based mortality (IBM) rates among different population groups for improved clinical practice. We aimed to investigate the trends of stomach cancer incidence and IBM by population characteristics of age groups, gender and ethnic groups. Methods: Data obtained from the National Cancer Institute’s Surveillance, Epidemiology, and End results (SEER) Registry 12 were obtained to determine the incidence and IBM rate of stomach incidence from 1992 to 2020. Joinpoint Regression Analysis program was used to calculate the annual percent change (APC) for trend analysis. Results: A total of 82,810 stomach cancer patients were identified from the dataset. Most of the patients were males; N = 49,909(60.27%) and Non-Hispanic Whites, N = 40,894 (49.38%). The overall incidence rate was 8.00 (95% Confidence Interval [CI]: 7.95 to 8.06) and the overall IBM rate was 6.44 (95%CI: 6.39 to 6.49). The incidence rate of stomach cancer decreased significantly by 1.28 % per year from 1992 to 2020; however the degree of decline from 1992 to 2017, APC (-1.18, 95% CI: -1.27 to -1.04, p &lt; .001) was lower compared to between 2017 and 2020, APC (-3.42, 95% CI: -6.08 to -1.69, p = 0.01). Conversely, IBM rate increased significantly from 1992 to 1994, APC (36.59, 95% CI: 22.51 to 52.29, p &lt; .001) followed by a significant decrease from 1994 to 2020, APC (-1.29, 95%CI: -1.43 to -1.15, p &lt; .001).Incidence rates reduced significantly from 1992 to 2020 for all gender, ethnic and age groups except among the Non-Hispanic Asian Indian or Alaska Native (NHAIAN) population with APC (-0.67, 95 CI% -1.93 to 0.61, p = 0.29) and &lt; 60 years age group with APC (0.03, 95 CI % : 0.18 to 0.25, p = 0.76). Significant decline in IBM rate was observed from 2000 to 2020 across all gender, ethnicities and age groups except among the NHAIAN, APC (-0.21, 95 CI%: -1.26 to 0.84, p = 0.68) and the &lt; 60 years age group, APC (0.16, 95 CI%: -0.33 to -0.65, p = 0.52). Conclusions: Stomach cancer incidence and IBM rates have decreased significantly over the last 20 years except in NHAIAN and &lt; 60 years age populations. These findings suggest the need for further research focused efforts in these potentially high-risk groups.

Tribally-led mobile outreach: improving access to harm reduction services in one rural reservation community.

American Indian and Alaska Native populations in the United States face significant disparities related to opioid use disorder and opioid-related mortality. Inequitable access to medications and harm reduction strategies due to structural, societal, and geographical factors prevent Tribal communities from obtaining needed services, and further contribute to the opioid epidemic. One Tribal Healing Center in the Rocky Mountain region identified mobile outreach to build upon existing opioid prevention, treatment, and harm reduction efforts. The Healing Center purchased a mobile outreach vehicle and worked with a combination of clinical staff, peer recovery support specialists, and Tribal elders to reach identified high-risk areas on the reservation. As of December 2023, the mobile outreach vehicle has disseminated 150 Narcan kits, 150 Fentanyl testing strips, 20 self-care kits, and 500 brochures detailing Healing Center services. Preliminary results from this formative evaluation demonstrate the success of MOV efforts and the process required to purchase and launch an MOV campaign.

Kidney Cancer Incidence among Non-Hispanic American Indian and Alaska Native Populations in the United States, 1999 to 2020.

Non-Hispanic American Indian and Alaska Native (NH-AI/AN) people exhibit a disproportionate incidence of kidney cancer. Nationally aggregated data do not allow for a comprehensive description of regional disparities in kidney cancer incidence among NH-AI/AN communities. This study examined kidney cancer incidence rates and trends among NH-AI/AN compared with non-Hispanic White (NHW) populations by geographic region. Using the United States Cancer Statistics American Indian and Alaska Native (AI/AN) Incidence Analytic Database, age-adjusted incidence rates (per 100,000) of kidney cancers for NH-AI/AN and NHW people for the years 2011 to 2020 combined using surveillance, epidemiology, and end Results (SEER)∗stat software. Analyses were restricted to non-Hispanic individuals living in purchased/referred care delivery area (PRCDA) counties. Average annual percent changes (AAPCs) and trends (1999-2019) were estimated using Joinpoint regression analyses. Rates of kidney cancer incidence were higher among NH-AI/AN compared with NHW persons in the United States overall and in five of six regions. Kidney cancer incidence rates also varied by region, sex, age, and stage of diagnosis. Between 1999 and 2019, trends in kidney cancer rates significantly increased among NH-AI/AN males (AAPC = 2.7%) and females (AAPC = 2.4%). The largest increases were observed for NH-AI/AN males and females aged less than 50 years and those diagnosed with localized-stage disease. Study findings highlight growing disparities in kidney cancer incidence rates between NH-AI/AN and NHW populations. Differences in geographic region, sex, and stage highlight the opportunities to decrease the prevalence of kidney cancer risk factors and improve access to preventive care.

Disparities in Multiple Myeloma Mortality Rate Trends by Demographic Status in the USA.

Multiple myeloma (MM) is a hematological malignancy that arises when plasma cells undergo malignant monoclonal proliferation. This study aimed to assess the demographic disparities and temporal trends in the mortality rates of this disease. We employed the Center for Disease Control and Prevention's Wide-ranging ONline Data for Epidemiologic Research (CDC WONDER) database. We found that for the overall U.S. population, the age-adjusted mortality rate per 1,000,000 (AAMR) decreased from 1999 to 2020. However, rates differed between demographic groups. In addition, we sought to find a significant average annual percent change (AAPC) in mortality rate from 1999 to 2020 for various demographic populations and compared groups to find disparities in mortality rate trend. In 2020, the AAMR due to MM was 38.0 and for women 24.1. The AAPC in AAMR from 1999 to 2020 in men was -1.0% (95%CI=-1.3 to -0.7) and in women was -1.6% (95%CI=-1.6 to -2.3). A significant difference in trend by sex was found, where women had a higher rate of decline. In 2020, the AAMR for the American Indian or Alaska Native (AI/AN) population was 15.0, the Asian American and Pacific Islander (AAPI) had 14.8, the Black and African American population had an AAMR of 55.6 and the White population had an AAMR of 28.1. The AAPC for the AI/AN population was -2.2% (95%CI=-3.5 to -0.9), for the AAPI population it was -0.9% (95%CI=-1.5 to -0.4), the Black and African American population had -1.5% (95%CI=-2.2 to -0.8) and the AAPC for the White population was -1.1% (95%CI=-1.6 to -0.6). A significant difference in trend of decline was found between the AAPI and Black and African American populations and between the AI/AN and Black and African American populations. When assessing the U.S. by states, the mid-southeast U.S. had the greatest density of the states with high AAMRs. These findings suggest which populations are at increased risk for mortality due to multiple myeloma and where we should apply additional resources and research.

Limited Access to Obstetric Services for the American Indian and Alaska Native Population [ID 2683412

INTRODUCTION: American Indian and Alaska Native (AI/AN) people face one of the highest rates of maternal mortality in the United States. Access to maternity care is correlated with health outcomes; however, research on availability of maternity care in areas largely composed of AI/AN populations is limited. METHODS: We identified the 69 counties and county-equivalents in the United States with greater than or equal to 25% of the population self-identifying as AI/AN. Counties and county-equivalents were further classified as rural (micropolitan and non-core) or urban (metropolitan). We then determined the availability of hospitals with obstetric care, obstetric providers (obstetricians and certified nurse-midwives), and the number of live births in counties and county-equivalents. Maternity care deserts were defined as counties and county-equivalents having no hospitals providing obstetric care nor obstetric providers. Limited access to maternity care services was defined as counties and county-equivalents having one or less hospital offering obstetric services and fewer than 60 obstetric providers per 10,000 births. RESULTS: These counties and county-equivalents spanned 13 states, and 65 (94.2%) were classified as rural. 39 counties and county-equivalents (56.5%) were classified as maternity care deserts, and 10 were classified as having limited access to maternity care (14.5%). CONCLUSION: The findings of this study suggest that access to maternity care is limited for AI/AN populations. Increasing access to care in counties and county-equivalents largely composed of AI/AN populations is a potential avenue to improve maternal health outcomes.

Demographic Disparities in Acute Myeloid Leukemia Mortality Trends in the United States.

Acute myeloid leukemia (AML) is a hematological malignancy with an overall poor prognosis; however, survival rates vary widely by clinical and demographic characteristics. This study sought to identify historical trends in AML mortality in the US and to identify any disparities by sex, race or ethnicity. For each demographic population, the age adjusted mortality rate (AAMR) per 1,000,000 for AML-related deaths from 1999 to 2020 in the United States was accessed from the CDC Wonder Database. These values were then used to calculate the average Annual Percent Change (AAPC) from 1999 to 2020 using the National Cancer Institute (NCI)'s Joinpoint Regression Program (Joinpoint V 4.9.0.0, NCI) with log-linear regression models. Statistical significance for all reported findings was determined using a 2-tailed t-test or parallel pairwise comparison with significance defined as p<0.05. The overall population had a significant downtrend in mortality rate between 2011 and 2020 with an APC of -0.61% [95% confidence interval (CI)=-1 to -0.2]. In 2020, the AAMR due to AML for males was 32 and for females was 20.2. Females did not have a significant overall AAPC from 1999 to 2020. Males had a significant AAPC of 0.5% (95%CI=0-0.9) from 1999 to 2020, signifying an overall uptrend. In 2020, the White population had the greatest mortality rate (29.6), followed by the Black or African American population (20.9), Asian or Pacific Islander (AAPI) population (18.6), and the American Indian/Alaska Native population (8.8). American Indian and Alaska Native population data could not be reliably compared. No race/ethnic group had a significant AAPC trend from 1999 to 2020. However, parallel pairwise comparison found a significant difference in the trend of mortality rates between the Black or African American and AAPI, Black or African American and White, and White and AAPI populations. Our findings highlight disparities in mortality due to AML and underscore the need for additional resources and support in affected populations and areas.

HSR24-127: Rectal Cancer Disparities in Age and Overall Survival Among American Indian and Alaska Native Vs Non-Hispanic White Populations.

HSR24-127: Rectal Cancer Disparities in Age and Overall Survival Among American Indian and Alaska Native Vs Non-Hispanic White Populations.